Winter habitat assessment strategies and incorporation of winter habitat in the Norwegian habitat assessment tools

HYDROLOGICAL PROCESSESHydrol. Process. 16, 927–936 (2002)DOI: 10.1002/hyp.364

Winter habitat assessment strategies and incorporation ofwinter habitat in the Norwegian habitat assessment tools

Knut Alfredsen* and Einar TesakerSINTEF Civil and Environmental Engineering, Water Resources, 7465 Trondheim, Norway

Abstract:

Applications of computer programs in the assessment of how a change in discharge, temperature and other physicalconditions affects the available fish habitat are increasing around the world. The programs are typically used as toolsfor setting minimum flow regimes in regulated rivers and in habitat remedial actions. So far most of these applicationshave been concerned with warm water and summer conditions, and few applications incorporate winter temperaturesand ice conditions. This is a flaw in the current procedure since winter may be the limiting period for fish productionin a river and the introduction of ice may completely alter the available fish habitat compared to summer conditions.It is particularly important to be aware of this when carrying out habitat remedial actions, since short periods withadverse winter conditions may be the limiting factor for the fish population. A winter habitat assessment procedurewill include a study of fish behaviour in winter conditions, the effects of various ice types on habitat selection andthe dynamics of ice breakup on the microscale. This paper outlines how fish respond to winter conditions and howhydraulic, hydrologic and biological modelling can be applied to describe winter conditions and their impact onphysical fish habitat. Some of these processes are currently being incorporated into the Norwegian habitat modellingsystem. This paper also points out several areas where more research is needed to describe the physical processes andthe biological responses to a changing environment. Copyright 2002 John Wiley & Sons, Ltd.

KEY WORDS physical fish habitat; river ice; river hydraulics; habitat simulation; hydraulic simulation

INTRODUCTION

In many cases, the use of rivers for different purposes may have negative impacts on fish and other streamliving organisms. Methods and computer tools have been developed to analyse the impact of changes indischarge and mitigation measures to reduce the negative impacts on the available physical habitat for fish(Bovee, 1982; Heggenes et al., 1994). So far most of these methods have considered only the summer situationin the river, or at most looked at responses to cold water conditions. In most northern climate countries variousforms of ice are important in characterizing the winter conditions in a river, and the ice may have severeimpacts on fish populations (Calkins, 1990; Power et al., 1993). Formation of ice can be a limiting factor forthe survival of fish in winter conditions, and it is therefore important to consider ice in the habitat assessmentprocess. Very little work has been done on integrating effects from ice into the existing habitat modellingsoftware. Research is therefore needed, particularly in the field of microscale effects from various types of iceformation and the description of how ice breakup and ice-induced erosion may affect fish habitat conditions.

At this stage it is important to stress that this work considers only the physical habitat. This is only oneof many factors that control the fish population in a river. Physical habitat is most often described througha set of variables that will change depending on the discharge in the river. The most commonly used habitatvariables are depth, velocity, substrate and cover. In addition, temperature and water quality may be includedif these are found to be important. Physical habitat is often grouped among the density-independent abiotic

* Correspondence to: K. Alfredsen, Department of Hydraulic and Environmental Engineering, NTNU, 7491 Trondheim, Norway.E-mail: [email protected]

Received 1 November 1999Copyright 2002 John Wiley & Sons, Ltd. Accepted 15 July 2000

928 K. ALFREDSEN AND E. TESAKER

factors that control a fish population. In addition there are density-dependent biotic factors like predation,competition and social interaction. These factors are, in many cases, most important. The biotic factors arenot included in the physical habitat modelling process. As will be discussed later, the importance of bioticfactors in winter conditions is reduced relative to the importance of the availability of suitable physical habitat.Because of this, it is necessary to include winter conditions in habitat assessment. If this is not done, wrongconclusions may be drawn from the analysis.

Many of the Norwegian rivers where habitat modelling is used are influenced by hydropower developments,most of them of the high head type releasing water from storage reservoirs through tunnels to the power plant.A hydropower system will alter the natural water temperature regime, and thereby the ice production regimein winter. Examples from regulated rivers in Norway show a higher production of anchor and frazil ice thanin natural rivers. Work has been done to try to alleviate this situation by changing the operation of the powerplants in critical ice production periods (Carstens and Tesaker, 1987). Currently many Norwegian hydropowerproducers are moving towards a short-duration peaking operation. This may lead to daily fluctuating dischargeand temperature that can further alter the ice production regime from its normal state.

To include winter conditions in habitat assessment requires both an understanding of the processes thatcreate ice in rivers and the local effects of different ice types on microscale hydraulics (habitat is mostoften studied at a microscale). It also requires knowledge of how fish and other target organisms respondto winter temperature conditions and different types of ice. Research has been carried out in these fields,but currently there is little work being done to integrate biology, hydraulics and hydrology into the physicalhabitat simulation tools.

The remainder of this paper provides information on current work to include methods for winter habitatassessment in the Norwegian habitat simulation system. The following two sections give a brief introductionto the HABITAT program system and an overview of aspects of winter habitat that are relevant to habitatmodelling. The modelling approach is outlined next, and illustrated with an example from a Norwegian river.

HABITAT MODELLING AND THE HABITAT PROGRAM SYSTEM

The HABITAT program system is a computer tool to analyse the impacts on fish of river regulations. It wasoriginally based on the PHABSIM computer tool (Bovee, 1982) and has recently been expanded to cover newanalysis methods and new hydraulic modelling tools (Alfredsen, 1997). Based on a completely object-orientedand flexible structure (Alfredsen and Sæther, 1997), the new HABITAT program system is well suited as aplatform for prototyping, testing and producing tools to assess winter and particularly ice impacts on habitat.

The most common procedure in habitat modelling is to develop fish preferences or suitability curves basedon observations of fish and the total available habitat in the selected area (Bovee, 1986; Heggenes, 1994).The reach is then divided into small areas, termed cells, and a hydraulic model is applied to describe thehydraulic conditions in each cell. The hydraulic parameters are then mapped into habitat classifications usingthe established fish preferences (Figure 1).

Habitat features are often classified as ‘macro’, ‘meso’ and ‘micro’ depending on their variability over theriver system (Figure 2).

ž Macro parameters describe entities that normally have a slow spatial variation, such as discharge andtemperature.

ž Mesoscale habitat describes the variability of the river features, commonly divided into types like Riffle,Run, Pool and Glide. Each of the classes will be defined according to parameters like average depth andvelocity conditions, slope and morphology. Since it is not feasible to do microscale modelling of an entireriver system, the mesoscale classification is often used to extrapolate microscale habitat to the entire riversystem.

Copyright 2002 John Wiley & Sons, Ltd. Hydrol. Process. 16, 927–936 (2002)

WINTER HABITAT ASSESSMENT STRATEGIES 929

Depth at location

Depth habitatclassification

Depth preference function

−1.0−0.8−0.6−0.4−0.20.00.20.40.60.81.0

0 0.2 0.4 0.6 0.8 1 1.2 1.4

Depth

Hab

itat P

refe

renc

e V

alue

Transform depth value to habitat preference

Map habitat area from the preference

d = 0.2p = −0.6

Figure 1. Principle of habitat mapping using hydraulic data and a preference curve

Mesoscale

POOL

POOL

GLIDE

RIFFLE

RUN

Microscale

dv

substrate

cover

Macroscale

Q,T

Figure 2. Overview of macro, meso and micro habitat scales

ž Microscale habitat covers the parameters that vary over a small scale such as velocity and depth. In mosthabitat analysis the microscale parameters form the foundation for the habitat assessment procedure.

Typically HABITAT runs are integrated with a variety of other simulation tools, such as hydropower productionmodels or water quality modelling tools as part of the River System Simulator (Killingtveit et al., 1995). TheRiver System Simulator is a software system that integrates a variety of simulation tools through a commondatabase, and it provides tools for data management and combined simulations.



WINTER HABITAT

Our efforts in habitat modelling are concerned with the juvenile stages of Atlantic salmon (Salmo salar)and resident, anadromous brown trout (Salmo trutta). This discussion will focus on juvenile life stagesof these species. Both species exhibit a marked habitat shift in winter, controlled mainly by temperature.The temperature that triggers the shift from summer to winter behaviour is reported to be in the range of5Ð0–8Ð0 °C (Jensen and Johnsen, 1986; Heggenes and Dokk, 1995a; Scruton and Clarke, 1999). There is somediscussion on the importance of light as a controlling factor, and some observations on increased feeding andswimming activity at low temperatures late in the winter season may indicate that increased day length canbe of importance. In winter the social interaction between fish is reduced, and less territorial behaviour andcompetition have been observed (Cunjak and Power, 1986). This may indicate that the abiotic factors aremore significant in winter (Heggenes et al., 1993).

The change of behaviour and changed habitat requirements in winter will have implications for the habitatmodelling procedure. The common reactions to winter conditions in juvenile Atlantic salmon and brown troutare as follows:

ž Reduced food requirements, reduced food processing capacity (Brett, 1979) and reduced swimming capacity(Heggenes and Saltveit, 1990). All of these indicate a shift away from the summer habitats to winter refugesthat provide more shelter and less exposure to areas of the river with higher velocities.

ž Fish shift from a photo-positive to a photo-negative behaviour and tend to hide in the substrate duringthe day and become night-active (Heggenes et al., 1993; Heggenes and Dokk, 1995a; Rimmer and Paim,1990). The reason for the night activity may be partly to avoid being trapped by freezing during high iceproduction at night and partly to avoid daytime predators (Heggenes et al., 1993). Due to the lethargic stateof the fish, the risk of predation increases during daytime.

Since both species basically hide in the substrate during the day, they seek out areas with larger substrate andwith little fine substrate in the hollows between rocks. The lack of sedimentation indicates that velocities in thewater column around daytime refuges may be high (Cunjak, 1988). Habitat with slower currents is preferredwhen the fish are out of the substrate, especially at night when the fish are active (Heggenes and Dokk,1995b). Together, this indicates the need for a combination of slow current habitat close to large substratewith possible hiding places. Such habitat can be found along stream margins and in slower parts of runs.

Particularly subsurface ice forms like frazil or anchor ice will provide a more hostile environment for thefish. Butler (1991) describes how frazil may distort the ability of the fish to orientate in the stream. Frazilmay also induce movement in the fish that will make them vulnerable to predation and increase their energyexpenditure. The formation of anchor ice may block the utilization of bottom substrate by the fish. If theanchor ice is exposed to air and freezes, it may lead to the formation of anchor ice dams that change flow pathsand dry out stream segments. When anchor ice is removed, it can remove stream substrate and vegetation. Iflarge anchor ice dams form in the river reach, breakup may lead to flood waves that can flush out fish andinflict heavy erosion on the substrate. The typical areas of anchor ice formation (riffle habitat) are also typicalspawning habitat, and formation of anchor ice may freeze up the reeds or block the inflow of oxygen-richwater to the eggs (Calkins, 1990). A stable ice cover is considered beneficial since it may keep temperaturesabove freezing and prevent the production of subsurface ice (Power et al., 1993). Formation of ice along theriverbank (border ice) can provide cover habitat for fish (Power et al., 1999), but as will be discussed later itmay also lead to blocking of vital juvenile habitat. Furthermore, breakup of border ice can lead to erosion inbankside habitat. In regulated rivers with fluctuating discharge conditions, repeated growth and collapse of anice cover may restrict fish movement in the reach and also alter the suitability of the habitat due to changedphysical conditions.



WINTER HABITAT ASSESSMENT STRATEGIES

Cold water habitat assessment

The most used assessment methodology for winter habitat in Norway is a combination of winter preferencesand ice-free hydraulic simulations for the discharge regime found in winter (Heggenes and Dokk, 1995b;Fjeldstad and Heggenes, 1999). This approach is similar to summer simulations, and the current version ofHABITAT is equipped with tools to simulate time series of available habitat using variable preferences overthe year. This is a useful method in cases where ice has little or no effect on the available habitat, and wherepreference curves have been developed for ice-free winter conditions.

An inherent problem with this method is the creation of winter preferences. To be able to create preferencecurves for fish and to monitor fish behaviour for model verification, it is necessary to observe fish in theriver in wintertime. There are several options in collecting fish data from rivers, but winter conditions mayinfluence their usability and reliability.

Diving is the most common procedure for observing fish habitat selection, since it is possible to pinpoint thefish location and get all physical data from that location at a later stage. There are methodological problemsin using diving as a method of creating winter preference curves due to fish hiding in the substrate in coldwater conditions. As an example, in water with a temperature of 2 °C, Heggenes and Saltveit (1990) foundtwo fish by diving while a follow-up with electro-fishing found 227 fish. This clearly illustrates the problemwith creating winter preferences data from diving observations.

Electro-fishing is also a common procedure for sampling fish in a river reach. To observe habitat selection,electro-fishing may bias the results by frightening fish (fright bias) and by forcing fish to swim along thevoltage gradient towards the electrode (galvanotoxic bias) (Heggenes et al., 1990). This makes it difficult topinpoint the location of the fish and thereby to get the detailed physical parameters necessary for creating thepreference curves.

Telemetry is a promising option as the transmitters are becoming small enough to use on juvenile fish. Withtelemetry it is possible both to pinpoint the fish and to find the type of habitat the fish prefers given variablemacro habitat conditions. It is also possible to track the fish as it responds to a change in its environment.

Sonar systems and video are possible methods for fish observation, but they require more research andverification before being used as a tool in fish preference creation. Experiences with under-ice sonar for fishpositioning show that the technique needs some fine-tuning before it can be considered useful for practicalpurposes.

A field of growing interest in habitat modelling is based on solving the energetic equation for a fish (Hughesand Dill, 1990; Addley, 1993; Braaten et al., 1997; Alfredsen, 1998). The energetic equation describes thebalance between the energy available for growth, the intake through food and losses through metabolism andexcretion of waste (Brett and Groves, 1979). The inputs to the model are a combination of data describing thefish, the available feed and the physical environment in the form of water temperature and velocity distributionin the modelled reach. To the authors’ knowledge there are no examples in the literature of using this approachin modelling winter habitat, but it is an interesting area of research since it combines the microscale physicalparameters with both temperature conditions and available feed. Energetic modelling is therefore a possibletool to eliminate the use of preference curves and to understand the energy deficit that is sometimes found infish after the winter season.

Macroscale habitat modelling

The macroscale habitat parameters identified as important in a winter habitat study are discharge and watertemperature. In the assessment of ice production additional macroscale parameters like river slope, site ele-vation and shade/exposure are also important. The mesoscale classification can be a useful way of roughlyassessing the type of ice that may form in each type of habitat, since each mesoscale classification definesthe most important physical parameters controlling ice formation. Typically a riffle habitat will most likelyhave bottom ice formations, while a pool habitat will form surface ice (Kanavin, 1970; Tesaker, 1994). The



mesoscale classification may therefore be well suited as a rough guideline to selecting the proper assessmentmethods for each type of habitat.

In many cases in Norway a hydropower production model will be used to establish the flow regime of theriver depending on the operation of the hydropower system. Typically control points will be defined in thehydropower system where discharge data are extracted and used for further habitat analysis. To simulate watertemperature and macroscale ice production the RICE program (Lal and Shen, 1989) has been used in a coupleof Norwegian rivers with varying results. RICE simulates the energy balance, hydraulics and ice production ina river. The hydraulic model is of the unsteady one-dimensional type, but only for subcritical conditions. Theice model calculates frazil and ice floe production and the formation of border ice. RICE will also generateice covers by accumulation of drifting ice against an obstacle or an existing ice cover. Simulation in the RiverOrkla gave reasonable predictions both regarding ice and temperature (Bjerke and Kvambekk, 1994), whilesimulations in the River Stjørdal proved difficult in the upper reaches, most likely due to the steep slope ofthe river, while the downstream reach gave reasonable predictions (Bjerke et al., 1994).

Microscale habitat modelling

To achieve the spatial resolution needed to describe the fish habitat (Heggenes, 1994) and to get the nec-essary velocity data to simulate both subsurface and surface ice processes, detailed hydraulic modelling isneeded. The best solution would be to base the physical habitat simulation on a 3D hydraulic model withintegrated climate and ice formation procedures that continuously updated the ice formation and included thisin the computation of the hydraulic conditions. To the authors’ knowledge, a system that combines climaticconditions, 3D hydraulics and ice production is currently not available. To apply the SSIIM model (whichis used for hydraulic simulations in the HABITAT program system) would require reprogramming to letice formation influence the hydraulic parameters, such as roughness parameters, velocity and water depth.A system that has not yet been tested in Norway, but could fulfil some of these requirements, is the 2DDynaRICE program system (Shen, 1999). DynaRICE combines a 2D finite-element hydraulic model withenergy balance and ice production models. Compared to RICE, this would provide a better spatial resolutionand the possibility to predict ice formation and ice transport in much better detail.

The option used so far in the HABITAT program system is the combination of hydraulic simulationsin ice-free conditions, winter-based fish preferences and the use of empirical data to assess what typesof ice will appear at different locations and how these may affect the fish habitat. The SSIIM hydraulicmodel (Olsen and Stokseth, 1995; Olsen, 1996) used in HABITAT is capable of simulating flow witha floating surface lid of specified roughness. This feature is used to simulate the under-ice hydraulicvelocities. SSIIM can also simulate suspended sediment transport, a feature that is used for the frazil transportsimulations.

An important topic of investigation in winter habitat is under-ice hydraulics and the computation of theunder-ice flow field. This will change the velocity field found in the free surface simulation and therebyalso the under-ice fish behaviour. Another related study is the effect of growing ice thickness on thevelocities and depths under the ice. With varying discharge conditions the growing ice cover may blockmigration passages and render usable habitat unavailable to the fish for a period of time. To study this theSSIIM hydraulic model has been used. SSIIM solves the Navier–Stokes equations in a 3D non-orthogonalgrid. SSIIM has the ability to simulate both free surface flows and flow with surface lids and in closedconduits.

Case study at Flornes

To develop habitat assessment strategies in ice-covered rivers, geometrical and roughness data were col-lected for a part of the Flornes reach in the Stjordal river, Norway. This regulated river reach has variable iceproduction and has been used as a test case for the implementation of winter habitat simulations. Fish data



has been collected for an area upstream of Flornes, and the preference curves created from these data havebeen used for habitat assessment (Fjeldstad and Heggenes, 1999).

The reach at Flornes was measured as a series of close cross-sections using a leveller. The SSIIM grid wascreated from the cross-sectional data, and a grid of 50 cross-sections with 30 points each was made. Thisgives a grid of 49 ð 29 cells, and the grid was made four cells deep. A simulation with free surface was thencarried out to establish the velocity distribution for ice-free conditions. The bottom roughness was given foreach cell in the grid based on observed substrate data. To simulate the under-ice velocity distribution, a rigidlid was placed on top of the geometry to represent an ice cover. The ice cover was given a constant roughnessof 10 mm based on observations of under-ice roughness from several Norwegian rivers (Tesaker, 1970).The simulation was then made for the ice-covered river. Figure 3 shows the free surface and the under-icevelocity profiles. These correspond well with the theoretical velocity distribution and also with observationsof under-ice velocities in other Norwegian rivers.

The next step would be to collect actual velocity profiles from the modelled reach for a direct comparisonbetween the modelled and the measured velocity field. Another interesting task will be to see how theflow conditions change with an increase in ice thickness. This can be achieved by using the closed conduitsimulation available in SSIIM with a variable roof thickness to represent the growing ice layer for a short riverreach. There is at the moment no method to automatically include the under-ice accumulation of suspendedice in the hydraulic simulation; the thickness of the lid must therefore be adjusted manually before eachsimulation as the ice thickness increases.

Border ice forms along the riverbank in areas with slow-flowing water. The extent of border ice will changedepending on water temperature and discharge. Border ice may alter the available habitat by blocking its useor create new habitat by providing cover for fish under the ice (Power et al., 1999). Border ice can also destroyhabitat through erosion of the bank at breakup. To account for habitat restricted by border ice formation, acombination of hydraulic simulations and preference curves has been used. Data from the hydraulic simulationwas used to identify both usable habitat and possible ice formation areas. Figure 4 shows a map of suitablevelocities (darkest areas) for the Flornes reach based on cold water preferences. Usable velocity habitat isdistributed in a small pool and along the riverbank.

LongitudinalVelocity, profile 6, 0.4 m/s arrow:SSIM IVB-NTH Date: 09 Jul 1999

LongitudinalVelocity, profile 6, 0.4 m/s arrow:SSIM IVB-NTH Date: 09 Jul 1999

8.0 m

a)

b)

8.0 m

Figure 3. Simulation of the Flornes reach with free surface (a) and with a thin ice cover of roughness 10 mm (b). The dotted line indicatescomparable profiles



Preferable Indifferent Avoidable

Plo

tcod

e (0

,1)h0

Figure 4. Habitat map for the Flornes reach based on a cold water preference curve

Summer cross-section

Winter cross-section ICEICE

Figure 5. Cross-sectional from the Flornes study reach showing winter cross-section profile with border ice compared to an ice-freecross-section

Measurements taken in the Flornes reach along each of the cross-sections (Bjerke, unpublished data) showthat border ice grows to the bottom of the river, thereby eliminating the bankside habitat by narrowing theriver profile with increased depth and velocity as a result (Figure 5). This also shows that there are no possiblerefuges (usable cover habitat) under the ice along the banks in this situation. The growth of border ice in theFlornes reach is most likely caused by the fluctuating discharge that will break down and refreeze the ice,thereby creating a compact layer along the banks.

The concentration and transport of frazil ice will have impacts on how fish select their positions in winter. Itis known from the literature that heavy frazil concentration may lead to dislocation of fish, inducing movementthat wastes energy. An option to describe frazil transport on a microscale would be to utilize the sedimenttransport capability of SSIIM. The particles in the sediment transport equations in SSIIM have a fall velocitythat can be set either as zero or negative to represent the buoyancy of the frazil disks. This can then becombined with the habitat parameters to see how the main frazil transport lanes interfere with the usablewinter habitat locations.

Anchor ice production is highest in turbulent areas (such as riffle or pocket water habitats). The hydraulicsimulation produces the turbulent diffusion as a measure of the magnitude of turbulence, and the approachselected is to try to link this parameter to the possibility of finding anchor ice in an area of the river reach.Another parameter that can be combined with the turbulence data is the size of the bottom substrate thatwill work as an ‘anchor’ point for the formation of anchor ice. The areas with a high possibility of anchorice production can then be compared to habitat maps for life stages like spawners or juveniles. The spawnerhabitat will give an indication whether anchor ice may interfere with the areas having reeds.



CONCLUSIONS AND FURTHER WORK

Data from biological studies of fish show that winter conditions may have severe impacts on fish populations.Currently models of ice and ice impacts on physical fish habitat are seldom used in habitat assessment, andin cold climate countries this neglect may cause the critical winter periods to be missed out in the habitatassessment process. This paper outlines some of the methods currently available in the Norwegian HABITATprogram system, and the method development that is currently under way to strengthen the winter habitatassessment process.

Even if many of the new procedures show some promise, more data is needed both to calibrate and verifythe procedures and to develop them further. This is particularly important in steep rivers and in smallerstreams with low availability of suitable habitat, in which we currently have little information available formodelling, but where we know that ice effects on the fish population may be severe. It is especially importantto further investigate the effects of the suspended ice forms on habitat and to utilize methods of monitoringfish behaviour during periods with heavy frazil and anchor ice production. In this work telemetry seems tobe the most useful tool for monitoring the fish behaviour and habitat selection. In the steep river environmentit will also be important to address the formation of anchor ice dams and their impact on fish behaviour andto look at the breakup process and the resulting impacts on the fish population.

ACKNOWLEDGEMENTS

The authors wish to thank Per Ludvig Bjerke for providing data from the Flornes reach for the modellingstudy and Dr. Kjetil A. Vaskinn for reviewing the manuscript. Thanks also go to the anonymous referees forcomments and suggestions that improved the paper.

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Documents

Winter habitat assessment strategies and incorporation of winter habitat in the Norwegian habitat assessment tools