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Draft Guidelines for the Selection of Methods to Determine Ecological Flows and Water Levels

Acknowledgements

Executive Summary – Recommendations

1 Introduction

2 Rivers

3 Lakes and Wetlands

4 Groundwaters

5. References of Main Text and Appendices

Appendix 1: Relationship between Total Allocation and Ecological Flow Requirements in Rivers

Appendix 2: Effects of Flow Regime on Stream Ecology

Appendix 3: Methods Used in Ecological Flow Assessments of Rivers

Appendix 3: Methods Used in Ecological Flow Assessments of Rivers

Hydraulic geometry method

Hydraulic geometry methods per se are not widely used in New Zealand although hydraulic geometry is captured by hydraulic-habitat methods (eg, 1D hydraulic/habitat models). They predict how wetted area changes with flow, but do not have strong links to biological requirements. If hydraulic geometry is measured, the data can also be used for an analysis of habitat suitability. Although changes in wetted area provide more information than historical flow methods, the additional step of habitat analyses provides even more; this method should be considered part of the suite of hydraulic-habitat methods that use hydraulic geometry (eg, 1D hydraulic/habitat models, generalised habitat models, some regional models, WAIORA – see below).

Channel shape is determined primarily by geology and the flow regime of a river. The relationship between hydraulic geometry and flow can be defined between rivers or sites on rivers, using downstream hydraulic geometry or at a site methods; the latter is also known as at-a-station method. For alluvial rivers, downstream hydraulic geometry relationships between channel form and flow are similar in rivers worldwide (eg, Leopold and Maddock 1953; Kellerhals and Church 1989). River width increases with the square root of discharge (exponents range from 0.45 to 0.54: Park 1977; Kellerhals and Church 1989; Jowett 1998). Water depth and velocity also increase with discharge, although the relationships are not as well defined. At a site, hydraulic geometry relationships are more variable and less well reported. For New Zealand rivers, Jowett (1998) gives the average relationships at a site as:

W proportional to Q^0.207

D proportional to Q^0.335

V proportional to Q^0.458

where Q is the discharge, W the average width, D the average water depth, and V the average velocity.

These at-a-site relationships are averages derived over low to normal flow ranges. For any particular river, the exponent of the relationship can change if there is an abrupt change in geometry, such as at the point where a river overflows its banks onto its floodplain, or at the point where a river is no longer confined between its banks. These abrupt changes in geometry will correspond to breakpoints of width/flow or depth/flow curves (eg, Mosley 1992). Breakpoints in the relationships between width, depth, or habitat with flow are usually well defined in rivers of moderate gradient in well-defined channels. Braided rivers are more problematical. As flows increase, additional braids form increasing width and usable habitat, until the wide gravel flood plain is inundated (Mosley 1982). In this situation there are no clear breakpoints, at least not in the low to median flow range.

When hydraulic geometry is used as a flow assessment method, the analysis is usually based on measurements of hydraulic data (wetted perimeter, width, depth or velocity) from one or several cross-sections in the stream. The aim of hydraulic methods is to maximise food production by keeping as much of the food-producing area below water. Because the streambed is considered the most important area for food production (periphyton and invertebrates), it is usually the wetted perimeter or the width that is used as the hydraulic parameter.

The variation of the hydraulic parameter with flow can be found from carrying out measurements at different flows, or from calculations based on rating curves or Manning’s equation. The graph of the hydraulic parameter versus flow (Figure 2.3 in main text) is used for prescribing recommended flows, or to specify a minimum flow. The minimum flow can be defined as the flow where the hydraulic parameter has dropped to a certain percentage of its value at mean flow, or the flow at which the hydraulic parameter starts to decline sharply towards zero (the curve’s ‘inflection point’ or more correctly, a breakpoint). If the wetted perimeter or width is used, the breakpoint is usually the point at which the water covers just the channel base. However, wetting of the channel base might not be enough to fulfil the requirements to depth and velocity for some species.

Gippel and Stewardson (1998) suggest an objective method for defining a breakpoint in wetted perimeter/flow (P/Q) relationships that could be very useful for maintaining consistency in flow assessments between rivers. They suggested the breakpoint could be selected as either the point of maximum curvature or the point where the slope (dP/dQ) is 1, after first normalising wetted perimeter and flow by dividing by their respective values at an index flow, such as the median flow.

Habitat methods

Of the three basic types of instream flow [incremental] methods (IFIM), historical flow methods are coarse and largely arbitrary, unless the natural flow paradigm is adopted and historical flows are specified so that they mimic natural flows. Hydraulic geometry methods provide information on the physical characteristics of the river, but do not have strong links to biological requirements. Habitat methods are an extension of the hydraulic methods. Their great strength is that they quantify the loss of habitat caused by changes in the natural flow regime, which helps the evaluation of alternative flow proposals. According to a review by the Environment Agency in the United Kingdom on river flow objectives, “Internationally, an IFIM-type approach is considered the most defensible method in existence” (Dunbar et al 1998). The Freshwater Research Institute of the University of Cape Town in South Africa states, “IFIM is currently considered to be the most sophisticated, and scientifically and legally defensible methodology available for quantitatively assessing the instream flow requirements of rivers” (Tharme 1996). A review of flow assessment methods in the book “Instream flows for riverine resource stewardship” (Annear et al 2002) describe IFIM as the “most appropriate for relative comparisons of habitat potential from among several alternative flow management proposals” and as “the method of choice when a stream is subject to significant regulation and the resource management objective is to protect the existing healthy instream resources by prescribing conditions necessary for no net loss of physical habitat”. Nevertheless controversy has accompanied the development of the IFIM, in particular the hydraulic and habitat models (eg, physical habitat simulation (PHABSIM: eg, Mathur et al 1985; Scott and Shirvell 1987; Kondolf et al 2000; Hudson et al 2003). A recent multi-authored review concluded with divergent opinions regarding the scientific defensibility of PHABSIM (Castleberry et al 1996).

The aim of habitat-based methods is to maintain, or even improve, the physical habitat for instream values, or to avoid limitations of physical habitat. They require detailed hydraulic data, as well as knowledge of the ecosystem and the physical requirements of stream biota. The basic premise of habitat methods is that if there is no suitable physical habitat for the given species, then they cannot exist. However, if there is physical habitat available for a given species, then that species may or may not be present in a survey reach, depending on other factors not directly related to flow, or to flow related factors that have operated in the past (eg, floods). In other words, habitat methods can be used to set the ‘outer envelope’ of suitable living conditions for the target biota.

Biological information is supplied in terms of habitat suitability curves for a particular species and life stage. A suitability value is a quantification of how well suited a given depth, velocity or substrate is for the particular species and life stage. Other relevant factors – such as cover, aquatic vegetation and presence of other species – can be incorporated into the evaluation of habitat suitability, although this is not common.

The result of an instream habitat analysis is strongly influenced by the habitat criteria that are used. If these criteria specify deep-water and high velocity requirements, maximum habitat will be provided by a relatively high flow. Conversely, if the habitat requirements specify shallow water and low velocities, maximum habitat will be provided by a relatively low flow and habitat will decrease as the flow increases. In contrast to historical flow methods, the habitat method does not automatically assume that the natural flow regime is optimal for all aquatic species in a river.

Habitat methods and water quality models can be integrated, although usually the results of hydraulic models are transferred into water quality models. For example, a water temperature model (SSTemp: Bartholow 1989) uses water depth and velocity for each flow and these data are then used to model how water temperature varies with distance downstream. The integration of stream geometry and water temperature, dissolved oxygen and ammonia models has been implemented in the decision support system WAIORA (Jowett et al 2003).

The two key elements of a habitat-based method are the habitat suitability criteria that are used to calculate habitat and the linkage between available habitat and aquatic populations. These two issues can be discussed and argued without resolution, although the bottom line is that there must always be suitable habitat if an aquatic species or use is to be maintained. An ecological justification can be argued for the MALF, and the concept of a low-flow habitat bottleneck for large brown trout has been partly justified by research (eg, Jowett 1992), but setting flows at lower levels, such as the seven-day, five- or 10-year low flow (Q7, 5 or Q7, 10) is rather arbitrary. Hydraulic methods do not have a direct link with instream habitat; interpretation of ecological thresholds based on breakpoints or other characteristics of hydraulic parameters, such as wetted perimeter and mean velocity, are arbitrary and depend on rules of thumb and expert experience. On the other hand, habitat-based methods have a direct link to habitat use by aquatic species. They predict how habitat (as defined by various habitat suitability models) varies with flow and the shape of these characteristic curves provides the information that is used to assess flow requirements. Habitat-based methods allow more flexibility than historical flow methods, offering the possibility of allocating more flow to out-of-stream uses while still maintaining instream habitat at levels acceptable to other stakeholders (ie, the method provides the necessary information for instream flow analysis and negotiation).

Generalised habitat models

Conventional instream habitat models link hydraulic models to habitat suitability curves for water depth, velocity and bed particle size. The hydraulic model predicts the values of point habitat variables (velocity, depth, particle size) for the discharge in a stream reach. Suitability curves are used to calculate values for each combination of point habitat variables. Their product is a habitat value (HV, ranging between 0 and 1), and when summed over the reach surface area, HV gives the weighted usable area (WUA), which can be simulated over a range of flows to give reach-scale relationships between WUA and discharge.

Applying conventional instream models in a stream reach requires considerable field effort and experience. It may involve a complete survey of bed topography, precise measurements of current velocities and water depths along several cross-sections, which may need to be geo-referenced, depending on the form of hydraulic model. The hydraulic model also requires calibration for which cross-section water levels need to be measured at two or more flows.

Lamouroux and Capra (2002) proposed this model to reduce habitat survey effort but still retain much of the predictive power of conventional habitat-based models. These generalised habitat models use simplified and cost-effective reach descriptions (depth- and width-discharge relationships, particle size, median flow). The advantage of the resulting generalised habitat models is that no simplifying hypothesis is made on the distribution of hydraulic variables within reaches. Their use requires little experience and field effort, and the models provide HV and WUA curves that can be interpreted in a similar way as conventional ones, although with some loss in precision (because they are based on average reach descriptions).

Tests of generalised models in France (Lamouroux and Capra 2002) and New Zealand (Lamouroux and Jowett 2005) found that habitat values for taxa were predictable from simplified hydraulic data. Reach hydraulic geometry (mean depth and mean width-discharge relationships), average bed particle size and mean natural annual discharge could be used to provide reliable estimates of habitat values in natural stream reaches. Key physical variables driving habitat values were found to be similar in New Zealand and in France. The Reynolds number of reaches (discharge per unit width) governs changes in habitat value within-reaches. The Froude number at the mean natural discharge, which indicates the proportion of riffles in stream reaches, was generally the major variable governing overall habitat value in the different reaches. This is consistent with the preference of the benthic fauna, such as many of the native New Zealand fish species and benthic invertebrates, for riffles (Jowett and Richardson 1996; Jowett 2000), and the non-benthic aquatic fauna for runs or pools (eg, Jowett 2002).

The generalised habitat models were robust. Tests of the French models of Lamouroux and Capra (2002) in New Zealand rivers were very satisfactory, and most New Zealand models gave reasonable accuracy when applied in rivers larger or smaller than those used to calibrate them (with some loss of accuracy for some taxa).

Generalised models necessarily lose some information compared to conventional models such as river hydraulic habitat simulation (RHYHABSIM: Figure A3.1). This loss must be balanced against requirements for field work and experience in conventional modelling. In particular, hydraulic geometry relationships in reaches (required by generalised models) can be easily obtained from field measurements made at two different discharges or using regional models (Leopold et al 1964; Jowett 1998; Lamouroux et al 1998). By combining generalised models and hydraulic geometry relationships, estimating habitat values in multiple streams is possible from few field measurements; detailed topographies of stream reaches, associated velocity measurements and hydraulic model calibration are not required.

Generalised habitat models suggest general, simple rules can be used to improve flow management or to estimate regulation impacts over whole river networks. An example of such a rule is that a discharge value of about Q = 0.3*Width would provide optimal habitat values for several freshwater taxa in New Zealand.

Generalised habitat models are fitted to relationships between HV and width-standardised flow for a large dataset of rivers from throughout the nation or a region. Dividing flow by width standardises HV–flow relationships among rivers.

The generalised model takes the form:

The values c and k describe the shape of the curve, whereas the parameter a is a scaling factor that varies from reach to reach. The values c and k are of most interest, because the assessment of flow requirements is based on the shape of the curve, rather than the absolute values. The equation has a maximum at c/k, so that this ratio specifies the discharge per unit width that provides maximum habitat.

The values of model coefficients for each taxa have been derived from a dataset of 99 reaches of New Zealand rivers. The reaches in this dataset have mean flows varying from 0.6 m³/s to 53.8 m³/s (the same data were used by Lamouroux and Jowett (2005). Jowett et al (in press) describe generalised habitat models, and their derivation, more fully.

WAIORA – generalised habitat and water quality

WAIORA, Water Allocation Impacts on River Attributes (Jowett et al 2003), is a decision support system that uses information on stream morphology, either from simple measurements at two flows or from a RHYHABSIM dataset, to predict how instream habitat, dissolved oxygen, total ammonia, and water temperature change with flow. Although WAIORA does not incorporate habitat suitability curves, the generalised models described in the previous section can be easily implemented, either in the programme or as an additional calculation. WAIORA calculates the effects of flow on instream habitat, dissolved oxygen, total ammonia, and water temperature, and links the output to ecological guidelines that can be specified by the user to determine if an adverse effect is likely to occur. A number of assumptions have been made during model development and these are detailed in a manual and help file. The outputs of WAIORA reflect the nature of these assumptions and the quality of the data entered by the user. The models are better at predicting the relative amount of change associated with flow scenarios than at predicting absolute changes. Some guidance on the expected accuracy of models and ‘comfort zones’ associated with guideline thresholds is provided in the help file and the summary plots.

Instream flow incremental methodology

The combination of a description of habitat suitability with hydraulic modelling of river flow is hydraulic habitat modelling; it is the main component of the instream flow incremental methodology (IFIM: Bovee 1982). Hydraulic habitat modelling is also known as instream habitat modelling or physical habitat modelling. The models are of physical habitat (water depth and velocity) and apply instream, so the term hydraulic encompasses both. Although the best known physical habitat model (PHABSIM) is limited to prediction of physical habitat (depth, velocity, and substrate), hydraulic habitat models can also predict the effect of flow on water temperature and dissolved oxygen concentration. They provide a means of condensing diverse data into a result that describes how the amount of instream habitat changes with flow.

Habitat and hydraulic spatial scales

Habitat can be defined at different spatial scales. It is used to describe the location and environmental conditions where organisms live, or where they could live (usually termed microhabitat). However, it is also used to describe a general area, such as riffle habitat (mesohabitat) or even broader conditions, such as an aquatic habitat (macrohabitat). Physical or hydraulic habitat describes the physical instream conditions (usually water depth, velocity and substrate) and does not consider biotic or water quality conditions. Here, suitable or preferred habitat is used to describe the range of physical conditions in which an organism is most likely to be found.

The aim of the minimum flow is to retain adequate water depths and velocities in the stream or river for the maintenance of aquatic life and other instream uses. Instream habitat models predict the flows necessary to maintain, or even improve, the physical habitat for target biota, or to avoid limitations of physical habitat. Because the purpose of hydraulic models is to predict physical habitat, the scale at which habitat is defined by the habitat suitability criteria and the scale of hydraulic model predictions should be similar.

There is some confusion about the scale to which hydraulic habitat models work. Although they are often claimed to predict microhabitat, they do not truly predict the range of velocities experienced in a river. For example, they do not predict the eddies and currents that surround a boulder. However, such currents and eddies around a boulder depend on depth of water and average column velocity and suitable microhabitats will be provided by the larger-scale hydraulic conditions. Thus, these models essentially consider habitat at a meso- to macrohabitat level rather than microhabitat level, maintaining suitable depths and average velocities, and a degree of habitat diversity that is generated by the morphology of the river and is largely independent of flow.

Hydraulic habitat modelling process

The first hydraulic habitat methods (eg, McKinley 1957) used simple hydraulic modelling or surveys at different flows to determine the flows that provided maximum salmonid spawning areas – gravel areas with water depths of 0.2–0.4 m and velocities of 0.2–0.7 m/s (Smith 1973). After this, the methods began to get more complicated with multiple options for hydraulic modelling and habitat evaluation (Milhous et al 1989). Of the available methods for minimum flow assessment, habitat-based methods are the most justifiable because of their simple yet defensible base of providing suitable habitat for aquatic species.

Hydraulic-habitat models are used to predict habitat changes with flow and to assist decisions on an acceptable flow regime, usually with an emphasis on minimum flow requirements. These models predict water depth, velocity, and other hydraulic variables for a range of flows and then evaluate habitat suitability. Current hydraulic-habitat models include PHABSIM (physical habitat simulation: Bovee 1982; Milhous et al 1989), RHABSIM (river habitat simulation), RHYHABSIM (river hydraulic habitat simulation: Clausen et al 2004), EVHA (evaluation of habitat: Ginot 1998), CASIMIR (Jorde 1997), RSS (river simulation system: Killingtviet and Harby 1994), River2D (2D model: Ghanem et al 1996; Waddle et al 2000), SSIIM (3D model: Olsen and Stokseth 1995).

The use of these models requires detailed hydraulic data, as well as knowledge of the ecosystem and the physical requirements of stream biota. The basic premise in evaluation of flow requirements is that if there is no suitable physical habitat for the given species, then they cannot exist. However, if there is physical habitat available for a given species, then that species may or may not be present in a survey reach, depending on other factors not directly related to flow, or to flow-related factors that have operated in the past (eg, floods). In other words, habitat can be used to set the ‘outer envelope’ of suitable living conditions for the target biota.

Hydraulic-habitat models can be separated into a hydraulic component and a habitat component. The hydraulic model predicts water velocity, depth and other hydraulic variables for a given flow for each point, represented as a cell in a grid covering the stream area under consideration. In addition, information on bed substrate and other relevant factors such as shade, aquatic vegetation and temperature, can be recorded for each cell.

Biological information for the habitat component is supplied in terms of habitat suitability criteria for a particular species and life stage. A suitability value is a quantification of how well suited a given depth, velocity or substrate is for a particular species, size, life stage, and behaviour.

The result of an instream habitat analysis is strongly influenced by the habitat criteria that are used. Selection of appropriate criteria and determination of habitat requirements for an appropriate flow regime requires a good understanding of the species’ life cycles and food requirements (Heggenes 1988, 1996).

The hydraulic habitat analysis starts by choosing a particular species, size, and life stage and behaviour and defining suitability criteria. Waters (1976) proposed the use of a suitability index that varies between 0 (unsuitable) and 1 (optimal) as an alternative to binary criteria (0 unsuitable or 1 suitable) that had been used by in earlier hydraulic-habitat studies (McKinley 1957; Collings 1972). Intuitively, it seems reasonable to consider conditions that are of intermediate habitat value, between optimal and barely useful. For each cell in the grid (Figure A3.2), velocity, depth, substrate, and possibly other parameters (eg, cover) at the given flow are converted into suitability indices, one for each parameter. The suitability indices can then be combined (usually they are multiplied), and multiplied by the cell area to give an area of usable habitat. Finally, all the usable habitat cell areas can be summed to give the weighted usable area (WUA m2/m) for the reach at the given flow. If the suitability is > 0 and ≤ 1, the cell will contribute to the total area, but if it is zero the cell makes no contribution. This whole procedure is then repeated for other flows to produce a graph of WUA versus flow for the given species. This graph has a typical shape, shown in Figure A3.3 with a rising part, a maximum and then may decline. The decline occurs when the velocity and/or depth exceed those preferred by the given species and life stage. Thus, in large rivers, the curve may predict that physical habitat will be at a maximum at flows less than naturally occurring.

The method is recognised as the most defensible for assessing instream flow needs in the United States although it has received some criticism (Mathur et al 1985; Scott and Shirvell 1987). The fundamental criticism was that, although it seemed reasonable to assess instream flow needs on the basis of the amount of suitable habitat, there was no evidence that there was any correlation between species abundance and the amount of suitable habitat.

Figure A3.2: Habitat survey of a stream reach, showing the cell area represented by a point measurement

See figure at its full size (including text description).

Since then, some studies have demonstrated relationships between WUA and species abundance and in some instances – such as for benthic invertebrates – suitability is derived from species abundance and is correlated. However, the warning is valid and use of inappropriate habitat suitability curves could give misleading results. It is also necessary to consider all requirements for a species’ continued survival. For example, the primary requirements for salmonids are both space and food (Chapman 1966), so assessment of instream flow needs for salmonids must consider both space and food requirements.

The relationship between habitat and flow (Figure 3.2) can be used to define a preferred flow range, a minimum flow, or a preferred maximum flow. As with hydraulic methods, the minimum flow can be defined as the break point or as the flow at which the habitat has dropped to a certain percentage of its value at mean or median flow. It can also be defined as the flow that has the lowest acceptable minimum amount of habitat in absolute terms. If minimum flows are at or above the habitat maximum for a particular species or instream use, the area of habitat available to that species will be less than maximum for most of the time. Often this does not matter because the rate of change in habitat with flow is less at high flow than at low flow (Figure A3.2) and the difference between maximum habitat and the amount of habitat at a high flow is relatively small. For example, most New Zealand native fish are found in shallow water along the edges of large rivers (Jowett and Richardson 1995) and there is usually some edge habitat available over a large range of flows.

When many fish species and life stages are present in a river, there are usually conflicting flow requirements. For example, young trout are found in water with low velocities, and adult trout are found in deep water with higher velocities. If the river has a large natural morphological variation with pools, runs and riffles, some of the different requirements may be provided for. Still, even in these rivers, and especially in rivers with small habitat variation, one species may benefit greatly from a reduction in depth and velocity, whereas habitat for another species will be reduced. If a river is to provide both rearing and adult trout habitat, there must be a compromise. One such compromise is to vary flows with the seasonal life stage requirements of spawning, rearing, and adult habitat; with the optimum flow gradually increasing as the fish grow and their food and velocity requirements increase. Biological flow requirements may be less in winter than summer because metabolic rates and food requirements reduce with water temperature. Whether fish are not food-limited in winter has not been tested in New Zealand and rarely has it been tested overseas. Some evidence has been found for reduced condition of trout in winter associated with reduced invertebrate food supplies (Filbert and Hawkins 1995; Simpkins and Hubert 2000). If flow requirements of individual species are different, solutions may be found by choosing one with intermediate requirements (Jowett and Richardson 1995) or by defining flow requirements for aquatic communities.

Generalised habitat models take into account the relationship between habitat and channel shape but do not require such detailed habitat surveys as a conventional instream habitat survey. Generalised models which are derived from ‘WUA times flow responses from several rivers determined from traditional instream habitat surveys’, can be applied to a specific stream knowing only the average width at one discharge.

Within the suite of habitat-based models, it is possible to select the model that is appropriate to the situation. In many situations, the simple generalised model, with one measurement of width and flow, can be used to define a minimum flow for the appropriate critical values and habitat retention levels. If the stream morphology is unusual (ie, substantially different from the range of rivers used to derive the generalised model) or if greater certainty is required, the width can be measured at two flows and WAIORA used to apply the generalised models. Finally, if the value of the instream or out-of-stream resource requires the most detailed level of consideration, instream habitat surveys and 1D, or even 2D, models can be used to predict habitat response curves for the critical values; or even fish energetics models, in the case of trout, which predict net rate of energy intake (Hayes et al 2003; Kelly et al 2005).

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