Aquatic ecosystem assessments for rivers

TE = 1 - [0.05 ÷ (Δτ_R^0.5)]

Values obtained represent % reduction in total sediment load.

6.2. Sediment transport - Bedload

6.2.1 Description and rationale

The habitat conditions of a river or stream are strongly associated with the river bed- material. The coarser sediments transported along the river bed also control the morphology of the channel and maintain the heterogeneity of aquatic habitat that is required by aquatic organisms during different stages of their lifecycles (Gordon et al. 2004). Because species differ in their substrate preferences and requirements, they depend on a mixture of particle sizes and interstices, among other attributes, to support colonization (Gordon et al. 2004). In this way, species have evolved along-side the dynamic equilibrium of the bedload sediment regime. However, the continuity of downstream bed-material transport that supports the biological and ecological functioning of the channel is disrupted by instream development such as dams, which alter the sediment supply and flow competencies to support bedload transport (Curtis et al. 2010).

Bedload transport is commonly thought of as a two-phase process. Phase I transport consists of sand and small gravel moving at relatively low rates over a stable channel surface. Phase II transport rates are considerably greater as gravels and larger sized material are moved, including material from both the channel surface and subsurface (Ryan et al. 2002). The initiation of Phase II transport defines the starting point of significant bed mobility and channel change if the upstream sediment supply changes, (Schmidt and Potyondy 2004). Schmidt and Potyondy (2004) refer to this threshold of Phase II transport in terms of a critical discharge (Q_trigger). This critical discharge is synonymous with the “channel maintenance flow”.

Estimation of bedload transport rates and loads in the field is challenging. In wadeable rivers, field based methods include the use of either hand held bedload samplers or trapping devices that are left on the streambed during floods (e.g. Bunte et al. 2007). On larger rivers, bedload samplers are deployed from a boat or bridge that spans the river (see Edwards and Glysson 1999). If bedload measurements are not feasible, estimates of bedload transport rates can be calculated from properties of flow and bedload transport equations. In practice, this modeling approach is commonly used given the difficulties of making direct measurements (Wilcock 2004). Bedload transport equations typically relate a property of flow (e.g. discharge Q, shear stress t, stream power ω) to the transport rate. Sediment transport is initiated when the magnitude of the flow property exceeds a critical threshold (e.g. Q_crt, t_crt, w_crt). For convenience, discharge is often used in screening level assessments for bedload predictions, despite the fact that models predicting bedload transport based on discharge are often inaccurate (Gomez and Church 1989) due to the difficulty of determining an appropriate value for Q_crt. When field data are lacking, one can use a characteristic discharge, for example the bankfull discharge, as a discharge threshold to evaluate how changes in flow might affect channel form. Bankfull discharge has often been equated with channel-forming or effective discharge (i.e. the flow that does the most geomorphic “work”). Bankfull discharge (see Chapter 2 Section 6.4) has traditionally been considered to have a recurrence interval of approximately 1.5 years (Leopold et al. 1964), thus channel- forming flows can be generally expected to occur two out of every three years, occurring mostly during the spring “flood” flows.

More rigorous assessments of bedload transport rates typically employ the use of bed shear stress or stream power. Fractional transport equations can be used to calculate how changes in the flow properties affect selected target bed sediment sizes of ecological importance or ambient grainsize distributions as measured in the field (Schmidt and Potyondy 2004; Ryan et al. 2005). These approaches focus on the conditions necessary to entrain bed particles.

6.2.2 Indicators

Indicators for bedload transport are related to the critical discharge (Q_crt) and thus, are strongly linked to the hydrologic regime presented in Chapter 2. While the preliminary assessment indictor uses a variant of the Bankull Flow indicator referred to in Chapter 2 to estimate Q_crt, a more detailed assessment of bed load movement using field data is used in the field-based assessment. In this case of equating Q_crt to the critical discharge using bankfull flow conditions, Q_crt is not a threshold for the initiation of sediment movement but a threshold for the channel maintaining transport conditions. That is, the bed may be mobile before bankfull conditions but the transport that occurs at bankfull is the right combination of frequency and magnitude to do the most work in terms of channel maintenance. In other cases, Q_crt can be calculated for certain grain size fractions of interest. In this case, Q_crt does refer to the discharge at which these grains are entrained by flow.

6.2.2.1 Preliminary assessment

Annual bankfull flow duration

Annual bankfull flow duration is the percent time per year that the bankfull flow magnitude is equaled or exceeded. This builds on the Bankfull Flow indicator used in Chapter 2 but focuses specifically on the geomorphological aspects of these high flows. Of interest here is simply the amount of time that a river is maintaining transport conditions and how that duration might change with a planned alteration to the flow regime.

6.2.2.2 Field-based assessment

Annual excess stream power

Stream power is the time rate at which work is done or energy is expended and is a useful measure of a river’s erosive capacity (Gordon et al. 2004). Unit stream power is the total stream power standardized by the width of flow. The unit stream power provides an estimate of the mean value of stream power per unit of river bed area (Ferguson 2005) and is given by:

ω = (ρ_wgQS) ÷ W

where

• ρw is the density of water (1000 kg m^-3);
• g is the gravitational constant (9.81 m sec^-2);
• Q is the discharge (in this case the 1.5 year recurrence interval (m³sec^-1);
• S is the slope (dimensionless); and
• W is the bankfull stream width (m)

In Section 4, we used the bankfull channel width because we were interested in the bankfull stream power. In channels with relatively vertical banks, the bankfull width can also be assumed as the width to be used in the calculation of stream power over a range of discharge conditions.

The critical stream power (ω_crt) defines the magnitude of energy expenditure required before channel bed material of a given size (D_x) will move and is controlled by the near- bed velocity of water moving downstream. Estimates of critical stream power for certain indicator bed material sizes are important for prescribing certain flow magnitudes to maintain the bedload transport regime or evaluate certain conditions that scour biota from the streambed. The critical stream power equation for motion for a given bed sediment size (Ferguson 2005) is used to calculate discharges to initiate bed sediment transport (See Section 6.2.6).

The threshold of incipient bedload motion occurs when:

ω = ω_crt

The bedload transport rate increases exponentially as a function of the excess stream power above the critical threshold:

ω_excess = ω - ω_crt

Thus, the sum of excess stream power calculated from a flow series is proportional to the total load that was transported.

If the mean unit stream power is greater than the critical stream power (ω > ω_crt), particles are being mobilized from their rest position on the bed and transported downstream. If the reach is in equilibrium in terms of sediment supply, where the amount of sediment supplied from upstream is equal to the amount being transported downstream, then no morphological change results. If the duration and magnitude of transport increases for that site, but the sediment supply of that grain size fraction does not change, then the channel boundary will erode (i.e. the grain size fraction will persist on the bed). Alternatively, if the duration and magnitude of transport decreases for a given sediment supply, then deposition of that grain-size fraction is likely to increase (aggradation). When the bankfull stream power is considered in this type of analysis, it is intended to be representative of the transport of a whole range of grain size fractions and thus, gives an indication of the likelihood of reach-scale aggradation or degradation (not just individual grain size fractions).

Similarly, transport calculations are often based on the median grain size of a sediment distribution (D₅₀) under the assumption that when the average grain size is in motion, all of the grain sizes are mobile. However, researchers have demonstrated that the amount of fine sediment on the bed makes the bed more susceptible to transport (Wilcock and Kenworthy 2002). To capture the initiation of bedload erosion from the river bed (which is the onset of channel change), Ryan et al. (2005) indicated that the movement of the D₁₆ to D₂₅ grain sizes seemed to correspond with the onset of Phase II transport (discussed earlier); thus, these grains sizes are used for the field-based assessment indicators rather than the D₅₀.

6.2.3 Information requirements

6.2.3.1 Preliminary assessment

Calculation of the bedload erosion indicator requires a streamflow time series (natural flow simulation i.e. reference condition, or observed) at the site of the flow alteration. Recommended methods for establishing the reference condition are provided in Chapter 2, Appendix I, Section 1.1.

6.2.3.2 Field-based assessment

In the field-based assessment, field measurements of channel characteristics at each field survey reach are used. The channel form and substrate should be characterized using the cross-channel transect approach discussed in Section 5. This includes undertaking Wolman (1954) Pebble Counts and obtaining bulk substrate samples to estimate bed sediment size distribution and characteristic grain size fractions (e.g. 2 mm sand, D₁₆, D₂₅, D₅₀ ). The Di notation refers to the frequency distribution of sediments sampled, where D₅₀ equals the particle size that 50% of the sample bed sediments are equal to or smaller than. The D₂₅ is the particle size that 25% of the sampled bed sediments are equal to or small than, etc. Bed sediment analyses should characterise these grain sizes (D₁₆, D₂₅, D₅₀).

If the natural flow simulation used in preliminary assessment has been refined through field-based assessment, the latter should be used to improve the stream power estimates.

6.2.4 Assessment criteria

6.2.4.1 Preliminary assessment

Assessment criteria for the annual excess stream power indicator include the values associated with the 13^th, 38^th, 62^nd, and 87^thpercentiles expressed as the percent time (duration) the critical stream power values associated with the D₁₆, D₂₅, D₅₀, grain sizes are equaled or exceeded annually.

6.2.5 Evaluating alteration

6.2.5.1 Preliminary assessment

Alterations in preliminary assessment indicators are evaluated as follows:

Low alteration: The annual bankfull flow duration (%) lies between the 38^thand the 62^nd percentiles of the annual bankfull duration for the reference condition.

Medium alteration: The annual bankfull flow duration (%) lies between the 13^thand 38^thor 62^nd and 87^thpercentiles of the annual bankfull duration for the reference condition.

High alteration: The annual bankfull flow duration (%) is less than the 13^thor greater than the 87^thpercentile of the annual bankfull duration for the reference condition.

6.2.5.2 Field-based assessment

Alteration in field-based assessment indicators are evaluated as follows:

Low alteration: The annual excess unit stream power duration for 2mm Sand, D16, D25, and D50 grain size materials lies between the 38^thand the 62^nd percentiles of the annual unit stream power duration for the reference condition.

Medium alteration: The annual excess unit stream power duration for 2mm Sand, D16, D25, and D50 grain size materials lies between the 13^th and 38^th or 62^nd and 87^th percentiles of the annual unit stream power duration for the reference condition.

High alteration: The annual excess unit stream power duration for 2mm Sand, D16, D25, and D50 grain size materials is less than the 13^th or greater than the 87^thpercentile the annual excess unit stream power duration for the reference condition.

6.2.6 Methods

For each cross section in the field survey reach (Section 5), estimate the critical stream power for incipient motion for a given grain-size fraction of interest (ω_crt W m^-2) (Ferguson 2005).

ω_crt = 0.104 × (D₅₀^1.5/S^0.17)(D_i/D₅₀)^0.67

Where

• D₅₀ is the median grain size (metres);
• D_i is the given grain-size fraction of interest (metres); and
• S is the water surface slope.

We can then rearrange the unit stream power equation to calculate the discharge (Q_crt) associated with the critical stream power (ω_crt),

Q_crt = (Wω_cr)/(ρ_wgS)

We can then calculate the duration of time when

Q > Q_crt

by using the flow duration curve of the associated streamflow time series.

6.3 Channel form and habitat

6.3.1. Description and rationale

Fluvial geomorphology not only includes processes related to the erosion, transport, and deposition of sediment but also the channel form that results from these processes. Channel form can be described in three dimensions: by its pattern (planform), slope (longitudinal profile) and cross-section (transverse section) (Petts and Foster 1985). Measures of these characteristics provide further information about the interactions of flow, parent material, and the sediment regime. A river’s channel form ultimately controls the amount and heterogeneity of biotopes important for maintaining the ecological condition of a river and specific habitat requirements of VECs.

6.3.2 Indicators

Sinuosity Index (SI)

Channel pattern is the term used to describe the planform view of a river reach or entire river as seen from a ‘birds-eye’ view. This channel pattern reflects the hydrodynamics of flow within the channel and associated processes of energy dissipation and sediment transfer (Eziashi 1999). The sinuosity of a stream is related to hydraulic and topographic factors and can be measured using the sinuosity index (SI) (Mueller 1968) which is the difference between channel length and valley length. Sinuosity has been used to discern the downstream impacts of in-stream structures such as dams as an analog for channel stability (Martson et al. 2005). Positive relationships between sinuosity index and in- stream habitat have been identified, where rivers with higher sinuosity indices are considered to support a more diverse aquatic community compared to river sections with a lower sinuosity index (Fukushimi 2001; Lohani 2008). Others have identified a higher habitat heterogeneity per unit distance in rivers with a high SI index (Goldstein et al. 2002; Ohio EPA 2010). Thus, alterations on rivers with higher SI values will be associated with higher degree of change to ecological condition and VEC state compared to rivers with lower SI values.

6.3.3 Information requirements

Calculation of a sinuosity index requires up-to-date planform maps or higher resolution imagery, including aerial photography or remotely sensed imagery, of the river channel focusing on the downstream zone of influence.

6.3.4 Assessment criteria

Assessment criteria for the sinuosity index are based on some commonly used classes of SI for single channel rivers. These, include: a) straight (SI < 1.05); sinuous (SI 1.05- 1.5), and: meandering (SI > 1.5) (Mount 1995; Gordon et al. 2004).

6.3.5 Evaluating alteration

The potential change to ecological condition and VEC state increases as the sinuosity decreases, associated with the straightening of a channel.

Low alteration: The sinuosity index remains in the SI class associated with its reference condition.

Medium alteration: The sinuosity index is one SI class removed from the reference condition.

High alteration: The sinuosity index is two SI classes removed from the reference condition.

6.3.6 Methods

The sinuosity index for the downstream zone of influence is determined by the ratio of channel length to downvalley length given by the equation (Knighton 1998) (Figure 2):

SI = channel length(metres)/straight line valley length (metres)

6.3.7 Indicators

Mean width-depth ratio

Width-depth ratio is an indicator of channel shape and is used for assessments of changing discharge and sediment load on channel morphology (Chorley et al. 1984). Resurveying established cross-sections along reaches of a river in locations that might be susceptible to erosion and/or sedimentation is one of the most straightforward methods to measure physical change in rivers. Generally, width-depth ratios increase with increasing stream power and bank erodibility (Robertson-Rintoul and Richards 1993; Brandt 2000). The width-depth ratio is a key variable for assessing change in channel dynamics, particularly changes between sediment load and capacity. Increases in width-depth ratio generally are associated with accelerated streambank erosion, excess deposition/aggradation processes, over-widening due to direct mechanical impacts, and other causes. Examples of width-depth ratio responses to changes in sediment capacity, competency, and flow are shown in Figure 3.

6.3.8 Information requirements

Measurements of bankfull width and bankfull depth at each cross section of each field survey reach.

6.3.9 Assessment criteria

Assessment criteria for the width-depth ratio indicator include the values associated with one and two standard deviations from the mean width-depth ratio of the reference condition.

Some general observations on width-depth ratios include:

• W-D Ratio < 10
  • small bedload and high suspended load
  • typically channel is narrow and deep
• 10 > W-D Ratio
  • intermediate bedload, intermediate bedload
  • mixed load channel
• W-D Ratio < 40
  • higher bedload
  • lower suspended load
  • lower sinuosity

6.3.10 Evaluating alteration

Low alteration: A mean width-depth ratio that is within values associated with one standard deviation of the reference condition.

Medium alteration: A mean width-depth ratio that is within values associated with two standard deviations of the reference condition.

High alteration: A mean width-depth ratio that is beyond values associated with two standard deviations of the reference condition.

6.3.11 Methods

The width-depth ratio is calculated by dividing the bankfull width by the mean bankfull depth. Methods for identifying bankfull stage in the field is provided in Section 2.2 of Chapter 2 Appendix I.

6.3.12 Indicators

Bed composition

Bed composition, including the size and distribution of particles is an indicator of in- stream channel change used to assess the effects of changing discharge and sediment load on channel bed and bank morphology (Chorley et al. 1984; Wilcock et al. 2009). The distribution and size of bed materials can change significantly following the construction of dams (Grant et al. 2003; Salant et al. 2006). The amount of geomorphic adjustment is generally dependent on dam operation, associated alteration to hydrologic regimes and the characteristic mode of sediment transport in a channel (Brandt 2000; Schmidt et al. 2001; Dade et al. 2011). Alterations to the natural dynamic equilibrium of sediment erosion and aggradation can lead to impacts on bed related habitat (Kondolf et al. 2008). For instance, where dams eliminate supplies of smaller mobile gravels, bed material may become too coarse for spawning fish to move (Parfitt and Buer 1980) and excessive levels of fine sediment can clog spawning gravels (Sear et al. 2008). In cases where increased sedimentation occurs downstream of dams, embeddedness (the degree to which fine sediments surround coarse substrates on the stream bed) can increase (Sylte and Fischenich 2002; Sennatt et al. 2006). Increased embeddedness has been correlated with degraded benthic habitat and declines in macroinvertebrate abundance and diversity (Waters 1995; Angradi 1999).

The composition and nature of the river bed can be an early indicator of changes in sediment regime with concurrent impacts on invertebrate production, biomass, and fish production. Morphological changes in riffle shape and substrate composition may reduce their suitability for the reproduction of certain species of fish.

6.3.13 Information requirements

Information on bed composition is collected using the Wolman Pebble Count and bulk sample methods outlined in Section 5.

6.3.14 Assessment criteria

Alteration in bed composition is assessed, ideally, by examining change in the entire grain size distribution. Of particular interest for calculations in this chapter are changes in the values associated with the % composition for the D16, D25, and D50 grain sizes. In predicting potential shifts in bed composition in response to an alteration, the bed composition indicator focuses on the D50 grain size.

6.3.15 Evaluating criteria

Low alteration: The bed composition indicator lies between the 38^thand the 62^nd percentiles of the grain size distribution for the reference condition.

Medium alteration: The bed composition indicator lies between the 13^thand 38^thor 62^nd and 87^thpercentiles of the grain size distribution for the reference condition.

High alteration: The bed composition indicator is less than the 13^thor greater than the 87^thpercentile of the grain size distribution for the reference condition.

6.3.16 Methods

Characterization of river bed material is achieved using Wolman Pebble Counts and bulk samples as described in Section 5.

7.0 Supporting information

The following information is suggested to accompany a sediment regime assessment. This will allow an adequate evaluation of the quality of the information and analyses used to estimate values for indicators and assessment criteria and for the interpretation of results:

1. A table comparing drainage basin area (km^-2), landscape characteristics (surficial geology, mean slope and percent area covered by water) and the river-bed characteristics (e.g. percent underlying surficial geology) for the drainage basin upstream of the development site and for all sites assessed as potential reference sites.
2. A table identifying HYDAT sediment stations used in sediment yield analysis, including a rationale for their use.
3. A list of any non-natural (anthropomorphic) impacts upstream of the proposed site (e.g. river alteration, mining, forestry, industry etc.) that might be influencing sediment yield and the percent area of the upstream drainage basin they occupy.
4. The anticipated maximum reservoir or headpond volume or capacity (m³) and residence time of water in reservoir.
5. Diagrams of longitudinal profiles scaled appropriately in m m^-1, noting any vertical exaggeration, for: i) the river extending from the upstream ZOI to the doswnsteam ZOI showing locations of the in-stream development and reservoir (existing or proposed) with all sampling site locations demarcated; and ii) the field survey reaches with all cross sectional survey locations demarcated. Geographic coordinates of start and end points for the profiles should also be provided.
6. Detailed diagrams of all river channel cross section surveys, identifying channel morphology and heights through the cross section, intervals used, including identification of bankfull stage and width. Details of the bank morphology and pictures taken to describe the site. Geographic coordinates of start and end points of all cross sections examined should also be provided.
7. The locations of sinuosity measurements, identified using imagery or by geographic coordinates.
8. Tables and graphs showing the complete grain size distributions obtained from the one bulk sediment sample from each field survey reach and from the Wolman pebble counts at each cross-section
9. A plan view map showing the location of the each field survey reach, cross sections, longitudinal profile, and locations of in-stream structures.

8.0 Post-alteration monitoring

Post-alteration monitoring of the sediment regime requires measurement of continuous discharge as described in Chapter 2 Section 7 and suspended sediment sampling to measure annual suspended sediment load upstream and downstream of the waterpower facility following the sampling strategy described in Section 6.1.3.2.

All measurements taken at the field survey reach cross sections or from planform maps or aerial imagery should be repeated using the sampling frequency outlined in Chapter 1. This will document any changes in the physical character of the river bed structure and composition.

Chapter 4: Water quality

1.0 Introduction

Water quality in riverine ecosystems is a function of a complex interaction between hydrologic, atmospheric/climatic (e.g. solar energy input), watershed (e.g. soils/geology, topography), and biotic variables. Chemical characteristics like dissolved oxygen (DO), alkalinity, pH, and nutrients, and physical characteristics like water temperature, turbidity and light transmission, are all influenced by flow regime, climate/weather, geology and land use patterns, and sources of organic matter. Together with the flow, sediment, and temperature regimes, these water quality properties strongly influence river productivity and biodiversity.

This chapter focuses on water quality factors that most strongly shape the ecological condition of river systems and that are often of greatest importance to the health of valued ecosystem components like species at risk or socio-economically important fish species. The purpose is to provide the information needed to assess potential changes to these indicators resulting from in-stream development. However, the principles and indicators described here can be used to help assess the effects of any type of project that will change riverine water levels or flows.

2.0 Rationale

Water quality strongly influences the structure and functioning of aquatic ecosystems. Alteration of water quality characteristics beyond the range of natural variability can cause changes in productivity (Clark et al. 2008; Wooton et al. 1996), shifts in biological communities that result in shortened food webs (Clark et al. 2008; Marty et al. 2008; Marks et al. 2000; Spence and Hynes 1971;) and reduced biodiversity (Bunn and Arthington 2002; Rosenberg et al. 1997; Coleman 1996).

The flow regime is the dominant variable affecting water quality in rivers and lakes (Sokal et al. 2009). Changes in flows and levels caused by in-stream developments can have significant effects on water quality, both upstream and downstream. For example, reductions in flow at a dam or within a reservoir increase the deposition of sediments (Petts 1984), alter nutrient transport and recycling processes (Vannote et al. 1980: Ward and Stanford 1989; Junk et al. 1989, Ittekkot and Haake 1990 in Rosenberg et al. 1997) and affect the downstream sediment regime (Knighton 1998; Bowen et al. 2003, Shields et al. 2000). The composition and concentrations of nutrients and suspended sediments in water strongly influence a river’s primary productivity and the types of biological communities it can support.

Reservoirs act as effective nutrient sinks, particularly for nutrients such as phosphorus (Friedl and Wüest 2002) and nitrogen (Marty et al. 2008). Increases in nutrient availability can stimulate primary production and lead to eutrophication, particularly in reservoirs where increased water residence times and higher water temperatures can create ideal conditions for phytoplankton and macrophyte growth. The additional organic matter resulting from higher primary productivity increases microbial decomposition and can lead to depletion of dissolved oxygen (DO) within the reservoir. Depending upon the design and operation of a dam, low DO water can be released downstream. Low DO concentrations can have a variety of lethal and sub-lethal effects on aquatic organisms (Doudoroff and Shumway 1970; Alabaster and Lloyd 1982) and increase the release of nutrients and contaminants like mercury from sediment (CCME 2003).

Suspended sediment levels determine turbidity and the depth of light penetration (Sokal et al. 2009) and hence, the amount of solar radiation available to algae and macrophytes (Krebs 1978; Rosenberg et al. 1997). Changes in light penetration can, in turn, affect fish behaviours such as predation, foraging efficiency, and nest protection.

A potential effect of large dams is the entrainment of high levels of atmospheric gases as water moves over a dam or through penstocks. Supersaturation of water with dissolved gases can lead to gas bubble trauma in fish and invertebrates. However, the severity of the effects varies among species (Clarke et al. 2008; Backman and Evans 2002; Backman et al. 2002) and must be assessed on a case by case (or species by species) basis.

Water temperature is a critically important characteristic that can be affected by in- stream development. Temperature directly influences the productivity of aquatic ecosystems through its effects on dissolved oxygen levels, carbon cycling and the ability of water to hold nutrients in solution (Poff et al. 1997; Olden and Naiman 2009). Temperature also plays a vital role in determining the presence or absence, life histories and spatial distribution of organisms in streams (Ebersole et al. 2001, Vannote et al. 1980). In particular, many critical life history processes in fish are regulated by temperature (Hauer and Hill 2007).

In summary, changes in flows and levels caused by in-stream developments can have significant effects on water quality and hence ecological condition both above and below a structure. Careful pre-alteration assessment and post-alteration monitoring can help to identify and evaluate potential effects of a development and options for mitigating them.

3.0 Indicator summary

4.0 Establishing a reference

To properly assess the potential effects of in-stream development on water quality and the ecological condition of a river, it is important to first understand the water quality regime of the site in its natural and current states. This information allows better estimates of the potential for changes in water quality resulting from an in-stream development, in order to answer the question “Is the planned project likely to cause changes in water quality that will affect aquatic ecosystem values?”

The purpose of the pre-alteration water quality assessment is to characterize current water quality conditions and provide a reference for estimating potential ecological changes associated with an in-stream development, establishing possible mitigation strategies, and identifying post-alteration monitoring requirements.

Data to establish a natural reference condition for water quality is typically more available than other types of data, since water quality is often measured by monitoring programs and as integral parts of many studies. However, when determining reference conditions, care must be taken to ensure that the data used are of high quality and that any differences in collection and analysis methods can be taken into account.

5.0 Information requirements

5.1. Preliminary assessment

The first step in assessing potential changes in water quality associated with an in- stream development is to determine if data are available to establish a reference and/or condition for the indicators of interest. Ideally, these would consist of multi-year time series from sampling locations above, below, and at the location of the proposed alteration. However, any available data for the site (or similar nearby sites) or a suitable model, may help inform the first stage of the assessment, the goal of which is to provide a rough indication of the potential effects of the alteration on the indicator of interest. For water quality indicators, existing data may be available from monitoring programs such as the Provincial Water Quality Monitoring Network (PWQMN) ^{footnote *[*]} or from studies conducted for other projects or purposes. In addition, for some indicator variables such as dissolved oxygen, it may be possible to model the response to the proposed alteration.

If sufficient data or suitable models are available to make a preliminary assessment of the effects of the proposed alteration and this assessment suggests a low impact, then field sampling may be not be required. However, if sufficient data or models aren’t available to make an informed judgement, or if examination of the data or modeling results suggest the potential for significant ecological changes, then field sampling will be required. Field sampling should also be done if effects on sensitive ecosystem components (e.g. endangered species) or biodiversity are anticipated.

5.2. Field-based assessment

Field sampling will provide more detailed information of the water quality regime upon which to make an informed judgement about the effects of an in-stream development. Ideally, field sampling would be conducted for a minimum of 2 to 3 years prior to the alteration to increase the likelihood of capturing the range of variation representative of each indicator at that particular site. The shorter the time over which pre-construction data is collected, the more difficult it is to make scientifically defensible inferences about the current state of the river and how it may change because of the structure.

6.0 Measuring indicator variables – sampling design

Water quality indicators described in this chapter were chosen to represent key ecosystem components thought to be important determinants of ecological condition and the state of valued ecosystem components (VECs). Indicator selection was based on the scientific literature and advice provided through an MNR hosted workshop on indicators for effectiveness monitoring for water management planning (ESSA Technologies, 2005).

6.1. Selecting site-specific water quality indicators

Decisions about which indicators to measure and how to measure them should be based on site-specific characteristics, the type of alteration, and a priori knowledge of the potential for changes in the indicator variables. Sampling methods and the type of equipment used will vary. The general sampling guidelines below apply to all indicators, unless otherwise noted in the detailed indicator description.

Although each indicator is discussed separately, many of the variables can be measured simultaneously. For example, dissolved oxygen, conductivity, pH, and temperature are often measured at the same time using a hand-held probe. Similarly, a single water sample can often be analyzed for multiple nutrients. Sampling requirements should be developed with advice from the laboratory that will analyze the samples.

A general reference on water quality sampling methods is the Canadian Council of Ministers of the Environment document “Protocols Manual for Water Quality Sampling in Canada” (CCME, 2011). Up to date methods are also described in Standard Methods for the Examination of Water and Wastewater (Eaton et al. 2005, or online at Standard Methods website).

6.2. Selecting sampling sites

Sites for sampling water quality must be carefully selected to ensure they accurately characterise the condition for the indicator of interest. General guidelines for selecting sampling sites include:

• Sample at a minimum of 4 locations (see sampling sites identified in Chapter 1):
  • In the upstream ZOI
  • At sample sites 1, 5 and 10 (or the most downstream site) in the downstream ZOI.
• Additional sampling sites may be required in the bypassed natural channel reach if it contains ecologically important habitat, a valued ecosystem component, or if there is concern about maintaining its ecological integrity.
• Where pre-existing data are available, if feasible, use the same sampling sites to maintain continuity of long term records and take maximum advantage of the existing data.
• For new alterations at existing in-stream structures, sampling should continue at existing reference sites if already established.

Unless specified below for an individual indicator variable, three replicate samples should be acquired in the river’s thalweg. The three replicate samples may come from three depth integrated water samples or three in-situ probe measurements at each specified depth.

6.3. Selecting sampling depths

The greater the proportion of the water column integrated in the sample, the more useful the data are for making inferences about potential changes in the indicator being measured. If the river being sampled is deep or contains deep pools that provide important habitat for fish or other aquatic species, samples taken at multiple depths in the water column may be required to adequately characterize water quality.

With modern instrumentation, water column profiles (samples taken at regular depths throughout the water column) of many water quality characteristics described here can be taken quickly and easily. If this type of sampling is conducted, collection of water column depth profiles at 0.5 m to 1 m depth increments is recommended. If not feasible, samples from discrete depths can be collected using samplers designed for this purpose, such as Kemmerer or Van Dorn water samplers. Recommended depths for fixed-depth samples are 0.3 m - 0.5 m below the surface, mid-water, and 0.5 – 1.0 m from the bed. Modifications to these recommendations may be required depending upon the indicator, the depth of the river, and the amount of variability in water levels.

In small rivers and streams, water depths may be shallow enough to preclude taking samples at multiple depths. In these locations, water sampled at a single depth, usually 0.3 m – 0.5 m will usually provide a representative sample.

6.4. Determining sampling frequency

Water quality characteristics can vary on short times scales and often measurements during events such as transient high flow periods are the most important for assessing potential effects on ecological integrity. Modern instrumentation makes high frequency in situ monitoring of water quality variables possible, and in many cases more economical than sampling with bottles or hand-held instruments. Therefore, whenever feasible, the use of in situ samplers is recommended.

When in situ monitoring is not possible, and for variables that cannot be measured with in situ instruments, the sampling frequency must be carefully selected to ensure the representative seasonal and higher frequency variation in the indicator is captured. Indicator-specific sampling recommendations are included in the description of each water quality characteristic below. However, general best practices for determining sampling frequencies include:

• Sample more frequently when rates of change in the indicator are high and less frequently when they are low. For example, monthly sampling may be increased to weekly during high flow periods for some indicators (see individual characteristics).
• Sampling may be necessary across a range of flow conditions (low, medium, and high) in order to establish a relationship between the variables (e.g. turbidity and total suspended solids).
• If nutrient and sediment issues are anticipated, daily sampling may be necessary to capture transient events.
• Depending upon the system and the operating plan for the in-stream structure, lower frequency sampling may be sufficient for post-alteration monitoring of some indicators. However, for most variables, a minimum of 12 samples per year (monthly sampling) is recommended.
• Frequency of sampling should also consider potential rates of change for the indicator.
• For valued ecosystem components such as SAR, additional sampling may be desirable during critical times such as spawning periods.

7.0 Assessment criteria

When assessing the potential effects of an in-stream development on ecological condition, the predicted post-alteration value of the indicator should be compared against the reference condition to determine the degree of alteration from both the reference (natural) condition and the current condition (if the river is not in its natural state). The mean and standard deviation of indicator variable values for the reference condition, or current condition, are used as assessment criteria unless otherwise stated in the indicator sections below.

8.0 Evaluating alteration

The degree of alteration for an indicator can be characterized as follows:

Low alteration

Estimated value of the indicator lies within one standard deviation of the reference condition.

Medium alteration

Estimated value of the indicator lies within two standard deviations of the reference condition.

High alteration

Estimated value of the indicator exceeds two standard deviations of the reference condition.

When the potential effect of a facility on a valued ecosystem component is of interest, the predicted post-alteration value of the indicator should be compared against known physiological requirements for the various life stages of the species of interest. The potential effect should then be qualitatively characterized as low, medium, or high based on the estimated impact to the species.

9.0 Characteristics, indicators, and assessment criteria

A brief description and rationale for each indicator variable is provided below. Additional sources of information on the effects of altering the magnitude of indicator variables on aquatic life are also provided.

If available, existing data that captures annual variation in each indicator variable should be used to determine the natural range of variability and to estimate the direction and magnitude of potential changes resulting from the proposed alteration. If sufficient data aren’t available to assess potential changes, or if the available data suggest a moderate to high probability of ecosystem alteration, then field sampling should be done.

In all cases where indicator variables are measured in the field using hand-held or in situ probes, the manufacturer’s guide should be consulted to ensure proper calibration and use of the instrument in the field. Further data collection and analysis methods using bottled samples are provided by CCME (2011) and Eaton et al. (2005).

9.1. Dissolved oxygen concentration

9.1.1. Description and rationale

Dissolved oxygen concentration (DO) is the amount of oxygen dissolved in water. Concentrations of DO vary seasonally and diurnally due, in part, to corresponding variation in temperature, photosynthetic activity, respiration, and the bacterial decomposition of organic matter (Chapman and Kimstach 1996). Aeration of streams can take place at any structural feature that introduces air bubbles into the water: waterfalls, rapids and man-made barriers, such as dams.

Most aquatic organisms require oxygen from the water to meet their metabolic demands. The sensitivity of fish and other aquatic organisms to low dissolved oxygen varies among species and their life stages (Alabaster and Lloyd, 1982). Fish exposed to low dissolved oxygen may suffer a variety of lethal and sub-lethal (physiological and behavioural) effects (Doudoroff and Shumway 1970; Alabaster and Lloyd 1982). Below 2 mg/L most fish species die (Chapman and Kimstach 1996). A review of dissolved oxygen requirements for aquatic organisms can be found in the British Columbia Ministry of Natural Resources water quality guidelines (criteria) report “Ambient Water Quality Criteria for Dissolved Oxygen” (British Columbia Ministry of Environment, 1997).

Dissolved oxygen concentrations also affect the solubility and availability of nutrients and low DO levels facilitate the release of nutrients and contaminants from sediments. For example, the methylation of mercury occurs at a faster rate in anoxic conditions (CCME 2003b).

The creation of a reservoir or impoundment, which often involves the flooding of large vegetated areas, can significantly reduce dissolved oxygen concentrations. In the newly created reservoir, the decomposition of flooded vegetation and soil, along with increased amounts of algae and aquatic macrophytes resulting from increased primary productivity, can drive hypolimnetic DO levels down (Baldwin and Mitchell 2000) making the reservoir’s waters unsuitable for many species. Depending upon the structure’s design, the release of this cold hypolimnetic water can affect downstream temperatures and DO concentrations (Olden and Naiman 2009). Therefore, it is important to understand pre-construction DO concentrations and to monitor DO both above the reservoir and below the structure after its construction to ensure adequate DO is available.

CCME (1999b) provides additional information on dissolved oxygen and its effects on aquatic life.

9.1.2. Indicator and methods

The concentration of oxygen dissolved in water; usually expressed as milligrams of oxygen per litre of water (mg/L) but the use of ml/L is also common.

When available, existing data that capture seasonal variation in DO concentration should be used to determine the natural range of variability and to estimate the direction and magnitude of potential changes in DO resulting from an alteration. If sufficient DO data are not available, it may be possible to predict DO changes using a model such as the U.S. Environmental Protection Agency’s River and Stream Water Quality Model (QUAL2K). If sufficient data or appropriate modelling results aren’t available to reliably determine seasonal trends, including oxygen minima, then field sampling should be done. A review of other public domain models that can be used to simulate DO in rivers can be found in Kannel et al. (2011).

Specific sampling protocols for dissolved oxygen include:

• Establish 3 transects across the reach at each sampling site.
• Sample at 3 points across each transect including 3 replicates at each point.
• Samples should be taken at approximately the same time, as early each morning as possible, to capture the DO concentration near its lowest value. Sampling between 6:00 a.m. and 8:00 a.m. is recommended. The time of sampling should be documented.
• Sampling sites should not occur near rapids, waterfalls, or at the bottom of the tailrace, where oxygen is likely to be entrained.
• If the site has a history of low DO or species particularly sensitive to low DO are present, continuous automated sampling to more reliably capture diurnal changes in oxygen may be advised.

Dissolved oxygen concentrations can be measured in the field using hand-held or in situ probes or water samples can be taken and analyzed in the lab using the Winkler titration method.

Recommended data collection method – Although chemical analysis is the most accurate way to determine DO concentrations, the collection, transport, and analysis of bottle samples is time consuming and must be done carefully to avoid introducing oxygen into the sample and to ensure accurate results. This makes the collection of multiple or time series samples impractical. Use of an accurate DO probe is therefore recommended. These types of probes have a number of advantages over bottle samples: they are simple to use in the field, can take multiple samples cheaply and easily, can be used to remotely collect time series, and typically incorporate other desirable measurements such as temperature and conductivity (see below). However, for quality control purposes, the accuracy of DO probes should occasionally be checked against bottles samples analyzed using Winkler titrations.

9.2. Total dissolved gas (TDG)

9.2.1. Description and rationale

Total Dissolved Gas (TDG) refers to the total amount of atmospheric gases dissolved in water. Supersaturation occurs when these partial pressures exceed those of gases in the atmosphere.

The movement of water over or through waterfalls, rapids, spillways, and turbines can cause high levels of atmospheric gases to be entrained in the water, raising TDG concentrations. Supersaturated water can have harmful effects on both fish and invertebrates. Gas-bubble disease or gas-bubble trauma, in which gas bubbles develop in the blood or tissues, can result in blocked blood vessels or torn tissues, which may cause death (Bouck 1980). Air bubbles trapped on the outside of invertebrates may also cause buoyancy problems, lifting them off the bottom and potentially leading to increased predation risk. The severity of gas bubble trauma effects appears to vary with species and life stage (Clarke et al. 2008; Backman and Evans 2002; Backman et al. 2002). Most dams in Ontario are unlikely to have sufficient head to produce damaging TDG levels. Nonetheless, the potential for high TDG levels to occur should be evaluated for each project to rule out potential problems.

CCME (1999a) provides additional information on total dissolved gas and its effects on aquatic life.

9.2.2. Indicator and methods

Mean monthly TDG concentration measured as pressure (mm Hg) or percent saturation relative to the ambient barometric pressure.

An in-stream development should be evaluated to assess its potential to produce harmful levels of gas supersaturation. Mitigation strategies can be used to reduce the occurrence of gas supersaturation if the risk to aquatic organisms is high. If the potential for supersaturation is moderate to high, despite mitigation measures, or if information on the design and operation of the in-stream structure is insufficient to assess the potential for supersaturation, then pre-construction field sampling should be done. These data will provide a reference for post-alteration effects monitoring.

Total dissolved gas is measured in the field using hand-held or in situ probes. Monthly TDG measurements should be obtained during the open water season, targeting event- specific measurements during periods of high flow.

9.2.3. Post-alteration monitoring

If the facility has the potential to cause damaging levels of TDG, monthly post-alteration monitoring is recommended at a site within 500 meter of the tailrace during the open water period (downstream ZOI sample site 1).

9.3. pH

9.3.1. Description and rationale

pH is a measure of the hydrogen ion concentration in a liquid. pH values range from 0 to 14: waters with ph below 7 are acidic, while those above 7 are basic (alkaline). pH varies seasonally and over shorter time scales with changes in photosynthesis and decomposition. Increases in pH in the summer are caused by increased photosynthetic activity in the water column which depletes CO₂ in the water, thus shifting the pH balance (Boers, 1991).

Most aquatic organisms require waters with near-neutral pH (7); depending upon the species, sublethal and lethal effects can occur at pH values less than 4.5 and above 9.5. Low pH levels can facilitate the release of metals from sediments; high pH levels can increase the solubilisation of ammonia and salts and cause dissolved metals to precipitate onto suspended solids or sediments. The acidity (pH) of the water column (Boers 1991) and water temperature (Boers and Van Hese 1988) also affect the release of phosphate from sediments.

A critical characteristic in the response of an aquatic system to changes in pH is buffering capacity (see alkalinity indicator). Well-buffered systems have high concentrations of dissolved minerals and are resistant to pH changes. Poorly buffered systems, such as rivers in pristine watersheds with granitic bedrock, are highly sensitive to pH changes (Washington State Dept of Ecology 2005).

9.3.2. Indicator and methods

pH measurement for water sample.

pH can be measured in the field using hand-held or in situ probes or water samples can be taken and analyzed in the lab.

Recommended data collection method – Hand-held probe.

9.4. Alkalinity

9.4.1. Description and rationale

Alkalinity is a measure of the acid neutralizing capacity of water. It is primarily an indicator of the concentrations of carbonate, bicarbonates, and hydroxides, although other basic compounds may be present. Alkalinity is usually expressed as an equivalent amount of calcium carbonate (CaCO₃). Low alkalinity waters have limited buffering capacity and can be susceptible to changes in pH, such as those caused by atmospheric acid deposition.

Waters from areas where the surficial geology is dominated by limestone typically have high alkalinity and hence, good buffering capacity. In contrast, waters from areas where the underlying rock is predominantly granitic have low alkalinity and poor buffering capacity.

9.4.2. Indicator and methods

Total Alkalinity measured in mg/L CaCO₃

Alkalinity is determined by titration of bottled samples.

9.5. Conductivity

9.5.1. Description and rationale

Conductivity or specific conductance is a measure of the ability of water to conduct a current. Specific conductance is related to the concentration of ions in the water; the greater the concentration of ions, the more current the water can carry.

With appropriate site-specific calibration, conductivity can often be used to estimate total dissolved solids, reducing the need for relatively more expensive laboratory analyses (Cavanagh et al. 1998a).

9.5.2. Indicator and methods

Specific conductance, reported in microsiemens per centimetre (µS/cm).

Specific conductance is usually measured in the field using a conductivity meter, but can be measured from bottle samples. Data may be collected intermittently or continuously recorded.

Recommended data collection method – Continuous sampling using a conductivity meter is recommended whenever possible. This allows more accurate characterization of conductivity, which in rivers, can change very rapidly in response to changes in TSS.

9.6. Dissolved solids

9.6.1. Description and rationale

Dissolved solids refer to the inorganic salts, organic matter and other dissolved materials in water. Concentrations of dissolved solids, measured as total dissolved solids (TDS), are of interest because they influence a variety of chemical and biological processes. The dissolved load in water includes nutrients such as calcium, magnesium, sodium, potassium, chloride, sulphate, silicate, bicarbonate, phosphorus, nitrogen, and dissolved organic material (Shields et al. 2009: Steinman and Mulholland 2007; Tank et al. 2007; Webster and Valett 2007; Hudson et al. 2000; Schindler 1977). Variation in TDS concentrations can result from inputs of pollutants, changes in flow levels, and precipitation events (Weber-Scannell and Duffy 2007).

The concentration and chemical composition of dissolved solids are important determinants of biodiversity in aquatic ecosystems. Major changes in dissolved solids can affect aquatic ecosystem structure and function (CCME 2002). For example, dissolved solids are the primary source of nutritionally important ions for phytoplankton (Wetzel 1975). Changes in TDS also affect osmotic regulation and can result in the elimination of some aquatic species when physiological tolerances are exceeded. In addition, as TDS increases, high levels of specific ions may become toxic to some species and life history stages (Weber-Scannell and Duffy 2007).

9.6.2. Indicator and methods

Total dissolved solids (TDS) measured in mg/L.

TDS is determined gravimetrically after water samples are filtered, evaporated, and dried in an oven at a given temperature.

9.7. Suspended solids

9.7.1. Description and rationale

Total suspended solids (TSS) refers to the particulate matter suspended in the water column, which can include sediment, organic and inorganic matter, microorganisms and plankton. High concentrations of particulates affect turbidity and light transmission, restricting light penetration into the water column and reducing photosynthesis in algae and aquatic macrophytes. High concentrations of suspended solids can also result in more rapid solar heating. Concentrations of TSS usually increase with flow velocities, and they can be highly variable over very short time scales.

High TSS concentrations can have direct negative effects on biota. Examples include interfering with filter feeding or causing the burial of benthic invertebrates. In fish, high TSS can cause physical damage to fish eye and gill membranes, affect food availability, inhibit egg development, and restrict fish movements (CCME, 2002).

Canadian Council of Ministers of the Environment (2002) provides additional information on total suspended solids and its effects on aquatic life

9.7.2. Indicator and methods

Total suspended solids (TSS) measured in mg/L.

Calculating TSS requires time series from samples collected throughout the year and during periods of low, normal, and high flows. This will allow determination of the relationship between flow and TSS for the site of interest and provide data to calculate monthly minima and maxima.

If existing data are not available to determine the natural range of variability in TSS, an alternative approach is to examine information on the underlying geology of the area to estimate the probability that a project would produce significant changes in TSS.

Determination of TSS concentrations requires the collection of bottled water samples for laboratory analysis, which includes filtering, drying, and weighing the residue from a known volume of water. Results are typically reported in mg/L.

Specific sampling protocols for total suspended solids include:

• Obtain monthly measurements during the open water period with targeted daily measurements during highest and lowest flows.
• Measurements taken in the thalweg using depth-integrating samplers, as described in Chapter 4, is recommended.

9.7.3. Post-alteration monitoring

With appropriate river-specific calibration, turbidity can often be related to TSS, particularly where there are large fluctuations in suspended matter (Chapman and Kimstach 1996). For monitoring purposes, the collection and analysis of TSS samples may be discontinued if a sufficiently reliable statistical relationship between turbidity and TSS is derived.

9.8. Turbidity and transparency

9.8.1. Description and rationale

Turbidity is a measure of the amount of light scattered and absorbed by the suspended particulate matter in water. Silt, clay, organic and inorganic material, plankton, micro- organisms, and other particulate substances all contribute to turbidity. Turbidity varies on seasonal or shorter time scales in response to changes in photosynthesis and other biological activity, flow rates, sediment regime, and rainfall. Turbidity is usually measured using a nephelometer or turbidity meter, which determines turbidity using the intensity of light scattered by a water sample.

Transparency is a measure of water clarity, which is influenced by the presence of both particulate matter and dissolved matter that affects water color. It is often measured in the field using a secchi disk.

Changes in turbidity and transparency can have a number of effects on ecological communities. Higher turbidity and reduced transparency resulting from increases in suspended sediment concentrations decrease the depth of light penetration, impairing photosynthesis in algae and macrophytes (Rosenberg et al. 1997, Cavanagh et al.1998b). Such changes in primary productivity may affect overall system productivity, including fish production (Cavanagh et al. 1998b). With respect to fish, changes in water transparency can affect predation rates, ability to find food, egg maturation, pre-spawning aggregations, and migration (Hauer and Hill 2007). Reduced transparency can also be an indicator of other environmental changes, such as increased bank erosion and changes in the uptake, transport, and deposition of toxic materials (Washington State Department of Ecology 2005).

9.8.2. Indicators and methods

Turbidity measured in nephelometric turbidity units (NTUs) Secchi depth (transparency) measured in meters.

Specific sampling protocols for turbidity and transparency include:

• Obtain monthly measurements during the open water period with targeted daily measurements during highest and lowest flows.

Turbidity can be measured in the field using a hand-held or in situ turbidity meter or water samples can be taken for laboratory analysis; transparency is measured with a secchi disk.

Recommended data collection method – Turbidity is best measured in the field, so the use of bottle samples is not recommended. Nephelometry is the most reliable method for measuring turbidity, so use of a turbidity meter is the preferred method of data collection.

Because turbidity is determined by suspended material, it can often be related to total suspended solids. For monitoring purposes, it may be possible to discontinue the collection and analysis of TSS samples if a sufficiently reliable site-specific statistical relationship between turbidity and TSS can be derived.

9.9. Phosphorus

9.9.1. Description and rationale

Phosphorus is an essential nutrient for all living organisms. Aquatic plants require inorganic phosphorus in the form of orthophosphate ions (PO₄^3-) for nutrition (CCME,2004). In freshwater ecosystems, phosphorus is often the limiting nutrient for algae, so its availability usually controls the primary productivity of water body (Boers and Van Hese 1988). Pristine water bodies usually have low concentrations of phosphorus and support diverse, productive aquatic communities.

Increased nutrient concentrations, resulting from human activities, are the primary cause of eutrophication, the over enrichment of nutrients in a water body (Chapman and Kimstach 1996). Inputs of phosphorus into freshwater systems can dramatically increase algal growth, leading to increases in turbidity and sedimentation, reductions in dissolved oxygen, and changes in nutrient and contaminant cycling that ultimately affect the aquatic biodiversity (Mason 1991; CCME 2004).

Total phosphorus is a measure of inorganic and organic phosphorus present in water as dissolved and particulate matter and is considered the most meaningful indicator of phosphorus for surface waters (Wetzel 2001).

Canadian Council of Ministers of the Environment (2004) provides additional information on phosphorus and its effects on aquatic life

9.9.2. Indicator and Information requirements

Total Phosphorus measured in mg/L.

Determination of phosphorus concentrations requires the collection of bottled water samples for laboratory analysis.

9.10. Nitrogen (general description)

9.10.1. Description and rationale

All organisms need nitrogen for growth and reproduction. Nitrogen occurs in water as nitrate (NO₃), nitrite (NO₂), ammonia (NH₃ & NH₄⁺), and organically bound nitrogen. The amount of nitrogen in water is indicative of a water body’s nutrient status and levels of organic pollution (Chapman and Kimstach 1996).

Changes in water column concentrations of nitrogen compounds and their subsequent effects on nitrogen cycling strongly influence the structure and functioning of aquatic ecosystems. Ecosystem alterations from nutrient enrichment can include increases in primary production, turbidity, and sedimentation, reductions in dissolved oxygen concentrations, and changes in nutrient and contaminant cycling (Mason 1991; CCME 2003c. Given the potential effects of altered nitrogen cycling, measurement of nitrogen is a component of most water quality assessment and monitoring programs.

Three indicators of nitrogen are described below:

• Nitrate/nitrite
• Total Ammonia
• Total Kjeldahl nitrogen

The importance of nitrogen in the aquatic environment varies with the relative amounts of nitrite, nitrate, ammonia, and organic nitrogen. The indicators recommended here provide a comprehensive picture of the concentration of all nitrogen compounds in a water body.

9.11. Nitrogen (nitrate/nitrite)

9.11.1. Description and rationale

Nitrate (NO₃) is the most stable form of nitrogen in a water body and the primary source of nitrogen for aquatic plants (Cavanagh et al. 1998b). Although phosphorus is usually the limiting nutrient in freshwater (Wetzel 1975), elevated nitrogen concentrations can also play an important role in eutrophication (CCME 2003c). Seasonal changes in nitrate can result from variation in algal and macrophyte growth and decay.

Nitrite (NO₂^-) can also be used as a source of nutrients by algae and macrophytes; however, it is an unstable intermediate in the nitrogen cycle and is quickly oxidized to nitrate or reduced to nitrogen gas (Cavanagh et al. 1998b). Because nitrite can be used by aquatic plants, increases in its availability may also contribute to eutrophication.

For additional information on nitrogen and its effects on aquatic life, see CCME (2003c;2007).

9.11.2. Indicator and methods

Nitrate/Nitrite measured in mg/L.

Determination of nitrate/nitrite concentrations requires the collection of bottled water samples for laboratory analysis.

9.12. Nitrogen (ammonia)

9.12.1. Description and rationale

Ammonia is a by-product of the microbial decomposition of nitrogenous organic matter, excretion by biota, and the reduction of nitrogen gas (Chapman and Kimstach 1996). Ammonia compounds typically occur in very small amounts in pristine waters. Excess ammonia can contribute to eutrophication, and at high concentrations, is toxic to aquatic organisms (Cavanagh et al. 1998b). Like nitrate/nitrite, seasonal fluctuations in ammonia concentrations are a result of variation in algal/macrophyte growth and bacterial decomposition, particularly in eutrophic waters. In a study of 75 small streams behind impoundments, ammonia was the most frequently elevated nutrient (Arnwine 2006). Elevated ammonia concentrations can also indicate the presence of a pollution source such as sewage or fertilizer.

Total ammonia measures concentrations of the un-ionized (NH₃) and ionized (NH₄⁺) forms of ammonia, which exist at equilibrium in water. Higher temperatures, and particularly increased pH, favour the formation of NH₃, which is the more toxic of the two ammonia species (CCME 2010). Because of this difference in toxicity, it is important to have measures of both components of total ammonia. These can be calculated from total ammonia data, provided water temperature and pH are measured at the same time water samples are collected for analysis.

CCME (2007 and 2010) provide additional information on nutrients and ammonia, respectively, and their effect on aquatic life.

9.12.2. Indicator and methods

Total Ammonia (NH₃ & NH₄⁺) measured in mg/L.

Determination of total ammonia concentrations requires the collection of bottled water samples for laboratory analysis. In addition, water temperature and pH must be measured for each sample to allow accurate calculation of the un-ionized ammonia (NH₃) concentrations.

9.13. Nitrogen (total kjeldahl)

9.13.1. Description and rationale

Total Kjeldahl Nitrogen (TKN) is the sum of organic nitrogen, ammonia (NH₃), and ammonium (NH₄⁺) in water. When nitrate/nitrite, total ammonia, and TKN samples are collected together, they can be used to calculate:

• Organic Nitrogen: Organic nitrogen = TKN – total ammonia
• Total Nitrogen: Total nitrogen = TKN + nitrate + nitrite

Organic nitrogen includes waste products from animals and plants; amino and nucleic acids, polypeptides, urine, and products of their transformation, such as humic and fulvic acids. Bacterial decomposition of these wastes produces ammonia, increasing nutrient availability for algae and macrophytes. Organic nitrogen fluctuates seasonally, largely due the dynamics of primary production, decomposition, and the cycling of nutrients through the food chain (Chapman and Kimstach 1996).

Total Nitrogen is a measure of both dissolved and particulate nitrogen compounds, including nitrate/nitrite, ammonia and ammonium, and organic nitrogen. Increases in organic and total nitrogen concentrations may result from eutrophication or from the presence of anthropogenic pollution such as sewage, so measuring Kjeldahl nitrogen along with nitrate/nitrite and ammonia can provide indicators for changes in ecosystem productivity and potential sources of ecological stress in water bodies.

CCME (2003c and 2007) provide additional information on nitrogen and its effects on aquatic life.

9.13.2. Indicator and methods

Total Kjeldahl Nitrogen measured in mg/L.

Determination of total Kjeldahl nitrogen concentration requires the collection of bottled water samples for laboratory analysis.

9.14. Organic matter

9.14.1. Description and rationale

Organic carbon represents an important complex of substances that affect a wide range of physical, chemical and biological processes in aquatic ecosystems. In natural freshwater systems, nearly all organic carbon is in the forms of dissolved and particulate organic carbon (DOC and POC respectively) which are primarily derived from terrestrial products of photosynthesis (Wetzel 1983).

Dissolved organic carbon is a measure of a wide range of plant and animal-derived organic compounds that have sufficiently broken down to become dissolved in water. In most natural waters, DOC is the predominant form of organic carbon (The ratio of DOC/POC is typically 6:1 to 10:1.) (Wetzel 1983). This terrestrially-derived (allochthonous) dissolved organic carbon, which enters aquatic systems through precipitation, leaching, and decomposition, is the primary source of external carbon loading in fresh waters (Wetzel 1983). In contrast, dissolved organic carbon produced by phytoplankton, algae, and macrophytes accounts for only a very small proportion of a water body’s total organic carbon (Gergel et al. 1999).

Dissolved organic carbon plays a central role in the chemical and nutrient dynamics of freshwater systems. Reductions in DOC can affect a water body’s pH and alkalinity (Dillon and Molot 1997), making it more susceptible to acidification and influencing the cycling of trace metals and their uptake by aquatic organisms. At higher concentrations, DOC forms complexes with trace metals, reducing their toxicity (Moore 1998) and with organic contaminants like PAHs and PCBs, reducing their bioavailability (Broman et al.1996). DOC also influences the availability of phosphorus and ammonium in fresh waters (Bushaw et al. 1996; Moore 1998).

Some components of dissolved organic carbon, like humic acids, affect water color and transparency. These characteristics, in turn, affect water temperature, the ability of water to attenuate harmful UV radiation, and the depth of the euphotic zone, potentially leading to changes in algal community composition and primary production.

Dissolved and particulate organic carbon (DOC and POC respectively) are important components in the carbon cycle and serve as a primary food sources for aquatic food webs (Moore 1998). Organic carbon, in particular, provides a source of energy and nutrients for the microbial food web (Moore 1998). However, high levels of organic carbon can increase bacterial metabolism to the point where it affects dissolved oxygen levels, leading to hypoxia or anoxia.

Changes in the quality and quantity of organic carbon entering an aquatic system can alter the relative contributions of phytoplankton, macrophytes and benthic algae to the organic carbon pool (Wetzel 1983) and dramatically affect the composition of fish and invertebrate communities. For example, macroinvertebrate communities in systems with high inputs of particulate organic carbon tend to have higher proportions of shredders and detritivores than systems with lower amounts of POC (Moore 1998). Recent studies suggest that even small increases or decreases in organic carbon inputs can produce adverse affects on aquatic ecosystems. Because in-stream developments have the potential to alter nutrient dynamics within the river system, including organic carbon inputs and cycling, the assessment and monitoring of DOC is highly recommended.

9.14.2. Indicator and methods

Dissolved organic carbon measured in mg/L.

Determination of dissolved organic carbon (DOC) concentrations requires the collection of bottled water samples for laboratory analysis.

9.15. Primary production

9.15.1. Description and rationale

Chlorophyll is present in most photosynthetic organisms. Chlorophyll measurements, usually in the form of chlorophyll-a concentrations, provide an indirect measure of algal biomass and an indication of the trophic status of a water body.

The growth of planktonic algae is related to the presence of nutrients (primarily N and P), temperature, and light. Therefore, concentrations of chlorophyll fluctuate seasonally and even daily, or with water depth, depending on environmental conditions. Waters with low levels of nutrients (oligotrophic) have low chl-a concentrations, while those with high levels of nutrients (eutrophic) have high concentrations (Chapman and Kimstach 1996).

Changes in primary productivity can strongly affect aquatic community composition and functioning. In reservoirs, for example, long water residence times combined with increased nutrient loading may cause severe eutrophication (Maybeck et al. 1996). The death and decomposition of increased algal and macrophyte biomass resulting from eutrophication may dramatically reduce dissolved oxygen concentrations, and in severe cases cause hypoxia or anoxia. Eutrophication can also cause the release of gaseous NH₃, which is highly toxic to fish (Maybeck et al. 1996).

9.15.2. Indicator and methods

Chlorophyll-a concentration (µg/l)

Specific sampling protocols for Chlorophyll-a include

• Obtain weekly samples during the open water period.

Chlorophyll-a concentrations can be measured in the field using a hand-held or in situ fluorometer, which measures the amount of fluorescence given off when chlorophyll-a is excited by a blue light, or water samples can be taken and analyzed in the laboratory.

Recommended data collection method – Although laboratory analysis is the most accurate way to determine chlorophyll-a concentrations, the collection, transport, and analysis of bottle samples is time consuming and can be expensive, making the collection of multiple or time series samples impractical. Use of an accurate fluorometer is recommended because they are simple to use in the field, can take multiple samples cheaply and easily (including depth profiles), and can be used to remotely collect time series. However, for quality control and to establish a relationship between chlorophyll-a and fluorescence, intermittent collection of water samples to verify the instrument’s readings is recommended.

9.16. Post alteration monitoring

Sampling design and frequency for post alteration monitoring are described in Chapter 1. Monitoring for all indicators should be conducted at the same sites used for field-based assessment and should follow the data collection protocol described in Section 6, unless specifically noted in the details for each indicator.

For post-alteration monitoring, it may be possible to reduce sampling intensity based on pre-alteration data:

• If the samples collected from multiple depths aren’t significantly different, a single sample from a representative depth can be taken.
• If the data from stations along a transect aren’t significantly different, a single representative sampling site can be established at mid-stream or another convenient sampling location.
• If evaluation of the data indicates it is appropriate, weekly or targeted monitoring during high or low flow periods may not be necessary for some indicators.

Chapter 5: Thermal regime

1.0 Introduction

Thermal regime is of central importance in sustaining the ecological integrity of aquatic ecosystems and limits the distribution and abundance of riverine species. Water temperature has been described as the ‘abiotic master factor’ for fishes (Brett 1971; Poff et al.1997) and as an ecological resource (Magnuson et al. 1979). Temperature influences overall water quality, nutrient and ice dynamics, and the metabolic activity, growth, timing of migration and spawning events. Species-specific thermal preferences and tolerances define thermal habitat. Recently, the “natural thermal regime” and its components: magnitude, frequency, duration, timing and rate of change, have been acknowledged as fundamental ecological variables (Chu et al. 2009; Olden and Naiman 2010) that should be included in environmental flow management.

This chapter describes a series of steps for collecting and analyzing a baseline set of data that can be used to characterize the thermal regime of a river prior to an alteration. The same set of indicators can also be used to monitor thermal regime following an alteration. Models and information are provided to predict the effect of an in-stream development on thermal regimes immediately below the structure and downstream in the zone of influence.

2.0 Rationale

In-stream development such as dams can alter thermal regimes and impact biota (see review by Clarke et al. 2008). Depending on dam design and operation, reservoir morphology, and whether a dam is top or bottom draw or a mix of both, water temperatures can increase, decrease, or match natural variation. For example, bottom- draw dams in thermally stratified reservoirs tend to increase temperatures in winter, lower them in summer, fluctuate less diurnally and seasonally, and exhibit seasonally displaced maxima (Table 1; Figure 1). Downstream of the dam, water temperature begins to adjust but the rate of change back to natural conditions is dependent on discharge (Figure 2). Peaking waterpower operations operate to synchronize with electricity demand which normally means high discharge during the day. If coupled with a hypolimnetic draw, minimum diurnal temperatures often occur with peak daytime discharges (Ward and Stanford 1979). Alternatively, a top-draw dam can increase temperatures in the summer and at night (Table 1). In coolwater systems affected by top-draw dams, streams may not be able to shed added heat during the summer and downstream water temperatures may continue to warm due to normal stream heating processes. A run-of-the-river facility may not alter the thermal regime depending on the size of the dam and location of water release.

Cold water releases may delay natural seasonal changes in river temperature and reduce the range of temperature variation, both seasonally and diurnally. These alterations to the thermal regime can have consequences for ecosystem condition (Haxton and Findlay 2008; Olden and Naiman 2010) including a reduction in ecosystem productivity and biodiversity, alteration of species’ metabolic rates, interference with breeding cycles, and a decrease in the development and survival of the eggs and larvae of fish and aquatic insects.

Altering temperature can change community composition as thermal limits are reached, alter predation and competition dynamics (Smith 1972), and facilitate the establishment of invasive species (Dunham et al. 2002). Thermal regime alterations may also result in strong compensatory strategies, such as delayed spawning by adults or slowed development by embryos (Olden and Naiman 2010). Changes in fish growth rates can result in biodilution or bioaccumulation of mercury in fish tissue (Simoneau et al. 2005). Warmer winter and spring temperatures from a bottom draw discharge can influence insect growth leading to earlier emergence and increased mortality when the terrestrial environment is snow-covered and weeks away from representing conditions for which the insect are adapted (Raddum 1985). Elevated temperatures decrease the concentration of dissolved oxygen in water while increasing metabolic rates, which may limit the scope of activity (Evans 1990).

Ultimately, the effects of altering water temperature are not straightforward. For example, Holtby (1988) found that logging increased winter water temperature and growth of juvenile salmon. While this alteration might be seen as beneficial, higher growth resulted in earlier outmigration, reduced marine survival, and a reduction in the number of returning spawners.

Large and sudden changes in water temperature (thermopeaking) below dams may cause thermal shock and death in aquatic biota (Donaldson et al. 2008). Evidence suggests the response to thermal shock is highly dependent on the acclimation temperature, the magnitude of the temperature change, and the final endpoint value (Threader and Houston 1983; Thomas et al. 1986; Tang et al. 1987). Sub-lethal effects have also been noted for smaller rates of change, including stress leading to metabolic dysfunction (Wedemeyer 1973), growth inhibition and disease (Wedemeyer and McLeay 1981), and increased predation (Coutant 1973) and polyploidy. Invertebrate drift may increase several fold during 2-4oC changes in temperature during thermopeaking (Carolli et al. 2011). Slower rates of heating or cooling can provide a period of acclimation to facilitate physiological adjustment (McCullough 1999). When flow is low and temperatures are high, hypolimnetic releases during peaking operations can cause rapid and large changes in downstream temperature multiple times per day (Ward and Stanford 1979). When flow is lower at night, as is often the case with peaking waterpower dams, water temperatures will be greater than during the day, which is opposite to the diurnal temperature fluctuations of an natural system (Flodmark et al.2004).

Temperature determines the formation, persistence, and break-up of river ice, which help define the physical character of rivers and fish habitat. Long Canadian winters represent a critical period that heavily impacts overwinter survival and community dynamics of fishes (Cunjak et al. 1998; Scruton et al. 2005). Increased winter temperatures below reservoirs can prevent the formation of ice cover, an effect shown to extend from 5 km (Webb and Walling 1996), 9 km (Ward and Collins 1974), to 32 km from the outlet (Lehmkuhl 1972). In some cases, higher winter temperatures can reduce ice-jam induced flooding, and consequently aquatic habitat availability on the floodplain (Peters and Prowse 2001; Beltaos et al. 2006), limiting ice scouring, resulting in changes to substrate composition and aquatic macrophyte dynamics (Rørslett et al. 1989). In contrast, reducing flow in the winter can result in lower than normal temperatures, increasing the formation of anchor ice and bottom scouring (Ward and Stanford 1979). Super-cooled water supports the formation and accumulation of frazil ice. Frazil ice can have direct deleterious effects on fish by damaging and plugging gill tissues and suffocating fish (Brown et al. 1993). In turbulent water, frazil ice and anchor ice can form to the extent that it occludes the river channel. As anchor ice thickens, it can become buoyant and float away, often taking parts of the substratum with it, including fish eggs. Frazil ice can also accumulate beneath the ice sheet of slower reaches of the river, forming hanging dams, which can fill most of the volume of pools and eliminate living space for fish (Cunjak and Caissie 1993).

In bypassed channels, a reduction of flow can increase water temperatures. The bypass will have less water and riparian vegetation to provide shade, potentially increasing the rate of warming and leading to more extreme temperature ranges.

3.0 Indicator summary

4.0 Data collection

The ability to capture seasonal and interannual variability in the thermal regime and accurately estimate statistical properties like mean monthly temperature improves as the number of years of data available for analysis increases. It is recognized that the timeframe for the collection of pre-development data are often limited. In these situations, pre-construction data collection over the longest period possible is recommended - ideally a minimum of 2 to 3 years - recognizing that uncertainty increases as the number of years of data decreases.

Temperature loggers should be deployed to provide a continuous measurement of temperature for the entire year. It is recommended that one of the following factors of 60 minutes is used: 5, 10, 15, 20, 30 or 60 minutes, with 30 minutes being preferred since it provides the optimum combination of temporal resolution and logger memory utilization. Longer time intervals may miss daily minima and maxima. It may be advantageous to sample at even shorter intervals (e.g. 15 mins) in small, flashy rivers. To simplify analyses, loggers should be synchronized in time, preferably on the hour or half hour e.g. 13:00, 13:30. For field and laboratory procedures on deploying data loggers, see technical guide by http://www.mnr.gov.on.ca/stdprodconsume/groups/lr/%40mnr/%40aquatics/documents/document/stdprod_068478.pdf [link inactive] (Jones and Allin (2010)).

To capture the within river variation in temperature (natural or existing thermal regime), five data loggers should be placed in the thalweg as noted in Chapter one. Three loggers should be deployed upstream of the in-stream structure past the predicted limit of backwater. If conditions prevent such placement, then three loggers can be placed in a neighbouring natural river with similar physiography and climate. Data from a natural system can be used to separate the effects of annual variability in temperature (hot vs. cold years) from other factors affecting temperature, and assist in yearly comparisons. For existing structures with a reservoir, data loggers should be placed upstream of the maximum extent of the inundation area and five loggers downstream from the structure as described above.

5.0 Thermal regime characteristics, indicators, and assessment criteria

The following sections provide a suite of indicators that can be used to determine thermal characteristics of the ecosystem (Table 2). Each characteristic includes a rationale, description, assessment criteria, and information for evaluating alteration.

Use existing information, if available, to establish an understanding of thermal regime. In many cases information is available but perhaps dated or collected using unidentified means. Traditional ecological knowledge can also help to understand historical and present day characteristics. If appropriate data are not available, or if the available information suggests the medium or high level of alteration, then the collection of field data is recommended to more accurately characterize current conditions.

Most of the indicator metrics and assessment criteria described below can be obtained using the software tool ThermoStat (Jones and Schmidt 2011), which is available online. The recommended methods are written with this in mind; however, all processing steps can be done manually if desired.

5.1 Thermal classification

5.1.1 Description and rationale

Classifying rivers and their reaches by the thermal requirements of fish is a useful preliminary assessment tool. Fish are good integrators of environmental conditions, so the thermal classification of a river is frequently defined by the thermal preferences and tolerances of the fish that inhabit it (i.e. warmwater, coolwater, and coldwater). This provides a simplistic representation of thermal regime. It will not provide information about other ecologically important aspects of temperature such as spatial/temporal variation and rates of change. Caution must be taken, fish and other organisms may exploit or trade-off habitat preferences to minimize the impacts of changing conditions. Migratory species add complexity simply due to their life history. Consider ground truthing by direct sampling of the fish community.

5.1.2 Indicator

Proportion of the temperature record above 25°C (warmwater), between 19-25°C (coolwater), and below 19°C (coldwater) (Coker et al. 2001) during June 1 to August 31.

5.1.3 Information requirements

There are several approaches, qualitative and quantitative, to estimate thermal class including existing knowledge (OMNR and traditional ecological knowledge), existing temperature information, and rapid field techniques described by Stoneman and Jones (1996) (also OSAP Stanfield 2005, and more recently Chu et al. 2009). Direct measures of water temperature following the methods in Jones and Allin ( 2010) collected over 2-3 years likely provides the best approach. Calculate the proportion of the record above 25°C (warmwater), between 19-25°C (coolwater), and below 19°C (coldwater). The proportion of time within each thermal category will help establish a classification. Fish species composition can provide additional support to determine thermal regime e.g. brook trout in abundance suggests a coldwater thermal regime (see Coker et al. 2001); however, there are other drivers of community composition (see Section 6 Biology). Thermal regime prediction is also possible based on landscape characteristics summarized through GIS (percent riparian forest, mean annual air temperature, percent surface water area, and groundwater potential) (Chu et al. 2009).

5.1.4 Assessment criteria

Significant change in the duration in each of the temperature range bins <19°C, 19- 25°C, and >25 °C, relative to the reference or expected condition.

5.1.5 Evaluating alteration

A shift to a different thermal class (<19°C, 19-25°C, and >25°C) is considered a high alteration. The effects of a bottom draw dam will be high in a warm water river. The effects of a top draw dam on a cold water river will also be high. In contrast, the top draw dam may have little effect on a warm water river. Please review introductory sections and see reviews e.g. Clarke et al. (2008). In some rivers, cool thermal refugia such as groundwater seeps might be present which allow coldwater species, e.g. brook trout, to persist during brief periods of high temperatures.

5.1.6 Methods

This classification procedure determines the proportions of temperature measurements greater than 25°C (warmwater), greater than or equal to 19°C and less than or equal to 25°C (coolwater), and less than 19°C (coldwater) (Coker et al., 2001) during June, July and August.

1. Collect all records within the period June 1^st and August 31^st
2. Bin records into the three thermal classes of greater than to 25°C, greater than or equal to 19 and less than or equal to 25°C, and proportion less than 19°C.
3. Divide the number of records in each thermal class by the total number of records of all three classes (excluding null values) and multiply by 100 to get the percentage of each class.

5.2 Timing

5.2.1 Description and rationale

Water temperatures exhibit seasonal minima and maxima and daily temperature fluctuations that can be significant, particularly on wide and shallow rivers with little groundwater input (Caissie 2006). Most biota inhabiting lotic environments are adapted to diurnal fluctuations in water temperature, which naturally occur on a 24 hour basis (Hubbs 1972) usually reaching a minimum in the early morning hours and a maximum in late afternoon (Caissie 2006). The daily timing of events such as spawning, feeding, hatching and emergence, frequently correspond to these changes in temperature. Artificially stabilizing water temperatures could negatively affect some species whose body processes require a wide daily temperature range for optimal energetic efficiency (Lehmkuhl 1972; Sweeney 1978; Ward and Stanford 1979). For example, spawning fishes and the subsequent emergence and survival of their young, as well as the emergence of benthic invertebrates that may serve as a food source rely on variable temperature. A shift in the annual timing of minimum and maximum temperatures may indicate a shift in the river’s entire thermal profile.

5.2.2 Indicator

Mean annual date of temperature maxima and minima. (Day-of-year, DOY)

5.2.3 Assessment criteria

Assessment criteria include the day-of-years (DOYs) that lie ± 2 weeks and ± 4 weeks from the mean annual date of temperature minima and maxima derived from the reference condition.

5.2.4 Evaluating alteration

The degree of alteration can be determined as follows:

Low alteration: Estimated degree of alteration in mean annual date of temperature min/max is < 2 weeks

Medium alteration: Estimated degree of alteration in mean annual date of temperature min/max is ≥2 weeks and ≤ 4 weeks

High alteration: Estimated degree of alteration in mean annual date of temperature min/max is ≥ 4 weeks

5.2.5 Indicator

Monthly modal hour of daily temperature maxima and minima

5.2.6 Assessment criteria

Assessment criteria include the monthly modal hour of daily maximum and minimum temperature that lie ± 2 hours and ± 6 hours from the monthly modal hour of daily temperature maxima and minima derived from the reference condition.

5.2.7 Evaluating alteration

The degree of alteration can be determined as follows:

Low alteration: Estimated degree of alteration in monthly modal hour of min/max temperature is < 2 hours

Medium alteration: Estimated degree of alteration in monthly modal hour of min/max temperature is ≥ 2 hours and ≤ 6 hours

High alteration: Estimated degree of alteration in monthly modal hour of min/max temperature is > 6 hours

5.2.8 Methods

Annual: This procedure determines a list of the dates of annual maxima and minima for each year within the period of record. The output is a list of minimum and maximum dates for each year of the record in “dd/mm/yyyy” format.

Bin all records into years (one bin for each calendar year). Determine the date of occurrence associated with each bin’s minimum temperature and maximum temperature (a single mean value of these dates can be calculated using the day-of year).

Note: Using partial years that have a large proportion of null data will produce less meaningful results.

Daily: This procedure determines the most common time a stream’s minimum and maximum temperature occur on a daily basis (i.e. daily high and low points in daily temperature). The output is two (i.e. minimum and maximum) modal hours of occurrence for each month.

Bin all record into months (12 bins). Determine the time of occurrence of the daily (midnight to midnight) minimum and maximum for each day within each bin. Days that have no significant troughs or peaks should not be included in the analysis since these will produce unreliable minima/maxima timing results. For example, winter days where temperature hovers around 0°C or cooling/warming trend days where temperature declines/rises steadily from midnight to midnight. Winter days that exhibit near flat-line temperature conditions can be identified as having a daily range of less than 0.25°C. If multiple minima/maxima (troughs/peaks) occur within one day, the lowest/highest minima/maxima should be used to calculate the timing. If minima/maxima include several consecutive equal temperature values (e.g. plateaus) then the earliest time of occurrence should be assigned to that minima/maxima. Bin the gathered times of minima/maxima occurrence for each month into hourly bins (e.g. 13:00 to 13:59, 14:00 to 14:59 etc.) Calculate the mode of all the daily minima and maxima occurrence hours within each monthly bin (i.e. the hourly bin within each month with the most occurrences). If two or more hourly intervals contain equal number of occurrences then the earliest hour interval is reported.

5.3 Magnitude

5.3.1 Description and rationale

Maximum and minimum temperatures provide information on seasonality in temperatures. This information is useful in assessing the shape of the annual pattern of temperature change and is key for defining species’ thermal habitat. Alteration in minimum and/or maximum temperatures can lead to species specific changes in abundance (e.g. loss of warmwater species of fish) and can directly impact survival of aquatic organisms especially for those with narrow temperature preferences (e.g. if a river approaches the upper or lower lethal temperature for a fish species prior to construction, the effects of an in-stream development on the thermal regime become more of a concern especially if the structure limits access to traditional thermal refugia). Temperature also determines the formation, persistence, and break-up of river ice, which help define the physical character of rivers and fish habitat. Winters represent a critical period that heavily impacts survival and community dynamics of fishes (Cunjak et al. 1998; Scruton et al. 2005). In-stream developments can lead to frazil and anchor ice, or prevent the formation of ice cover for several kilometres downstream. Ice dynamics including ice jams, frazil and anchor ice are natural disturbances, like floods, that help maintain biodiversity and for which fishes are adapted.

5.3.2 Indicator

Mean annual temperature maxima and minima

5.3.3 Assessment criteria

Assessment criteria include mean annual minimum and maximum temperatures that lie ±1°C and ±2°C from the mean annual minimum and maximum temperatures derived from the reference condition.

5.3.4 Evaluation alteration

The degree of alteration can be determined as follows:

Low alteration: Estimated degree of alteration is ≤ +1.0° C of mean annual min/max

Medium alteration: Estimated degree of alteration is between +1.0°C - 2.0°C of mean annual min/max

High alteration: Estimated degree of alteration is ≥ +2.0°C of mean annual min/max

5.3.5 Indicator

Monthly means of daily temperature minima and maxima

5.3.6 Assessment criteria

Assessment criteria include mean monthly minimum and maximum temperatures that lie ±1°C and ±2°C from the monthly modal hour of daily temperature maxima and minima, derived from the reference condition.

5.3.7 Evaluating alteration

The degree of alteration can be determined as follows:

Low alteration: Estimated degree of alteration is ≤ +1.0°C of mean monthly temperature min/max

Medium alteration: Estimated degree of alteration is between +1.0°C - 2.0°C of mean monthly temperature min/max

High alteration: Estimated degree of alteration is ≥ +2.0°C of mean monthly temperature min/max

5.3.8 Methods

Annual: This procedure determines the mean annual minimum and maximum temperatures. The output is two values (i.e. averages of all annual minima, averages of all annual maxima). Bin all records into annual bins (one bin for each calendar year) Determine the minimum and maximum temperature value within each bin. Calculate the average of both the minima and maxima within each annual bin.

Daily: This procedure determines the monthly means of daily minimum and maximum temperatures. The output is 24 values: 12 monthly average minima and 12 monthly average maxima. Bin all record into months (12 bins). Determine the daily minimum and maximum for each day within each bin. Days that have no significant troughs or peaks should not be included in the analysis since these will produce unreliable min-max results. For example, winter days where temperature hovers around 0°C or cooling/warming trend days where temperature declines/rises steadily from midnight to midnight. Winter days that exhibit a near flat-line temperature conditions can be identified as having a daily range of less than 0.25°C. If multiple troughs/peaks occur within one day, the lowest/highest troughs/peaks should be used to calculate the mean monthly min/max temperatures. Calculate the average of all the minima and all the maxima.

5.4 Variability

5.4.1 Description and rationale

The daily pattern of water temperature consists of a minimum and a maximum temperature and the pattern resembles a sinusoidal curve. The timing of events such as feeding, hatching and emergence frequently correspond with daily changes in temperature. Most biota inhabiting lotic environments are adapted to diurnal fluctuations in water temperature, which naturally occur on a 24 hour basis (Hubbs 1972), usually reaching a minimum in the early morning hours and a maximum in late afternoon (Caissie 2006). The daily timing of events such as spawning, feeding, hatching and emergence, frequently correspond to these daily changes in temperature. Artificially stabilizing water temperatures could negatively affect some species whose body processes require a wide daily temperature range for optimal energetic efficiency (Lehmkuhl 1972; Sweeney 1978; Ward and Stanford 1979). For example, spawning fishes and the subsequent emergence and survival of their young, as well as the emergence of benthic invertebrates that may serve as a food source rely on variable temperature.

5.4.2 Indicator

Mean Annual Temperature Range

5.4.3 Assessment criteria

Assessment criteria include mean annual temperature range that lie ±1°C and ±4°C from the mean annual temperature range derived from the reference condition.

5.4.4 Evaluating alteration

The degree of alteration can be determined as follows:

Low alteration: Estimated degree of alteration is ≤ +1.0°C of mean annual temperature range

Medium alteration: Estimated degree of alteration is between +1.0°C - 4.0°C of mean annual temperature range

High alteration: Estimated degree of alteration is ≥ +4.0°C of mean annual temperature range

5.4.5 Indicator

Monthly Means of Daily Temperature Range

5.4.6 Assessment criteria

Assessment criteria include monthly mean of daily temperature ranges that lie ± 1°C and ± 4°C from the monthly mean of daily temperature ranges derived from the reference condition.

5.4.7 Evaluating alteration

The degree of alteration can be determined as follows:

Low alteration: Estimated degree of alteration is ≤ +1.0°C of monthly mean of daily temperature range for each month

Medium alteration: Estimated degree of alteration is between +1.0°C - 4.0°C of monthly mean of daily temperature range for each month

High alteration: Estimated degree of alteration is ≥ +4.0°C of monthly mean of daily temperature range for each month

5.4.8 Methods

Annual: This procedure determines the mean annual temperature range. The output is one value representing the average of all annual ranges. Bin all records into years (one bin for each calendar year). Determine the minimum and maximum temperature value for each bin. Calculate the annual temperature range for each bin by subtracting the minimum temperature from the maximum temperature for each bin. Calculate the average of all the annual range values.

Daily: This procedure determines the monthly means of daily temperature ranges. The output is 12 values representing the monthly averages of all daily ranges. For each month, subtract the monthly mean daily minimum from the monthly mean daily maximum to arrive at the monthly mean daily ranges.

Note: because the daily minima and maxima described in section 4.3.8 are used to calculate the monthly means for daily temperature range, the results will reflect the exclusion of days that have no significant troughs or peaks

5.5 Rate of change

5.5.1 Description and rationale

Large and sudden changes in water temperature below in-stream structures can cause thermal shock in aquatic biota (Donaldson et al. 2008). Evidence suggests the response to thermal shock is highly dependent on the acclimation temperature (both constant and cyclic), the magnitude of the temperature shift, and the final endpoint value (Threader and Houston 1983; Thomas et al. 1986; Tang et al. 1987). Sub-lethal effects have also been noted for smaller rates of change including physiological stress leading to metabolic dysfunction (Wedemeyer 1973), growth inhibition and disease initiation (Wedemeyer and McLeay 1981) and increased predation (Coutant 1973). Slower rates of heating or cooling exposure can provide a period of acclimation to facilitate physiological adjustment (McCullough 1999).

5.5.2 Indicator

Monthly Mean of Daily Maximum Hourly Rates of Temperature Change (°C hr^-1). This examines the monthly means of daily maximum hourly +/- rates of change for the period of record.

5.5.3 Assessment criteria

Assessment criteria include monthly mean of daily maximum hourly rates of temperature change that lie ± 2°Chr-1 and ± 5°Chr-1 from the monthly mean of daily maximum hourly rates of temperature change derived from the reference condition.

5.5.4 Evaluating alteration

The degree of alteration in the indicator can be determined as follows:

Low alteration: Estimated degree of alteration is ≤ +2.0°C hr^-1 relative to the monthly mean of daily maximum hourly rates of temperature change

Medium alteration: Estimated degree of alteration is between +2.0°C hr^-1 - 5.0°C hr^-1 relative to the monthly mean of daily maximum hourly rates of temperature change

High alteration: Estimated degree of alteration is ≥ +5.0°C hr^-1 relative to the monthly mean of daily maximum hourly rates of temperature change.

5.5.5 Methods

This procedure determines the monthly means of daily maximum hourly +/- rates of change for the period of record. The output is 24 values representing the monthly averages of all daily maximum hourly positive and negative rates of change.

1. Resample the time series by removing all records with the exception of full hour records (e.g. 12:00:00, 13:00:00, 14:00:00 …).

   Note: Do not use hourly averages during resampling.

2. Calculate a hourly rate of change value between records by subtracting the next record from the current record (e.g. record (i+1) – record(i)).

   Note: Positive rates represent warming rates and negative rates cooling rates.

3. Bin all rates according to their sign (2 bins: 1 positive rate bin, 1 negative rate bin).

   Note: Zero rates are excluded since they cannot be classified into these bins.

4. Bin the records again with the previous bins according to month (24 bins: 12 positive monthly bins, 12 negative monthly bins).
5. Calculate the average of each bin.

5.6 Duration

5.6.1 Description and rationale

The thermal characteristics of a stream play an important role in defining the availability of species-specific habitat. Species-specific thermal preferences and tolerances are critical biological elements that define these thermal habitats. Shifting the thermal regime outside a species’ preferred thermal range or beyond its temperature tolerances can lead to changes in community composition and/or the loss of some species.

5.6.2 Indicator

Species-specific temperature duration (+2°C of preferred temperature)

Species-specific temperature duration ≥ lethal temperature during summer period

5.6.3 Assessment criteria

Assessment criteria include species specific temperature duration for preferred and lethal temperatures that lie ±5% and ±10% from the duration of preferred and lethal temperatures derived from the reference condition.

Change in species specific temperature duration ≥ lethal temperatures relative to the reference condition.

5.6.4 Evaluating alteration

The degree of alteration can be determined as follows:

Low alteration: Estimated degree of alteration is ≤ 0–5% of reference condition and/or preferred and lethal temperatures

Medium alteration: Estimated degree of alteration is between > 5 and ≤ 10% of reference condition and/or preferred and lethal temperatures

High alteration: Estimated degree of alteration is ≥ 10% of reference condition and/or preferred and lethal temperatures

5.6.5 Methods

This procedure calculates species-specific temperature durations for the range of +2ºC around the Final Temperature Preferrendum (FTP) and the duration of Upper Incipient Lethal Temperature (UILT) exceedance during the months of June, July and August (i.e. the summer period). The output is two percentage values for each species; one representing the proportion of the summer records that fall within the FTP range and one representing the proportion of summer records that exceed the UILT threshold.

Note: Species-specific temperature values for FTP and UILT are found in Hasnain et al. (2010). If a FTP value is not available, use the Optimum Growth Temperature (OGT) instead. If a UILT value is not available, use the maximum Critical Temperature (CTmax) value instead.

1. Collect all records that fall within the period of June 1^st and August 31^st.
2. Using the information from step (a), collect all records that fall within the FTP range of +2°C (inclusive).
3. Using the information from step (a), collect all records that are greater than or equal to the UILT threshold.
4. Calculate the proportion (%) of the number of summer records within the FTP range to the total number of summer records.
5. Calculate the proportion (%) of the number of summer records exceeding the UILT threshold to the total number of summer records.

Chapter 5: Thermal regime - appendix I

Data preparation

The temperature data time series must be processed before performing any calculations. This series of processing steps is necessary to detect any errors and to optimize the time series format for analysis and reporting. Unlike streamflow time series, which are readily available from standardized sources like the Water Survey of Canada, stream temperature data are often collected by individual agencies requiring this data, with no standardized oversight of the collection and reporting process. This often requires stream temperature data to be processed to some degree into a format that is suitable for numerical analysis by “logical” algorithms. It is important to note that although the following indicators can technically be calculated from very few data points, it is highly recommended that no more than 10% of the record be missing (i.e. null data) within each intra-annual analysis period (i.e. seasons and months).

These processing steps may be performed manually. Alternatively, all indicator metrics and assessment criteria can be obtained automatically using the software tool ThermoStat.

Sampling intervals

The data sampling interval determines the temporal resolution of the time series. It is recommended that one of the following factors of 60 minutes is used: 5, 10, 15, 20, 30 or 60 minutes, with 30 minutes being preferred since it provides the optimum combination of temporal resolution and logger memory utilization. Note that if multiple, sequential time series are to be analyzed as a whole they must share a common sampling interval.

Synchronization

The data time stamps must start at a common time on exactly a full hour (e.g. 12:00:00). This makes a direct comparison between multiple time series possible (e.g. from different sampling sites). Ideally, a field data logger should be set up to collect data using this criterion. However, if this is not the case, the time stamps must be synchronized by “rounding” them up or down. In order to minimize the “distance” the time stamps need to be shifted, the shift should be in the direction of the nearest whole multiple of the sampling interval. For example, consider the following series of 30 minute interval data: 12:11:45, 12:41:45, 13:11:45 etc. This should be shifted backward by 11 minutes and 45 seconds to 12:00:00, 12:30:00, 13:00:00 etc Now consider this series: 12:15:00, 12:45:00, 13:15:00 etc. This series sits right on the dividing line between shifting forward or backward. In this type of scenario the times should be shifted backwards to 12:00:00, 12:30:00, 13:00:00, etc. Following this rule will ensure all temperature data are processed in the same way, allowing for more consistent comparisons between data sets. Note that the largest shift introduced using this method will be one half of the sampling interval.

Duplicate records

Data loggers often automatically adjust their time stamps for daylight savings time changes resulting in “duplicate” time stamped records being introduced into the time series. Duplicates must be corrected or deleted.

Below zero days

Negative temperatures are assumed to be the result of less than ideal logger installation, resulting in the logger being embedded in ice during parts of the winter. ThermoStat will accept this data but set these records to 0°C.

Missing records

Missing records are gaps in the data. These gaps must be filled; either by inserting null data, or by another suitable data gap filling technique. When the sampling interval is 60 minutes or less it is possible to estimate single record gaps using linear interpolation of neighbouring data. Gaps longer than one record require more complex gap filling methods.

Leap day records

Temperatures recorded on leap days must be removed to facilitate the numerical analysis of intra-annual time periods of seasons and months. Note that since stream temperatures in Ontario are very likely to be stable (around 0ºC) at the end of February the programming advantages greatly outweigh any disadvantages of removing these “leap” records. Also, removing one day of observations is not likely to impact the analyses from a statistical perspective.

Out-of-water days

Out of water days occur when the water level drops to the point that a logger is exposed to ambient air temperatures. This often results in much larger diel temperature fluctuations than normal for the stream and will adversely affect subsequent analyses. Days with a temperature range exceeding a site dependent threshold can be used to ascertain whether a logger was out-of-water and such days should be removed (i.e. set to null) prior to analysis.

Partial start and end years

Full years of data facilitate partitioning of the time series into seasons and months, which are then analyzed as collections of these periods. For partial start and end years, null records (i.e. no data) serve as placeholders, allowing the time series to remain continuous and permitting the inclusion of these partial years during analysis.

Full leading and trailing year padding

In addition to padding the data to complete partial start and end years it is also necessary to add a full year of null values to the beginning and end of the time series. This is required for analysis of winter seasons that span the end of the calendar year (i.e. December 31). This also allows the autumn season to end before December 31.

Chapter 6: Biology

1.0 Introduction

This chapter describes a process to assess ecosystem change resulting from in-stream development. The data from this process can also be used to monitor ecological characteristics following alteration. The focus in this chapter is on the section of river downstream from an in-stream structure; however, a similar approach and methods can be used in bypassed channels and upstream of the structure. The creation of a reservoir or inundation of a lake is not covered in this chapter.

2.0 Rationale

River ecosystems include a diversity of biotic life that is adapted to the unique dynamics of rivers. Development activities that alter the passage of fish, hydrologic, thermal, chemical, or sediment regimes in rivers will have effects on riverine biota and their habitat. In general, impoundments trap sediments and disrupt the natural process of sediment movement and deposition in the river. In turn, water clarity may increase below dams (Allan and Castillo 2007). Changes to thermal and flow regimes can substantially alter community composition and productivity. Reservoirs typically allow higher levels of primary production than rivers. Organic material trapped in the reservoir releases nutrients and dissolved organic carbon that can lead to large amounts of seston (ultra fine particulate material including phytoplankton and zooplankton). Much of this organic matter drifts downstream of the structure and often feeds a large and productive community of filter feeding invertebrates and fishes. These organisms quickly remove particles, creating a longitudinal (upstream-downstream) gradient in system productivity. In addition to seston, changes in sediment size and water temperature are the primary factors that develop longitudinal zonation (Ward and Stanford 1983). On a temporal scale, the effects of in-stream developments can be immediate (i.e. behavioural responses to flow changes), of moderate term (i.e. changes to biota, communities), and long-term (i.e. geomorphological evolution of the river) (Stoneman 2005).

Many have noted how waterpower facilities affect fish and benthic invertebrates (e.g. Armitage 1984; Dewson et al. 2007; Haxton and Findlay 2008; Murchie et al. 2008). In general, previous studies reported decreases in fish and invertebrate abundance and/or richness and discontinuities in longitudinal zonation (see Ward and Stanford 1979). The response of biota, however, to different in-stream developments and environmental contexts, varies greatly. Fewer studies have focused on the effects of intermittent peaking flows. The addition of other stressors, e.g. invasive species, may confound responses in the dynamics of nutrients and the biological community.

Fish species are often valued ecosystem components (VEC) within rivers and their population status is often a primary socioeconomic interest. However, fish communities depend on the function of lower trophic levels. Primary production supports higher trophic levels by providing food (plants and organic matter) and physical habitat structure. Invertebrates play an essential role in processing and cycling nutrients within ecosystems and pass this energy to fish. The use of single species in assessments, e.g. fish, has been frequently criticized for a lack of comprehensiveness in evaluations of ecosystem condition. Modern monitoring programs have embraced a multi-trophic, ecosystems approach. However, there may also be a need or interest to conduct targeted assessments for VEC species or species at risk.

3.0 Indicator summary

4.0 Establishing a reference

In unaltered rivers, current conditions can be used to establish a natural reference for biological indicators but in systems that have already been altered, there will often be insufficient information to do so. As a result, the current condition will serve as the reference condition for assessing potential changes in most biological indicators. Further information on establishing a reference can be found in chapter one, section 3.4.

5.0 Sampling fish

The status of fish and fish populations reflect the health of ecosystems. Fish are relatively long-lived, require distinct habitats during various life history stages, and are generally sensitive to environmental stressors and pollutants and, as such, they integrate the effects of their environment. Many fish occupy high trophic positions, and rely on production in lower trophic levels. As a result, fishes are one of the most commonly used biological indicators in aquatic environments. A variety of species are usually present in freshwater systems, and many species are important for social and economic reasons. It is common to monitor a single fish species of economic or recreational value, or a set of fish community parameters to measure the effects of human alteration on river systems. The environment may affect each life history stage differently.

Spatial considerations

It is important to know what species use the zone of influence, and where and when use happens. Techniques for sampling abiotic and biotic variables in riverine systems are not as well developed as those used in lakes (Flotemersch et al. 2006). While there are few methods for sampling rivers, there are even fewer that specifically address sampling issues in altered rivers where flows fluctuate daily (Jones 2011a, b). In these types of rivers, the lateral areas of riverbed that are routinely wetted and dried create an “intertidal” (Fisher and LaVoy 1972) or varial zone (Lorang et al. 1993). Many have also noted longitudinal gradients in biotic indicators associated with changes in food sources, water temperature, and substrate composition in natural rivers (Vannote et al. 1980; Naiman et al. 1987), altered rivers (Ward and Stanford 1983), and lake outlet systems (Jones 2010). Recognizing the existence and extent of longitudinal and lateral gradients is essential for defining methodological approaches, experimental designs, and the development of monitoring programs.

Temporal considerations

The environmental conditions of rivers are strongly influenced by annual and seasonal variation. Annual variation includes dry and hot years, average years, and wet and cold years. These annual variations in weather can influence fish movement patterns and year-class strength. The seasonality of rivers is well documented. Spring and fall are times of larger flows, colder temperatures, and spawning and overwintering migrations. For example, many tributaries to Lake Superior see thousands of suckers migrate upstream each spring, but by July, most of these rivers are low and contain much fewer fishes. In the fall, many trout, salmon, char, and whitefish ascend these rivers to spawn or overwinter. Observation and sampling only during the summer would result in a large underestimate of use of the river by fishes.

Sampling in rivers can be intimidating and difficult due to the logistical considerations and safety risks associated with high-energy flows. Due to the variability in habitat types, depths, and flow conditions within the zone of influence of a proposed development, a single sampling method is generally not sufficient to provide a representative sample of the community. Professional judgement is required to determine the best suite of methods to measure habitat and sample biota based on the characteristics of the system and the species and life stages sought. The use of standardized techniques is, however, important to provide data that is comparable over time and among systems.

Methods for collecting fish community data in rivers and reservoirs are described in the American Fisheries Society “Standard methods for sampling North American freshwater fishes” (Bonar et al. 2009), the Riverine Index Netting (RIN) manual (Jones and Yunker 2009) and standardized OMNR techniques. Johnson et al. (2007) provide an excellent account of field protocols for sampling salmon and trout in rivers (e.g. boat electrofishing, snorkel surveys).

Electrofishing

Electrofishing using a backpack, shore-side shocking unit or boat are common methods for collecting fishes. Boat electrofishing is possible in deeper rivers with suitable water conductivities and relatively shallow depths (<3m) which allow penetration of the electric field (Carl personal communication). For larger rivers, Jones (http://www.mnr.gov.on.ca/stdprodconsume/groups/lr/%40mnr/%40aquatics/documents/document/stdprod_093462.pdf">2011a [link inactive]) has developed a protocol for sampling the near-shore fish community in wadeable portions of the river. This protocol acknowledges that regulated rivers can have strong longitudinal and lateral gradients in fish abundance that must be considered when developing a sampling plan.

This protocol also works well in rivers with low water conductivity where boat electrofishing is unsuitable. The Ontario Stream Assessment Protocol (OSAP) (Stanfield 2005) incorporates a standard backpack electrofishing procedure for use in wadeable streams (<1m).

Netting protocols

Most netting protocols have been developed for use in lake environments and may present challenges when used in riverine environments due to water flow. The River Index Netting protocol (RIN) is a recommended netting protocol for sampling of fishes in Ontario (Jones and Yunker 2009). The protocol is designed for use in slowly flowing rivers (sections) that cannot be sampled by electrofishing. This net is the same as the North American standard (Bonar et al. 2009), but is shorter in height (0.9m). Research by Jones and Yunker (2011) found that most fish (87%) were captured in the lower half of 1.8-m-high gill nets.

Seining fishes

In shallow (<1.5m), wadeable sections of rivers, beach seining may be used to collect fishes. Seining is a commonly used method in Ontario to sample fish communities in streams. Seining works well for rivers with a slow current and is not recommended in complex environments such as areas with dense aquatic vegetation or large rocky substrate (Freeman et al. 1984). It can be highly variable in capture efficiencies and is not typically as reliable as electrofishing (Poos et al. 2007). However, seining can be a good alternative to electrofishing when there are concerns about the effects of electrofishing on fish populations, especially if species at risk are present (Nielsen 1998). Seining methods can be found in Poos et al. (2007). This method was developed for Ontario streams and includes moving over obstructions in the stream.

Snorkelling

Snorkelling procedures have mainly been developed for use in coldwater rivers and streams. Snorkelling can be applied to streams or rivers that are deep enough to submerge a mask (20cm) and where visibility is not impaired (O’Neal 2007). It is most commonly used to estimate abundance of fish; however, it has been used to sample other characteristics of the community (e.g. habitat use, diversity). Although often selected as the best method to sample salmonids, snorkel surveys have also been used to sample benthic fishes using transects (Magoulick 2004). Use of snorkel surveys as a sampling method can be useful in rivers where conductivity is low or water too deep for electrofishing, or when it may be difficult to use traps or seining (O’Neal 2007). Snorkelling methods can be found in Dunham et al. (2009) and Curry et al. (2009).

Other protocols

Other sampling protocols are available that have not been tested in Ontario or in regulated rivers. For example, Johnson et al. (2007) and Bonar et al. (2009) provide a number of field protocols for sampling fishes in rivers (e.g. redd counts, weirs, larval fish drift nets, and screw-trap, hydroacoustics, aerial fish counts).

6.0 Biological characteristics, indicators, and analyses

The following sections describe a suite of indicators that can be used to determine ecological characteristics of the ecosystem (Table 2). Each indicator includes a rationale for its inclusion in the characterization process, a description of the indicator, and suggested sampling methods. Not all methods are appropriate for all river environments. However, in many cases, the collection of one sample can be used to calculate several indicators. For example, riverine index netting can provide information on presence/absence, community composition, and size structure of fish. In addition, it may be possible to conduct sampling for several indicators concurrently. Recommended analyses for each indicator are also identified in Table 2.

6.1 Fish presence and absence

6.1.1 Description and rationale

To accurately understand the ecological characteristics of a river system, its use by fishes must be assessed within the ZOI during spring, summer, and fall. The time when fish traditionally arrive, spawn and disperse must be known. This phenology can also be used in conjunction with thermal regime to predict activities of fish.

6.1.2 Indicator and methods

A list of fish species occupying the portion of the river expected to be influenced by the proposed development. This will include species that use the zone of influence for any portion of their life history throughout the year (e.g. spawning by migratory species) including essential areas such as spawning habitat.

6.2 Fish species index of abundance

6.2.1 Description and rationale

Riverine fish communities typically include a number of species that differ in life histories and habitat requirements for cover, feeding, spawning, and nursery areas, all of which can be affected by changes in the physical and chemical characteristics described in the previous chapters. Ecosystem alterations may result in loss of native fish species, a shift in species composition, or the introduction of non-indigenous species. The assessment and monitoring of fish community composition can provide a more comprehensive indication of ecological condition than any single species. However, there may be interest in collecting information about individual species if they are VECs or species at risk.

6.2.2 Indicator and methods

A list of fish species occupying the ZOI for any portion of their life history throughout the year (e.g. spawning by migratory species) including essential areas such as spawning habitat. Fish community composition is determined by field sampling providing catch per unit effort. Riverine Index Netting and shoreline electrofishing are likely the appropriate sampling methods and can be done singly or together.

6.3 Size structure of fish populations

6.3.1 Description and rationale

The size distribution of fishes is important for understanding growth and recruitment, both of which might be effected by changes in physical and chemical characteristics below in-stream structures. Length frequency distributions provide an important description of population structure.

6.3.2 Indicators and methods

Determine the size structure of fish populations (fork lengths in mm) for VEC, species at risk, or species of interest. Riverine Index Netting and shoreline electrofishing are likely the best sampling methods and can be done singly or together.

6.4 Young of year (YOY) abundance and growth

6.4.1 Description and rationale

Spawning areas and larval and juvenile fish rearing habitat are generally very sensitive to hydrologic alterations associated with in-stream developments. Flow rates can be a trigger for spawning migrations, certain water levels and flows may be necessary to access and utilize spawning habitat, and egg survival within spawning beds is related to water levels and flows. For VEC and SAR species, assessing recruitment and growth of YOY may identify changes in ecological condition and loss of essential habitat earlier than indicators of population structure.

6.4.2 Indicator and methods

Field surveys of YOY abundance as an index or catch per unit effort and size measurements of fish captured in the fall (15 August – 15 September). Sampling at this time will result in measurements representing the majority of growth (fork length mm) for the first year of life. The preferred sampling method is shoreline electrofishing ([link inactive] http://www.mnr.gov.on.ca/stdprodconsume/groups/lr/%40mnr/%40aquatics/documents/document/stdprod_093462.pdf Jones 2011a).

6.5 Mercury in fish tissue

6.5.1 Description and rationale

Mercury is a naturally occurring trace metal typically found in very small quantities in pristine waters. However, the flooding of large areas to create reservoirs can result in conditions which increase the production of the biologically active methyl mercury through increased microbial transformation (methylation) of the inorganic mercury contained in flooded vegetation and soils (Hecky et al. 1991). Mercury originating in a reservoir can be moved downstream and made available for uptake by food webs throughout the ZOI (Rosenberg et al. 1997). Naturally occurring mercury levels and the potential for increased production of methyl mercury are associated with a number of factors and may not be directly related to the area flooded.

Methyl mercury is accumulated in aquatic organisms and because it has a long retention time in animal tissue, biomagnification occurs up the food chain, with predatory fishes such as walleye having the highest mercury concentrations (Jackson 1980). High levels of methyl mercury can affect fish biochemistry, gene transcription, behaviour, reproduction, histology, and growth (Sandheinrich and Miller 2006; Scheuhammer et al. 2007; Drevnick, et al. 2008; Sandheinrich and Wiener 2011). Mercury in fish tissue is also an important concern because of its implications for human consumption.

Because mercury concentrations in water are very small and highly variable, assessment and ongoing monitoring often relies on measurements from fish tissue samples, where bioaccumulation results in higher, more easily measured concentrations.

6.5.2 Indicator and methods

Assess methyl mercury in fish tissue measured in µg/g. If available, existing data on mercury in fish tissue should be used to determine the natural range of variability and to estimate the magnitude of potential changes resulting from construction and operation of the proposed facility. If sufficient data aren’t available or if the available data suggests a moderate to high probability of ecosystem alteration, then field sampling should be done. Field sampling should be done for any development that will create or enlarge an existing reservoir.

Fish samples for mercury analyses should be collected above the predicted limit of backwater due to a reservoir, in the deepest part of the proposed/existing reservoir, within 500 m downstream of the proposed tailrace discharge (MOE), and at the downstream end of the ZOI, and should include:

• One or more species that are sufficiently abundant to ensure capture of a suitable sample size, including:
  • young of the year forage fish. Typical species include yellow perch (Perca flavescens) and spottail shiners (Notropis antherinoides). Sampling should be conducted in September, or October if necessary.
  • large predatory fish including walleye (Sander vitreus) and northern pike (Esox lucius). Sampling can occur any time during the open-water season.

Tissue sampling protocols for the determination of mercury in tissue from large fish are described in the Ontario Ministry of Environment publication “Protocol for the Collection of Sport Fish Samples for Inorganic and Organic Contaminant Analysis”. MOE should be consulted directly for instructions on sampling forage fish. Tissue analysis should be conducted by a certified laboratory.

6.6 Benthic invertebrates

6.6.1 Description and rationale

Benthic invertebrates are consumers of basal resources (algae, biofilms, organic matter) and secondary consumers. They link basal resources to higher trophic levels, including fishes. Benthic invertebrates are often sampled in aquatic monitoring programs because they are diverse, generally sedentary, and are responsive to environmental alterations. More importantly, they are good indicators of ecosystem productivity and health. In Ontario, there are over 60 species of dragonfly that are provincially rare. Fluctuating flows and changes in course particulate organic matter, thermal regime, sediment dynamics, and water quality can cause changes in the composition and productivity of the invertebrate community.

A number of protocols using benthic invertebrates to assess river health are available but these typically involve many reference rivers and complex statistical analysis (e.g. Environment Canada 2010; Rosenberg et al. 1997; Jones et al. 2004; Barbour et al. 1999; Flotemersch et al. 2006). Most were developed to assess water quality issues, rather than changes in habitat. All protocols provide details on sample design and sampling equipment and methods, as well as data analysis and reporting.

The applicability of the different protocols will depend on site conditions and whether specific biological responses or sentinel species are being investigated. One drawback to these protocols is that they are focussed primarily on small wadeable streams and rivers and may not be suitable for surveying larger non-wadeable rivers. Another is that they describe the composition of the benthic invertebrate community but don’t quantify density or distribution patterns along a river. The latter are important when investigating the effects of water level alterations. The benthic sampling protocol developed by Jones http://www.mnr.gov.on.ca/stdprodconsume/groups/lr/%40mnr/%40aquatics/documents/document/stdprod_093461.pdf (2011b) [link inactive] provides guidance for quantitatively sampling the density and distribution of benthic invertebrates.

Factors such as the type of sampling gear used, habitat types sampled, time of year, level of identification of the biota, and the year that sampling occurred all affect the ability to compare data from different areas. To compare various locations along a river or between rivers, samples should be collected in as short a time frame as possible. The sampling of aquatic invertebrates over a three to four month period compromises the value of comparing data collected at various locations along a river (Fiset 1995).

Quantitative sampling uses a device to sample a known area or volume of habitat. Sampling gear appropriate for the habitat types present are used to obtain biomass or population estimates of the aquatic invertebrate community, as well as information on species composition and species richness. Comparisons of such attributes can only be made when similar sampling gears and effort are used at each location. To account for site variability, replicate sampling is required. To compare quantitative samples between locations, it is necessary to sample similar habitats at each location.

6.6.2 Indicators and methods

Composition and density of invertebrates including sentinel taxa. Data is required on the composition and abundance of the invertebrate community including the percentage Anisoptera, Plecoptera, Trichoptera, Ephemeroptera. Characterization of the community can usually be accomplished with identification to the Family level. Use of the benthic sampling protocol developed by Jones (2011b) is recommended. This method requires sampling each site only once in August and consists of 3-6 Surber samples collected in water 20-30 cm deep during low flow conditions.

6.7 Basal resources

Organic matter, attached algae (periphyton), and aquatic macrophytes provide basal energy sources and critical habitat for many species (e.g. spawning northern pike and macroinvertebrates). In lakes and rivers, macrophytes provide cover for fish and substrate for aquatic invertebrates, produce oxygen, and act as food for some fish and wildlife. Algae and aquatic macrophyte communities respond to water levels, varying flows, water clarity, the timing and frequency of floods. These plants can have both positive and negative effects on the population dynamics of invertebrates and fish. In addition to living plants, particulate organic plant matter such as leaves and dying macrophytes provide food and habitat for many species. In-stream developments can potentially interrupt flow of this organic material and thus change energy flow through the system.

6.7.1 Organic matter

6.7.2 Description and rationale

Dissolved and particulate organic carbon serves as primary food sources for aquatic food webs. Coarse particulate organic matter (CPOM, >1mm), such as leaves and sticks, is the main input into smaller streams, especially in the headwaters (Bilby and Likens 1980). CPOM connects the terrestrial system to the aquatic and once in the stream, it is broken down into smaller fragments by physical and biological processes. CPOM has been shown to correlate with the macroinvertebrate community (Wipfli and Musslewhite 2004) and is the main input of energy to support the food web within the stream. Even small changes in the amount of organic matter entering a river can dramatically affect the composition of fish and invertebrate communities (Moore 1998).

6.7.3 Indicator and methods

Biomass of coarse particulate organic matter. Sampling organic matter requires one site visit and a small amount of laboratory time (see Basal resource sampling protocol Jonesand Houston 2011). Other sampling efforts can be done concurrently.

6.7.4 Periphyton

6.7.5 Description and rationale

Periphyton is a mixture of algae, cyanobacteria, heterotrophic microbes, and detritus attached to submerged surfaces in most aquatic ecosystems. It serves as an important food source for invertebrates, amphibians, and fish. Attached algae responds to changes in water clarity, velocity, depth, nutrients, and the timing and frequency of floods (Biggs 1996). In unshaded streams, periphyton is an important source of energy as it converts sunlight into a food source. At the base of the food web, invertebrates feed on periphyton transferring its energy to higher trophic levels. Although periphyton can have a positive effect on population dynamics, under certain conditions its growth can be too prolific and negatively impact invertebrate and fish communities.

6.7.6 Indicator and methods

Assess the biomass of attached algae. Sampling attached algae requires one site visit and a small amount of laboratory time (see Basal resource sampling protocolJones and Houston 2011). Other sampling efforts can be done concurrently.

6.7.7 Aquatic macrophytes

6.7.8 Description and rationale

Fish use aquatic macrophytes for shelter and refuge and as a place to forage. Macrophytes often enhance diversity in littoral zones by providing structured habitat within the water column and into the substrate, converting light to energy for primary consumers, and influencing nutrient cycling, water quality, water velocities and sedimentation. However, the decomposition of high densities of macrophytes may deplete dissolved oxygen concentrations and cause fish kills (Ploskey 1986). Changes in water flow can affect the distribution of macrophytes, as well as the reverse, with macrophyte distribution influencing water flow (Madsen et al. 2001). Because of this, it is important to get a base-line of macrophytes conditions prior to any in-stream developments.

6.7.9 Indicator and methods

Assess the percentage cover of aquatic macrophytes. Sampling aquatic macrophytes requires one site visit and a small amount of laboratory time (see Basal resource sampling protocol http://www.mnr.gov.on.ca/stdprodconsume/groups/lr/%40mnr/%40aquatics/documents/document/stdprod_093463.pdf Jones and Houston 2011 [link inactive]). Other sampling efforts can be done concurrently.

References

Acres International Limited., 1988a. Streamflow analysis methodology for ungauged small-scale hydro sites in Ontario: Study documentation report. Prepared for Environment Canada Inland Waters Directorate.

Acres International Limited., 1988b. Streamflow analysis methodology for ungauged small-scale hydro sites in Ontario: Applications Manual. Prepared for Environment Canada Inland Waters Directorate.

Acres International Limited., 1994. Hydrologic design methodology for small scale hydro at ungauged sites – Upgrading of Ontario and Atlantic province models. The CANMET Energy Technology Centre (CETC), Energy Technology Branch, Energy Sector, Department of Natural Resources Canada, Ottawa, Ontario.

Ajami, N.K., Gupta, H., Wagener, T. and Sorooshiam, S., 2004. Calibration of a semi- istributed hydrologic model for streamflow estimation along a river system, Journal of Hydrology, 298: 112–135 p.

Alabaster, J. S., and Lloyd, R., 1982. Water quality criteria for freshwater fish. 2^nd edition. London, England: Butterworth Scientific. 127-142 p.

Allan J.D. and Castillo, M.M., 2007. Stream Ecology: Structure and Function of Running Waters. 2^nd edition. Springer: Dordrecht, Netherlands.

Andrews, E.D., 1980. Effective and bankfull discharges of streams in the Yampa river basin, Colorado and Wyoming. Journal of Hydrology, 46:311-330 p.

Andrews, E.D., 1986. Downstream effects of Flaming Gorge reservoir on the Green River, Colorado and Utah. Geological Society of America Bulletin, 97: 1012-1023 p.

Angradi, T.R., 1999. Fine Sediment and Macroinvertebrate Assemblages in Appalachian Streams: A Field Experiment With Biomonitoring Applications. Journal of the North American Benthological Society, 8(1):49-66 p.

Annable, W.K., 1994. Morphological relations and rural watercourses in southeastern Ontario for use in natural channel design. Masters thesis, University of Guelph, School of Engineering, Guelph, Ontario, Canada.

Annable, W.K., 1996. Morphologic relationships of rural watercourses in Southern Ontario and selected field methods in fluvial geomorphology. Ontario Ministry of Natural Resources, 92 p.

Annear, T., Chisholm, I., Beecher, H., Locke, A., and 12 other authors, 2004. Instream Flows for Riverine Resource Stewardship, revised edition. The Instream Flow Council, Cheyenne, WY., 267-268 p.

Arcement Jr., G.J. and Schneider, V.R., 1989. Guide for selecting Manning’s roughness coefficients for natural channels and flood plains. U.S. Geological Survey Water Supply Paper 2339, 38 p.

Armitage, P.D., 1984. Environmental changes induced by stream regulation and their effect on lotic macroinvertebrate communities. A. Lillehammer and S.J. Saltveit, editors. Regulated Rivers. University of Oslo Press, Oslo, Norway. 139-165 p.

Arnold, J.G., and Allen, P.M., 1999. Automated methods for estimating baseflow and groundwater recharge from stream flow records. J. American Water Resources Association 35 (2): 411-424 p.

Arnwine, D. H., Sparks, K. J., and James, R. R., 2006. Probabilistic monitoring of streams below small impoundments in Tennessee. - Tenn. Dep. Envir. Conserv., Div. Wat. Pollut. Control, Nashville. 282 p.

Arthington, A.H., Bunn, S.E., Poff, N.L., and Naiman, R.J., 2006. The challenge of providing environmental flow rules to sustain river ecosystems. Ecological Applications, 16 (4): 1311- 1318 p.

Auer, N., 1996. Importance of habitat and migration to sturgeons with emphasis on lake sturgeon. Canadian Journal of Fisheries and Aquatic Science 53(Suppl. 1): 152 – 160 p.

Backman, T.W.H. and Evans, A.F., 2002. Gas bubble trauma incidence in adult salmonids in the Columbia River basin. North American Journal of Fisheries Management 22: 579- 584 p.

Backman, T.W.H., Evans, A.F. and Robertson, M.S., 2002. Gas bubble trauma incidence in juvenile salmonids in the Lower Columbia and Snake Rivers. North American Journal of Fisheries Management 22: 965-972 p.

Baldwin, D. S. and Mitchell, A.M., 2000. The effects of drying and re-flooding on the sediment and soil nutrient dynamics of lowland river-floodplain systems. Regulated Rivers Res. Management 16:457-467 p.

Bain, M.B., Harig, A.L., Louks, D.P., Goforth, R.R. and Mills, K.E., 2000. Aquatic ecosystem protection and restoration: advances in methods of assessment and evaluation. Environmental Science & Policy 3: S89-S98 p.

Barbour, M.T., Gerritsen, J., Snyder, B.D., and Stribling, J.B., 1999. Rapid Bioassessment Protocols for Use in Streams and Wadeable Rivers: Periphyton, Benthic Macroinvertebrates and Fish, Second Edition. EPA 841-B-99-002. U.S. Environmental Protection Agency; Office of Water; Washington, D.C.

Barnes Jr., H.A. 1967. Roughness characteristics of natural channels. U.S. Geological Survey Water Supply Paper 1849, 213 p.

Baron, J.S., Poff, N.L., Angermeier, P.L., Dahm, C.N., Gleick, P.H., Hairston, N.G. Jr., Jackson, R.B., Johnston, C.A., Richter, B.D., Steinman, A.D. 2002. Meeting ecological and societal needs for freshwater. Ecological Applications, 12(5): 1247-1260 p.

Bathurst J.C., 1997. Environmental River Flow Hydraulics. in Applied Fluvial Geomorphology for River Engineering and Management (Thorne C. R., Hey R. D. and Newson M. D., eds.), 69-93 p. John Wiley & Sons Ltd., New York.

Bayley, P.B. 1995. Understanding large river-floodplain ecosystems. BioScience 45: 153– 158 p.

Beamesderfer, R.C.P., 1998. Management and trade in Pacific sturgeon. In Proceedings on the Symposium on the Harvest, Trade and Conservation of North American Paddlefish and Sturgeon.[eds.] Williamson, D.F, Benz, G.W. & Hoover, C.M., 95 – 105 p. Chattanooga, TN. TRAFFIC North America/World Wildlife Fund, Washington, DC, USA

Beltaos S, Prowse TD, Carter T., 2006. Ice regime of the lower Peace River and ice-jam flooding of the Peace-Athabasca Delta. Hydrological Processes 20: 4009–4029 p. DOI: 10.1002/hyp.6417

Bergkamp, G., McCartney, M., Dugan, P., McNeely, J., Acreman, M., 2000. Dams, Ecosystem Functions and Environmental Restoration. WCD Thematic Review Environmental Issues II.1. Final Version: November 2000. Prepared for the World Commission on Dams (WSC). 199 p.

Bergström, S., 1976. Development and application of a conceptual runoff model for Scandinavian catchments. SMHI Reports RH0, No. 7, Norrköping.

Bergström, S., 1992. The HBV model - its structure and applications. SMHI Reports RH, No. 4, Norrköping.

Bevelhimer, M.S., 2002. A bioenergetic model for white sturgeon Acipenser transmontanus: assessing differences in growth and reproduction among Snake River reaches. Journal of Applied Ichthyology 18: 550 – 556 p.

Beven, K.J., Kirkby, M.J., Schofield, N., and Tagg, A.F., 1984. Testing a physically-based flood forecasting model (TOPMODEL) for three U.K. Catchments. Journal of Hydrology. 69:119- 143 p.

Bicknell, B.R., Imhoff, J.C., Kittle, J.L., Jr., Donigian, A.S., Jr., and Johanson, R.C., 1997. Hydrological Simulation Program--Fortran, User’s manual for version 11: U.S. Environmental Protection Agency, National Exposure Research Laboratory, Athens, Ga., EPA/600/R-97/080, 755 p.

Biggs, B.J.F., 1996. Hydraulic habitat of plants in streams. Regulated rivers: Research and Management 12: 131-144 p.

Bilby, R.E. and Likens, G.E., 1980. Importance of organic debris dams in the structure and function of stream ecosystems. Ecology 61: 1107-1113 p.

Boers, P.C.M., 1991. The influence of pH on phosphate release from lake sediments. Water Res. 25: 309-311 p.

Boers, P.C.M., and Van Hese, O., 1988. Phosphate release from the peaty sediments of the Loosdrecht Lakes (The Netherlands). Water Res. 22: 355-363 p.

Bonar, S.A., Hubert, W.A., and Willis, D.W., editors. 2009. Standard Methods for Sampling North American Freshwater Fishes. American Fisheries Society, Bethesda, Maryland.

Bouck, G. R., 1980. Etiology of Gas Bubble Disease. Transactions of the American Fisheries Society 1980; 109: 703-707 p.

Bowen, Z.H., Bovee, K.D. and Waddle, T.J., 2003. Effects of flow regulation on shallow water habitat dynamics and floodplain connectivity. Transactions of the American Fisheries Society. 132: 809-823 p.

Brandt, A.S., 2000. Classification of geomorphological effects downstream of dams. Catena, 40: 375-401p.

Brett, J.R., 1971. Energetic responses of salmon to temperature: a study of some thermal relations in the physiology and freshwater ecology of sockeye salmon (Oncorhynchus nerka). American Zoology 11: 99–113 p.

Brilly, M., Kobold, M., and Vidmar, A., 1997. Water information management system and low flow analysis in Slovenia. FRIEND '97 - Regional Hydrology: concepts and models for sustainable water resource management. Proceedings from the International Conference, 246:117-124 p.

British Columbia Ministry of Environment, 1997. Ambient Water Quality Criteria for Dissolved Oxygen.

Broman, D., Naf, C., Axelman, J., Bandh, C., Pettersen, H., Johnstone, R. and Walberg, P., 1996. Significance of bacteria on marine waters for the distribution of hydrophobic organic contaminants. Environmental Science and Technology 30(4):1238-1241 p.

Brookes, A., 1988. Channelized Rivers: Perspectives for Environmental Management. John Wiley. New York

Brown, C., and King, J., 2000. Environmental Flow Assessments for Rivers. A summary of the DRIFT process. Southern Waters Information Report No 01/00, 26 p.

Brown, D.R., 2007. Freshwater fish in Ontario’s Boreal: Status, conservation and potential impacts of development. WCS Canada Conservation Report No. 2. 98 p.

Brown, R.S., Stanislawski, S.S., Mackay, W.C., 1993. Effects of frazil ice on fish. In Proceedings of the Workshop in Environmental Aspects of River Ice, Prowse TD (ed). NHRI Symposium Series No. 12, National Hydrology Research Institute, Saskatoon, Canada; 261-278 p.

Brune, G.M., 1953. Trap Efficiency of Reservoirs. Transactions of the American Geophysical Union, 34(3), 407-418 p.

Bunn, S.E. and Arthington, A.H., 2002. Basic principles and ecological consequences of altered flow regimes for aquatic biodiversity. Environmental Management, 30(4): 492-507 p.

Bunte, K., Swingle, K.W. and Abt, S.R., 2007. Guidelines for using bedload traps in coarse- bedded mountain streams: construction, installation, operation, and sample processing. United State Department of Agriculture Forest Service, Rocky Mountain Research Station, General Technical Report RMRS-GTR-191. 91p.

Bushaw K.L., Zepp, R.G., Tarr, M.A., Schulz-Jander, D., Bourbonniere, R.A., Hodson, R.E., Miller, W.L., Bronk, D.A., and Moran, M.A.,1996. Photochemical release of biologically labile nitrogen from aquatic dissolved organic matter. Nature 381. 404-407p.

Caissie, D. 2006. The thermal regime of rivers: a review. Freshwater Biology 51: 1389- 1406. DOI: 10.1111/j.1365-2427.2006.01597.x

Canadian Council of Ministers of the Environment. 1999a. Canadian water quality guidelines for the protection of aquatic life: Dissolved gas supersaturation. In: Canadian environmental quality guidelines, 1999, Canadian Council of Ministers of the Environment, Winnipeg.

Canadian Council of Ministers of the Environment. 1999b. Canadian water quality guidelines for the protection of aquatic life: Dissolved oxygen (freshwater). In: Canadian environmental quality guidelines, 1999, Canadian Council of Ministers of the Environment, Winnipeg.

Canadian Council of Ministers of the Environment. 2002. Canadian water quality guidelines for the protection of aquatic life: Total particulate matter. In: Canadian environmental quality guidelines, 1999, Canadian Council of Ministers of the Environment, Winnipeg.

Canadian Council of Ministers of the Environment. 2003a. Canadian water quality guidelines for the protection of aquatic life: Guidance on the Site-Specific Application of Water Quality Guidelines in Canada: Procedures for Deriving Numerical Water Quality Objectives. In: Canadian environmental quality guidelines, 1999, Canadian Council of Ministers of the Environment, Winnipeg.

Canadian Council of Ministers of the Environment. 2003b. Canadian water quality guidelines for the protection of aquatic life: Inorganic mercury and methylmercury. In: Canadian environmental quality guidelines, 1999. Canadian Council of Ministers of the Environment, Winnipeg.

Canadian Council of Ministers of the Environment. 2003c. Canadian water quality guidelines for the protection of aquatic life: Nitrate Ion. In: Canadian environmental quality guidelines, 1999, Canadian Council of Ministers of the Environment, Winnipeg.

Canadian Council of Ministers of the Environment. 2004. Canadian water quality guidelines for the protection of aquatic life: Phosphorus: Canadian Guidance Framework for the Management of Freshwater Systems. In: Canadian environmental quality guidelines, 2004, Canadian Council of Ministers of the Environment, Winnipeg.

Canadian Council of Ministers of the Environment. 2007. Canadian water quality guidelines for the protection of aquatic life: Nutrients. In: Canadian environmental quality guidelines, 1999, Canadian Council of Ministers of the Environment, Winnipeg.

Canadian Council of Ministers of the Environment. 2010. Canadian water quality guidelines for the protection of aquatic life: Ammonia. In: Canadian environmental quality guidelines, 1999, Canadian Council of Ministers of the Environment, Winnipeg.

Canadian Council of Ministers of the Environment. 2011. Protocols Manual for Water Quality Sampling in Canada.

Carling, P.A., 1988. The concept of dominant discharge applied to two gravel-bed streams in relation to channel stability thresholds. Earth Surface Processes and Landforms, 13:355- 367 p.

Carlisle, D.M., Wolock, D.M., and Meador, M.R., 2010. Alteration of streamflow magnitudes and potential ecological consequences: a multiregional assessment. Frontiers in Ecology and the Environment 2010; DOI: 10.1890/100053.

Carolli M., Bruno M.C., Siviglia A., Maiolini B., 2011. Responses of benthic invertebrates to abrupt changes of temperature in flume simulations. River Research and Applications. DOI: 10.1002/rra.1520

Carpenter, T.M. and Georgakakos, K.P., 2006. Intercomparison of lumped versus distributed hydrologic model ensemble simulations on operational forecast scales. Journal of Hydrology, 1-2: 174-185 p.

Cavanagh, N.S., Nordin, R.N., Pommen, L.W. and Swain, L.G., 1998a. Guidelines for Designing and Implementing a Water Quality Monitoring Program. British Columbia Ministry of Environment, Lands and Parks.

Cavanagh, N.S., Nordin, R.N., Pommen, L.W. and Swain, L.G., 1998b. Guidelines for Interpreting Water Quality Data. British Columbia Ministry of Environment, Lands and Parks.

Chang, C., Ashenhurst, F., Damaia, S. and Mann, W., 2002. Ontario Flow Assessment Techniques, Version 1.0. OMNR, Northeast Science & Information, South Porcupine, Ontario.

Chapman, D. and Kimstach, V., 1996. Selection of Water Quality Variables in Water Quality Assessments - A Guide to Use of Biota, Sediments and Water in Environmental Monitoring - Second Edition. Chapman, D. (editor). University Press, Cambridge

Chapman, T.G., 1999. A comparison of algorithms for stream flow recession and baseflow separation. Hydrological Processes, 13: 701–714 p.

Chorley, R.J., Schumm, S.A., Sugden, D.E. 1984. Geomorphology. Methuen, New York. 605 p.

Chu, C., Jones, N.E., Piggott, A.R., Buttle, J.M., 2009. Evaluation of a simple method to classify the thermal characteristics of streams using a nomogram of daily maximum air and water temperatures. North American Journal of Fisheries Management 29: 1605–1619 p. DOI: 10.1577/M08-251.1

Church, M., Ham, D., Hassan, M., Slaymaker, O., 1999. Fluvial clastic sediment yield in Canada: scaled analysis. Canadian Journal of Earth Science, 36: 1267-1280 p.

Church, M., 2002. Geomorphic threshold in riverine landscapes. Freshwater Biology 47: 541-557 p.

Clarke, K.D., Pratt, T.C., Randall, R.G., Scruton, D.A., Smokorowski, K.E., 2008. Validation of the flow management pathway: effects of altered flow on fish habitat and fishes downstream from a hydropower dam. Canadian Technical Report of Fisheries and Aquatic Sciences 2784, Ottawa, Canada; 111.

Clarke, R.T., 1990. Bias and variance of some estimators of suspended sediment load, Hydrological Sciences Journal, 35(3): 253-261 p.

Coker, G.A., Portt, C.B., Minns, C.K., 2001. Morphological and ecological characteristics of Canadian freshwater fishes. Canadian Manuscript Report of Fisheries and Aquatic Sciences 2555, Ottawa, Canada; 89. http://dsp-psd.pwgsc.gc.ca/collection_2007/dfo-mpo/Fs97-4-2554E.pdf [link inactive] [22 November 2011].

Coleman, W.G., 1996. Biodiversity and industry ecosystem management. Environ. Manage. 20: 815-825 p.

Collier, M., Webb, R.H., and Schmidt, J.C., 1996. Dams and Rivers, Primer on the Downstream Effects of Dams. U.S. Geological Survey Circular 1126, 94 p.

Coutant, C.C., 1973. Effect of thermal shock on vulnerability of juvenile salmonids to predation. Journal of the Fisheries Research Board Canada 30: 965-973 p.

Covich, A.P., Clements, W.H., Fausch, K.D., Stednick, J.D., Wilkens-Wells, J., Abt, S.R., 2005. Ecological Integrity and Western Water Management: A Colorado Perspective. Water in the balance No. 3. Colorado Water Resources Research Institute. 25 p.

Cunjak, R.A., Caissie, D., 1993. Frazil ice accumulation in a large salmon pool, in the Mirimichi River, New Brunswick: ecological implications for overwintering fish. In Proceedings of the Workshop in Environmental Aspects of River Ice, Prowse TD (ed). NHRI Symposium Series No. 12, National Hydrology Research Institute, Saskatoon, Canada; 279-295 p.

Cunjak, R.A., Prowse, T.D., Parrish, D.L., 1998. Atlantic salmon Salmo salar in winter:"the season of parr discontent"? Canadian Journal of Fisheries and Aquatic Sciences 55: 161- 180 p.

Curry, R.A., Hughes, R.M., McMaster, M.E. and Zafft, D.J., 2009. Coldwater fish in rivers. 139-154p. in S.A. Bonar, W.A. Hubert, and D.W. Willis, editors. Standard Methods for Sampling North American Freshwater Fishes. American Fisheries Society, Bethesda, Maryland.

Curtis, K.E., Renshaw, C.E., Magilligan, F.J., Dade, W.B., 2010. Temporal and spatial scales of geomorphic adjustments to reduced competency following flow regulation in bedload-dominated systems. Geomorphology, 118(1-2): 105-117 p.

Dade, W.B., Renshaw, C.E. and Magilligan, F.J., 2011. Sediment transport constraints on river response to regulation. Geomorphology, 126: 245-251 p.

Danish Hydraulic Institute (DHI). 1998. MIKE SHE Water Movement - User Guide and Technical Reference Manual, Edition 1.1.

Davies, S.P. and Jackson, S.K., 2006. The biological condition gradient: A descriptive model for interpreting change in aquatic ecosystems. Freshwater Bioassessment 16: 1251

Department Of Water Affairs And Forestry (DWAF), 1999. Resource directed measures for Protection of water resources. Volume 3. River ecosystems. Version 1.0. Department of Water Affairs and Forestry, Pretoria.

Dewson, Z.S., James, A.B.W., and Death, R.G., 2007. A review of the consequences of decreased flow for instream habitat and macroinvertebrates. Journal of the North American Benthological Society 26: 401-415 p.

Dickinson, W.T., 1981. Accuracy and precision of suspended sediment loads. In: Erosion and Sediment Transport Measurement (Proc. Florence Symp. June 1981) 195-202 p. IAHS Publ. no. 133.

Dillon, P.J. and Molot, L.A., 1997. Dissolved organic and inorganic carbon mass balances in central Ontario lakes. Biogeochem. 36:29-42 p.

Dingman, S.L., 1994. Physical Hydrology. New York: MacMillan Publishing Company, 575 p.

Donaldson M.R., Cooke S.J., Patterson D.A., Macdonald J.S., 2008. Cold shock and fish. Journal of Fish Biology 73: 1591-1530. DOI: 10.1111/j.1095-8649.2008.02061.x

Doudoroff, P. and Shumway, D.I., 1970. Dissolved oxygen requirements of freshwater fishes. F.A.O. Fish. Tech. Pap. 86. 291 p.

Drevnick, P.E., Roberts, A.P., Otter, R.R., Hammerschmidt, C.R., Klaper, R., and Oris, J.T.,2008. Mercury toxicity in livers of northern pike (Esox lucius) from Isle Royale, USA. Comp. Biochem. Physiol. Part C 147:331–338 p.

Dunham J.B., Adams S.B., Schroeter R.E., Novinger D.C., 2002. Alien invasions in aquatic ecosystems: toward an understanding of brook trout invasions and potential impacts on inland cutthroat trout in western North America. Reviews in Fish Biology and Fisheries 12: 373-391. DOI:10.1023/A:1025338203702

Dunham, J.B., Rosenberger A.E., Thurow R.F., Dolloff C.A., and Howell, P.J., 2009. Coldwater fish in wadeable streams. Pages 119-138 in S.A. Bonar, W.A. Hubert, and D.W. Willis, editors. Standard Methods for Sampling North American Freshwater Fishes. American Fisheries Society, Bethesda, Maryland.

Dunne, T., and Leopold, L.B., 1978. Water in environmental planning. San Franscisco, CA: W.H. Freeman and Co., 181 p.

Dury, G.H., Hails, J.R. and Robbie, M.B., 1963. Bankfull discharge and the magnitude- frequency series. Australian Journal of Science, 26:123-124.

Dury, G.H., 1973. Magnitude-frequency analysis and channel morphology, In: Morisawa, M. (ed), Fluvial Geomorphology, SUNY Binghamton, Publications in Geomorphology, 91- 121 p. -1266

Eaton, A.D., Clesceri, L.S., Rice, E.W., Greenberg, A.E., and Franson (ed.), M.A.H., 2005. Standard methods for the examination of water and wastewater, 21^st ed. American Public Health Association, Washington, DC.

Ebersole, J.l., Liss, W.J. and Frissel, C.A., 2001. Relationship between stream temperature, thermal refugia and rainbow trout, Oncoryhnchos mykiss abundance in arid-land streams in the northwestern United States. Ecology of Freshwater Fish 10:1-10 p.

Eckhardt, K., 2008. A comparison of baseflow indices, which were calculated with seven different baseflow separation methods. Journal of Hydrology, 352: 168-173 p.

Edwards, T.K. and Glysson, G.D., 1999. Field methods for measurement of fluvial sediment: U.S. Geological Survey Techniques of Water-Resource Investigations. Book 3, Chapter C2. (http://water.usgs.gov/pubs/twri/twri3-c2/pdf/TWRI3-C2.pdf) [link inactive]

EPA, 1997. Hydrological Simulation Program – Fortran (HSPF). United States Environmental Protection Agency.

Environment Canada., 2010. Canadian Aquatic Biomonitoring Network: Wadeable Streams Field Manual. 52 pp.

Environmental Protection Agency., 2003. Multimedia, multipathway, and multireceptor risk assessment (3MRA) modeling system, Volume I: modeling system and science. SAB Review Draft [EPA530-D-03-001a].

ESSA, Technologies Ltd. 2005. Ecological indicators for effectiveness monitoring for water management planning. ESSA Technologies Limited, 11 Angelica Avenue, Richmond Hill, Ontario. 18 pp.

Eziashi, A.C., 1999. An appraisal of the existing descriptive measures of river channel patterns. Journal of Environmental Sciences 3(2): 253-257.

Evans, D.O., 1990. Metabolic thermal compensation by rainbow trout: effects on standard metabolic rate and potential usable power. Transactions of the American Fisheries Society 119: 585-600.

Ferguson, R.I., 2005. Estimating critical stream power for bedload transport calculations in gravel-bed rivers. Geomorphology 70: 33-41.

Fiset, W., 1995. A review of aquatic invertebrate studies conducted in the Moose River Basin. OMNR, Northeast Science and Technology. TR-024. 60pp.

Fisher, S.G. and LaVoy, A., 1972. Differences in littoral fauna due to fluctuating water levels below a hydroelectric dam. Journal of the Fisheries Research Board of Canada 29: 1472-1476.

Flodmark, L.E.W., Vøllestad, L.A., Forseth, T., 2004. Performance of juvenile brown trout exposed to fluctuating water level and temperature. Journal of Fish Biology 65: 460-470. DOI: 10.1111/j.0022-1112.2004.00463.x

Flotemersch, J.E., Stribling, J.B., and Paul, M.J., 2006. Concepts and Approaches for the Bioassessment of Non-wadeable Streams and Rivers. EPA 600-R-06-127. US Environmental Protection Agency, Cincinnati, Ohio.

Flügel, W.A., and Lüllwitz, T.H., 1993. Using a distributed hydrologic model with the aid of GIS for comparative hydrological modelling of micro – and mesoscale catchments in the USA and in Germany. Macroscale Modelling of the Hydrosphere. Proceedings of the Yokohama Symposium, July 1993. IAHS Publication No. 214: 59-66 p.

Freeman, B.J., Greening, J.S., and Oliver, J.D., 1984. Comparison of three methods for sampling fishes and macroinvertebrates in a vegetated freshwater wetland. Freshwater Ecology2: 603–609 p.

Friedl, G., and Wüest, A., 2002. Disrupting biogeochemical cycles - Consequences of damming. Aquatic Sciences 64: 55–65.

Fukushima, M., 2001. Salmonid habitat-geomorphology relationships in low-gradient streams. Ecology, 82: 1238-1246.

Galster, J.C., Pazzaglia, F.J., Hargreaves, B.R., Morris, D.P., Peters, S.C., Weisman, R.N., 2006. Effects of urbanization on watershed hydrology: The scaling of discharge with drainage area. Geology, 34(9): 713-716 p.

Galster, J.C., 2007. Natural and anthropogenic influences on the scaling of discharge with drainage area for multiple watersheds. Geosphere, 3(4): 260-271 p.

Gassman, P.W., Reyes, M.R., Green, C.H., and Arnold, J.G., 2007. The Soil and Water Assessment Tool: Historical development, applications, and future research directions. Transactions of the ASABE, 50(4): 1211-1250 p.

Gergel, S.E., Turner, M.G., and Kratz, T.K., 1999. Dissolved organic carbon as an indicator of the scale of watershed influence on lakes and rivers. Ecological Applications, 9(4), 1377– 1390 p.

Gleick, P.H., 1992. Environmental consequences of hydroelectric development: The role of facility size and type. Energy, 17(8): 735-747 p.

Goldstein, R.M., Wang, L., Simon, T.P., Stewart, P.M., 2002. Development of a stream habitat index for the Northern Lakes and Forests Ecoregion. North American Journal of Fisheries Management, 22: 452-464 p.

Gomez, B., and Church, M., 1989, An assessment of bed load sediment transport formulae for gravel bed rivers. Water Resources Research, 25:. 1,161–1,186 p.

Gordon, N.D., McMahon, T.A., Finlayson, B.L., Gippel, C.J., and Nathan, R.J., (eds.), 2004. Stream Hydrology, An Introduction for Ecologists. 2^nd edition., John Wiley & Sons, 429 p.

Graf, W.L., 2006. Downstream hydrologic and geomorphic effects of large dams on American rivers. Geomorphology, 79: 336-360 p.

Grant, G.E., Duval, J.E., Koerper, G.J, and Fogo, J.L., 1992. xspro: a channel cross- section analyzeer. In Dodson and Associates, Inc., Hydro-CD 6^th Edition.

Grant, G.E., Schmidt, J.C. and Lewis, S.L., 2003. A geological framework for interpreting downstream effects of dams on rivers; A Unique River; Water Science and Application 7; American Geophysical Union; 209-225 p.

Hasnain, S.S., Minns, C.K., Shuter, B.J., Birk-Urovitz, E., Birk-Urovitz, A., 2010. Compilation of Ecological Temperature Metrics for Canadian Freshwater Fishes. Climate Change Research Report CCRR-17, Ontario Ministry of Natural Resources; 55.

Halleraker, J.H., Alfredsen, K., Arnekleiv, J.V., Fjeldstad, H.P., Harby, A., and Saltveit, S.J. ,1999. Environmental impacts of hydro peaking with emphasis on river Nidelva in Trondheim, Norway. Paper presented at the International Seminar “Optimum use of run-of- river hydropower schemes, 21–23 June, Trondheim, International Center for Hydropower, 7 p.

Harby, A., Halleraker, J.H., Alfredsen, K., Arnekleiv, J.V., Johansen, S., Saltveit, S.J., 1999. Impacts of hydropeaking on Norwegian riverine ecosystems. Proceedings of the 3^rd International Symposium of Ecohydraulics. Salt Lake City, USA. 12-16 July.

Harman, C. and Stewardson, M., 2005. Optimizing dam release rules to meet environmental flow targets. River Research and Applications, 21:113-129 p.

Hauer, F. P. and Hill, W.R., 2007. Temperature Light and Oxygen. In Methods in Stream Ecology, Second Edition, 2007, Edited by Hauer, F. R. and G. A. Lamberti. Academic Press, Burlington, MA, USA. 103-118 p.

Haxton, T.J., Findlay C.S., 2008. Meta-analysis of the impacts of water management on aquatic communities. Canadian Journal of Fisheries and Aquatic Sciences 65: 437-447, 537-557 p. DOI: 10.1139/F07-175

Hayes, D.C., and Nelms, D.L., 2001. Base-flow characteristics of streams in the Valley and Ridge, Blue Ridge, and Piedmont Physiographic Provinces of Virginia and other Mid-Atlantic states. U.S. Geological Survey, Appalachian Region Integrated Science Workshop Proceedings, Open-File Report 01-406, Gatlinburg, Tennessee, October 22-26, 2001.

Hecky, R.E., Ramsay, D.J., Bodaly, R.A. and Strange, N.E., 1991. Increased methymercury contamination in fish in newly formed freshwater reservoirs. In Advances in mercury toxicology. Edits by T. Suzuki, N. Imura and T. W. Clarkson. Plenum, New York. 33-52 p.

Hicks, D.M, and Gomez, B. 2003. Sediment Transport, pp: 425-461, In: G.M. Kondolf and H. Piégay, (Eds), Tools in Fluvial Geomorphology. Wiley, Chichester, 688 p.

Holling, C.S. 1973. Resilience and stability of ecological systems. Ann. Rev. Ecol. Syst. 4:1-23

Holtby, L.B., 1988. Effects of logging on stream temperatures in Carnation Creek, British Columbia, and associated impacts on the coho salmon (Oncorhynchus kisutch). Canadian Journal of Fisheries and Aquatic Sciences 55: 502–515 p.

Hubbs, C., 1972. Some thermal consequences of environmental manipulations of water. Biological Conservation 4: 185-188 p.

Hudson, J.J., Taylor, W.D., and Schindler, D.W., 2000. Phosphate concentrations in lakes. Nature: 406:54-56 p.

Jackson, T., 1980 Mercury speciation and distribution in a polluted river-lake system as related to the problems of lake restoration. In: Proceedings of the International Symposium for Inland Waters and Lake Restoration. United States Environmental Protection Agency/Organisation for Economic Cooperation and Development, Portland, Maine, 93-101 p.

Jones, N.E., Allin, L., 2010. Measuring Stream Temperature Using Data Loggers: Laboratory and Field Techniques. Ontario Ministry of Natural Resources, Aquatic Research and Development Section, 29 p.

Jones, N.E., Schmidt, B., 2011. ThermoStat: Tools for Analyzing Thermal Regimes Reference Manual Version 3. Ontario Ministry of Natural Resources, Aquatic Research and Development Section, River and Stream Ecology Lab.

Huggett, R.J., 2007. Fundamentals of Geomorphology. Routledge, London, UK. 400 p. Hughes, D.A. and Smakhtin, V.Y., 1996. Daily flow time series patching or extension: A spatial interpolation approach based on flow duration curves. Hydrological Sciences, 41(6):851-871 p.

Jinfa, L. and Xiuhua, H., 2004. The relationship between sediment yield and catchment characteristics in the middle Yellow River basin of China. Sediment Transfer through the Fluvial System (Proceedings of a symposium held in Moscow, August 2004. IAHS Publ. 288: 212-219 p.

Johnson, D.H., Shrier, B.M., O’Neal, B.S., Knutzen, J.A., Augerot, X., T.A., O’Neil et al. 2007. Salmonid Field Protocols Handbook: Techniques for Assessing Status and Trends in Salmon and Trout Populations. American Fisheries Society, Bethesda, Maryland. 478 p.

Johnson, W.C., 2002. Riparian vegetation diversity along regulated rivers: contribution of novel and relict habitats. Freshwater Biology 47: 749-759 p.

Jones, C., Somers, K.M., Craig, B., and Reynoldson, T., 2004. Ontario Benthos Biomonitoring Network Protocol Manual, Version 1.0. Ontario Ministry of Environment.

Jones, N.E., 2010. Incorporating Lakes within the River Discontinuum: Longitudinal Changes in Ecological Characteristics in Stream-Lake Networks. Canadian Journal of Fisheries and Aquatic Sciences 67: 1350-1362 p.

Jones, N.E., 2011a. Electrofishing Rivers: Nearshore Community. Sampling Methodologies for Ontario’s Flowing Waters. Ontario Ministry of Natural Resources, Aquatic Research and Development Section, River and Stream Ecology Lab, Aquatic Research Series 2011-06

Jones, N.E., 2011b. Benthic Sampling in Natural and Regulated Rivers. Sampling Methodologies for Ontario’s Flowing Waters. Ontario Ministry of Natural Resources, Aquatic Research and Development Section, River and Stream Ecology Lab, Aquatic Research Series 2011-05

Jones, N.E. and Yunker, G., 2009. Riverine Index Netting Manual of Instructions. Ontario Ministry of Natural Resources, River and Stream Ecology Unit. 29 p.

Jones, N.E. and Yunker, G., 2011. Development of a Riverine Index Netting Protocol: Comparisons of Net Orientation, Height, Panel Order, and Line Diameter. North American Journal of Fisheries Management 31:23–31 p.

Jones, N.E. and Houston, B.E., 2011. Basal Resources Sampling in Rivers. Sampling Methodologies for Ontario’s Flowing Waters. Ontario Ministry of Natural Resources, Aquatic Research and Development Section, River and Stream Ecology Lab, Aquatic Research Series 2011-07.

Junk, W.J., Bayley, P.B., and Sparks, R.E., 1989. The flood pulse concept in river floodplain systems. Can. J. Fish. Aquat. Sci. Spec. Publ. 106:110-127 p.

Kannel, P.R., Kanel, S.R., Lee, S., Lee, Y.S., and Gan, T.Y., 2011. A Review of Public Domain Water Quality Models for Simulating Dissolved Oxygen in Rivers and Streams Environmental Modelling and Assessment 16(2): 183-204 p.

Karr, J.R., 1991. Biological Integrity: A long-neglected aspect of water resource management. Ecological Applications 1(1): 66-84 p.

Karr, J.R., 1999. Defining and measuring river health. Freshwater Biology 41, 221-234 p. King, J., Brown, C. and Sabet, H., 2003. A scenario-based holistic approach to environmental flow assessments for rivers. River Research and Applications 19: 619-639 p.

King, J. and Louw, D., 1998. Instream flow assessments for regulated rivers in South Africa using the Building Block Methodology. Aquatic Ecosystem Health and Management, 1: 109-124 p.

Knighton, D., 1998. Fluvial Forms and Processes, A New Perspective. John Wiley & Sons, New York, 383 p.

Kondolf, G.M., and Piégay, H.((eds)), 2003. Tools in Fluvial Geomorphology. Wiley, Chichester, 688 p.

Kondolf, G.M., Lisle, T.E, Wolman, G.M., 2003. Bed sediment measurement. Chapter 13 In G. M. Kondolf and H. Piégay, (Eds.). Tools in fluvial geomorphology. Wiley, New York.

Kondolf, G.M., Montgomery, D.R., Piegay, H. and Schmitt, L., 2003. Geomorphic Classification of Rivers and Streams. In Tools in Fluvial Geomorphology (Kondolf G. M., Piégay, H., eds.), John Wiley and Sons, Ltd. 688 p.

Kondolf, G.M, Williams, J.G., Horner, T.C., Milan, D., 2008. Assessing physical quality of spawning habitat. American Fisheries Society Symposium 65: 249-274, 2008: 1-26 p.

Kouwen, N., 1988. Watflood: A Micro-Computer based Flood Forecasting System based on Real-Time Weather Radar, Canadian Water Resources Journal, Vol. 13 (1): 62- 77 p.

Krebs, C.J., 1978. Ecology: The Experimental Analysis of Distribution and Abundance. Second Edition. Harper and Row, Publishers. 678 p.

Land and Water British Columbia Inc., 2005. Hydrological guidelines for waterpower projects. Land and Water Management Division, Surrey, British Columbia, 20 p.

Leavesley, G.H., Lichty, B.M., Troutman, L.G. & Saindon, L.G., 1983. Precipitation runoff modelling system: user’s manual. USGS Water-Resources Investigations Report 83-4238, Denver, Colorado.

Lehmkuhl, D.M., 1972. Changes in thermal regime as a cause of reduction in benthic fauna downstream of a reservoir. Journal of the Fisheries Research Board of Canada 29: 1329-1332 p.

Leopold, L.B., Wolman, M.G. and Miller, J.P., 1964. Fluvial Processes in Geomorphology. W.H. Freeman and Company, San Francisco, 522 p.

Lind, P.R., Robson, B.J, Mitchel, B.D., 2007. Multiple lines of evidence for the beneficial effects of environmental flows in two lowland rivers in Victoria, Australia. River Research and Applications, 23: 933-946 p.

Lohani, M., 2008. Effects of stream order and data resolution on sinuosity using GIS. Unpublished Master’s Thesis, Civil and Environmental Engineering, Virginia Polytechnic Institute and State University. 74 p.

Lorang, M.S., Komar, P.D., and Stanford, J.A., 1993. Lake level regulation and shoreline erosion on Flathead Lake, Montana: a response to the redistribution of annual wave energy. Journal of Coastal Research 9: 494-508 p.

Luce, J.J.W., 2009. Investigating the impact of moving sand during summer spates on the spatial distribution of stream periphyton biomass in a gravel-cobble bed boreal river Ph.D. Thesis pp. 234 McGill University, Montreal.

Lyne V.D., Hollick M., 1979. Stochastic time-variable rainfall runoff modelling. Hydrology and Water Resources Symposium, Institution of Engineers Australia, Perth; 89–92 p.

Lytle, D.A. and Merrit, D.M., 2004. Hydrologic Regimes and Riparian Forests: A structured population model for cottonwood. Ecology, 85(9): 2493-2503 p.

MacGregor, R., Casselman, J.M., Allen, W.A., Haxton, T., Dettmers, J.M., Mathers, A., LaPan, S., Pratt, T.C., Thompson, P., Stanfield, M., Marcogliese, L., Dutil, J.D., 2009. Natural heritage, anthropogenic impacts, and biopolitical issues related to the status and sustainable management of American eel: a retrospective analysis and management perspective at the population level. American Fisheries Society Symposium 69: 713 – 740 p.

Maddock, I., 1999. The importance of physical habitat assessment for evaluating river health. Freshwater Biology 41: 373-392 p.

Madsen, J.D., Chambers, P.A., James, W.F., Koch, E.W., and Westlake, D.F., 2001. The interaction between water movement, sediment dynamics, and submersed macrophytes. Hydrobiologia 444: 71-84 p.

Magilligan, F.J., Nislow, K.H., Graber, B.E., 2003. Scale-independent assessment of discharge reduction and riparian disconnectivity following flow regulation by dams. Geology, 31(7): 569-572 p.

Magnuson, J.J., Crowder, L.B., Medvick, P.A., 1979. Temperature as an ecological resource. American Zoologist 19: 331-53 p.

Magoulick, D.D., 2004. Effects of predation risk on habitat selection by water column fish, benthic fish, and crayfish in stream pools. Hydrobiologia 527: 209-221 p.

Maidment, D., 1993. Handbook of Hydrology. New York: McGraw-Hill Inc.

Makhlouf, Z. and Michel, C., 1994. A two-parameter monthly water balance model for French watersheds. Journal of Hydrology, 162: 299–318 p.

Marks, J.C., Power, M.E. and Parker, M.S., 2000. Flood disturbances, algal productivity, and interannual variations in food chain length. Oikos 90: 20-27 p.

Martson, R.A., Mills, J.D., Wrazien, D.R., Bassett, B., Splinter, D.K., 2005. Effects of Jackson Lake Dam on the Snake River and its floodplain, Grand Teton National Park, Wyoming, USA. Geomorphology, 71: 79-98 p.

Marty, J., Power, M. and Smokorowski, K.E., 2008. The effects of flow regulation on food- webs of boreal shield rivers. Verh. Internat. Verein. Imnol. 30(2): 275-278 p.

Mason, C.F., 1991. Biology of Freshwater Pollution. 2^nd Ed. Longman, Scientific and Technical. Longman Group UK Limited. 351 p.

McCartney, M.P., Sullivan, C. and Acreman, M.C., 2001. Ecosystem Impacts of Large Dams, Background Paper Nr. 2 Prepared for IUCN / UNEP / WCD. International Union for Conservation of Nature and Natural Resources and the United Nations Environmental Programme.

McCullough, D.A., 1999. A Review and Synthesis of Effects of Alterations to the Water Temperature Regime on Freshwater Life Stages of Salmonids, with Special Reference to Chinook Salmon. U.S. Environmental Protection Agency, Water Division, Seattle, Washington, USA. EPA 910-R-99-010.

Meade, R.H., Yuzyk, T., Day, T., 1990. Movement and storage of sediment in rivers of the United States and Canada, pgs. 255-280, In: W.H. Riggs (Ed.), The Geology of North America. Geological Society of America.

Metcalfe, R.A., Chang, C., Smakhtin, V., 2005a. Tools to support the implementation of environmentally sustainable flow regimes at Ontario’s waterpower facilities. Canadian Water Resources Journal 30(2): 97-110 p.

Metcalfe, R.A., Schmidt, B., and Pyrce, R.S., 2005b. A surface water quality threats assessment method using landscape-based indexing. WSC Report No.01-2005, Watershed Science Centre, Trent University, Peterborough, Ontario, 41 p. + App

Meybeck, M., Friedrich, G., Thomas, R. and Chapman, D., 1996. Rivers. Chapter 6 in A Guide to Use of Biota, Sediments and Water in Environmental Monitoring - Second Edition. Chapman, D. (editor). University Press, Cambridge

Moin, S.M.A and Shaw, M.A., 1986a. Canada/Ontario flood damage reduction program – Regional flood frequency analysis for Ontario streams: Volume 1, Single Station Analysis and Index Method. Inland Waters Directorate, Environment Canada.

Moin, S.M.A., and Shaw, M.A., 1986b. Canada/Ontario flood damage reduction program – Regional flood frequency analysis for Ontario streams: Volume 2, Multiple regression method. Inland Waters Directorate, Environment Canada.

Moog, O., 1993. Quantification of daily peak hydropower effects on aquatic fauna and management to minimize environmental impacts. Regulated Rivers Research & Management, 8: 5-14 p.

Moore, D.R.J., 1998. Ambient Water Quality Criteria for Organic Carbon in British Columbia. British Columbia Ministry of Water, Land and Air Protection

MOE. Ontario Ministry of the Environment. 2010. Lakeshore Capacity Assessment Handbook: Protecting Water Quality in Inland Lakes on Ontario’s Precambrian Shield. . Queen’s Printer for Ontario. 106 p.

Morris, G.L. and Fan, J., 1998. Reservoir Sedimentation Handbook – Design and Management of Dams, Reservoirs, and Watersheds for Sustainable Use. Chapter 10., Sediment Deposits in Reservoirs. McGraw-Hill, 10.1-10.42 p.

Mount, J., 1995. California Rivers and Streams: The Conflict Between Fluvial Process and Land Use. University of California Press, 376p.

Mueller, J.E., 1968. An introduction to the hydraulic and topographic sinuosity indexes. Annals of the Association of American Geographers, 58: 371–385 p.

Murchie, K.J., Hair, K.P.E., Pullen, C.E., Redpath, T.D., Stephens, H.R., and Cooke, S.J., 2008. Fish response to modified flow regimes in regulated rivers: research methods, effects, and opportunities. River Research and Applications 24: 197-217 p.

Naiman, R.J., and Decamps, H., 1997. The ecology of interfaces: Riparian zones. Annual Review of Ecology and Systematics, 28: 621-658 p.

Naiman, R.J., Melillo, J.M., Lock, M.A., Ford, T.E., and Reice, S.R., 1987. Longitudinal patterns of ecosystem processes and community structure in a subarctic river continuum. Ecology 68: 1139-1156 p.

Nathan, R.J. and T.A. McMahon, 1990. Evaluation of Automated Techniques for Baseflow and Recession Analysis. Water Resources Research, 26(7): 1465-1473 p.

Neff, B.P., Day, S.M., Piggott, A.R., Fuller, L.M., 2005. Base flow in the Great Lakes Basin. U.S. Geological Survey Scientific Investigations Report 2005-5217, 23 p.

Nielsen, J.L. 1998. Scientific sampling effects: electrofishing California’s endangered fish populations. Fisheries 23: 6-12 p.

Nilsson, C. and Berggren, K., 2000. Alterations of riparian ecosystems caused by river regulation. BioScience, 50: 783-792 p.

Nilsson, C. and Svedmark, M., 2002. Basic principles and ecological concequences of changing water regimes: riparian plan communities. Environmental Management, 30(4):468-480 p.

Nolan, K.M., Gray, J.R., and Glysson, G.D., 2005. Introduction to Suspended Sediment Sampling. USGS Scientific Investigations Report 2005-5077 (CD).

Northcote, T.G., 1978. Migratory strategies and production in freshwater fishes. Pages 326- 359 in S.D. Gerking, editor. Ecology of Freshwater Fish Production. Blackwell Science, Oxford.

Ohio Environmental Protection Agency. 2010. Qualitative Habitat Evaluation Index. Internet: http://www.epa.state.oh.us/portals/30/VAP/docs/Training/QHEI%202%20Day%20training%202010.pdf . 101 p. [link inactive]

Olden, J.D., and Naiman, R.J., 2009 Incorporating thermal regimes into environmental flows assessments: modifying dam operations to restore freshwater ecosystem integrity. Freshwater Biology 1-22 p.

Olden, J.D., Naiman, R.J., 2010. Incorporating thermal regimes into environmental flows assessments: modifying dam operations to restore freshwater ecosystem integrity. Freshwater Biology 55: 86-107 p. DOI: 10.1111/j.1365-2427.2009.02179.x

OMNR, 1994. Natural channel systems: An approach to management and design. Ontario Ministry of Natural Resources, 103 p.

OMNR, 2000. Flood regionalization for Ontario. Prepared by Cumming and Cockburn Limited, Markham, Ontario.

OMNR, 2002a. River and stream systems: Flooding hazard limit technical guide. Ontario Ministry of Natural Resources, Peterborough, Ontario, 88 p + App..

OMOE, 1995. Regional Analysis of Low Flow Characteristics, Central and Southern Regions, August, 1995. Prepared by Cumming Cockburn Limited for Ontario Ministry of Environment and Energy.

OMOE, 2008. Technical Guidance Document for Surface Water Studies In Support of Category 3 Applications for Permit to Take Water, Operations Division, April, 2008.

O’Neal, J.S., 2007. Snorkel surveys. Pages 325-340 in D.H. Johnson, B.M. Shrier, J.S. O’Neil, J.A. Knutzen, X. Augerot, T.A. O’Neil, and T.N. Pearsons, editors. Salmonid field protocols handbook: techniques for assessing status and trends in salmon and trout populations. American Fisheries Society, Bethesda, Maryland.

Onyando, J.O., Schumann, A.H., Schultz, G.A., 2003. Simulation of flood hydrographs based on lumped and semi-distributed models for two tropical catchments in Kenya. Hydrological Sciences Journal, 48(4): 511-524 p.

Page, K.J., 1988. Bankfull discharge frequency for the Murrumbidgee River, New South Wales, 267-281 p., In: R.F. Warner (Ed.), Fluvial Geomorphology of Australia,. Academic Press, Sydney.

Parfitt, D., and Buer, K., 1980. Upper Sacramento River spawning gravel study. California Department of Water Resources, Northern Division, Red Bluff.

Peters, D.L., Prowse, T.D., 2001. Regulation effects on the lower Peace River, Canada. Hydrological Processes 15: 3181–3194 p. DOI: 10.1002/hyp.321

Petit, N.E., Froend, R.H., Davies, P.M., 2001. Identifying the natural flow regime and the relationship with riparian vegetation for two contrasting western Australian rivers. Regulated Rivers: Research and Management, 17(3): 201-215 p.

Petts, G.E., 1984. Impounded Rivers – Perspectives for Ecological Management. John Wiley & Sons, 326 p.

Petts, G. and Foster, I., 1985. Rivers and landscape. London: Edward Arnold Publishers Ltd.

Petts, G.E., Bickerton, M.A., Crawford, C., Lerner, D.N., and Evans, D., 1997. Flow management to sustain groundwater-dominated stream ecosystems. Hydrological Processes, 13: 497-513 p.

Petts, G.E., 1984. Impounded rivers: perspectives for ecological management. Wiley. NewYork.

Pickup, G. and Warner, R.F., 1976. Effects of hydrologic regime on magnitude and frequency of dominant discharge. Journal of Hydrology, 29:51-75 p.

Piggott, A.R., Moin, S. and Southam, C., 2005. A revised approach to the UKIH method for the calculation of baseflow. Hydrological Sciences Journal. 50:911-920 p.

Ploskey, G.R., 1986. Effects of water-level changes on reservoir ecosystems, with implications for fisheries management. Pages 86 – 97 in G.E. Hall and M.J. Van Den Avyle, editors. Reservoir Fisheries Management Strategies for the ‘80’s. American Fisheries Society, Bethesda, Maryland.

Poddubny, A.G. and Galat, D.L., 1995. Habitat associations of Upper Volga River fishes: effects of reservoirs. Regulated Rivers: Research and Management 11: 67 – 84 p.

Poff, N.L., Allan, J.D., Bain, M.B., Karr, J.R., Prestegaard, K.L., Richter, B.D., Sparks, R.E. and Stromber, J.C., 1997. The natural flow regime: A paradigm for river conservation and restoration. Bioscience, 47(11):769-785 p.

Poff, N.L. and Ward, J.V., 1990. The physical habitat template of lotic systems: recovery in the context of historical pattern of spatio-temporal heterogeneity. Environmental Management 14: 629-646 p.

Pollock, M.M., Naiman, R.J., Hanley, T.A., 1998. Plant species richness in forested and emergent wetlands—A test of biodiversity theory. Ecology 79: 94–105 p.

Porterfield, G., 1972, Computation of fluvial-sediment discharge: U.S. Geological Survey Techniques of Water-Resources Investigations, book 3, chap. C3, 66 p.

Poos, M.S., Mandrak, N.E., and McLaughlin, R.L., 2007. The effectiveness of two common sampling methods for assessing imperilled freshwater fishes. Journal of Fish Biology 70:691-708 p.

Raddum, G.C., 1985. Effects of winter warm reservoir release on benthic stream invertebrates. Hydrobiology 122: 105-111 p., DOI:10.1007/BF00032096

Radecki-Pawlik, A., 2002. Bankfull discharge in mountain streams: theory and practice. Earth Surface Processes and Landforms, 27:115-123 p.

Reid, L.M. and Dunne, T., 2003. Sediment budgets as an organizing framework in fluvial geomorphology. Pgs. 463-500, In: G.M. Kondolf and H. Piégay, (Eds), 2003. Tools in Fluvial Geomorphology. Wiley, Chichester, 688 p.

Resh, V.H., Brown, A., Covich, A.P., Gurtz, M.E., Li, H.W., Minshall, W., Reice, S., Sheldon, A.L., Wallace, J.B., and Wissmar, R., 1988. The role of disturbance theory in stream ecology. Journal of the North American Benthological Society 7:433-455 p.

Ries, K.G., 1997. August median streamflows in Massachusetts, U.S. Geological Survey Water-Resources Investigations Report 97-4190, 27 p.

Riley, S.J., 1972. A comparison of morphometric measures of bankfull. Journal of Hydrology, 17:23-31.

Ritter, Michael E., 2006. The Physical Environment: an Introduction to Physical Geography. http://www.uwsp.edu/geo/faculty/ritter/geog101/textbook/title_page.html [link inactive]

Robertson-Rintoul, M.S.E. and Richards, K.S., 1993. Braided-channel pattern and palaeohydrology using an index of total sinuosity. Geological Society, London, Special Publications, 75: 113-118 p.

Rørslett, B., Mjelde, M., Johansen, S.W., 1989. Effects of hydropower development on aquatic macrophytes in Norwegian rivers: present state of knowledge and some case studies. Regulated Rivers: Research and Management 3: 19–28 p. DOI:10.1002/rrr.3450030104

Rosenberg, D.M., Berkes, F., Bodaly, R.A., Hecky, R.E., Kelly, C.A. and Rudd, J.W.M., 1997. Large-scale impacts of hydroelectric development. Environ. Rev. 5: 27-54 p.

Rosenberg, D.M., Davies, I.J., Cobb, D.G., and Wiens, A.P., 1997. Ecological Monitoring and Assessment Network (EMAN) Protocols for Measuring Biodiversity: Benthic Macroinvertebrates in Fresh Waters. Dept. of Fisheries & Oceans, Freshwater Institute, Winnipeg, Manitoba.

Rosgen, D., 1994. A classification of natural rivers. Catena, 22:169-199.

Rosgen, D., 1996. Applied river morphology. Wildland Hydrology, Pagosa Springs, CO., 390 p.

Rowntree, K.M., Wadeson, R.A., 1998. A geomorphological framework for the assessment of instream flow requirements. Aquatic Ecosystem Health and Management 1: 125-141 p.

Ryan, S.E., Porth, L.S. and Troendle, C.A., 2005. Coarse sediment transport in mountain streams in Colorado and Wyoming, USA. Earth Surface Processes and Landforms, 30: 269-288 p.

Salant, N.L., Renshaw, C.E., Magilligan, F.J., 2006. Short and long-term changes to bed mobility and bed composition under altered sediment regimes. Geomorphology, 76: 43-53 p.

Samuel, J.M, Coulibaly, P., Schmidt, B., and Metcalfe, R., 2010. MAC-HBV (Rainfall- Runoff Model for Gauged and Ungauged Basins) Version 1.0: User’s Manual. Department of Civil Engineering/SGES, McMaster University, Ontario, Canada. 50 p.

Samuel, J., Coulibaly, P., and Metcalfe, R., 2011a. Estimation of Continuous Streamflow in Ontario Ungauged Basins: Comparison of Regionalization Methods. In press ASCE Journal of Hydrologic Engineering.

Samuel, J., Coulibaly, P., and Metcalfe, R., 2011b. Identification of Rainfall-Runoff Model for Improved Baseflow Estimation in Ungauged Basins. In press Hydrological Processes.

Sanders, L.L. 1998. A manual of field hydrogeology. Prentice Hall, New Jersey, 381 p.

Scruton, D.A., Robertson, M.J., Ollerhead, L.M.N., Clarke, K.D., Pennell, C.J., Alfredsen, K., Harby, A., McKinley, R.S., 2005. Seasonal response of juvenile Atlantic salmon (Salmo salar) to experimental hydro peaking power generation on a Newfoundland, Canada river. North American Journal of Fisheries Management 25: 964-974 p. DOI:10.1577/M04-133.1

Sandheinrich, M.B., and Miller, K.M., 2006. Effects of dietary methylmercury on reproductive behavior of fathead minnows. Environ. Toxicol. Chem. 25: 3053–3057 p.

Sandheinrich, M.B., and Wiener, J.G., 2011. Methylmercury in Freshwater Fish: Recent Advances in Assessing Toxicity of Environmentally Relevant Exposures. Editors W. N. Beyer and J.P. Meador in Environmental Contaminants in Biota Interpreting Tissue Concentrations, Second Edition, CRC Press, Florida 169–190 p.

Scheuhammer, A.M., Meyer, M.W., Sandheinrich M.B. and Murray M.W., 2007. Effects of environmental methylmercury on the health of wild birds, mammals, and fish. Ambio 36:12–18 p.

Schindler, D.W., 1977. The evolution of phosphorus limitation in lakes. Science 195: 260- 262 p.

Schmidt, L.J., and Potyondy, J.P., 2004. Quantifying channel maintenance instream flows: an approach for gravel-bed streams in the western United States. United States Department of Agriculture, Rocky Mountain Research Station, General Technical Report RMRS-GTR-128, 33p.

Schmidt, J.C., Grams, P.E., Parnell, R.A., Hazel, J.E., Kaplinski, M.A. Stevens, L.E. Hoffnagle, T.L., 2001. The 1996 Controlled Flood in Grand Canyon: Flow, Sediment Transport, and Geomorphic Change. Ecological Applications, 11(3):657-671 p.

Schumm, S.A., 1960. The shape of alluvial channels in relation to sediment type. U.S. Geological Survey Professional Paper 352-B, 17-30 p.

Sear, D.A., Frostick, L.B., Rollinson, G., Lisle, T.E., 2008. The significance and mechanics of fine-sediment infiltration and accumulation in gravel spawning beds 149-174 p., In, D. A. Sear and P. DeVries (Eds.) Salmonid Spawning Habitat in Rivers: Physical Controls, Biological Responses, and Approaches to Remediation. Bethesda, USA, American Fisheries Society, Symposium 65.

Searcy, J.K., 1959. Flow-duration curves, Manual of Hydrology Part 2, Low-flow Techniques. Water Supply Paper 1542-A, U.S. Geological Survey, 33 p.

Sedell, J.R., GReeves, G.H., Hauer F.R., Stanford, J.A. and Hawkins, C.P., 1990. Role of refugia in recovery from disturbances: modern fragmented and disconnected river systems. Environmental Management 14: 711-724 p.

Selby, M.J., 1985. Earth’s Changing Surface, An Introduction to Geomorphology. Clarendon Press, Oxford, 607 p.

Sennatt, K.M., Salant, N.L., Renshaw, C.E., Magilligan, F.J., 2006. Assessment of methods for measuring embeddedness: Application to sedimentation in flow regulated streams. Journal of the American Water Resources Association, 42(6): 1671-1682 p.

Shields, F.D., Jr., A. Simon and L.J. Steffen., 2000. Reservoir effects on downstream river channel migration. Environmental Conservation 27: 54-66 p.

Shields, F.D., Testa, S. and Cooper, C.M., 2009. Nitrogen and phosphorus levels in the Yazoo River Basin, Mississippi. Ecohydrology 2: 270-278 p.

Simon, A., Dickerson, W., Heins, A., 2004. Suspended-sediment transport rates at the 1.5- year recurrence interval for ecoregions of the United States: transport conditions at the bankfull and effective discharge? Geomorphology, 58: 243-262 p.

Simoneau, M., Lucotte, M., Garceau, S., Laliberte, D., 2005. Fish growth rates modulate mercury concentrations in walleye (Sander vitreus) from eastern Canadian lakes. Environmental Research 98: 73-82 p. DOI: 10.1016/j.envres.2004.08.002

Sloto, R.A., and Crouse, M.Y., 1996, hysep: A computer program for streamflow hydrograph separation and analysis: U.S. Geological Survey Water-Resources Investigations Report 96-4040, 46 p.

Smakhtin, V.Y., 1999. Generation of natural daily flow time-series in regulated rivers using a non-linear spatial interpolation technique. Regulated Rivers: Research & Management,15: 311-323 p.

Smakhtin, V.Y., 2001. Low flow hydrology: a review. Journal of Hydrology 240: 147-186 p.

Smakhtin, V.Y. 2007. Environmental flows: a call for hydrology. Hydrological Processes,21: 701-703 p.

Smakhtin, V.Y., 2001. Low flow hydrology: a review. Journal of Hydrology 240: 147-186 p.

Smakhtin, V.Y., Hughes, D.A., and Creuse-Naudin, E., 1997. Regionalization of daily flow characteristics in part of the Eastern Cape, South Africa. Hydrological Sciences, 46(6): 919-936 p.

Smakhtin, V.Y. and Masse, B., 2000. Continuous daily hydrograph simulation using duration curves of precipitation index. Hydrological Processes, 14: 1083-1100 p.

Smokorowski, K.E., Metcalfe, R.A., Finucan, S.D., Insley, M., Jones, N., Marty, J., Niu, S.L., Power, M., Pyrce, R.S., and R. Steele, 2009. Studying ramping rate restrictions. Hydro Review 28(5): 68-88 p.

Smith, K., 1972. River water temperatures an environmental review. Scottish Geographical Magazine 88: 211-220. DOI: 10.1080/00369227208736229

Spence, J.A. and Hynes, H.B.N., 1971. Differences in benthos upstream and downstream of an impoundment. Journal of Fisheries Research Board of Canada 28: 35-43 p.

Stanford, J.A., Ward, J.V., Liss, W.J., Frissell, C.A.A., Williams, R.N., Lichatowich, J.A. and Coutant, C., 1996. A general protocol for restoration of regulated rivers. Regulated Rivers: Research & Management, 12: 391-413 p.

Stanfield, L., Jones, M., Stoneman, M., Kilgour, B., Parish, J. and Wichert, G., 1999. Stream Assessment Protocol for Southern Ontario, V 3.1.

Stanfield, L.W. (Editor). 2005. Ontario Stream Assessment Protocol Version 7, Fish and Wildlife Branch. Ontario Ministry of Natural Resources, Peterborough, Ontario. 256 p. http://www.mnr.gov.on.ca/226871.pdf [22 November 2011]. [link inactive]

Steinman, A. D. and Mulholland, P.J., Phosphorus Limitation, Uptake and Transport in Benthic Stream Algae. In Methods in Stream Ecology, Second Edition, 2007, Edited by Hauer, F. R. and G. A. Lamberti. Academic Press, Burlington, MA, USA. 187-212 p.

Stillwater Sciences, Confluence Research and Consulting and Heritage Research Associates Inc. 2006. Scientific approaches for evaluating hydroelectric project effects. Prepared by Stillwater Sciences, Arcata, California for: Hydropower Reform Coalition, Washington, D.C.

Stone, M., and Saunderson, H., 1996. Regional patterns of sediment yield in the Laurentian Great Lakes basin. In: Erosion and Sediment Trends: Global and Regional Perspectives. IAHS Publication No.234, 125-131 p.

Stoneman, C.L., Jones, M.L. 1996. A simple method to classify stream thermal stability with single observations of daily maximum water and air temperatures. North American Journal of Fisheries Management 16: 728-737 p.

Stoneman, M.G. (Editor). 2005. Canadian Electricity Association / Fisheries and Oceans Canada Science Workshop Proceedings: Setting Research Priorities on Hydroelectricity and Fish or Fish Habitat: St. John’s Newfoundland. June, 2004. Canadian Technical Report of Fisheries and Aquatic Sciences 2614: v + 138 p.

Summer, W. and Walling, D.E., 2002. Modelling Erosion, Sediment Transport and Sediment Yield. IHP-VI Technical Documents in Hydrology, No. 60, UNESCO, Paris. 262 p.

Sundborg, A., 1992 Lake and reservoir sedimentation. Prediction and interpretation. Geografiska Annaler, 74A, 93–100 p.

Swanson, F.J., Jones, J.A., Wallin, D.O. and Cissel, J.H., 1993. Natural variability: Implications for Ecosystem Management. IN: Jensen, M.E. and P.S. Bourgeron (eds), Eastside Ecosystem Health Assessment Vol. 2: Ecosystem Management, Principles and Application, US Dept. of Interior, Forest Services, Missoula, Montana, 80-94 p.

Sweeney, B.W. 1978. Bioenergetic and developmental response of a mayfly to thermal variation. Limnology and Oceanography 23: 461-477p.

Sylte, T. and Fischenich, C., 2002. Techniques for Measuring Substrate Embeddedness. ERDC TN-EMRRP-SP-36.

Tang, J., Bryant, M.D., Brannon, E.L., 1987. Effect of temperature extremes on the mortality and development rates of coho salmon embryos and alevins. Progressive Fish- Culturist 59: 167-175 p. DOI: 10.1577/1548-8640(1987)49<167:EOTEOT>2.0.CO;2

Tank, J.L., Bernot, M.J. and Rosi-Marshall, E.J., 2007. Nitrogen limitation and Uptake. In Methods in Stream Ecology, Second Edition, 2007, Edited by Hauer, F. R. and G. A. Lamberti. Academic Press, Burlington, MA, USA. pp. 213-238 p.

Tennant, D.L., 1976. Instream flow regimens for fish, wildlife, recreation and related environmental resources. Fisheries 1: 6-10 p.

Tessmann, S.A., 1980. Reconnaissance Elements of the Western Dakotas Region of South Dakota Study – Environmental Assessment – Appendix E: 57 p.

Tharme, R.E., 1996. Review of international methodologies for the quantification of the instream flow requirements of rivers. Water Law Review: Final report for policy and development. For, the South African Department of Water Affairs and Forestry, Pretoria. Freshwater Research Unit, University of Cape Town, 116 p.

Tharme, R.E., 2003. A global perspective on environmental flow assessment: emerging trends in the development and application of environmental flow methodologies for rivers. River Research and Applications, 19:397-441 p.

Thomas, R.E., Gharrett, J.A., Carls, M.G., Rice, S.D., Moles, A., Korn, S., 1986. Effects of fluctuating temperature on mortality, stress, and energy reserves of juvenile coho salmon. Transactions of the American Fisheries Society 15: 52-59 p.

Thorp, J.H., Thoms, M.C. and Delong, M.D., 2006. The riverine ecosystem synthesis: Biocomplexity in river networks across space and time. River Research and Applications 22: 123-147 p.

Threader, R.W., Houston, A.H., 1983. Heat tolerance and resistance in juvenile rainbow trout acclimated to diurnally cycling temperatures. Comparative Biochemistry and Physiology 75: 153-155 p.

Tiegs, S.D., O’leary, J.F., Pohl, M.M., Munill, C.L., 2005 .Flood disturbance and riparian species diversity on the Colorado River Delta. Biodiversity and Conservation, 14(5): 1175-1194 p.

Toniolo, H. and Schultz, J., 2005 Experiments on sediment trap efficiency in reservoirs. Lakes and Reservoirs: Research & Management, 10(1), 13–24 p.

Van Kirk, R., and Burnett, B., Hydrologic Alteration and its Ecological Effects in the Henry’s Fork Watershed upstream of St. Anthony. Project completion report for Henry’s Fork Watershed Council and others. Department of Mathematics, Idaho State University, Pocatello, ID, 2004.

Vannote, R.L., Minshall, G.W., Cummins, K.W., Sedell, J.R., and Cushing, C.E., 1980. The river continuum concept. Canadian Journal of Fisheries and Aquatic Sciences 37:130-137 p.

Vehanen, T., Bjerke, P.L., Heggenes, J., Huusko, A. & Ma¨ ki-Peta¨ ys, A., 2000. Effect of fluctuating flow and temperature on cover type selection and behaviour by juvenile brown trout in artificial flumes. Journal of Fish Biology 56, 923–937 p.

Vogel, R.M. and Fennessey, N.M., 1995. Flow duration curves II: A review of applications in water resources planning. Water Resources Bulletin, 31(6): 1029-1039 p.

Wallace, T.B. and Cox, W.E., 2002. Locating information on surface water availability in Virginia (draft). Accessed: March 2004, <http://www.rappriverbasin.state.va.us/studies>, 24 p.

Walling, D. E. and Webb, B. W., 1981. The reliability of suspended sediment load data. In:Sediment Budgets (Proc. Florence Symp. June 1981) 177-194 p. IAHS Publ no 133

Ward, J.V., 1989. The four-dimensional nature of the lotic ecosystem. Journal of the North American Benthological Society 8:2-8 p.

Ward, J.V. Collins, F., 1974. A temperature-stressed stream ecosystem below a hypolimnial release mountain reservoir. Archives of Hydrobiology 74: 247-275 p.

Ward, J.V. and Stanford, J.A., 1979. Ecological factors controlling stream zoobenthos with emphasis on thermal modification of regulated streams. In The Ecology of Regulated Streams, Ward JV, Stanford JA (eds). Plenum Press: New York, NY; 35–56 p.

Ward, J.V. and Stanford, J.A., (Eds)., 1979. The Ecology of Regulated Streams. Plenum Press, New York. 398 p.

Ward, J.V. and Stanford, J.A., 1983. The serial discontinuity concept of lotic ecosystems. Pages 29-42 in T.D. Fontaine and S.M. Bartell, editors. Dynamics of Lotic Ecosystems. Ann Arbor Sciences, Ann Arbor, Michigan.

Ward, J.V. and Stanford, J.A., 1989. Riverine ecosystems: the influence of man on catchment dynamics and fish ecology. Canadian Special Publication Fisheries and Aquatic Sciences 106: 56-64 p.

Washington State Department of Ecology. 2005. Water Quality Certifications for Existing Hydropower Dams Guidance Manual. Publication No. 04-10-022

Waters, T.F., 1995. Sediment in streams: sources, biological effects and control. American Fisheries Society Monograph 7., 251p.

Webb, B.W. and Walling, D.E., 1996. Long-term variability in the thermal impact of river impoundment and regulation. Applied Geography 16: 211-223 p. DOI: 10.1016/0143 6228(96)00007-0

Weber-Scannell P.K. and Duffy, L.K., 2007. Effects of Total Dissolved Solids on Aquatic Organisms: A Review of Literature and Recommendation for Salmonid Species. American Journal of Environmental Sciences 3 (1): 1-6 p.

Webster, J.R. and Valett, H.M., 2007. Pages 169-186. In Methods in Stream Ecology, Second Edition, 2007, Edited by Hauer, F. R. and G. A. Lamberti. Academic Press, Burlington, MA, USA.

Wedemeyer, G., 1973. Some physiological aspects of sublethal heat stress in the juvenile steelhead trout (Salmo gairdneri) and coho salmon (Oncorhychus kisutch). Journal of the Fisheries Research Board Canada 30: 831-835 p.

Wedemeyer, G.A. and McLeay, D.J., 1981. Methods for determining the tolerance of fishes to environmental stressors. In Stress and Fish, Pickering AD (ed). Academic Press, London, UK; 257-275 p.

Welcomme, R.L., Ryder, R.A., & Sedell, J.A., 1989. Dynamics of fish assemblages in river systems – a synthesis. In Proceedings of the International Large River Symposium. [ed] Dodge, D.P., 569 – 577 p.Canadian Special Publication of Fisheries and Aquatic Sciences 106.

Wetzel, R., 2001. Limnology, 3E. Lake and River Ecosystems. Academic Press, 525 B Street, Ste. 1900, San Diego, CA 92101, USA. 850 p.Feb 2001.

Wifpli, M.S. and Musslewhite, J., 2004. Density of red alder (Alnus rubra) in headwaters influence invertebrate and detritus subsidies to downstream fish habitats in Alaska. Hydrobiologia 520: 153:163p.

Wilcock, P.R., 2004. Sediment transport in the restoration of gravel-bed rivers. Critical Transitions in Water and Environmental Resources Management, Proceedings World Water & Environmental Resources Congress, Salt Lake City, Utah, June 27 - July 1, 2004. Edited by G. Sehlke, D.F., Hayes and D. K. Stevens, American Society of Civil Engineers, Reston, Virginia. 11p.

Wilcock, P., Pitlick, J., and Cui, Y., 2009. Sediment transport primer: estimating bed- material transport in gravel-bed rivers. Gen. Tech. Rep. RMRS-GTR-226. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. 78 p.

Wildi, W., 2010. Environmental hazards of dams and reservoirs. NEAR curriculum in Natural Environmental Science, Terre & Environment, 88: 187-197 p.

Williams, G.P., 1978. Bank-full discharge of rivers. Water Resources Research, 14:1141- 1154 p.

Williams, G.P. and Wolman, M.G., 1984. Downstream effects of dams on alluvial rivers. United States Geological Survey Professional Paper 1286. United States Government Printing Office, Washington, 83 p.

Wolman, M.G., 1955. The natural channel of Brandywine Creek, Pennsylvania. U.S. Geological Survey Professional Paper 282, 86-109 p.

Wolman, M.G., 1954. A method for sampling coarse bed material. Transactions of the American Geophysical Union, 35: 951-956 p.

Wolman, M.G. and Miller, J.P., 1960. Magnitude and frequency of forces in geomorphic processes. Journal of Geology, 68:54-74 p.

Wooton, J.T., Parker, M.S. and Power, M.E., 1996. Effects of disturbances on river food webs. Science 273: 1558-1561 p.

Glossary

Adaptive management

A process for continually improving management policies and practices through a formal, systematic and rigorous program of learning from the outcomes of new studies and operational programs.

AFDM

Ash-free dry mass.

Anchor Ice

Ice attached to the streambed.

Annual flow

The total volume of water passing a given point in one year. Usually expressed as a volume (such as cubic meters) but may be expressed as an equivalent constant discharge over the year, such as cubic meters per second, and referred to as the Mean Annual Flow.

Aquatic biota

All organisms that, as part of their natural life cycle, live in or on waters.

Aquatic habitat

The physical, chemical, and biological components of the water environment.

Armoring

The formation of an erosion-resistant layer of relatively large particles on the surface of a streambed or stream bank that results from removal of finer particles by erosion, and which resists degradation by water currents. The process of continually winnowing away smaller substrate materials and leaving a veneer of larger ones.

Assessment criteria

Values of an indicator metric derived from a reference condition, existing condition, or an established standard against which deviation in an indicator variable is assessed.

Attenuation

Gradual loss in intensity of any kind of flux through a medium as distance from the source increases.

Autochthonous Production

Energy that comes from photosynthesis within the river.

Bankfull flow

The flow stage when water just begins to overflow onto the floodplain, corresponding to a discharge at which channel maintenance is thought to be most effective.

Base flow

The streamflow portion contributed by persistent, slowly varying sources (i.e. groundwater, lakes, wetlands) between precipitation events.

Biotope

An area of uniform environmental conditions (climatic and abiotic components) and in its distribution of plants and animals.

CPOM

Coarse particulate organic material. Organic material larger than 1mm e.g. leaves.

Dam

A concrete or earthen barrier constructed across a river and designed to control water flow or create a reservoir.

Discharge

The rate at which a volume of water passes a given point; expressed as m³sec^-1 (also referred to as streamflow)

Drawdown

The difference between maximum and minimum water levels in a reservoir. Also refers to that act of lowering reservoir levels.

Dynamic stability

Refers to an open system in a steady state, wherein the system functions within a range of natural variation, but within which the form or character of the system remains unchanged.

Ecological integrity

An ecosystem’s capability of supporting and maintaining a balanced, integrated, adaptive community of organisms having a species composition, diversity, and functional organization comparable to that of natural habitat in the region.

Ecological condition

A broad, holistic concept for describing the state of ecosystems as characterized by their structure and function.

Ecological sustainability

The maintenance or restoration of the composition, structure, and processes of ecosystems over time and space. This includes the diversity of plant and animal species and communities, the productive capacity of ecological systems, disturbance processes, soil productivity, water quality and quantity, and air quality.

Ecosystem

A dynamic complex of living organisms interacting with non-living chemical and physical components that form and function as a natural environmental unit.

eDNA

Environmental DNA. DNA left behind from an organism rather than from a physical specimen. The DNA of an aquatic organism remains in the water after it is shed and can be collected in a water sample.

Epilimnion

The epilimnion is the top-most layer in a thermally stratified lake, occurring above the deeper hypolimnion.

ESA

Endangered Species Act. A provincial document that gives legal protection to species and their habitat that are on the endangered, threatened or extirpated lists in Ontario.

Forebay

The section of a reservoir that is immediately upstream from the powerhouse.

Frazil Ice

Frazil ice is a collection of loose, randomly oriented needle-shaped ice crystals in water. It resembles slush and has the appearance of being slightly oily when seen on the surface of water. It sporadically forms in open, turbulent, supercooled water.

HADD

Harmful alteration, disruption or destruction of fish habitat (Federal Fisheries Act, Section 35.

Head pond

The reservoir immediately above a dam or intake structure of a generating station.

Hypolimnion

The hypolimnion is the dense, bottom layer of water in a thermally- stratified lake. It is the layer that lies below the thermocline.

Hyporheic zone

Zone of substrate in a stream bottom extending as deep and wide as interstitial flow; interface between the stream bed and shallow ground water.

Indicator

A measurable (quantitative) or descriptive (qualitative) variable used to characterize the state of key ecosystem components.

Lacustrine

Of, related to, or inhabiting lakes.

Least Disturbed Reference Condition

Present-day ecological condition found in conjunction with the lowest amount of anthropogenic disturbance (i.e. the best of what is left).

Macrophyte

Aquatic vascular plants that are permanently submerged or floating- leaved, and may be attached or unattached to the substrate.

Mean monthly flow

The average flow for one month that is computed from several years’ worth of data for that month, expressed as cubic meters per second.

Mesohabitat

A discrete area of stream exhibiting relatively similar characteristics of depth, velocity, slope, substrate, and cover, and variances thereof (e.g. pools with maximum depth <5 feet, high gradient riffles, side channel backwaters).

Microhabitat

Small localized areas within a broader habitat type used by organisms for specific purposes or events, typically described by a combination of depth, velocity, substrate, or cover.

Natural Reference Condition

Pristine, natural, or unaltered condition: unaffected by anthropogenic disturbance, or disturbance is indistinguishable from natural variability.

One-dimensional (1-d) model

Models for rivers that solve mass continuity and total energy loss between cross sections. They do not explicitly deal with velocity distribution across cross sections. Both velocity and mass flux are calculated as a single value for each cross section. Velocity distribution is handled empirically and conditions between cross sections are assumed to be linearly interpolated. Models exist that can handle either steady state or dynamic channel characteristics.

Peaking facility

A waterpower facility that stores water then releases it in short-term flow events (e.g. sub-daily, daily, or weekly) to produce electricity.

Penstock

A pressure shaft connecting the water intake to the turbines of a hydroelectric generating station.

Periphyton

Also known as attached algae. Benthic algae that grow on submerged substrata.

PIT Tag

Passive integrated transponder tag. A coded marker injected into individual animals to mark them. Can be used to collect data on movement patterns, growth rates, and survivorship.

Ramping rate

The rate of change of flow (m³/sec/hr) from one magnitude to another. This includes both the slope of the rising (up-ramping) and falling (down-ramping) limbs on a hydrograph that occur during increasing and decreasing generation and flow discharge.

Recruitment

The number of new young fish entering a population in a given year.

Reservoir

A body of water collected and stored behind a dam, usually in the form of an artificial lake.

Resilience

The capacity to recover from disturbance.

Resistance

The capacity to withstand a disturbance.

Riparian flow

Overbank flows that inundate riparian areas. Riparian flow results in significant interaction between the channel and flood plain. The duration and occurrence of these flows over bankfull determine the time available for recharge of subsurface moisture, deposition of sediments and transformation of nutrients.

Riparian zone

Areas adjacent to a stream or body of water that are saturated by ground water or intermittently inundated by surface water at a frequency and duration sufficient to support the prevalence of vegetation typically adapted for life in saturated soil. Typically is a transition zone between the open water ecosystem and the terrestrial, upland ecosystem.

River continuum concept

A framework for integrating predictable and observable biological features of lotic systems based on consideration of the gradient of physical factors formed by the drainage network.

River Segment

A section of river with relatively homogenous habitat over large-scales (km).

Run-of-the-river facility

Waterpower facilities with little or no upstream storage capacity. Instantaneous and continuous discharge from the facility is not appreciably different from the head pond inflow and alteration to the flow regime is indiscernible.

SAR

Species at risk. A species that is listed as a species at risk (extirpated, endangered, threatened, or of special concern) under the Species at Risk Act.

Sentinel Species

A species whose presence is related to a quality of the environment at that location.

Seston

Ultra fine particulate material and phyto- and zooplankton.

Spillway

The channel or passageway around or over a dam through which excess water is released or spilled without passing through the turbines; a safety valve for the dam.

Storage capacity

The volume of water contained between the maximum and minimum allowable levels within a reservoir.

Sublethal Effects

Physiological or behavioural changes after being exposed to a change in temperature.

Tailrace

A pipe or channel through which water from a turbine is discharged into a river.

TEK

Traditional ecological knowledge. Aboriginal or other forms of traditional knowledge on environmental resources that have been passed down through generations.

Thalweg

The line connecting the deepest part of the stream or river.

Thermal Refugia

Cooler areas in the stream that are sought out by an organism when the stream temperature becomes too high. Seeking refugia is a method of behavioural thermoregulation.

Thermal Shock

A sudden change in water temperature that causes negative effects in fish, including direct mortality or indirect mortality by behavioural changes that make it more susceptible to predators.

Thermopeaking

A sudden change in water temperature often in concert with changes in flow magnitude.

Turbidity

A measure of the extent to which light passing through water is reduced due to suspended materials.

Two-dimensional model (2-d)

Models for rivers that solve mass continuity and momentum flux between elements defined by mesh nodes. The entire area of river is represented by the mesh so the length of interpolation is smaller. Hydrodynamic conditions are calculated at the nodes and interpolated along mesh edges. Solution of the momentum equations allows explicit description of velocity vectors at each node. Simulated velocities are depth-averaged. Model formulations are typically fully dynamic, but are often solved to steady state equilibrium.

Valued ecosystem components (VECs)

A general term to describe species of particular ecological and/or social value (e.g. gamefish, species at risk)

Varial Zone

The lateral areas of riverbed that is routinely wetted and dried.

Wetted perimeter

The length of the wetted contact between a stream of flowing water and the stream bottom in a plane at right angles to the direction of flow.

YOY

Young-of-the-year fishes.

ZOI

Zone of influence.