IMPLEMENTING ENVIRONMENTAL FLOWS IN COMPLEX WATER RESOURCES SYSTEMS – CASE STUDY: THE DUERO RIVER...

IMPLEMENTING ENVIRONMENTAL FLOWS IN COMPLEX WATER RESOURCESSYSTEMS – CASE STUDY: THE DUERO RIVER BASIN, SPAIN

J. PAREDES-ARQUIOLAa*, F. MARTINEZ-CAPELb, A. SOLERAa and V. AGUILELLAa

a Instituto de Ingeniería del Agua y Medio Ambiente, Universidad Politécnica de Valencia, Valencia, Spainb Institut d’Investigació per a la Gestió Integrada de Zones Costaneres, Universitat Politècnica de València, Valencia, Spain

ABSTRACT

European river basin authorities are responsible for the implementation of the new river basin management plans in accordance with the EuropeanWater Framework Directive. This paper presents a newmethodology framework and approach to define and evaluate environmental flow regimesin the realistic complexities that exist with multiple water resource needs at a basin scale. This approach links river basin simulation models andhabitat time series analysis to generate ranges of environmental flows (e-flows), which are evaluated by using habitat, hydropower production andreliability of water supply criteria to produce best possible alternatives.

With the use of these tools, the effects of the proposed e-flows have been assessed to help in the consultation process. The possible effectsanalysed are impacts on water supply reliability, hydropower production and aquatic habitat. After public agreements, a heuristic optimizationprocess was applied tomaximize e-flows and habitat indicators, while maintaining a legal level of reliability for water resource demands. The finaloptimal e-flows were considered for the river basin management plans of the Duero river basin.

This paper demonstrates the importance of considering quantitative hydrologic and ecological aspects of e-flows at the basin scale in addressingcomplex water resource systems. This approach merges standard methods such as physical habitat simulations and time series analyses forevaluating alternatives, with recent methods to simulate and optimize water management alternatives in river networks. It can be integrated withor used to complement other frameworks for e-flow assessments such as the In-stream Flow Incremental Methodology and Ecological Limits ofHydrologic Alteration. Copyright © 2011 John Wiley & Sons, Ltd.

key words: e-flows; river basin management plan (RBMP); habitat time series; environmental optimization; AQUATOOL

Received 22 March 2011; Revised 26 October 2011; Accepted 9 November 2011

INTRODUCTION

The assessment and implementation of environmental flows(e-flows) in significantly altered basins are complex tasks thataffect many other socioeconomic and environmental aspects.It is now widely accepted that human water demands mustbe balanced with the needs of rivers themselves, but tensionsin water resource allocation are intensifying (Petts, 2009).Therefore, e-flows should cover the ‘quantity, timing,duration, frequency and quality of water flows required tosustain freshwater and estuarine ecosystems and the humanlivelihood and wellbeing that depend on these ecosystems’(Brisbane Declaration, http://www.eflownet.org/viewinfo.cfm?linkcategoryid=4&linkid=64&siteid=1&FuseAction=display).However, the balance between biodiversity and the ecologicalservices to people is still missing in some of the methodsavailable, which generally do not consider real constraints,such as legal water rights. The generation of e-flows forbiodiversity without considering real water managementalternatives and public consultation can potentially lead to

social and legal conflicts, and the final result could be nochange to how flows are regulated now and in the future.The European Water Framework Directive (EC, 2000)

establishes that the river basin management plans (RBMP)should include all actions needed to attain adequate ecologicalstatus in all the water bodies. Thus, the e-flows, which lead toattaining adequate ecological status, must be defined orreviewed while developing every RBMP. It is clear that in thisframe of water management, the complexity of the e-flowstudies and implementation must be afforded at a basin-widescale to implement compatible flow regimes throughout theriver network within a realistic legal framework.Since the initial applications of the in-stream flow

methods in the 1970s, the integration of analyses at differentspatial and temporal scales has been a major challenge. TheIn-stream Flow Incremental Methodology (IFIM; Bovee,1982 Q1; Bovee et al., 1998 Q2) was the first methodologyframework for the environmental impact assessmentand negotiation in water allocation schemes. The IFIMintegrated the evaluation of hydraulics and habitat suitability(physical habitat simulation, PHABSIM; Milhous et al.,1981), water quality and temperature in a river segment ora river network (Bartholow and Waddle, 1986), as well asthe habitat time series (HTS) and duration curves to evaluate

*Correspondence to: J. Paredes-Arquiola, Instituto de Ingeniería del Agua yMedio Ambiente, Universidad Politécnica de Valencia, Caminos de Veras/n 46022, Valencia, Spain.E-mail: [email protected]

RIVER RESEARCH AND APPLICATIONS

River Res. Applic. (2011)

Published online in Wiley Online Library(wileyonlinelibrary.com) DOI: 10.1002/rra.1617

Copyright © 2011 John Wiley & Sons, Ltd.

Journal Code Article ID Dispatch: 20.11.11 CE: Jessa Mae P. DagpinR R A 1 6 1 7 No. of Pages: 18 ME:

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http://www.eflownet.org/viewinfo.cfm?linkcategoryid=4&linkid=64&siteid=1&FuseAction=display

http://www.eflownet.org/viewinfo.cfm?linkcategoryid=4&linkid=64&siteid=1&FuseAction=display

habitat in a period (Milhous et al., 1990). Among the methodsto assess e-flows at a global scale, the IFIM was the methodapplied in most countries of the world (Tharme, 2003),and it was considered by some practitioners as the mostscientifically and legally defensible methodology availablefor assessing e-flows (Shirvell, 1986; Gore and Nestler,1988; Dunbar et al., 1998). A critical step in the IFIM is theevaluation of river hydrologic regimes and ecologicalresponse functions of aquatic biota, that is, fish (Moutonet al., 2011) or macroinvertebrates (King and Tharme, 1994:Jowett and Davey, 2007). Tools such as PHABSIMs andothers allow the generation of response functions of habitatindicators, weighted usable area (WUA), specific for eachtarget species and size class in a study site, with the in-streamflow in the river segment under study. These curves areimportant outputs for decision support and e-flow negotia-tions. After determining WUA versus flow curves, the lastphase in IFIM includes the HTS and duration curves for theevaluation of e-flow alternatives. This technique is very usefulto evaluate e-flows and management scenarios in comparisonwith the baseline conditions (natural flow regime). It provideshypotheses about possible threats and bottlenecks affectingaquatic populations, and it can be integrated in models ofpopulation dynamics (Bovee, 1989; Cheslack and Jacobsen,1990; Milhous et al., 1990; Waddle, 1992; Nehring andAnderson, 1993).Habitat simulation has been applied in Spain with different

configurations of habitat analyses (e.g. Mayo, 2000; García deJalón, 2003;Martínez-Capel et al., 2006; Agència Catalana del’Aigua, 2008), and a considerable effort was dedicated tomicrohabitat studies in the country during the last decade(e.g. Martínez-Capel, 2000; Martínez-Capel et al., 2009;Mouton et al., 2011;Q3 Costa et al., in press). The hydrologicalmethods for e-flows have been applied in the desk; however,in the practise, the Spanish legislation requires the applicationof habitat simulation to fixing minimum e-flows with a rangeof 50%–80 % of the maximum WUA, in normal years, or30% of minimum during severe drought. The same normallows the determination of minimum as the ‘nickpoint’, thatis, the flow where a dramatic reduction of the curve slopeoccurs (García de Jalón, 2003). In study sites with severehydrological alteration, those percentages were restricted to30%–80%. The decision about these altered sites is made bythe water planning authorities, based on the indexes ofhydrological alteration calculated by site (Richter et al.,2006); the assessment of those indexes does not affect theprocess of defining e-flows further. The minimum flowobtained in this approach is different at each month; thus,the result is not a single minimum flow but a regime of e-flowsthat mimics the natural flow pattern. The definition ofminimum flow follows the legal norm, corresponding onlyto 1month per year (minimum monthly average); the e-flowregime followed the pattern established by hydrological

methods in each site (as explained below), and the relationsamong the magnitudes of monthly flows are permanent. Thepresent approach was developed for application within thislegal framework, emphasizing the habitat simulationmethods,although the approach presented here can be integratedwith or used to complement other frameworks for e-flowassessments such as the IFIM and holistic approaches suchas the Ecological Limits of Hydrologic Alteration (ELOHA).Hydrologic assessment methods and tools constitute

bases of this approach. Some of them were assumed in thedevelopment of IFIM (Bovee et al., 1998). Later on, one ofthe most relevant steps for these approaches was the Rangeof Variability Approach method ( Q4Richter et al., 1997), whichuses 32 hydrological parameters to characterize flow recordsin natural and regulated conditions. This is the basis tocalculate the Indicators of Hydrologic Alteration that allowthe user to evaluate flow regime alternatives. This method-ology has been applied worldwide; in the Iberian Peninsula,it was used to estimate the degree of hydrological alterationbelow the dams of the Segura River basin (Belmar Díazet al., 2010) Q5and to classify river segments into hydrologicalriver types (Belmar et al., 2011). However, a differenthydrological method has been extensively applied to estimatee-flows in Spain (e.g. Agència Catalana de l’Aigua, 2008)known as the Basic Flow method (Palau and Alcazar, 1996).Since the 90s, new holistic methods have been developed

to integrate hydrological and habitat analysis together withsocioeconomic values in the e-flows assessment (Poffet al., 2010). These methods are oriented to identify thecritical flow events (i.e. parameters of the natural ornear-natural flow regime) for the conservation of the majorcomponents, attributes or processes of the riverine ecosys-tem. Some of them construct a modified flow regime in abottom-up procedure, based on a time sequence (e.g. monthby month) and element by element, where an element is aparameter of the flow regime intended to achieve particularecological, geomorphological, water quality or social objec-tives in the modified river system (King and Tharme, 1994;Arthington, 1998). Other holistic approaches construct a flowregime with a top-down procedure (e.g. DRIFT, King et al.,2003), and they are potentially less susceptible to anyomission of critical flow characteristics or processes thantheir bottom-up counterparts (Bunn, 1998). Therefore, it isnecessary to agree on acceptable degrees of flow alterationfrom natural states that meet goals for river management. Thisgroup of methods evolved and rapidly dominated othermethods in South Africa and Australia, where the emphasisis on ensuring the protection of entire rivers with often poorlyknown biota (Tharme, 2003).One of the most recent holistic methods, the ELOHA

approach, proposes the classification of river segments usingenvironmental criteria, which facilitate the integration andextrapolation of results from the segment to the river basin

J. PAREDES-ARQUIOLA ET AL.2

Copyright © 2011 John Wiley & Sons, Ltd. River Res. Applic. (2011)

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scale. The relationship between flow alteration and ecologicalcharacteristics for different river types constitute the keyelement of this approach for developing scientifically credibleregional e-flows criteria. A principle for setting e-flows is thatthis should be carried out at a regional level because theyare related to river types that will have differing natural or‘reference’ conditions (Poff et al., 2010). However, theintegration of hydrological and physical habitat analyses toinform water management at a basin scale requires thecoordination and optimization of e-flows in a river network.The protection of riverine ecosystems downstream from

dams requires reservoir operations to satisfy e-flow require-ments (Richter et al. 2006; Yin et al., 2010). Therefore,tools and decision support systems (DSS) are necessary todesign and manage dam operations to achieve multiplefreshwater resource values. The DSS should take intoaccount the variations of water availability in a specificreach, due to climate and upstream dam operations, toestimate the results of different e-flows on in-stream flow,reliability of water supply demands, hydropower produc-tion and habitat characteristics. Some previous works inthe Klamath river basin with SIAM (Flug et al., 1999) andin the Murray river basin (Young et al., 2003) are examplesof this kind of approach to integrated river basin flowmanagement. With these tools, it is possible to optimizee-flows in a realistic context; with other approaches focusedon optimizing e-flows for biodiversity, the legal constraintscan raise social and legal conflicts, leading to no implemen-tation or any change in the e-flows.

The aim of this work is to develop a new methodologyframework to define and evaluate e-flow regimes at a basinscale, in real and complex water management contexts. Itintegrates habitat analyses with water resource managementneeds and objectives. The method has two steps and a publicparticipation process in between. The first step is the assess-ment of the individual effect of each e-flow proposed.Secondly, a process of heuristic optimization is used tomaximize e-flows in the whole basin. This method is appliedin a large and complex river system, the Duero river basin(Spain). The application of this approach provided ane-flow management scenario for the RBMP at a basin scalethat optimized environmental conditions while maintainingor improving hydropower production and reliability ofwater supply.

STUDY AREA: DUERO RIVER BASIN

The Duero river basin is a transboundary system. Of the97 290 km2 area of the basin, 81% (78 952 km2) is in Spainand 19% (18 338 km2) is in Portugal (CHD, 2008). Theclimate is continental with a strong Mediterranean character.Mean basin precipitation is approximately 625mm/year,resulting in nearly 15 000 million m3/yr of available water inthe river and aquifers.Agriculture in the basin includes unirrigated (3.5 million

ha) and irrigated (0.5 million ha) crops, irrigation being thelargest water consumer in the basin, consuming 80% (3600million m3/yr) of the total volume of water consumed.

Figure 1. Location of the Duero River basin in the Iberian Peninsula, with detail of its hydraulic management subsystems

ENVIRONMENTAL FLOWS IN COMPLEX SYSTEMS 3


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Installed capacity of hydropower is 4000MWwith an averageproduction of 7300 GWh/yr. The urban water demand in thebasin is low, with most of the 2.3 million people living insmall towns of 1000–5000. To comply with the objectivesof supplying agricultural demands and producing energy,the water system has 75 large reservoirs with a total storagecapacity of 7500 million m3. It is divided into 12 subsystemsrepresented in FigureF1 1. These subsystems work independ-ently, although complying with management conditionsdefined by basin policies; some of their main features aresummarized in TableT1 I.Habitat suitability models were available for 7 out of the 12

fish species native to the Duero river basin; all of them arenative, including the brown trout. Several physical habitatsimulations were applied previously in the Duero river basinto define WUA–flow curvesQ7 for some size classes of thesespecies (INFRAECO, 2009). Those curves were estimatedwith available tools for physical habitat simulation(RHYHABSIM, Jowett, 1999; RHABSIM, Payne and DiezHernandez, 2005), for each species indicated below. Thecurves did not include any confidence intervals and weregenerated with the common procedures indicated in themanual of IFIM (Bovee et al., 1998). The physical habitatsimulation is a procedure where two major components areinvolved, a hydraulic model of a representative river segmentand habitat suitability criteria, to describe the suitability of ahabitat variable (usually depth, velocity, substrate and cover)for a given aquatic species and life stage. In the Duero riverbasin, the habitat suitability criteria consisted of univariatecurves. With the results of the hydraulic simulation, thehabitat suitability criteria provide the habitat evaluation foreach variable, in the range from 0 (unacceptable values) to 1(optimal). TheWUA is the sum of habitat suitability weightedby the area at each of the cells defined in the hydraulicmodel, which is calculated for a set of flows, thus definingthe WUA versus flow curve.Biological studies identified seven species that are most

representative of the fish assemblage of the river basin basedon presence and density, and these species were used todevelop habitat suitability models: Iberian barbel (Lucioarbusbocagei); brown trout (Salmo trutta fario); northern straight-mouth nase (Pseudochondrostoma duriense); bermejuela(Achondrostoma arcasii); northern Iberian chub (Squaliuscarolitertii); Iberian straight-mouth nase (Pseudochondrostomapolylepis) and European eel (Anguilla anguilla). A total of 284WUA–flow curves were used in habitat simulation models torepresent these seven species and their size classes in 32 sitesacross the basin.Although the total amount of water to support agricultural

demands is sufficient when calculating it using annualaverages, the reliability of water supply can be insufficientin some situations because of hydrologic variability in spaceand time. Additionally, the currently defined e-flows are too T

ableI.Mainfeatures

ofwaterresourcessubsystemsof

theDuero

riverb

asin

andnativ

efish

speciesconsidered

inthephysicalhabitatsim

ulation.The

Portuguesereservoirsof

the

internationalpartareincluded

Subsystem

Area

(km

2)

Naturalized

monthly

flow

s(

Q6

millionm

3/yr)

Dem

and

(millionm

3/yr)

Storage

capacity

(millionm

3)

Iberian

barbel

Brown

trout

Northern

straight-m

outh

nase

Bermejuela

Northern

Iberian

chub

Iberian

straight-m

outh

nase

European

eel

Tera

5055

2099

148

480

XX

XX

X–

–Órbigo

5005

1500

884

339

XX

XX

X–

–Esla-Valderaduey

9361

2628

690

2185

XX

XX

X–

–Carrión

4928

582

547

169

XX

XX

––

Pisuerga

7057

922

409

325

XX

XX

X–

–Arlanza

5342

890

109

97X

XX

XX

––

Alto

Duero

8888

1118

228

259

XX

XX

X–

–Riaza

4036

338

153

79X

XX

XX

––

Adaja-Cega

7881

657

176

83X

XX

X–

––

Tormes

7588

1369

364

3092

XX

XX

XX

–Águeda

6196

1119

59132

X–

XX

X–

XBajoDuero

7521

284

588

632(*)

X–

XX

X–

–Total

78858

13506

4355

7240

––

––

––

–



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low to achieve desired habitat conditions. Using differenthabitat simulation models and more data to address temporaland spatial patterns, we generated a new set of e-flow rangesto achieve the requirements of the European Water Frame-work Directive. According to Spanish legislation, these flowsmust be established after a series of statistical and habitatsimulation studies and a consultation process with all thestakeholders present in the basin. The impact of e-flowalternatives on the reliability of water supply and hydropowerproduction were primary issues addressed in review andconsultation with stakeholders.

TOOLS AND METHODOLOGY

Themethod presented here links a basin simulationmodel anda tool for HTS analysis. Both tools are implemented in

Q8 AQUATOOL, a DSS for water resources management(Andreu et al., 1996). A simulation model contains the timeseries hydrology (surface and groundwater), water demands,e-flows, hydroelectric plants, the topology, the infrastructure(reservoir, channels, pumps) and the management of thesystem. With this information, a network optimizationapproach is used to estimate time series of water supply orshortage, hydropower production, water levels in reservoirs,

water extraction from aquifers and habitat needs. TheCAUDECO programme can be used to estimate HTS fordefined periods once flows are estimated, taking into accountwater availability and flow management proposals.The approach presented here consists of two technical

steps with a stakeholder review and input process betweenthem (Figure F22). Previous to the application of the method,a water management and habitat model must be developed(Step 0). The water management model at the basin scalecan be developed with the programme SIMGES. The habitatmodel is developed with CAUDECO to estimate the HTS inall the study sites in the basin. The coupling of both modelsconstitutes a Management Habitat Model (MHM) thatreflects the situation of the uses and the habitat in the wholebasin.Once these models are implemented in the DSS, Step 1

consists of estimating the effects of the range of proposede-flows to water supply, energy production and habitatconditions. To do this, an iterative simulation process ofthe MHM is developed. Each proposed e-flow represents arange of minimum flow conditions; this range is onlyapplicable to the month of minimum monthly averagebecause the values in other months follow the flow regimepattern defined. As explained in the Introduction, theminimum flow is not defined with the criteria of little

Figure 2. SchemeQ9 of the methodological approach applied for the coupling of habitat simulation, environmental flows and water managementsimulation at the basin scale. The Step 0 comprises the construction of water management model and habitat simulation model, which allowsthe assessment of alternatives’ effects on the hydraulic system. The Step 1 comprises the assessment of effects of the environmental flows atthe study sites (Q1, at n sites) on the water management and habitat at the basin scale and produces response functions for public negotia-tion. After public participation, in the Step 2, a new set of environmental flows (Qi*) are introduced in the optimization process to improve

environmental flows and habitat conservation while maintaining the legal requirements for water demands

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inprint



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hydrological alteration nor based on imitating the high-flowor low-flow events detected in natural conditions. Differentlevels within this range were used in the MHM simulationto estimate the effects of each flow level on water supplyand energy production at sites across the basin.These outputs are the bases for the public participation

process. They should be very clear for the stakeholders tounderstand the positive and negative effects of each e-flow.The process of public participation is essential for theimplementation of e-flows, as it is recognized in differentapproaches. Within the IFIM, from the first phase of problemidentification and diagnosis to the final negotiation andproblem resolution, a group of stakeholders implements theIFIM, which is a process for solving water resource allocationproblems (Bovee et al., 1998). Consultation can also becarried out when holistic methods are applied; for example,the holistic approach allows consultation regarding waterdemands (Arthington, 1998).In this process, the results of minimum e-flows within the

established ranges from Step 1 were discussed for the wholeriver basin. Public consensus may result in changes in e-flowvalues, but they must be within designated ranges. Thisprocess may involve discussion about the flow variability ofthe e-flow regime (monthly variation), which is establishedat each study site by hydrological estimation (consideringthe relative magnitude of the mean monthly flows to theminimum monthly flow). The participants are informed aboutthe methods applied to estimate natural flow variability. Theresulting minimum e-flows by site were the inputs for Step 2.Step 2 is an optimization analysis of e-flows focused

on maximizing habitat conditions while maintaininghydropower production and the reliability of water supplyas established by law. E-flows are evaluated starting withtheir minimum values and increased until any water supplyor energy production is compromised. In this case, theparticular e-flow is fixed in the previous level and the nexte-flow starts. One limitation of this procedure is that itdepends on the order of increment established; therefore,different orders have to be tested. The following explainsthe programmes and the criteria of water supply andenvironmental parameters used to characterize the situation.

SIMGES system modelling for water resources

The SIMGES model (Andreu et al., 1996) is a managementsimulation model (water allocation model) broadly appliedin several Spanish basins and abroad. The SIMGES modelis based on the conceptualization of hydrological basins innetworks composed by arcs and nodes. Arcs represent riverreaches, reservoirs, demands etc. Nodes represent junctionsor divergences. This provides a flow topology to generatespatially explicit quantitative models for the basin. Moreover,by combining arcs and nodes, it is possible to model other

elements such as hydropower schemes or returns to thesystem. The arcs are defined by their initial and final nodes,the maximum and minimum flows which can circulate, andthe circulation cost of each resource unit. Mathematically,the model solves at each time step (a month in this case) aconservative and connected network flow. Under theseassumptions, the optimization problem proposed can besolved, efficiently, with the Out-of-Kilter algorithm (Fordand Fulkerson, 1962). The non-linearity of some processes,such as evaporation, infiltration or aquifer modelling, issolved by iterations in the resolution of the network flows.In fact, the proposed objective function contains a term foreach of the modelled elements. The contribution of each termis based on a group of formulas that take into account severalconditions for each element. A more detailed explanationof the model is in the SIMGES’ user manual (Andreuet al., 1992). SIMGES runs under the graphic interfaceAQUATOOL, a DSS that allows the creation of models ofhydrological basins within a user-friendly interface.

Programme CAUDECO for habitat time series analysis

CAUDECO is a programme available in the AQUATOOLDSS that can be used to estimate HTS when sufficient dataon WUA–flow curves are available, similar to the use ofTSLIB (see Milhous et al., 1990). The great advantage ofCAUDECO is its linkage to the simulation model SIMGES,which allows the estimation of habitat indicators under eachconfiguration of water management, in every study site ofthe basin. The series are obtained with the following equation:

HTS ¼ WUA Q ið Þ½ ��BIOP ið Þ�LONG�Xmj¼1

SIj C ið Þ½ �Where:

• HTS is the value of the habitat series at the time step i for eachtarget species (and by size class or life stages, if it is the case);

• WUA is the value of the weighted usable area curve for thecirculating flow Q in the time step i; it is obtained in otherstudies for each target species (and, if possible, by sizeclass or life stages);

• BIOP is a function that defines the size class of the speciesin the time step considered;

• LONG is the length of the water body; and

•Pmj¼1

SIj C ið Þ½ � is the sum of the suitability of a contaminant j

with a concentration Cj(i) in the time step i, for the targetspecies (and size class), for the m contaminants modelledin a water quality model. This term is optional.

An example of an HTS curve is shown in Figure F33(a).These series, by study sites, can be calculated in m2 or asthe percentage of the maximum of the corresponding WUAcurve. Therefore, the HTS as well as the WUA are specific



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for each species (species and size class in some cases) in eachstudy site. They are indicators of the potential habitat availableat each time step (usually days, weeks or months). In ourexperience, percentages are more comparable and understand-able for the communication with technicians, water managersand stakeholders in general. From the HTS, it is possible tocalculate the habitat duration curves (HDC, accumulatedfrequency curves), which provide a more comprehensiveresult for comparing alternatives. Figure 3(b) shows anexample of an HDC.Moreover, because the SIMGESmodel can work with both

small and large basins, it is possible to manage a large numberof HTS results. Therefore, the HTS curves can be accumu-lated or aggregated for a practical evaluation of the subsystemor basin status. Although aggregation often implies loss ofinformation, because of the vast quantity of information thatcan be generated with this tool, such simplification providesa more practical product for analysis and decision making.First, in each water body where an e-flow is proposed, anaccumulated HTS was calculated by aggregating, monthby month, the different life stages of each species. Weimplemented three options to carry out this aggregation, thatis, considering a multiplication factor, the minimum valueamong life stages/size classes or their average. It should benoticed that the aggregation is performed month by month,meaning that the minimumWUA in the HTS may correspond

to different life stages of the same species across months.Then, by subsystem, it is possible to make a second aggrega-tion of the HTS available for a given species in different waterbodies (the alternatives to aggregate are the same threedescribed above). In this way, we can obtain a series of HTSfor a species, which represents a general habitat indicator ina subsystem. A similar method was applied to obtain anHTS at a basin scale for each species.

Indicators of system status

There is no single indicator to define the status of a system(Hashimoto et al., 1982). However, to evaluate the supplystatus of one or a group of demands, reliability criteria aretraditionally used to define the supply. In Spain, both fortradition and legal control (IPH 2008), the criteria used foragricultural demands are simple binary criteria (complies/does not comply). The supply to a demand has been satisfac-tory (complies) if the maximum deficit in 1 year is lower thanA% of the annual demand, the maximum accumulated deficitin 2 consecutive years is lower than B% of the annual demandand the maximum deficit of 10 consecutive years is lower thanC% of the annual demand. The deficit is defined as the totalwater demand minus the water supplied. According to IPH(2008), the current threshold values are 50%, 75% and100% for A, B and C, respectively. In this study, we also usedthe annual mean deficit of a group of demands as an indicator.As an energy production indicator, we have used the values ofthe mean annual production of each one of the modelledhydropower schemes in the model, its accumulated value foreach subsystem and for the whole basin.For the environmental scope, the interpretation of HTS is

complex because of the variety of species and size classesevaluated across a large number of sites. Therefore, a usefulpractise is to aggregate habitat information over time in theHDC, which represent the accumulated frequency curves ofthe HTS. Bovee (1997) considers them very useful foridentifying the alteration of the habitat, both in normal andextreme situations. Capra et al. (1995) defined the continuousunder threshold curves that define continuous periods inwhich the indicator of habitat (WUA) stays under a predefinedthreshold. Parasiewicz (2008) modified this concept to takethe bio periods into account by defining the uniform continu-ous under threshold curves. However, in our case, as thesimulation model works with a monthly step, other reliableindicators at this scale were selected, related to the reliability,resilience and vulnerability of the available habitat. Thereliability is based on the probability of maintaining anacceptable habitat status. To do this, we established athreshold of the HTS below, which the habitat could be understress. That threshold is fixed as a percentage of the maximumof the WUA curve. In the case under study, the thresholdvalue was 40%, which is higher than the one defined by theSpanish norm for e-flows (IPH, 2008). The resilience

Figure 3. (a) Example of habitat time series for a 26-yearsimulation; (b) example of habitat duration curves



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measures the recovery capacity of the system. Translating thisconcept to the HTS in this study, we measured the resilienceas the number of consecutive months in which a failure inthe potential habitat has occurred. From the HTS, the monthsof failure, reliability and resiliency were calculated as follows:

Failure ¼ If HTSi < X% � MaxWUAð Þ½ �Reliability ¼ 1� number of months of failure

number of months simulated

� �� 100

Resilience ¼ number of consecutive steps with failure

WhereHTSi is the value of theHTS in the step ‘i’ (usually amonth or day).The last indicator was the accumulated percentage in the

HDC. We defined the accumulation threshold at 80% (seeLafayette and Loucks, 2003). We evaluated whether 80%was exceeded and the accumulated value higher than 80%.

Assessment of e-flow effects

Once simulation and HTS models were developed andreliability and environmental criteria were defined, Step 1was implemented to assess the effects of each e-flow atdifferent levels of implementation (Figure 2). The initialproposal of e-flows consists of a range of values for theminimum flow (e.g. in August) and a temporal monthlypattern distribution. In this method, we have considered theminimum value and the annual monthly flow pattern (percent-age of variation of mean flow from one month to the next) asfixed parameters at each site (depending on the naturalhydrological pattern). The range of e-flows in each site (tobe applied in the month of minimum flow) was divided intoten equal intervals, that is, different levels of possible e-flows.For each level (interval) defined, a simulation of the MHM isrun and time series of results of every element of the modelwere obtained. Because of quantity of results, these are storedin a database. Once the process is repeated for each level of therange and for each e-flow proposed, a database of all theresults is available.Once all simulations have been developed, a large-scale

analysis of results has to be performed to obtain graphs andtables that summarize the effect of each e-flow. These graphsand tables can be generated for different scales (basin,subsystem and local scale), depending on the effect of thee-flow. The analyses illustrate how specific e-flowsmay affectone or many aspects of habitat, hydropower or water supply,and the graphs and tables portray these effects clearly forevaluation by stakeholders. Those plots and tables were thenused in the public participatory process, as described before.

Public consultation

In this study, we do not focus on the public consultationprocess for the reason of it being developed by technicians

responsible for the basin management administration.However, it is an important step in the methodology proposed.The inputs of this step are the ranges of e-flows proposed andthe analysis of the effects of each e-flow. This analysis is akeystone for the public participation process becausestakeholders can understand the effects of the decisions takenin the consultation. The output of this step is a new range ofe-flows that will be the input for the next step.

Basin-scale integration and optimization of environmental flows

After the public participatory process, the resulting minimume-flows define the scenario called ‘base situation’ in the wholeriver basin. The ‘base situation’ is defined and ready forimplementing the optimization process. In this step, the userobtains the optimal outcome for environmental criteria acrossthe entire basin. This is achieved by incrementing the e-flows,in order and step by step, until the maximum level where thelegal thresholds of water supply is met.The e-flows are classified by order of increment in differ-

ent groups. This classification can be done using severalcriteria: downstream to upstream, from more to less sensi-tive, random and others. Once e-flows are grouped for thefirst group of e-flows, a first increment of its minimum valueis carried out, and consequently, a simulation of the MHMis produced. Simulation results indicate whether e-flowsare within legal thresholds or whether demand exceedssupply requirements. If it is the first case, all the e-flowsof the same group are incremented again. Q10The process ofincrementally increasing the first group of e-flows continuesuntil any demands fail. In this situation, values of e-flows ofthe first group are decreased in one step and the next groupof e-flows is selected to increment its values. The process con-tinues until all the groups of e-flows have been incrementallyincremented.The final situation results in higher minimum e-flows

while achieving reliable water supply demands within legalrequirements. If e-flows affect hydropower productionnegatively, a minimum level of hydropower productioncan be defined for the simulation. The final situationdepends on the order of the groups where differentoptimization runs are necessary to define the ‘best’ situation.The optimization is only made with minimum e-flow, but itdoes not affect the range of variability (defined asintermonth variation), which is determined as previously.

IMPLEMENTATION AND RESULTS IN THE DUERORIVER BASIN

The application of this methodology to the Duero basinwater system helped the redefinition of e-flows in the wholebasin in the new RBMP. Previous e-flows were fixed in theRBMP during the 90s, they were lower and the assessment



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was made only with hydrological methods. During thedevelopment of the present RBMP, physical habitat simula-tion studies were carried out and WUA–flow curves wereestimated in each site. Moreover, in the last few years, a verydetailed management model in SIMGES was developed.The water management model contains all the data

gathered during the development of the RBMP of the Dueroriver basin. The most important reservoirs, demands (urban,rural and industrial), hydropower schemes, aquifers, pumpingsites and others are represented in the model. The hydrologicalinflows are obtained both by a rainfall–runoff model andnaturalizing gauged monthly flows. The rainfall–runoff modelis a tool developed by the CEH (Hydrological Studies Centre,Government of Spain) called SIMPA (Ruiz, 1999). Themodelestimates the water distribution in the basin and the mostimportant flows in the different river reaches. It shouldbe noted that a rainfall–runoff model is not part of theAQUATOOL DSS. For AQUATOOL, time series of inflowsare an input to the models. There are hydrological inflowsavailable from 1940 to 2005. However, because of the mostimportant droughts occurring after 1980, the series used forthis study were chosen to start in October 1980. The modelwas calibrated so that water management was close to reality.To do this, SIMGES’ options include the prioritization ofsupply to the different demands, a system of zones prioritiesin reservoirs to establish the reservoir releases and,finally, the operation rules that allow the definition of othermanagement decisions.For the application of CAUDECO to the Duero river basin,

the starting points were the hydro, biological and habitatsimulation studies carried out for the development of theRBMP, which analysed 32 representative of the majority ofbiological, hydrologic, biotic and habitat patterns of the basin.The WUA–flow curves for the different species consideredand their different size classes were available (there are 284HTS in the whole basin). Although the use of HTS in amonthly step is not common, it was necessary because a greatproportion of the sites belong to reaches suffering a completeregulation of their water flow, which makes the instantaneousflows very similar to the monthly average. With regard to theaccumulation of results of HTS, after several accumulationtrials, assessing the programme possibilities, we concludedthat the best option was an accumulation based on averageof the percentage.

Results of site-specific assessment

Spanish legislation requires e-flows to be defined with aconsultation process with stakeholders. To deal with thisconsultation and being able to explain to stakeholders whatwould be the effects of the proposed e-flows, series of simula-tions were carried out to analyse the effects at every site. Foreach of the 32 study sites, the range of minimum e-flow,corresponding to the range of 50%–80% of the maximum

WUA, was divided into 10 even intervals and theircorresponding 10 values. First, a subroutine of multiplesimulations of SIMGES and CAUDECOwas run (see schemein Figure 2), which consisted of trying each of the 10minimum flows at each of the 32 locations, running bothmodels (basin simulation and HTS estimation). After eachsimulation, results were automatically summarized to presentclear results for the consultation process, which allows theanalysis of the effects to be communicated to the differentstakeholders in the river basin.To identify possible problems in the whole basin, an

up–down analysis was performed in which several variableswere analysed at a basin scale and later by subsystem andby site to find lower scale effects. A summary of this is shownin Table T2II and is explained later in more detail, where possibleconflicts due to e-flows have been detected. Some e-flows(nine) did not show possible relevant effects within theirpossible range. These e-flows were in the headwaters, wherejust few demands and hydropower plants are located. Amongthe other 23 e-flows, five had a considerable positive effect onthe habitat indicators without any effect on demands, and theywere named as ‘high influence’ sites. In the other five e-flows,there was a negative effect on the reliability of supply, and theeffect on habitat was small and local (not affecting any othersite). Ten e-flows were defined as ‘compromised e-flows’because they have a positive effect on habitat but can have anegative impact on demands. Detailed analysis of their resultsallows a balanced decision to be reached. Three e-flows wereconsidered ‘special’ because of their great impact on severalvariables. Two of them, ‘Duero en Toro’ and ‘Duero enPeñafiel’, are located in the mainstream of the Duero Riverand affect habitat quality, hydropower production and watersupply demands for most of the basin. The third is TormesAguas Abajo de Almendra (Tormes River downstreamAlmendra Dam), which has a very high negative effect onhydropower production because the e-flow cannot passthrough the most powerful turbine of the basin. This speciale-flow is out of the scope of this study and was consideredin a detailed analysis by engineers and the stakeholders thatwere affected.Here, we present three examples of the site-specific

analyses of possible e-flows where different variables playrelevant roles in the assessment. Figures F4�4 F6–6 show someof the estimated effects of the e-flows in sites with differentmanagement situations, as explained below:

• Figure 4 illustrates a situation on a main river stem that canaffect many subsystems in the basin (Duero River at Toro,near the border with Portugal). Agricultural supply andhydropower generation respond differently to increasingminimum e-flows, which are benefiting adult barbel, ashydropower generation increases with increased e-flows.Figures such as these are used to work with stakeholders



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TableII.Resultsof

environm

entalfl

owanalyses

bysite.F

oreach

studysite,the

initialflow

range(Q

range)

isgeneratedin

thephysicalhabitatsim

ulation;

thus,itisan

inputin

Step1.

Thisrangecanbe

modified

during

thepu

blicparticipation,

resulting

inQ*range;theseflow

sgo

into

theoptim

izationprocessin

Step2where

theoptim

alenvironm

ental

flow

sareobtained

(thisoptim

alvalueisonly

theminim

umannual

monthly

flow

;itisindependentof

thevariability

oftheflow

regime)

Q11

Study

site

(nam

esin

Figure3)

Qrange(m

3/s)

Level

ofeffect

Mostpositiv

eeffect

Mostnegativ

eeffect

Q*range(m

3/s)

Optim

alenvironm

ental

flow

(m3/s)

Duero

enToro

7–40

Veryhigh

STH

Guareña

inToro

Total

annual

averagedeficit

7–29

29Tormes

aguasabajo

deAlmendra

0.5–10

Veryhigh

STH

samelocatio

nTotal

annual

averageenergy

productio

n1.55

–2.61

2.61

Duero

inPeñafiel

6–9

Veryhigh

STH

Duratón

downstream

Las

Vencías.Q

uantil80%

Total

annual

averagedeficit

–6

Duero

downstream

Riaza

river

5–10

High

STH

Riaza

downstream

Linares

delarroyo,A

cumulated

Annualaveragedeficit.

Alto

Duero

water

system

6.66

–7.22

6.66

Tormes

inContiensa

4–6

High

STH

samelocatio

n,Acumulated

Annualaveragedeficit.Tormes

water

system

–4

Tormes

downstream

Villagonzalo

2.5–7

High

STH

Tormes

downstream

Villagonzalo,Acumulated

Annualaveragedeficit.Alto

Duero

water

system

–2.5

Duratón

downstream

Las

Vencías

0.5–1

High

STH

Duratón

downstream

Las

Vencías,A

cumulated

Failure

inUTAH

criteria.

Riaza

water

system

0.5–

0.66

0.66

Adaja

inArévalo

0.4–1

Medium

STH

Adaja

inArévalo,

Acumulated

Failure

inUTAH

criteria.

Adaja-Cegawater

system

0.4–0.6

0.4

Carrión

inPalencia

2–4

Medium

STH

Carrión

inPalencia,

Acumulated


Carrión

water

system

2–2.88

2.66

Eresm

ain

Segovia

0.1–

0.5

Medium

STH

brow

ntrout,Acumulated

STH

Eresm

ain

Segovia

0.1–

0.45

0.1

Esgueva

inVillanueva

delosInfantes

0.3–

0.6

Medium

STH

Esgueva

inVillanueva

delosInfantes,A

cumulated


Pisuergawater

system

0.3–

0.36

0.3

Órbigoin

Cebrones

2.5–

10Medium

–Annualaveragedeficit.

Órbigowater

system

2.5–

3.33

2.5

Terain

Mozar

deValverde

3–6

Medium

STH

Barbo,A

cumulated


Terawater

system

3–3.33

3.33

Riaza

downstream

Linares

delArroyo

0.1–

0.5

Medium

STH

samelocatio

n,Acumulated


Riaza

water

system

–0.1

Voltoya

inCoca

0.1–

0.2

Medium

STH

samelocatio

n,Acumulated

––

0.2

Águedain

Castillejom

Martín

Viejo

1–2

Low

–STH

Europeaneel

1–2

1.11

Duero

inAldeadávila

60–8

0Low

STH

Guareña

inToro

––

80Duero

inGarray

1–2

Low

–Annualaveragedeficit.

Riaza

water

system

–1

Eslain

Villom

ar3.5–7

Low

STH

Órbigo,

Acumulated

––

7Guareña

inToro

0.5–1

Low

–Failure

inUTAH

criteria.

BajoDuero

water

system

0.5–

0.66

0.5

Huebrain

PuenteResbala

0.6–

1.2

Low

–Failure

inUTAH

criteria.

Águedawater

system

–0.6

Pormain

Secos

dePorma

1.5–6

Low

STH

samepoint,Acumulated

–6

Tuertoupstream

Duerna

0.1–2

Low

STH

samelocatio

n,Acumulated


Órbigowater

system

0.31

–1.36

1.36



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to understand constraints and options for different minimume-flows. Finally, the 80% percentile indicator of habitat forthe adult barbel (river Toro at Guareña) shows a slowincrease and remains constant after 29m3/s. This graphhelps the water planning office technicians and thestakeholders to adjust possible flow ranges.

• Another situation is where supply deficit at a basin scale didnot change significantly but specific sites did. For instance,at the Duraton downstream Vencias point, minimume-flows over 0.66m2/s result in 15 failures of criteria for

rural water supply security. Nevertheless, the increase ofminimum e-flow produces a benefit on the accumulatedvalue of habitat for the adult brown trout.

• Figure 6 illustrates a case where the e-flow effects are local.In the river Riaza, downstream of Linares Dam, the onlyrelevant variable regarding demand status is the maximumdeficit in a year for the whole subsystem of this river. Theeffect on the hydropower production of the subsystem isconstant with the increase of flows. Finally, an increase ofthe e-flow from 0.32m3/s implies an improvement in theresilience of the adult barbel at the studied area by reducinga failure during 9 consecutive months to zero.

Table II summarizes the initial flow range (50%–80% ofmaximum WUA), the level of effect, the most importantpositive and negative impacts and the new range proposedafter the analysis in Step 1 of the methodology. In the column,‘optimal’ is the e-flow proposed after the optimizingprocedure of Step 2, detailed in the following section.

Public consultation process

The public negotiation of water management alternatives isnecessary to reach a realistic agreement and to mitigate socialand legal conflicts. In complex river systems such as theDuero river basin, the probability of e-flows implementationat the basin scale would be very low without the informationand agreement of the society affected. In this case, the processwas carried out by technicians of the Duero River BasinAuthority, and the participants came from the waterplanning office of the Duero River Basin Authority, farmers’organizations, environmental NGOs, hydropower producers,

Figure 4. Effect of the environmental flow Duero at Toro over theannual average of total deficit of agricultural demand, annual hydro-electric production and percentile of 80% of Iberian barbel adult

at Guareña at Toro

Figure 5. Effect of the environmental flow Duratón downstreamLas Vencías over the number of failures in reliability criteria ofDuratón irrigation agricultural demand, annual hydroelectric produc-tion and percentage accumulated of STH of Brow Trout adult at the

same place

Figure 6. Effect of environmental flow Riaza downstream Linaresover the maximum deficit of 1 year for all the demands of Riazasubsystem, annual hydroelectric production and resilency of Iberian

barbel adult at riaza downstream Linares



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environmental regional administration and other publicadministrations (municipalities), and other affected stake-holders. After this first consultation process and severaldetailed studies at specific points, they agreed on a feasiblerange of flows.

Results of basin-scale integration and optimization ofenvironmental flows

After the analyses of the e-flows in the whole basin by site andhaving studied all the particular impacts, the study ofimplementing all the e-flows jointly in the whole basin canbe addressed. The starting point was the range of flowproposed in the consultation process for each site (seeTable II). With these new ranges, we analysed the status ofthe river basin when the e-flows in operation were theminimum value of their corresponding ranges. The simula-tions showed that there were no great impacts to the demandreliabilities if all the e-flows were just at their minimum.From this situation, we raise the challenge of obtaining the

e-flows that produce the best possible habitat indicators whilemaintaining the reliability of supply to the consumptiondemands. This is done by a heuristic optimization method,which starts from the lowest flows of the range at each studysite and increases their e-flows following a pre-establishedorder until the maximum allowed is reached (maximum isdetermined by the level of reliability of water supply todemands). Several procedures for optimization were tried:from upstream to downstream, downstream to upstream,higher to lower influence and lower to higher influence.

Finally, the best option was from upstream to downstreamand among flows in the same level from lower to higherinfluence. The ‘best option’ is based on the analysis, at basinscale, of habitat indicators and some site-specific problemsof great relevance (such as the three special cases describedpreviously).Figures F77 and F88, and Table T3III show the comparative results

of the base versus the optimized situation for hydropowerproduction, deficit demands and habitat indexes. As it wasexpected, the optimized situation for habitat would increasethe deficit of the demands, yet maintaining the legal criteria.Compared with the base situation, 46 of the basin demandspresent similar results, 22 demands suffer a deficit and 7 areimproved. Thirty out of the 75 agricultural demand unitsdo not present deficit in the whole study period. It is worthhighlighting that in the optimized scenario, the number offailures of reliability is smaller than in the base situation.With regard to energy production, there is a total improve-

ment of 50GW∙h/yr in the optimized situation. The plantswith a greater increase in production were located inthe downstream part of the main stem. Figure 7 showscomparative energy production between both scenarios.Detailed analysis shows that some hydropower plants hadreductions in production compared with the base situation;however, almost all of them belong to the same company,and we estimated that it has a total net increase in production.Figure 8 summarizes the comparison of environmental

indicators accumulated by species in both scenarios (baseand optimized). Reliability is maximized in both options,and accumulated habitat and resilience were improved in

Figure 7. Comparison of annual hydroelectric production for basic and optimized scenarios in the 12 subsystems where production is relevant



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the optimized alternative for almost all the species,maintaining the legal reliability of the supply. The habitatindicators improved in relation to the good situation of thebase scenario. For example, there is a possible improvementof habitat for the Iberian barbel and Iberian nase. Theimprovement for the Iberian barbel was related to the accumu-lated improvement of WUA in several sites throughout thebasin. For the Iberian nase, however, the improvementoccurred at a very small scale, in the only two sites where itlives. Conversely, for brown trout and Iberian chub, therewas no relevant improvement in the basin-scale indexes.The basin-scale indicators of habitat by sites showed

incremental improvements after the optimization (optimalvalues detailed in the last column of Table II). The more

relevant case was in the river Esgueva (in Villanueva de losInfantes), where results improved greatly from the basesituation without affecting the reliability of supply. Incontrast, the river Eresma in Segovia was not improvedbecause a large percentage of the water resource wascompromised by human water supply.The final solution improves several indicators of the HTS at

site location, particularly the accumulated, percentile andresilience values, the last one only in some cases. Improve-ments of percentile 80% are presented in 25 site locations.The same sites presented improvements in the accumulatedvalues over this percentile. A lesser number of sites, six in total,presented improvement in resiliency indicator, whereas the re-liability of the habitat improved more than 10% in 18 locations.

Figure 8. Comparison of environmental indicators of fish habitat for basic and optimized scenarios

Table III. Indicators of reliability of water supply, accumulated for water subsystem comparing present and proposed situations

Subsystem

Annualdemand(hm3)

Increments of % over annual demandIncrementof failurein UTAH-criteria

Mean annualdeficit

Maximum deficitin 1 year

Maximum deficitin 2 consecutive

years

Maximum deficitin 10 consecutive

years

Tera 133.9 1.44 18.19 21.33 21.33 0Órbigo 432.78 0.52 0.72 0.93 7.33 0Esla-Valderaduey 978.44 �0.16 �0.37 �0.84 �2.93 �25Carrión 281.47 1.48 4.52 11.36 25.34 0Pisuerga 212.26 1.43 2.92 4.19 15.39 1Arlanza 63.25 0.04 1.14 1.14 1.14 0Alto Duero 163.21 1.13 22.17 22.07 28.9 �2Riaza 115.73 0.95 4.88 4.8 9.2 �5Adaja-Cega 170.56 �1.95 �4.93 �8.07 �25.1 �14Bajo Duero 130.07 0.04 0.19 0.25 0.46 0Tormes 277.03 1.64 18.33 18.92 18.92 5Águeda 15.65 0.22 5.65 5.65 5.65 0



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DISCUSSION

Defining e-flows in complex basins is a difficult andmultidisciplinary task as any decision impacts many aspectsof the system. In this paper, a methodology to define e-flowsin water systems is presented. Its main advantage is theoptimization of habitat within the real constraints of the legalwater rights. In the optimization process, we estimated howfar one can benefit the environment and biodiversity whileworking within the constraints of hydropower productionand water supply.One characteristic of this approach was that minimum

habitat thresholds (i.e. range of 50%–80% of the maximumWUA or 30% during severe drought or in very altered sites)were established previously in the Spanish norms forhydrological planning. These values allow the practicalapplication of this approach in such a complex river basin.On the other hand, they were selected to cover a wide rangeof situations in a whole country and may therefore needadjustments or further consultation in some study sites, giventhat those thresholds do not guarantee all the requirements forthe survival of riparian animals or plants. The optimizationprovides an objective method to assess the optimal habitatwithin the legal constraints, but any increase may not besufficient to benefit the habitat in a significant way, in relationto the minimum established in the ‘base situation’. In someplaces, the optimal minimum e-flows may not be sufficientto sustain biodiversity; thus, further negotiations may benecessary to address these specific situations..Although not presented in the article, this integrated

approach includes water quality analysis in case it wasconsidered necessary for the habitat evaluation. It is possibleto develop a water quality model of the basin with theprogramme GESCAL, included in the AQUATOOL DSS.That model should be developed during the ‘Step 0’ of theprocess (Figure 2). For example, GESCAL allows themodelling of temperature, dissolved oxygen and suspendedsediment; it has been applied to solving water quality issuesin some large basins of the Iberian Peninsula (Paredes-Arquiola et al., 2010). In the Duero river basin, there was nowater quality model; thus, it was not integrated in thisapplication. However, water temperature and sediments areimportant issues at the basin scale. For example, watertemperature plays a key role in stream ecosystemmaintenance(Olivares, 2008), with effects on living organisms and onphysicochemical processes that influence the quality of thephysical habitat. The importance of integrating watertemperature in the physical habitat simulation and in-streamflow studies (Jowett, 1997; Bovee et al., 1998) is clear,especially when hydropower production is involved (Toffolonet al., 2010). Sediment transport can be partially implementedin GESCAL, but complementary analyses are necessary todesign a sediment release strategy, which is of great import-ance in Spain where the deficit of sediments is very common

because of the large dams. Also, in relation to sediments, theflushing flows to maintain the river habitats and morphologyneed specific methodologies for its application (e.g. Reiseret al., 1989; Milhous, 1998), which is experimental in theIberian Peninsula since 2003 (Batalla and Vericat, 2009) andis legally recognized in a new regional management plan fore-flows (Agència Catalana de l’Aigua, 2008).Another relevant characteristic of this approach is that, in

the current version, only the minimum flows for habitatmaintenance are analysed, but with a monthly variation. Themaintenance of a natural flow variability is an importantprinciple for riverine ecosystem protection and restoration(Jowett and Biggs, 2009; Poff et al., 2010); this methodologypresents a group of analyses performed on a monthly basis,which are limited in the assessment of flow variability.Moreover, the minimum monthly e-flows register a variationthat may be different in years with different water yield (e.g.dry, normal, wet years), and they were calculated andoptimized to meet habitat objectives and legal requirements.However, other components are necessary to afford a holisticapproach of e-flows, that is, the assessment of e-flow events orflow releases, of great importance for the reproduction ofaquatic fauna, as well as the recruitment of the woody riparianvegetation (Rood et al., 2003; Werren and Arthington, 2003).The period of seed dispersal varies with the species and theclimatic areas within the basin, but in general, hydrochoryrequires at least a partial coincidence of the seedling with flowreleases, as well as suitable patterns of decreasing flows(Mahoney and Rood, 1998), which were not analysed in thisapproach. The time scale of analysis is one of the problemsbecause the flow releases should be designed for smaller timescales, not monthly. Previous approaches have considered theflow variability with analyses at the daily scale (e.g. Richteret al., 1996 Q12; Richter et al., 2006); however, it is recognizedthat such data are not available in many countries, and theassociated uncertainty in the hydrological modelling at thatscale should be considered; our approach is based on thefrequent availability of monthly data among the institutionsof water planning. Following the presented methods andtechniques, an extra module could be added to study thehydrological conditions required for other ecologicalprocesses aforementioned. In our opinion, this is the line offurther research that deserves the largest effort in the develop-ment of this approach.In this work, we explain a real case of e-flows definition in

the Duero river basin, complex and beyond. It was necessaryto link a detailed basin simulation model to a habitatevaluation model that integrates flow and habitat along aperiod, at a large scale, for multiple species and size classes.The basin simulationmodel, developed with the SIMGES toolof the AQUATOOLDSS, allows the estimation of circulatingflows in each water body, the hydropower production and theguarantee of supply to the different demands. These results



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can be put together with the HTS of the six studied species inthe 32 analysed points, and habitat indicators are aggregatedin different ways for decision support. A first stage of thelinkage of these models allowed the assessment of the effectof possible flows depending on the operation level. The resultsof this stage were useful in the consultation process to proposenew e-flows. Stakeholder’s engagement is not only a legalrequirement, but it creates also an agreement upon e-flowprescription for the basin, supported by a broad range ofconstituents, optimizing flow for biodiversity and socialbenefits of water resource management. After this stage, weapplied an optimization process to maximize the minimume-flow while maintaining the legal standards for guarantee.With this application in the Duero river basin, the importanceof integrating quantitative, qualitative and ecological aspectstogether in the definition of e-flows, as well as the advantagesthat this methodology can offer to the water and environmen-tal managers of river basins was demonstrated.One of the previous approaches to e-flows, ELOHA, was

based on existing techniques and mainly relies on the hydro-logical methods of e-flows, whereas the approach presentedhere relies on the assessment of a hydrological baseline (meanmonthly values), which provides the annual pattern ofe-flows, and the assessment of the water management andhabitat indicators in relation to flow, calculated by standardmethods applied in water resources planning and the physicalhabitat simulation. ELOHA proposes to classify river typesusing relevant hydrological metrics, whereas the study sitesin the Duero river basin were distributed throughout thenetwork with the cost-effective criteria of the public adminis-tration for water management.The relationships between the flow regime and the

ecological response are generally described in the ELOHAapproach; those authors propose to develop these relation-ships based on hypotheses testing, and the independentvariables might be hydrological metrics (relevant in the riverclassification) and other variables of management interest.They indicated the interest of using specific functions toevaluate habitat (habitat suitability models), as it is commonin habitat simulation methods (e.g. PHABSIM, in the IFIMmanual, Bovee et al., 1998). In these standard methods,applied in the Spanish river basins (Step 0), the relationsbetween flow and aquatic species (habitat indicators, e.g.WUA) are obtained from hydraulic simulation at the study siteand habitat suitability models for hydraulic and habitatvariables. The habitat suitability models are developed withwell-known procedures (e.g. Bovee, 1986; Mouton et al.,2011; Costa et al., in press), with empirical data by speciesin natural conditions where the organism’s behaviour isanalysed without the influence of hydrological alteration; thisis a relevant difference with the general approach of ELOHA.Empirical models to predict ecological responses to flowalteration are not readily available (Poff et al., 2010), although

it might be an economic approach if the data collection iscorrectly oriented to the hypotheses testing and very valuablewhere biological data and scientific resources are scarce.Our approach presents a relevant increase in the accuracy of

the results, and that is at the cost of decision support modelsand ecological studies to develop habitat suitability models.However, in a regional context with little ecological informa-tion, it would be possible to apply this new approach based onsegment-scale functions of ecological responses, developedby river type (different to the curves WUA–flow used here),as proposed in ELOHA. The generalized habitat–dischargerelationships (Lamouroux and Jowett, 2005; Booker andAcreman, 2007) may be more economic and suitable for thatcontext, and they can be integrated in this approach. Riverclassification may be also integrated in this approach toprioritize the study sites by river types, giving an ecologicalsupport in the development of the river network to be analysedin the DSS (e.g. AQUATOOL-SIMGES-CAUDECO).Our approach proposes a range of values for minimum

e-flows that is used in the public participation process, likeother approaches. However, previous approaches in thee-flows literature were not including the accuracy of the watermanagement models (DSS) together with the process ofoptimization, which goes further to obtain the best feasiblee-flows in realistic water management scenarios, with theactual constrains of water rights in the river basin.This approach was an experience in a social frame where

the water law defines the e-flows as a reserve before anyuse, but the basin development and the water demands greatlyrestrict the range of possible e-flows in the short term, until thelaw is effectively applied; thus, the improvement of the riverecosystems is very limited so far. With these restrictions, ourpragmatic approach allows the optimization of the habitatindixes, as a surrogate to aquatic biodiversity; an importantcharacteristic of this approach is that the aquifers, dam oper-ation rules and water quality can be modelled in the presentedtools for an integrated water planning. Other authorssuggested that the boundaries of e-flow regimes should befirstly defined within sustainability boundaries (Richter, 2009 Q13;Richter et al., 2011) at the basin scale; when that ‘sustainabil-ity boundary approach’ is applied, the full array of valuesassociated with water could be fully realized. Within thatframe, it would be possible to use different tools ortechniques to define and evaluate flow scenarios to increasebiodiversity; in fact, the application of the sustainabilityboundary approach requires an integrated water resourcesmanagement for its implementation (Richter, 2009).The definition of sustainability boundaries would be

possible a posteriori in the Spanish situation; however, itwould not be really applicable in the actual legal frame unlesssocial pressure would make it effective through the publicparticipation in the future. Therefore, the ‘sustainabilityboundary approach’ is not applicable today with the legal



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norms for e-flows. In other countries with different legalrestrictions, a pro-active approach by limiting the hydrologicalalteration for the ecosystem sustainability could be powerfuland easier to address, providing the base for the applicationof more detailed techniques at the basin or the segment scale.This may be the case in developing countries where theadministrations for water planning could establish limits ofhydrological alteration a priori, before the licencing of damconstruction and the register of new water rights.Q14 However,at the basin scale, it is necessary the hydrologicalcharacterization of the study sites (daily scale), and it isimportant the selection of ecologically meaningful parametersof hydrological alteration for the practical application to thewater planning, which demands ecological studies with acost that may be very relevant. For countries or regionswhere detailed scientific assessments of e-flows cannot beundertaken in the near term,Q15 Richter (2011) presented apresumptive standard for e-flow protection; however, the costassociated would not be negligible because it is necessary todevelop hydrologic modelling tools (at daily scale) and toinstall and maintain monitoring networks of stream flow.The requirement of daily data contrasts with the morecommon hydrologic models used by water planners, with amonthly time step (Richter, 2011), for example, AQUATOOLand the approach we present here.In complex basins with a great development, the applica-

tion of e-flow regimen face different challenges; a pro-activeapproach in countries under development could partiallymitigate or solve some of the issues associated to theassessment and implementation. One of those issues is thelow priority given to e-flows in allocation systems. In Spain,the water law indicates that e-flows must be deserved firstand that they are not a ‘water right’ to be assigned; thus, thee-flows should not ‘compete’ with consumptive extractionsin the processes of water planning. The water law is ofsuperior level and rules over the water rights, but in thepractise, the economic compensation to the owners of the rightmay be necessary in some cases, which can economicallylimit the implementation at the basin scale. The implementa-tion is very difficult in cases where the permitting of waterwithdrawals was supported by inefficient estimation of thewater resources; this is the case where the sum of water rightsis near to the mean annual flow (or even larger), or thehydropower generation and/or irrigation demands a flowregime with non-natural flow patterns or even opposite to thatpattern (e.g. the maximum water release in the period whenminimum rainfall occurs). In very developed basins, animportant process to facilitate the water planning is theextinction of water rights (with specific cases listed in nationallaws), which started in recent years in the Duero river basins.The presented approach provides valuable tools to evaluate

and prioritize the acquisition of water rights or the negotiationwith the owners, because it is possible to assess the most

critical segments for the improvement of the aquatic habitatat the basin scale and with an ample time frame, thanks tothe time series analyses. Another challenge, in developedand nondeveloped countries, is the ecological funding of themethods based on hydrological alteration (e.g. Poff et al.,2010; Richter et al., 2011) and of habitat-based methods fore-flows. Although many countries have some knowledge ofthe habitat suitability for target species at small scale, essentialto apply habitat simulation techniques (Tharme, 2003), theempirical models necessary for approaches at larger scale suchas mesohabitat (e.g. Costa et al., 2011; Vezza et al., 2011) andthe empirical models to predict ecological responses tovarious degrees of hydrological alteration at basin scale arenot developed (Poff et al., 2010) or have received very littleattention. To the challenges mentioned before, it is possibleto add the lack of understanding of the e-flow benefits forthe human development, deficient or inexistent coordinationin the water management, the restriction of e-flows implemen-tation to minimum flows, the lack of understanding of thedamage of too much water to the river ecosystem (high flowsin regular operation, e.g. for hydropower or irrigation duringthe summer) and the difficulty of implementing complexe-flow specifications (Richter, 2009).The results from this study demonstrate that optimizing

e-flows after negotiations for e-flow ranges is an importantapproach to improve flow and habitat conditions withinmultiple water management constraints. The methodologypresented here and the AQUATOOL DSS integrate aspectsof water resource and river habitat management into theEuropean Water Framework Directive framework and riverconservation. Further negotiations can be carried out toaddress specific situations where habitat conditions may notbe sufficient to maintain biodiversity. This approach is aniterative, incremental method, where several consultationscan lead to satisfactory results for all water resourcemanagement stakeholders and benefits to biodiversity on abasin-wide scale.

ACKNOWLEDGEMENTS

We are grateful to Professor Jay Lund and the reviewers fortheir very helpful comments and suggestions. We thank theConfederación Hidrográfica del Duero (Spanish Ministry ofEnvironment) for the data provided to develop this studyand the Spanish Ministry of Science and Innovation(Comisión Interministerial de Ciencia y Tecnología, CICYT)for the funding projects, INTEGRAME (contract CGL2009-11798) and SCARCE (programme Consolider-Ingenio2010, project CSD2009-00065).

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http://aca-web.gencat.cat/aca/documents/es/planificacio/cabals/validacio_cabals_CIC_complet.pdf

http://aca-web.gencat.cat/aca/documents/es/planificacio/cabals/validacio_cabals_CIC_complet.pdf

http://www.fort.usgs.gov/Products/Software/tslib/

http://www.fort.usgs.gov/Products/Software/tslib/

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IMPLEMENTING ENVIRONMENTAL FLOWS IN COMPLEX WATER RESOURCES SYSTEMS – CASE STUDY: THE DUERO RIVER...

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