GIS-based models for water quantity and quality assessment in the Júcar River Basin, Spain, including climate change effects

Science of the Total Environment 440 (2012) 42–59

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Science of the Total Environment journal homepage: www.elsevier.com/locate/scitotenv

GIS-based models for water quantity and quality assessment in the Júcar River Basin, Spain, including climate change effects Javier Ferrer a,⁎, Miguel A. Pérez-Martín b, Sara Jiménez a, Teodoro Estrela a, Joaquín Andreu b a b

Confederación Hidrográfica del Júcar (CHJ) Júcar River Basin Authority, Avd. Blasco Ibáñez nº 48, 46010, Valencia, Spain Research Institute of Water and Environmental Engineering (IIAMA), Universitat Politècnica de Valencia, Camino de Vera s/n, 46022, Valencia, Spain

H I G H L I G H T S ► ► ► ► ►

Establishment of measures to accomplish the Water Framework Directive in Mediterranean basins. Description of two GIS-based tools used to support the implementation of the WFD. Water resources assessment and measures to achieve good chemical status. Recent water resources have been reduced by approximately 18% compared to the period 1961–1990. Climate change impact: water resources reduction by 19% in the short-term and 40–50% in the long-term.

a r t i c l e

i n f o

Article history: Received 30 April 2012 Received in revised form 30 June 2012 Accepted 4 August 2012 Available online 7 September 2012 Keywords: Water planning Water Framework Directive Large river basin Mediterranean GIS model Climate change

a b s t r a c t This paper describes two different GIS models – one stationary (GeoImpress) and the other non-stationary (Patrical) – that assess water quantity and quality in the Júcar River Basin District, a large river basin district (43,000 km2) located in Spain. It aims to analyze the status of surface water (SW) and groundwater (GW) bodies in relation to the European Water Framework Directive (WFD) and to support measures to achieve the WFD objectives. The non-stationary model is used for quantitative analysis of water resources, including long-term water resource assessment; estimation of available GW resources; and evaluation of climate change impact on water resources. The main results obtained are the following: recent water resources have been reduced by approximately 18% compared to the reference period 1961–1990; the GW environmental volume required to accomplish the WFD objectives is approximately 30% of the GW annual resources; and the climate change impact on water resources for the short-term (2010–2040), based on a dynamic downscaling A1B scenario, implies a reduction in water resources by approximately 19% compared to 1990–2000 and a reduction of approximately 40–50% for the long-term (2070–2100), based on dynamic downscaling A2 and B2 scenarios. The model also assesses the impact of various fertilizer application scenarios on the status of future GW quality (nitrate) and if these future statuses will meet the WFD requirements. The stationary model generates data on the actual and future chemical status of SW bodies in the river basin according to the modeled scenarios and reflects the implementation of different types of measures to accomplish the Urban Waste Water Treatment Directive and the WFD. Finally, the selection and prioritization of additional measures to accomplish the WFD are based on cost-effectiveness analysis. © 2012 Elsevier B.V. All rights reserved.

1. Introduction The European Water Framework Directive (WFD) (EC, 2000) aims to achieve good status for all water bodies by 2015, which means implementing all water quality directives, such as the Nitrates Directive (EC, 1991b) and the Urban Waste Water Treatment Directive (EC, 1991a, 1991b). To achieve this goal, the WFD establishes that River Basin Authorities (RBAs) must implement River Basin Management Plans (RBMPs), including a Program of Measures (PoM). ⁎ Corresponding author. Tel.: +34 39 387 97 94. E-mail address: [email protected] (J. Ferrer). 0048-9697/$ – see front matter © 2012 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.scitotenv.2012.08.032

The selection of measures to be implemented requires a quantification of their individual effectiveness in achieving both the final goal and the cost-effectiveness analysis of each measure. To perform this task, it is necessary to use mathematical models to quantify the consequences of the proposed measures. Selecting which models to apply depends on the available data and the type of problem under consideration. The Júcar River Basin District (RBD) was one of the pilot river basins for the implementation of the WFD in Europe. Therefore, in this basin, different methodologies and models to undertake the Directive's requirements have been applied and developed. Pressure-impact analysis (CHJ, 2005) identified that the main pressures in the surface water

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Fig. 1. (a) Júcar RBD location and (b) river basins and river network in the Júcar RBD.

(SW) bodies are (CHJ, 2009) point source (PS) pollution (37% of SW bodies are affected), non-point source (NPS) pollution (59%), water withdrawals (21%), morphological pressure (42%), and other pressures (42%). A large number of groundwater (GW) bodies (47%) do not achieve good status because they do not reach good quantitative status (22%), do not have good chemical status (7%), or a combination of the two (16%). The main pressure on GW bodies that prevents the achievement of good chemical status is nitrate pollution from agriculture and livestock.

The Júcar RBD is characterized by a strong interaction between SW and GW, which requires an integrated analysis of both and the use of models that include these interactions. The studies developed in this basin show that the main challenges to meet the WFD objectives are (CHJ, 2009) 1) improving the quantitative status of GW bodies, which will also reduce the withdrawal pressure on associated SW bodies, 2) improving the nitrate level in GW bodies, which will also reduce the diffuse pressure on associated SW bodies, and 3) reducing point source pollution in SW bodies.

Fig. 2. Annual rainfall data (mm/year−1) in the Júcar RBD.

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Table 1 Parameters of the GeoImpress model and physical process. Process

River

Current streamflows Biological oxygen demand BOD5 Total phosphorous PT

Fgs KBODriver Organic matter degradation –

Reservoir KBODreservoir Organic matter degradation KPreservoir Sedimentation

In relation to the availability of water resources, the Mediterranean area is one of the most vulnerable regions to climate change (Milly et al., 2005). Different climate change scenarios predict a rise in temperature and a reduction in precipitation (van der Linden and Mitchell, 2009; EC, 2007 and Dore, 2005), exacerbated by a higher temporal and spatial variability, which together would significantly reduce the available resources in the river basin. In the Júcar RBD, a set of GIS-based models have been developed and applied to analyze these problems from a practical approach. The undertaken quantitative analyses include water resource assessment, GW balances, estimation of available GW, and analysis of climate change impact on the water resources. The qualitative analyses developed include the impact of urban PS pollution on SW bodies, including the selection of measures to reach good status, and the impact of nitrogen NPS pollution on GW bodies. In this way, GW bodies that achieve the WFD objectives are identified, as are the time needed and the required measures. To conduct this analysis, two models have been used: 1) a GISbased stationary model (GeoImpress) to provide a global overview of the main problems in the basin and to permit easy evaluation of the measures' effectiveness and 2) a GIS-based monthly water balance and water quality model (Patrical) to analyze problems in which variations in time are relevant to water resource assessment or nitrate evolution in GW. The GIS-based stationary model (GeoImpress) applies a pressureimpact scheme to a large river basin (Henández-Lumbreras, 2007). The model assesses the impact of urban PS pollution (pressure) on SW bodies in hydrological averaged streamflows, considering the concentration of total phosphorous (PT) and the biological oxygen demand (BOD5). The PT case corresponds to a conservative type pollutant, while

the BOD5 case corresponds to a non-conservative type pollutant (organic matter). This model provides a general vision of the existing problems and allows for determining the effectiveness of the considered measures. The model is currently being applied to other river basin districts in Spain, such as Duero RBD or Guadiana RBD. The GIS-based monthly water balance model (Patrical) is a hydrological and water quality catchment simulation model (Pérez-Martín, 2005) that has been used for the water resource assessment of the river basin (Pérez-Martín et al., in press-a, in press-b), including long-term resources, spatial variability, inter- and intra-annual variability and climate change impact and for the analysis of the temporal evolution of processes with higher inertia, such as nitrate pollution in GW bodies. The model has been applied throughout Spain, and its results are used by different Spanish river basin authorities, such as Júcar RBD, Duero RBD, Guadiana RBD, and Ebro RBD. The remainder of the paper is organized as follows. Section 2 describes the main characteristics of the case study, the Júcar RBD. Section 3 provides a brief description of the stationary model (GeoImpress) and the non-stationary model (Patrical). Section 4 includes the application of both models and a discussion of the results. Finally, the last section describes the conclusions and experiences gained by combining these types of models in solving practical problems related to the implementation of the WFD. 2. Case study The Júcar River Basin District (RBD) (43,000 km 2) (Confederación Hidrográfica del Júcar, CHJ) is located in the eastern part of the Iberian Peninsula in Spain and is formed by the aggregation of watersheds that flow into the Mediterranean Sea (Fig. 1). Júcar, Turia, and Mijares are the three main rivers in the Júcar RBD. GW is especially relevant in the Júcar RBD, with 90 defined GW bodies and over 70% of the streamflow coming from GW bodies' drainage (CHJ, 2009). The Júcar RBD's climate is characterized by high temporal and spatial variability, with an average annual rainfall of 500 mm in the historical records varying between 320 mm in the driest years and nearly 800 mm in the wettest years, but from 1990 to 2010 the annual rainfall averaged 487 mm (Fig. 2). This average annual rainfall has important spatial differences. For example, in southern regions, the

Fig. 3. GeoImpress model overview.

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Fig. 4. Maps of (a) monthly temperature and precipitation and results of water flows in the drainage network and (b) flux diagram of the Patrical model.

average annual rainfall is lower than 300 mm, while in other areas, it reaches values above 800 mm. 3. Simulation models The analysis developed in relation to the WFD relies on the use of two different GIS simulation models (one stationary (GeoImpress) and the other non-stationary (Patrical)) to assess water quantity and quality in the Júcar RBD. A relation between the two models exists, as the GeoImpress model uses the average distributed streamflows obtained by the Patrical model. GeoImpress assesses the quality of SW bodies, while Patrical assesses water quality for GW bodies. 3.1. Stationary simulation model River Basin Management Plans (RBMPs) must include a Program of Measures (PoM) to be implemented to reach WFD objectives (EC, 2000). These PoMs include a selection of the most effective sets of measures to achieve these objectives. To study these measures, the Júcar RBA developed the GeoImpress model as a simplified tool, which has been subsequently used by many Spanish RB Authorities. In a GIS environment, this tool estimates the effectiveness of the PoM in SW bodies, including a conservative pollutant, such as total phosphorous (PT), and a non-conservative pollutant, such as organic matter and its impact on SW and the biological oxygen demand (BOD5).

The GeoImpress model (Henández-Lumbreras, 2007) was developed by means of graphical scripts with the ModelBuilder included in the Geographical Information System (GIS) ArcGIS 9.3. The model is fully distributed, with cells of 100 × 100 m, and allows the routing of point source (PS) pollution in the river network. The pressure, PS pollution, is routed based on the Digital Terrain Model (DTM), taking pollutant decay into account. The decay is simulated through an exponential law defined by the decay constant K. Two types of decay are considered: decay in rivers Kriver, calculated for each pixel of the river basin, and decay in reservoirs Kreservoir, obtained for each reservoir. The decay K depends on the chemical compound obtained by calibration, taking into account the observed water quality data in the water quality control network of the Júcar RBD. The model simulates the degradation of the organic load due to the natural purification of waters along the river network, which reduces the concentration of BOD5, the decay in rivers. The model also simulates the effect of the total phosphorus sedimentation in reservoirs by means of the phosphorous decay in reservoirs. The model has only four parameters (Table 1): one to fit average streamflows (Fgs), two to simulate BOD5 (KBODriver and KBODreservoir), and one to simulate PT (KPreservoir). The model permits the assessment of measures to be applied in SW bodies, and when necessary, supports decisions about exemptions from the environmental objectives. The low number of parameters makes it a very robust model, as experience demonstrate.

Fig. 5. Simulated and observed time series of monthly natural inflows of the Júcar River into the Alarcón reservoir (m3/s).

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Fig. 6. Long-term (1940/41-2009/10) water balance of the Júcar RBD.

Fig. 7. Annual total river flows (hm3) in the Júcar RBD (1940/41-2009/10).

The current average annual streamflow QCirc is obtained by the following expression: Q Circ ¼ maxð0; Q nat þ GWret−GWw−SwÞ þ Sret

ð1Þ

where Qnat is the natural average annual streamflow obtained from the Patrical model, which will be described later. Sw and GWw are, respectively, the surface and groundwater withdrawals for energy generation and urban, agricultural, and industrial use. Sret and GWret are, respectively, the surface and groundwater returns from waste water treatment plants and other discharge points or are estimated from water uses for irrigation. The current fitted average annual streamflow QcirF is obtained by the following: Q CircF ¼ F gs ⋅Q Circ

ð2Þ

where Fgs is a parameter representing the ratio between the observed average streamflows and the Qcirc. The organic matter decay in rivers and the BOD depend on the mean temperature and the distance of the flow. The constant

KBODriver is obtained according to the following expression:

ðT−20Þ

KBODriver ¼ Kb⋅θ

ð3Þ

Table 2 Available groundwater resources in the Júcar RBD. Component

hm3/year

Percentage over ROR

Rainfall infiltration 1980–2008 Total return (2000–2008) River losses (2000–2008) GW lateral inflows (2000–2008) GW overall recharge GW lateral outflows (2000–2008) Regional overall recharge ROR Base flow Wetlands GW flows into the sea Total environmental requirements Available groundwater resources

2442.88 475.54 272.34 920.05 4092.89 858.31 3234.58 671.44 99.76 225.35 996.55 2238.03

21% 3% 7% 31% 69%

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Fig. 8. Long-term climate change impact on water resources in the Júcar RBD.

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Fig. 9. Discharge point characterization (equivalent population).

where T is the average water temperature in °C in each cell of the basin, θ = 1.047, and Kb is the constant of decay, which depends on the distance and varies between 0.01 and 0.15 km −1. The model's data input is derived from urban discharge points (e.g., the discharge pipe from a sewage plant) located in the river basin, characterized by the annual volume, PT concentration, and BOD5. From these data, the model obtains (Fig. 3) the accumulated pressure (the sum of pollutants located upstream) in the river network, the PT, and the BOD5. Moreover, it calculates the current average annual flow rate at each point of the river network. The relation between the accumulated pressure, taking into account the decay of pollutant concentration in rivers and reservoirs, and the current average annual flow rate determine the impact on the SW bodies, total PT, and BOD5 concentration. 3.2. Non-stationary simulation model Patrical Decision Support System (DSS) (Pérez-Martín, 2005) includes a distributed water balance and water quality model for large river basins. This model has supported the following activities: 1) water resources assessment in the Júcar RBD, including SW

resources, GW resources, their interactions, and monthly streamflow time series in gaged and ungaged basins, 2) assessment of renewable and available GW resources and GW body balance, 3) climate change impact on water resources, and 4) the definition of nitrate concentration objectives in the GW bodies, including the effect of the measures to reduce fertilizer application in agriculture. In the Patrical model, the river basin is divided into two vertical layers: an upper zone, where the model is distributed because the basin is divided into cells, and a lower zone, where the model is semi-distributed because the simulation of GW is divided into aquifer sectors. The Patrical model simulates the hydrological cycle under both natural conditions and conditions affected by human activity and obtains results for each month and each cell for (Fig. 4) liquid precipitation, snow storage, generation of hydrological surplus, actual evapotranspiration (ET), soil moisture, infiltration into aquifers, surface runoff, base flow in aquifers, river losses, and flow at each point of the drainage network. For each aquifer sector, it obtains the average piezometric level, rainfall recharge, lateral inflow and outflow from and to other aquifers, runoff into rivers, runoff into wetlands, and runoff directly into the sea (Pérez-Martín et al., in press-a).

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Fig. 10. (a) Fgs parameter and (b) KBODriver parameter.

This model attempts to overcome the difficulties in hydrological models to adequately adjust to a large river basin, sufficiently detail the GW balance, and solve practical problems. It fits the natural monthly flows and two additional elements (GW levels and riveraquifer interaction) well, compared to other models for large watersheds. The model is being used in the Júcar RBD for more than 250 aquifers and throughout Spanish territory (500,000 km 2), with over 800 aquifers in the simulation. 4. Results and discussion The combined use of the two proposed simulation models can solve various needs associated with WFD implementation. Water resources assessment, determination of the available ground water resources, and evaluation of the climate change impact on water resources are analyzed with the Patrical water balance model. One major problem that prevents the achievement of good status in SW bodies is the impact produced by urban pollution, which causes a reduction in oxygen content and increases the risk of eutrophication. Analysis of the measures needed to achieve good status of SW bodies in relation to pollution from urban sources is conducted with the GeoImpress model, as the measure's effect is produced in the short term and can be analyzed with stationary conditions and current average streamflows and discharges. Regarding GW, the major problem preventing good status is nitrate pollution due to farming practices. The Patrical model is used to analyze the measures necessary to achieve the objectives in the GW bodies and the time required, as recovery in aquifers is a slow process. 4.1. Water resources assessment in the Júcar RBD, including climate change

which was calibrated for the period October 1940–September 2004 and was validated from October 2004 until September 2010. A proxy basin test was also conducted for the entire simulation period (October 1940–September 2010) (Pérez-Martín et al., in press-a) at points that were not used during calibration and validation and that were located in the same river basin and in other river basins. Calibration, validation, and proxy basin tests were performed with the simulated and observed streamflows (Fig. 5) and with the simulated average GW level and observed water table in wells. Calibration and validation were performed at 17 surface checkpoints and 33 wells, and the proxy basin test was performed at 24 surface checkpoints and 60 wells. The types of error statistics used (values obtained for the streamflows fits) were as follows: bias, defined as the difference between the average simulated inflow (ASI) and average observed inflow (AOI); relative bias; Nash and Sutcliffe's (1970) efficiency coefficient E (calibration average value 0.47 and range [0.22 to 0.81], validation −1.05 [−4.19 to 0.74] and proxy basin test −0.37 [−3.09 to 0.50]); the special correlation coefficient Rs (Sarma et al., 1973) (calibration 0.82 [0.62 to 0.95], validation 0.68 [0.38 to 0.91] and proxy basin test 0.24 [−1.69 to 0.91]); and the integral square error ISE (Sarma et al., 1973) (calibration 0.53 [0.87 to 0.25], validation 0.63 [0.32 to 0.95] and proxy basin test 1.53 [5.54 to 0.33]).

Table 3 Calibration process of GeoImpress parameters. Parameter

Procedure

Range values

Fgs

Calibrated using streamflows data from gaging stations Calibrated using water quality data from the ICA network Calibrated using water quality data from the ICA network Calibrated using water quality data from the ICA network

0.1 to >5.0

KBODriver KBODreservoir

Water resources assessment consists of determining water flows and storages in the river basin. For the Júcar RBD, this assessment was performed using the monthly results from the Patrical model,

KPreservoir

0.01 to 0.11 0.003 to 0.753 0.002 to 0.570

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Table 4 Thresholds to establish the limits for good/moderate status of BOD5 and total phosphorus. Parameter

Cut-off value good / moderate

BOD5 Total phosphorus PT

≤6 mg/l b0.4 mg/l

4.1.1. Water resources assessment The long-term (1940/41-2009/10) water balance of the river basin (Fig. 6) quantifies the components of the hydrological cycle and their spatial distribution. The average rainfall (503 mm) in the basin is divided between ET (409 mm) and hydrological surplus (Wa = 94 mm), which represents a runoff coefficient of 19%. The Wa is, in turn, distributed between surface runoff (30 mm) and infiltration (64 mm) into the aquifers, which means that approximately 70% of water resources in this river basin passed through the soil and ground phases. The total annual streamflows (3343.8 hm 3) are composed of SW (1087.9 hm3) and GW baseflow (2255.9 hm3) to the river network. The remaining GW discharges flow into wetlands (288.4 hm3) or the sea (438.5 hm3). The overall balance in other sub-periods of time allows for analysis of changes in the basin's hydrological cycle across time. The period 1961–1990 is wet compared with the long-term hydrological cycle (Fig. 7), while the period 1990–2010 is drier, with a reduction in the average total river flows of 11% compared with the long-term balance and a reduction of 18% relative to the period 1961–1990. 4.1.2. Groundwater balances and available groundwater resources The WFD defines (Article 2) “Available groundwater resource” as the long-term annual average rate of overall recharge of the body of groundwater less the long-term annual rate of flow required to achieve the ecological quality objectives for associated surface waters specified under Article 4, to avoid any significant diminution in the ecological status of such waters and to avoid any significant damage to associated terrestrial ecosystems.

The overall long-term recharge Rtotk of the GW body “k” is obtained as the sum of the mean values of recharge due to rainfall infiltration Infilk, mean recharge due to return from irrigation and urban uses Retk, river losses Rlk, and transfers from other GW bodies Ilk, obtained with the Patrical simulation model (Table 2). Rtot k ¼ Inf ilk þ Ret k þ Rlk þ Ilk

ð4Þ

The water volumes that must be maintained in the aquifers to meet the environmental objectives include the baseflow maintenance, the GW outflow maintenance to wetlands, and the GW outflow maintenance to the sea to avoid seawater intrusion in coastal aquifers. Some specific environmental studies have determined those values at certain points of the basin. Awaiting future detailed studies, a preliminary assessment of the environmental water needs was conducted at the remaining points of the river basin. This preliminary assessment is based on a combination of the streamflows of recent years simulated in the observed hydrological regime (modified by human activities) with the natural hydrological regime. 4.1.3. Climate change impact on water resources Assessment of the climate change impact on water resources is performed through a simulation of the hydrological cycle with the Patrical model and by correcting available maps of precipitation and temperature according to the monthly anomalies for the different climate change scenarios. Two studies have been developed with the Patrical model to assess the long- and short-term climate change impact in the Júcar RBD (Estrela et al., 2012). For the long-term forecast (2070–2100), climate change scenarios are available based on A2 and B2 SRES emissions (Special Report on Emission Scenarios from IPCC, 2000). These scenarios were obtained with the HadCM3 model and adapted to local conditions in Spain with the PROMES model (Gallardo et al., 2001); they correspond to the scenarios elaborated for AR3 by the Intergovernmental Panel on Climate Change (IPCC, 2001). Based on those monthly climatic anomalies (Fig. 8), impacts on natural water resources, water needs for crops, and water management in hydrological

Fig. 11. (a) Averaged annual natural streamflow and (b) current averaged annual streamflow for the period 1980–2008.

Fig. 12. Baseline scenario status: (a) BOD5, (b) PT, and (c) BOD5 and PT.

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Fig. 13. (a) Basic measures and (b) reuse improvement measures.

systems in the Júcar RBD were assessed (Hernández Barrios, 2007). The impact on natural water resources was calculated with the Patrical model, including the monthly distributed anomaly in temperature and precipitation. The results obtained show a global reduction of streamflow of approximately 40% for the entire Júcar RBD with great spatial variations, specifically, 38% in the A2 scenario and 43% in the B2 scenario. The most affected areas, with 50% reduction, are the inner zones of the basin, while the coastal areas close to the sea show lower reductions of approximately 25% (Estrela et al., 2012.). For short-term forecasting (2010–2040), Chirivella (2010) characterizes future climate scenarios in the Júcar RBD by a climatic regionalization obtained through dynamic downscaling. The regional model employed is the RegCM3, with future climate data taken from the global model ECHAM5 and considering the A1B emission scenario, which corresponds to the scenarios elaborated for AR4 (IPCC, 2007). The predicted impact on water resources for the Júcar RBD for the period 2010–2040, also estimated with the Patrical model, represents a reduction of 19% compared to the control period 1990–2000 (Estrela et al., 2012.).

4.2. Compliance with WFD objectives for SW bodies Urban point source pollution is one of the main pressures preventing the achievement of good status in many SW bodies. Urban discharges reduce the oxygen content in water and increase the eutrophication risk. Therefore, the GeoImpress model is used to analyze the effect of the measures to reduce urban pollution on these two chemical parameters.

4.2.1. Input data The urban pressure in the Júcar RBD is produced by 675 discharge points (Fig. 9), which produced a total volume of 400 hm 3 in 2009. The average pressure of these points is 15.7 mg/l of BOD5 and 3.0 mg/l of PT.

As mentioned above, the current average annual streamflow QCirc (Fig. 11b) is obtained by Eqs. (1) and (2). For the Jucar River Basin, Qnat is used as the natural average annual streamflow for the period 1980–2008 (Fig. 11a) obtained from the Patrical model. Sw and GWw are the surface and groundwater withdrawals in 2009 for energy generation, urban, agricultural and industrial use (Rivera-Urban, 2011). Sret and GWret are the surface and groundwater returns from waste water treatment plants (year 2009) and other discharge points (average 2005–2009 volume) or are estimated from water uses for irrigation (Rivera-Urban, 2011). 4.2.2. Model calibration The current streamflow is fitted to the observed streamflows with the Fgs parameter (Fig. 10a) as the ratio between the observed average streamflow in the gaging stations of the Official Network of Gauging Stations (ONGN) and the Qcirc. F gs ¼

Q Obs ½ONGN Q circ

The parameters associated with water quality in the model are calibrated using data from the water quality network of the JRBD (Fig. 10b). The reservoir parameters are adjusted using quality data of the input and output flows of the reservoirs (Table 3). 4.2.3. Scenarios Three scenarios have been simulated with the GeoImpress model to determine the degree of fulfillment of the objectives, the necessary measures to attain them, and their effectiveness: • Baseline scenario. This scenario is based on the current conditions, corresponding to current hydrology and current pressures. It is identical to the conditions used to calibrate model for chemical water status in the year 2009, calculated from the water quality data observed in the network. • Basic and reuse measures (B&Rm) scenario. This scenario includes the basic measures for compliance with the Urban Waste Water

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Fig. 14. B&Rm scenario status: (a) BOD5, (b) PT, and (c) BOD5 and PT.

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Table 5 Prioritization of additional measures based on qualitative effectiveness assessment and unitary cost. Measure type

A B C D E F

Waste water network management (WwNM) WwNM + waste water plant management for additional nutrient removal (PT) (P ≤ 2, P ≤ 1) WwNM + waste water plant management for additional organic matter and nutrient removal (PT and DBO5) WwNM + additional nutrient removal at waste water plant (PT) (P ≤ 2, P ≤1) WwNM + regeneration treatment (RT) (SS ≤ 10, DBO5 ≤ 5) WwNM + RT + post treatment with green filters (needs prefiltration)

Unitary cost €/m3

Qualitative effectiveness assessment Non-fulfillment due to BOD5 and PT

Non-fulfillment due to PT

Non-fulfillment due to BOD5

0.11 0.19

1 2

1 2

1 *

0.20

3

3

*

0.32 0.50 0.53

4 5 6

* 4 5

2 * 3

* indicates that it is not applicable

Treatment Directive (EC, 1991a, 1991b) and measures to improve water efficiency in the river basin by means of waste water reuse. • Additional measures (Am) scenario. This scenario includes a set of additional necessary measures to achieve the WFD objectives and less stringent objectives (LSO). The B&Rm scenario is based on pressure reduction in the river basin, due to the Urban Waste Water Treatment Directive (EC, 1991a, 1991b) implementation, through reduction of pollutant concentration in the discharge or development of waste water reuse facilities that reduce the discharge volume into the surface waters. The Am scenario is defined by means of the effectiveness evaluation of the additional measures and the degree of achievement of the objectives in the SW bodies that are used as threshold values (Table 4) for good status and good ecological potential in highly modified water bodies for each parameter (BOD5 and PT). Those that achieve good and moderate status in Table 11 of the Water Planning Instruction (includes the ARM/1195/2011 order, from May 11) are used as a reference here. The process of defining the measures to reduce the urban pressures contains two steps: (1) the development of the measures in the B&Rm scenario, the basic measures associated with the fulfillment of the Waste Water Treatment Directive (EC, 1991a, 1991b) and the improvement of the waste water reuse and (2) the Am scenario application to accomplish the WFD goals or to set the LSO.

4.2.4. Model results Due to the clear connection between flow rate (quantity) and water chemistry conditions (quality) in the Júcar RBD, the model first calculates the current average annual streamflow in the river basin based on the natural streamflow (Fig. 11). The model assesses for each scenario whether the point source pollution considering the current streamflow prevents reaching the goals (Table 4) and determines the reason for each water body. In the baseline scenario, 23 water bodies do not achieve good status (Fig. 12). The measures included in the B&Rm scenario are the necessary measures for the urban discharges to comply with the Directive's requirements (basic measures). The basic measures include the following (Fig. 13a): maintain the infrastructure, improve collectors, improve secondary treatment (T2), improve nutrients removal treatment (T3), and improve appropriate treatment (TA). This scenario also includes measures to increase the water efficiency through waste water reuse (Fig. 13b). The B&Rm scenario has been modeled by reducing the discharge concentration for the basic measures or by reducing the annual volume of discharges to the SW bodies due to increased reuse. As a result, the B&Rm scenario implementation mainly reduces the number of SW bodies with phosphorous impact (Fig. 14). The total cost associated with the B&Rm scenario is 1228.20 M€, where 665.15 M€ relates to basic measures to accomplish the Urban Waste Water Treatment Directive (EC, 1991a, 1991b) and 563.05 M€ relates to measures that increase waste water reuse in agriculture.

Table 6 CEI of the additional measures. SW body code

Type of measure

EAC (M€/year) (price 2009) (a)

Efficiency on SWB (b)

CEI (a/b)

Objective

Year

30.01 16.01 31.04 18.12.01.03 18.32.01.01 10.13 18.32.01.05 28.03 24.01 29.04 31.04 15.05 18.32.01.04 15.18 18.32.01.04 31.04 15.18 30.01 18.14.01.06 18.12.01.03 18.12.01.03 18.14.01.06 18.12.01.03

B B B D A D D D A D E D A D C B D B D D F F E

0.02 0.05 0.08 0.05 0.10 0.10 0.12 0.14 0.18 0.18 0.23 0.27 0.34 0.29 0.15 0.21 0.34 0.07 0.55 0.04 0.42 2.94 0.10

98% 100% 88% 55% 100% 100% 100% 100% 100% 100% 100% 100% 100% 84% 9% 12% 16% 2% 14% 1% b1% b1% b1%

0.02 0.05 0.09 0.09 0.10 0.10 0.12 0.14 0.18 0.18 0.23 0.27 0.34 0.35 1.72 1.83 2.08 3.38 3.89 4.16 >20 >83 >587

Good Good Good LSO Good Good Good Good Good Good Good Good Good Good Good Good Good Good Good LSO LSO Good LSO

2021 2021 2021 2015 2021 2021 2021 2021 2021 2021 2021 2021 2021 2021 2021 2021 2021 2021 2021 2015 2015 2021 2015

status status status status status status status status status status status status status status status status status potential

potential

J. Ferrer et al. / Science of the Total Environment 440 (2012) 42–59

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Fig. 15. (a) Additional analyzed measures and (b) accumulated EAC and CEI.

4.2.5. Cost-efficiency analysis The cost-effectiveness analysis was performed to determine the set of additional measures to meet the WFD objectives. The application of a methodology based on the analysis of all possible measures and their possible combinations was rejected due to the large number of alternatives that would have been necessary to assess. For this reason and using the results of pressure, the GeoImpress model includes the following methodology: 1) identifying the main pressure that prevents achieving good status in the 15 SW bodies (Fig. 14), 2) defining the applicable measure types and their prioritization in terms of cost, 3) selecting the measures required for each water body and validating its effect with the GeoImpress model. Applicable measures have been prioritized by the degree of goal compliance and the average cost (a value of 1 indicates lower priority and 6 higher priority in Table 5, and * indicates that it is not applicable). The unitary cost by cubic meter is the ratio between the Equivalent Annual Cost (EAC) and the annual water volume. The EAC includes the annualized capital costs and operational annual costs (OAC) and was calculated using Technical Guidance for the Characterization of Measures (CEDEX, 2011) for populations between 1000 and 50,000 population equivalents (pe). The annual water volume is estimated considering a flow rate of 270 l/pe/day. To achieve good status in the 15 SW bodies, the cost-effectiveness of 23 measures (Table 6) was analyzed by calculating the costeffectiveness indicator CEI, which is the ratio between EAC and the compliance degree with the final goal in the SW body. The 23 measures sequenced by the CEI show a disproportionate cost (CEI > 10)

in the last 3 measures because its efficiency is nearly zero. Therefore, these measures were discarded. Moreover, this indicator also shows a clear relation between high values and the establishment of less stringent objectives (LSO). The comparison between accumulated EAC and CEI of the 20 accepted measures (Fig. 15) also permits the prioritization of the measures to be developed, giving higher priority to those with a CEI below 0.5, as these first 14 measures are clearly more effective. The additional investment in those measures is 15.55 M€ (Table 7), well below the measures cost of the scenario B&Rm. Most of the selected measures correspond to Waste water Network Management (A) and WwNM + Regeneration Treatment (D). In the baseline scenario, 285 SW bodies achieve good status and 29 SW bodies do not (Fig. 16). The B&Rm scenario, which corresponds to the implementation of basic measures of compliance with the Urban Waste Water Treatment Directive (665.15 M€) and the reuse increase (563.05 M€), reduces the number of SW bodies that do not achieve good status to 15. Finally, implementation of the Am scenario (15.55 M€) allows for all but two water bodies to achieve good status. 4.3. Groundwater nitrate levels and compliance with WFD objectives Changes in the nitrate levels in GW require a long period of time due to aquifer inertia. The necessary time to achieve environmental objectives in GW bodies depends on many factors, including aquifer characteristics, water renewal time in the aquifer, and type of applied mitigation measures. To evaluate the effectiveness of the measures to

Table 7 Additional selected measures.

A B C D E F Total

Number of adopted measures

Investment (M€) (price 2009)

OAC (M€/year) (price 2009)

EAC (M€/year) (price 2009)

CEI

3 5 1 10 1 – 20

7.63 0.00 0.00 7.50 0.61 – 15.55

0.14 0.43 0.15 1.62 0.29 – 2.54

0.62 0.43 0.15 2.10 0.33 – 3.54

0.10–0.34 0.02–3.38 1.72 0.09–4.16 0.23

56 J. Ferrer et al. / Science of the Total Environment 440 (2012) 42–59

Fig. 16. (a) Baseline scenario, (b) B&Rm scenario and (c) Am scenario.

J. Ferrer et al. / Science of the Total Environment 440 (2012) 42–59 Table 8 Summary characteristics of the scenarios considered. Scenario

Baseline

Optimal

TR&I

Nitrogen inputs (tN) (a) 182,100 135,700 164,000 Nitrogen outputs (tN) 104,300 90,500 103,100 Nitrogen surplus (tN) (b) 77,800 45,200 60,100 Relative surplus (b/a) 43% 33% 37% Local Nitrogen pressure (kg N/ha of crops and 24.9 14.5 19.9 pastures) General Nitrogen pressure (kg N/ha) 18.1 10.5 14.2

be applied and the time needed to achieve the objectives, the use of simulation models that consider all of these factors is necessary. Due to this large inertia, a monthly simulation model was used to evaluate the effectiveness of the mitigation measures and the needed time to achieve the objectives of nitrate concentration in GW bodies. The environmental objectives for each Spanish GW body in relation to pollution by nitrates have been defined for the following water planning horizons: 2015, 2021, and 2027 (Pérez-Martín et al., in press-b). With this simulation model, the effects of three fertilizer application scenarios (Table 8) on the GW nitrate levels were assessed. 1) The baseline scenario serves to maintain the current fertilization. 2) The optimal scenario evaluates the application of the optimal nitrogen dose but requires a strong economic investment through the application of techniques such as “fertigation” (i.e., the application of fertilizers, soil amendments, or other water-soluble products through an irrigation system). This scenario implies a 25% reduction in the current nitrogen inputs on soil. 3) The trend reversal and improvement (TR&I) scenario is an intermediate stage between the two above scenarios and includes the development of an action plan defined for current vulnerable areas. It is the most plausible scenario for the short and medium term and implies a 10% reduction of the current nitrogen inputs to the soil. The Patrical model first reproduces nitrate concentrations observed in the control period and then evaluates future nitrate levels for the three considered scenarios. In the case of the “Plana de Valencia Sur” (PVS) (Fig. 17), it can be observed that the baseline scenario maintains current nitrate levels, the trend reversal scenario reverses the trend and stabilizes the nitrate levels at approximately 60–65 mg/l, and the optimal scenario achieves nitrate levels of approximately 50 mg/l and may meet the target set by 2027. It must

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be considered that some variations over nitrate levels exist along the time associated with the hydrological scenario used; during dry periods, nitrate levels tend to increase, and in wet periods, nitrate levels tend to decrease. The obtained results permit the identification of those GW bodies that will reach the objectives by 2015, with a nitrate concentration lower than 50 mg NO3/l in that year and without a growing trend; the identification of the GW bodies that require an extended deadline until 2021 or 2027; and the detection of those GW bodies that require less stringent objectives, as they cannot obtain nitrate concentrations lower than 50 mg NO3/l by 2027, even with the implementation of optimal doses of fertilizer. For the TR&I scenario (Fig. 18a), 8 GW bodies will require the establishment of less stringent objectives, as the aquifers have high inertia, and extensive time is needed for recovery; therefore, they will not reach nitrate levels below 50 mg/l by the year 2027. If significant investments to implement measures such as fertigation were made to further reduce the nitrogen surplus, the number of GW bodies that require the establishment of less stringent objectives would total 3 (Fig. 18b). 5. Conclusions The definition of the measures that should be implemented to reach the objectives established by the WFD requires the realization of multiple analyses using the available information about the River Basin District (RBD), which has a heterogeneous character. Evaluating the effectiveness of those measures requires the use of tools and models that must adapt to the type of problem and to the type of information available to solve the practical problems at the level of the RBD. In this paper, the operation and implementation of a set of GISbased models to assess the water quantity and quality in the Júcar RBD is described, including climate change effects, which allow for solving practical problems related to WFD implementation in the Júcar RBD. These problems include water resource assessment, assessment of the available GW resources in each GW body, climate change impacts on water resources, the definition of the Program of Measures to reduce the urban pollution impacts and eutrophication risk, and achieving the objective of nitrate levels in GW bodies. This study demonstrates how the tools that have been developed and used can address and solve problems with different characteristics

Fig. 17. Nitrate levels simulated for each scenario in the GW body “Plana Valencia Sur” (PVS) in the Júcar RBD and observed data.

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Fig. 18. Final state of GW bodies in the (a) TR&I scenario and (b) optimal scenario.

from a practical approach and that the models can be implemented in medium and large river basins. The processes related to SW and with a reduced inertia can be addressed at the river basin level with simpler tools, taking into account the stationary conditions, which has been the case for both average oxygen content in the water and phosphorus concentration. Processes that change over time or that have a higher temporal inertia, such as for changes in GW, require simulation models of the hydrological cycle that consider water quality. Monthly models, such as the employed Patrical model, are sufficient. With this model, current and future water resources and temporary variations that occur were evaluated. In addition, an assessment of the effectiveness of measures to reduce the nitrate concentration in GW bodies and the time required to achieve this objective was conducted. The water resource assessment developed for a 70-year period shows that water resources have recently experienced a significant reduction, estimated at 18% compared to the control period 1961–1990. It is necessary to consider that if this reduction is maintained in the future, it may significantly impact river ecosystems and water quality due to its strong relation to the streamflow in this basin and water availability. In the Júcar RBD, the renewable groundwater resources are approximately 3200 hm 3/year. The quantitative status improvement in the groundwater bodies set by the WFD, which will consequently improve the morphological and chemical status of surface water bodies, involves the establishment of water volumes that must be maintained in the aquifers (approximately 30% of the renewable resource). This volume is divided into baseflow maintenance (21%), GW outflow maintenance to wetlands (3%), and GW outflow maintenance to the sea to avoid seawater intrusion in coastal aquifers (7%). Finally, the remaining 69% may be considered available groundwater resources, which represent approximately 2200 hm 3/year. The climate change impact on water resources in the Júcar RBD implies a great reduction in the natural streamflows. The main impact in the short-term (2010–2040), based on the dynamic downscaling A1B scenario, is a 19% reduction in water resources compared to 1990–2000. This reduction is in addition to the reduction observed in the streamflows in recent years. The long-term

(2070–2100) impact on water resources, based on the dynamic downscaling A2 and B2 scenarios, indicates a significant reduction of approximately 40–50%. These hydrological changes affect the river ecosystem, water quality, and availability of water, so they introduce strong uncertainties regarding compliance with the WFD targets in the medium- and long-term. Future studies related to water quality or good status compliance of water bodies must take them into consideration. Related to the good status of SW bodies, one of the main pressures preventing compliance is urban point pollution, specifically organic matter and phosphorous pollution. The GeoImpress model was used to assess the measures needed in different scenarios to accomplish the WFD objectives. In the baseline scenario, 285 SW bodies achieved good status and 29 SW bodies did not. The B&Rm scenario, which corresponds to the implementation of basic measures for compliance with the Urban Waste Water Treatment Directive (investment cost 665.15 M€) and the reuse increase with the aim to augment the available resources (investment cost 563.05 M€), and reduced the number of SW bodies that did not achieve good status to 15. Finally, implementation of the additional measures (Am) scenario (investment cost 15.55 M€) allowed all but 2 water bodies to achieve good status. The developed cost-effectiveness indicator (CEI) allows for selection and prioritization of the additional measures to be implemented. The cost of additional measures is less than 2% of the others' cost, so implementing the WFD objectives represents a very low cost after the Urban Waste Water Treatment Directive implementation. Nitrate pollution is one of the major problems in meeting the WFD objectives for groundwater, and the quality standard recovery is a slow process that may prevent achieving the objectives by 2027. The water balance model has helped to identify the GW bodies that can achieve the objectives and those that will require less stringent objectives (LSO) for two scenarios with different degrees of reduction in the total amount of applied nitrogen. For a 10% reduction, associated only with a reduction in the use of fertilizers, 8 GW bodies will require LSO. For a 25% reduction, associated with the implementation of “fertigation” techniques (i.e., the application of fertilizers, soil amendments, or other water-soluble products through an irrigation system), only 3 GW bodies will require LSO.

J. Ferrer et al. / Science of the Total Environment 440 (2012) 42–59

Acknowledgments The authors thank the Spanish Ministry of Science and Innovation (Comisión Interministerial de Ciencia y Tecnología, CICYT) for financing the following projects: “INTEGRAME” (contract CGL2009-11798) and “SCARCE” (Consolider-Ingenio 2010 CSD2009-00065). We would also like to express our gratitude to the Júcar River Basin District — Confederación Hidrográfica del Júcar (Spanish Ministry of Agriculture, Food and Environment) for providing data to develop this study.

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