Refill and Drawdown Rules for Parallel Reservoirs: Quantity and Quality

The final publication is available at Springer via http://dx.doi.org/10.1007/s11269-006-0325-4This paper presents two operating rules for the refill and drawdown seasons of reservoirs in parallel for water supply, considering water quality. For the refill season a Linear Programming form of the New York City Rule is developed. Another Linear Programming form based on equalizing the probability of emptying each reservoir is developed for the drawdown season. Both formulations are extended to consider stratified water quality in the reservoirs and a water quality requirement for a downstream demand. The refill rule is applied to Shasta and Whiskeytown reservoirs in California (USA). The drawdown rule is applied to Alarcon and Contreras reservoirs in the Jucar Basin (Spain). The results of these applications show the effect of a water quality consideration in water supply operation.Paredes Arquiola, J.; Lund, JR. (2006). Refill and Drawdown Rules for Parallel Reservoirs: Quantity and Quality. Water Resources Management. 20(3):359-376. doi:10.1007/s11269-006-0325-4S359376203Arnold, U. and Orlob, G. T., 1989, ‘Decision support for estuarine water quality management’, J. Water Resour. Plng. Mgmt. ASCE, 115(6), 775–792.Bower, B. T., Hufschmidt, M. M., and Reedy, W. W., 1966, ‘Operating procedures: Their role in the design of water—resource systems by simulation analyses’, A. Maass et al. (eds.), Design of Water-Resource System, Harvard University Press, Cambridge, Mass., 443–458.Brooke, A., Kendrick, D. and Meeraus, A., 1992, GAMS: A Users Guide: Release 2.25, The Scientific Press Series, Boyd and Fraser Publishing Co. Danvers, MA 01923.Chapra, S. C., 1997, Surface Water-Quality Modeling. McGraw-Hill, New York.Clark, E. J., 1950, ‘New York control curves’ J. AWWA, 42(9), 823–827.Clark, E. J., 1956, ‘Impounding reservoirs’ J. AWWA, 48(4), 349–354. Engineering manual: Engineering and design, Hydropower. (1985). EM 1110–1701, U.S. Army Corps of Engineers, Washington, D.C.Costa, J. R. and Loucks, D. P., 1987, ‘Water quality management in the Ave River: From research to practice’, System Analysis in Water Quality Mgmt. Proc. IAWPRC Symp.de Azevedo, L. G. T., 1994, ‘Integration of water quantity and quality in multi-sector river basin planning’, PhD thesis, Dept. of Civ. Engrg., Colorado State University, Fort Collins, Colo.de Azevedo, L. G. T., Gates, T. K., Fontane, D. G., Labadie, J. W., and Porto, R. L., 2000, ‘Integration of water quantity and quality in strategic river basin planning’, J. Water Resour. Plng. Mgmt. ASCE, 126(2), 85–97Dai, T. and Labadie, J. W., 2001, ‘River basin network model for integrated water quantity/quality management’, J. Water Resour. Plng. Mgmt. ASCE 27(5). 295–305.Gu, R. R. and Li, Y., 2002, ‘River Temperature sensitivity to hydraulic and meteorological parameters’, Journal of Environmental Management 66, 43–56.Hayes, D., Labadie, J., Sanders, T., and Brown, J., 1998, ‘Enhancing water quality in hydropower system operations’, Water Resour. Res. 34(3), 471–483.Johnson, S. A., Stedinger, J. R., and Staschus, K., 1991, ‘Heuristic operating policies for reservoir system simulation’, Water Resour. Res., 27(6), 673–685.Labadie, J., 2004, ‘Optimal operation of multireservoir systems: State-of-the-art review’, Journal of Water Resources Planning and Management 130(2), 93–111.Loftis, B., Labadie, J. W., and Fontane, D. G., 1985, ‘Optimal operation of a system of lakes for quality and quantity’, H. C. Torno (ed.), Computer Applications in Water Resources, ASCE, New York, 693–702.Loucks, D. P., Stedinger, J. R., and Haith, D. A. 1981, Water Resource Systems Planning and Analysis, Englewood Cliffs, N. J. Prentice-Hall Inc. ISBN:013945923-5.Lund, J. R. and Guzman, J., 1996, ‘Developing seasonal and long-term reservoir system operation plans using HEC-PRM’, Tech. Rep. No. RD—40, Hydrologic Engineering Center, U.S. Army Corps of Engineers, Davis, Calif.Lund, J. R. and Guzman, J, 1999, ‘Derived operating rules for reservoirs in series or in parallel’, J. Water Resour. Plng. Mgmt. ASCE 143–153.Mehrez, C., Percia, C., and Oron, G., 1992, ‘Optimal operation of a multisource and multiquality regional water system’, Water Resour. Res. 28(5), 1199–1206.Orlob, G. and Simonovic, S., 1982, ‘Reservoir operation for water quality control’, Experience in Operation of Hydrosystems, Water Resources Publications, Highlands Ranch, Colo., 263–285Sand, G. M., 1984, ‘An analytical investigation of operating policies for water-supply reservoirs in parallel’, PhD dissertation, Cornell University, Ithaca, N.Y.Strzepek, K. M. and Chapra, S. C., 1990, ‘Do the right thing’, Civ. Engr. ASCE 60(1), 55–56.Tu, M-Y., Hsu, N-S., and Yeh, W-G., 2003, ‘Optimization of reservoir management and operation with Hedging rules’, J. Water Resour. Plng. Mgmt. ASCE 129(2), 86–97.Willey, R. G., Smith, D. J., and Duke, J. H. Jr., 1996, ‘Modeling water-resource systems for water-quality management’, J. Water Resour. Plng. Mgmt. ASCE 171–179.Wu, R. S., 1988, ‘Derivation of balancing curves for multiple reservoir operation’, MS thesis, Dept. of Civ. and Envir. Engrg., Cornell University, Ithaca, N.Y

Hydrological Alteration Index as an Indicator of the Calibration Complexity of Water Quantity and Quality Modeling in the Context of Global Change

Modeling is a useful way to understand human and climate change impacts on the water resources of agricultural watersheds. Calibration and validation methodologies are crucial in forecasting assessments. This study explores the best calibration methodology depending on the level of hydrological alteration due to human-derived stressors. The Soil and Water Assessment Tool (SWAT) model is used to evaluate hydrology in South-West Europe in a context of intensive agriculture and water scarcity. The Index of Hydrological Alteration (IHA) is calculated using discharge observation data. A comparison of two SWAT calibration methodologies are done; a conventional calibration (CC) based on recorded in-stream water quality and quantity and an additional calibration (AC) adding crop managements practices. Even if the water quality and quantity trends are similar between CC and AC, water balance, irrigation and crop yields are different. In the context of rainfall decrease, water yield decreases in both CC and AC, while crop productions present opposite trends (+33% in CC and -31% in AC). Hydrological performance between CC and AC is correlated to IHA: When the level of IHA is under 80%, AC methodology is necessary. The combination of both calibrations appears essential to better constrain the model and to forecast the impact of climate change or anthropogenic influences on water resources

Improved modelling of the freshwater provisioning ecosystem service in water scarce river basins

Freshwater provisioning by the landscape contributes to human well-being through water use for drinking, irrigation and other purposes. The assessment of this ecosystem service involves the quantification of water resources and the valuation of water use benefits. Models especially designed to assess ecosystem services can be used. However, they have limitations in representing the delivery of the service in water scarce river basins where water management and the temporal variability of water resource and its use are key aspects to consider. Integrating water resources management tools represents a good alternative to ecosystem services models in these river basins. We propose a modelling framework that links a rainfall-runoff model and a water allocation model which allow accounting for the specific requirements of water scarce river basins. Moreover, we develop a water tracer which rebounds the value of the service from beneficiaries to water sources, allowing the spatial mapping of the service

Improved modelling of the freshwater provisioning ecosystem service in water scarce river basins

[EN] Freshwater provisioning by the landscape contributes to human well-being through water use for drinking, irrigation and other purposes. The assessment of this ecosystem service involves the quantification of water resources and the valuation of water use benefits. Models especially designed to assess ecosystem services can be used. However, they have limitations in representing the delivery of the service in water scarce river basins where water management and the temporal variability of water resource and its use are key aspects to consider. Integrating water resources management tools represents a good alternative to ecosystem services models in these river basins. We propose a modelling framework that links a rainfall-runoff model and a water allocation model which allow accounting for the specific requirements of water scarce river basins. Moreover, we develop a water tracer which rebounds the value of the service from beneficiaries to water sources, allowing the spatial mapping of the service.The authors acknowledge the support of Universitat Politecnica de Valencia through its Support Programme for Research and Development. We also wish to thank Confederacion Hidrogr afica del Duero (belonging to the Spanish Ministry of Agriculture, Food and Environment) for the data provided in developing this study and the Spanish Ministry of Economy and Competitiveness for its financial support through the projects SCARCE (Consolider-Ingenio 2010 CSD2009-00065) and NUTEGES (CGL2012-34978). We also value the support provided by the European Community in financing the Seventh Framework Program projects DROUGHTR&SPI (FP7-ENV-2011, 282769), ENHANCE (FP7-ENV-2012, 308438), the H2020 project IMPREX (H2020-WATER-2014-2015, 641811), the grant WAMCD (EC-DG Environment No. 07.0329/2013/ 671291/SUB/ENV.C1) and the Life þ project LIFE ALBUFERA (LIFE12 ENV/ES/000685).Momblanch Benavent, A.; Andreu Álvarez, J.; Paredes Arquiola, J. (2017). Improved modelling of the freshwater provisioning ecosystem service in water scarce river basins. Environmental Modelling & Software. 94:87-99. https://doi.org/10.1016/j.envsoft.2017.03.033S87999

Probabilistic Forecasting of Drought Events Using Markov Chain- and Bayesian Network-Based Models A Case Study of an Andean Regulated River Basin

[EN] The scarcity of water resources in mountain areas can distort normal water application patterns with among other effects, a negative impact on water supply and river ecosystems. Knowing the probability of droughts might help to optimize a priori the planning and management of the water resources in general and of the Andean watersheds in particular. This study compares Markov chain- (MC) and Bayesian network- (BN) based models in drought forecasting using a recently developed drought index with respect to their capability to characterize different drought severity states. The copula functions were used to solve the BNs and the ranked probability skill score (RPSS) to evaluate the performance of the models. Monthly rainfall and streamflow data of the Chulco River basin, located in Southern Ecuador, were used to assess the performance of both approaches. Global evaluation results revealed that the MC-based models predict better wet and dry periods, and BN-based models generate slightly more accurately forecasts of the most severe droughts. However, evaluation of monthly results reveals that, for each month of the hydrological year, either the MC- or BN-based model provides better forecasts. The presented approach could be of assistance to water managers to ensure that timely decision-making on drought response is undertakenAvilés-Añazco, A.; Celleri, R.; Solera Solera, A.; Paredes Arquiola, J. (2016). Probabilistic Forecasting of Drought Events Using Markov Chain- and Bayesian Network-Based Models A Case Study of an Andean Regulated River Basin. Water. 8(2). doi:10.3390/w8020037S8

Comparing performance indicators to characterize the water supply to the demands of the Guadiana River basin (Spain)

Añadir el siguiente texto en el campo descripción: "This is an Accepted Manuscript of an article published in Hydrological Sciences Journal on 31-Mar-2020, available online: http://www.tandfonline.com/10.1080/02626667.2020.1734812."[EN] Water indicators and indices are useful tools to assess river basin performance, that is, to measure whether the basin operates satisfactorily under a wide range of possible future demands and hydrological conditions. Spanish regulations assess the performance of water demands by using reliability indicators (RIs), established by law in 2008. This article raises the possibility of updating RIs by comparing them with sustainability indicators (SIs). SIs are widely used for the assessment of river basin performance and several policy scenarios. We applied a water allocation model to the Guadiana River basin in Spain to compare indicators under three scenarios. The study was framed within the science of socio-hydrology, combining the physical environment of a water system with its influence on social aspects. SIs gave better results than RIs when comparing future scenarios. We also propose the introduction of a vulnerability indicator into Spanish regulations.The authors thank the Spanish Research Agency (MINECO) for the financial support to the ERAS project [CTM2016-77804-P], including EU-FEDER funds. Additionally, we value the support provided by the European Community in financing the project IMPREX [H2020-WATER-2014-2015, 641811].Palop-Donat, C.; Paredes Arquiola, J.; Solera Solera, A.; Andreu Álvarez, J. (2020). Comparing performance indicators to characterize the water supply to the demands of the Guadiana River basin (Spain). Hydrological Sciences Journal. 1-15. https://doi.org/10.1080/02626667.2020.1734812S115Aguilera, H., Castaño, S., Moreno, L., Jiménez-Hernández, M. E., & de la Losa, A. (2013). Model of hydrological behaviour of the anthropized semiarid wetland of Las Tablas de Daimiel National Park (Spain) based on surface water–groundwater interactions. Hydrogeology Journal, 21(3), 623-641. doi:10.1007/s10040-012-0950-3Alarcón, J., Garrido, A., & Juana, L. (2016). Modernization of irrigation systems in Spain: review and analysis for decision making. International Journal of Water Resources Development, 32(3), 442-458. doi:10.1080/07900627.2015.1123142Andreu, J., Capilla, J., & Sanchís, E. (1996). AQUATOOL, a generalized decision-support system for water-resources planning and operational management. Journal of Hydrology, 177(3-4), 269-291. doi:10.1016/0022-1694(95)02963-xAshofteh, P.-S., Rajaee, T., & Golfam, P. (2017). Assessment of Water Resources Development Projects under Conditions of Climate Change Using Efficiency Indexes (EIs). Water Resources Management, 31(12), 3723-3744. doi:10.1007/s11269-017-1701-yBOE (Boletín Oficial del Estado), 2008. ORDEN ARM/2656/2008, de 10 de septiembre, por la que se aprueba la instrucción de planificación hidrológica. BOE. 229 de 22 de septiembre 2008, 38472–38582. https://www.boe.es/buscar/doc.php?id=BOE-A-2008-15340.BOE (Boletín Oficial del Estado), 2010. Protocolo de Revision del Convenio Sobre Cooperación Para La Protección y el Aprovechamiento Sostenible de Las Aguas de las Cuencas Hidrográficas Hispano-Portuguesas y el Protocolo adicional. Albufeira, Portugal, 30 de Noviembre de 1998. BOE. 14, de 16 de enero de 2010, 3425–3432CEDEX (Centro de Estudios y Experimentación de Obras Públicas), 2011. Evaluación del Impacto del Cambio Climático en los recursos hídricos en régimen natural. Encomienda de gestión de la Dirección General del Agua (MARM) para el estudio del cambio climático en los recursos hídricos y las masas de agua. Madrid, Spain: Centro de Publicaciones, Secretaría General Técnica del Ministerio de Fomento.Collet, L., Ruelland, D., Estupina, V. B., Dezetter, A., & Servat, E. (2015). Water supply sustainability and adaptation strategies under anthropogenic and climatic changes of a meso-scale Mediterranean catchment. Science of The Total Environment, 536, 589-602. doi:10.1016/j.scitotenv.2015.07.093Official Journal of the European Communities. (1984). Analytical Proceedings, 21(6), 196. doi:10.1039/ap9842100196Estrada Lorenzo, F., 1993. La garantía en los sistemas de explotación de recursos hidráulicos. Thesis (PhD). Universidad Politécnica de Madrid.García-Santos, G., de Brito, M. M., Höllermann, B., Taft, L., Almoradie, A., & Evers, M. (2018). Methodology to explore emergent behaviours of the interactions between water resources and ecosystem under a pluralistic approach. Proceedings of the International Association of Hydrological Sciences, 379, 83-87. doi:10.5194/piahs-379-83-2018Gheisi, A., Forsyth, M., & Naser, G. (2016). Water Distribution Systems Reliability: A Review of Research Literature. Journal of Water Resources Planning and Management, 142(11), 04016047. doi:10.1061/(asce)wr.1943-5452.0000690Gohari, A., Mirchi, A., & Madani, K. (2017). System Dynamics Evaluation of Climate Change Adaptation Strategies for Water Resources Management in Central Iran. Water Resources Management, 31(5), 1413-1434. doi:10.1007/s11269-017-1575-zGoharian, E., Burian, S. J., & Karamouz, M. (2018). Using Joint Probability Distribution of Reliability and Vulnerability to Develop a Water System Performance Index. Journal of Water Resources Planning and Management, 144(2), 04017081. doi:10.1061/(asce)wr.1943-5452.0000869Hashimoto, T., Stedinger, J. R., & Loucks, D. P. (1982). Reliability, resiliency, and vulnerability criteria for water resource system performance evaluation. Water Resources Research, 18(1), 14-20. doi:10.1029/wr018i001p00014Hernández-Bedolla, J., Solera, A., Paredes-Arquiola, J., Pedro-Monzonís, M., Andreu, J., & Sánchez-Quispe, S. (2017). The Assessment of Sustainability Indexes and Climate Change Impacts on Integrated Water Resource Management. Water, 9(3), 213. doi:10.3390/w9030213(2018). Water and Environment Journal, 32(1). doi:10.1111/wej.2018.32.issue-1Lall, U., & Miller, C. W. (1988). An optimization model for screening multipurpose reservoir systems. Water Resources Research, 24(7), 953-968. doi:10.1029/wr024i007p00953LOUCKS, D. P. (1997). Quantifying trends in system sustainability. Hydrological Sciences Journal, 42(4), 513-530. doi:10.1080/02626669709492051Loucks, D. P., & van Beek, E. (2017). Water Resource Systems Planning and Management. doi:10.1007/978-3-319-44234-1Milano, M., Reynard, E., Köplin, N., & Weingartner, R. (2015). Climatic and anthropogenic changes in Western Switzerland: Impacts on water stress. Science of The Total Environment, 536, 12-24. doi:10.1016/j.scitotenv.2015.07.049Ortega-Gómez, T., Pérez-Martín, M. A., & Estrela, T. (2018). Improvement of the drought indicators system in the Júcar River Basin, Spain. Science of The Total Environment, 610-611, 276-290. doi:10.1016/j.scitotenv.2017.07.250Pedro Monzonís, M., 2014. Análisis de metodologías de balances hídricos en sistemas complejos en el contexto europeo de la Planificación hidrológica. Aplicación a la cuenca del Júcar. Thesis (MS). Universitat Politècnica de València.Pedro-Monzonís, M., 2016. Assessment of water exploitation indexes based on water accounting. Thesis (PhD). Universitat Politècnica de València.Pedro-Monzonís, M., Solera, A., Ferrer, J., Estrela, T., & Paredes-Arquiola, J. (2015). A review of water scarcity and drought indexes in water resources planning and management. Journal of Hydrology, 527, 482-493. doi:10.1016/j.jhydrol.2015.05.003Ruiz Pulpón, Á. R. (2006). Regadíos y gestión sostenible de los recursos hídricos en la cuenca del Guadiana: propuesta territorial previa a la toma de decisiones. Investigaciones Geográficas, (40), 183. doi:10.14198/ingeo2006.40.09Sandoval-Solis, S., McKinney, D. C., & Loucks, D. P. (2011). Sustainability Index for Water Resources Planning and Management. Journal of Water Resources Planning and Management, 137(5), 381-390. doi:10.1061/(asce)wr.1943-5452.0000134Sarang, A., Vahedi, A., & Shamsai, A. (2007). How to Quantify Sustainable Development: A Risk-Based Approach to Water Quality Management. Environmental Management, 41(2), 200-220. doi:10.1007/s00267-007-9047-5Shilling, F. and Shilling, F., 2014. California Water Sustainability Indicators Framework : Assessment at State and Region Scales Final Report California Water Sustainability Indicators Framework : Assessment at State and Region Scale. California, USA: California Department of Water Resources.Sivapalan, M. (2018). From engineering hydrology to Earth system science: milestones in the transformation of hydrologic science. Hydrology and Earth System Sciences, 22(3), 1665-1693. doi:10.5194/hess-22-1665-2018Sivapalan, M., Konar, M., Srinivasan, V., Chhatre, A., Wutich, A., Scott, C. A., … Rodríguez‐Iturbe, I. (2014). Socio‐hydrology: Use‐inspired water sustainability science for the Anthropocene. Earth’s Future, 2(4), 225-230. doi:10.1002/2013ef000164Sivapalan, M., Savenije, H. H. G., & Blöschl, G. (2012). Socio-hydrology: A new science of people and water. Hydrological Processes, 26(8), 1270-1276. doi:10.1002/hyp.8426Srdjevic, Z., & Srdjevic, B. (2017). An Extension of the Sustainability Index Definition in Water Resources Planning and Management. Water Resources Management, 31(5), 1695-1712. doi:10.1007/s11269-017-1609-6Troy, T. J., Pavao-Zuckerman, M., & Evans, T. P. (2015). Debates-Perspectives on socio-hydrology: Socio-hydrologic modeling: Tradeoffs, hypothesis testing, and validation. Water Resources Research, 51(6), 4806-4814. doi:10.1002/2015wr017046Xu, L., Gober, P., Wheater, H. S., & Kajikawa, Y. (2018). Reframing socio-hydrological research to include a social science perspective. Journal of Hydrology, 563, 76-83. doi:10.1016/j.jhydrol.2018.05.061Yustres, Á., Navarro, V., Asensio, L., Candel, M., & García, B. (2013). Groundwater resources in the Upper Guadiana Basin (Spain): a regional modelling analysis. Hydrogeology Journal, 21(5), 1129-1146. doi:10.1007/s10040-013-0987-

Water Quantity and Quality Models Applied to the Jucar River Basin, Spain

“The final publication is available at Springer via http://dx.doi.org/ 10.1007/s11269-010-9578-z ”.Traditionally, water quality modelling has focused on modelling individual water bodies. However, water quality management problems must be analyzed at the basin scale. European Water Framework Directive (WFD) requires introducing physical, chemical and biological aspects into the management of water resources systems. Water quality modelling at a basin scale presents the advantage of incorporating in a dynamic way the relationships between the different elements and water bodies. Currently, there are few tools to deal with water modelling of water quality and management at the basin scale. This paper presents the development of a water quantity model and a water quality model for a very complex water resources system: the JA(0)car River Basin (Spain). The basin is characterized by a high degree of use of the water and by many water problems related to point and diffuse pollution, on top of a complex water quantity management of the basin. To deal with this problem, SIMGES (water allocation) and GESCAL (water quality) basin scale models have been used. Both are part of the Decision Support System AQUATOOL, one of the main instruments used in Spain in order to analyze water quantity and quality aspects of water resources systems for the compliance with WFD, as shown for the case of study.This study was supported by funds from Jucar River Basin Agency (Spanish Ministry of Environment), from the Spanish Ministry of Education and Culture (project "Desarrollo de elementos de un sistema soporte de decision para la gestion de recursos hidricos", HID1999-0656), and from the European Union (project "SEDEMED-Secheresse et Desertification dans les bassins mediterranees", ref. 2002-024.4-1084).Paredes Arquiola, J.; Andreu Álvarez, J.; Martín Monerris, M.; Solera Solera, A. (2010). Water Quantity and Quality Models Applied to the Jucar River Basin, Spain. Water Resources Management. 24(11):2759-2779. doi:10.1007/s11269-010-9578-zS275927792411Andreu J, Capilla J (1993) Optimization and simulation models applied to the Segura water resources system. In: Marco J, Harboe R, Salas JD (eds) Stochastic hydrology in water resources systems: simulation and optimization. Kluwer, DordrechtAndreu J, Capilla J, Ferrer J (1992) Modelo Simges de simulación de la gestión de esquemas de recursos hídricos, incluyendo utilización conjunta. Serv. Publ. UPV, ValenciaAndreu J, Capilla J, Sanchis E (1996) AQUATOOL: a generalized decision support-system for water-resources planning and operational management. J Hydrol 177:269–291Andreu J, Solera A, Paredes J, Pérez MA, Pulido M (2008) Decision support tools for policy making in European Water Research Day (Zaragoza). European CommunitiesArnold U, Orlob GT (1989) Decision support for estuarine water quality management. J Water Resour Plan Manage, ASCE 115(6):775–792Bhakdisongkhram T, Koottated S, Towprayoon S (2007) A water model for water and environmental management at Mae Moh area in Thailand. Water Resour Manag 21:1535–1552CHJ (1998) Plan Hidrológico de la Cuenca del Júcar. Confederación Hidrográfica del Júcar. Ministerio de Medio Ambiente, Spainde Azevedo LGT, Gates TK, Fontane DG, Labadie JW, Porto RL (2000) Integration of water quantity and quality in strategic river basin planning. J Water Resour Plan Manage ASCE 126(2):85–97EC (2000) Directive 2000/60/EC of the European Parliament and of the Council, of 23 October 2000, establishing a framework for Community action in the field of water policy. Official Journal of the European Commission, L 327/1, 22.12.2000Edinger JE, Geyer JC (1965) Heat exchange in the environment. Department of Sanitary engineering and Water resources, Research Project No. 49. John Hopkins University, BaltimoreFord CR, Fulkerson DR (1962) Flow in networks. Princeton University Press, Princeton, p 194Huang GH, Xia J (2001) Barriers to sustainable water-quality management. J Environ Manag 61(1):1–23Koch H, Grünewald U (2009) A comparison of modelling systems for the development and revision of water resources management plans. Water Resour Manag 23:1403–1422Kotti ME, Vlessidis AG, Thanasoulias NC, Evmiridis NP (2005) Assessment of river water quality in Northwestern Greece. Water Resour Manag 19(1):77–94Letcher R, Croke B, Jakeman A (2007) Integrated assessment modelling for water resources allocation and management: a generalised conceptual framework. Environ Model Softw 22(5):733–742. doi: 10.1016/j.envsoft.2005.12.014Loucks DP, van Beek E (2005) Water resources systems planning and management—an introduction to methods, models and applications. UNESCO, ParisParedes J, Lund J (2006) Refill and drawdown rules for parallel reservoirs: quantity and quality. 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Contribution of decision support systems to water management improvement in basins with high evaporation in Mediterranean climates

[EN] The entry into force of Directive 2000/60/EC of the European Parliament and the Council of 23 October 2000 established a new model for the management and protection of surface water and groundwater in Europe. In this sense, a thorough knowledge of the basins is an essential step in achieving this European objective. The utility of integrative decision support systems (DSS) for decision-making in complex systems and multiple objectives allows decision-makers to identify characteristics and improve water management in a basin. In this research, hydrological and water management resource models have been combined, with the assistance of the DSS AQUATOOL, with the aim of deepening the consideration of losses by evaporation of reservoirs for a better design of the basin management rules. The case study treated is an Andalusian basin of the Atlantic zone (Spain). At the same time, different management strategies are analysed based on the optimization of the available resources by means of the conjunctive use of surface water and groundwater.The study was performed with the support of the Ecological Transition Ministry, through the Biodiversity Foundation.Ruíz-Ortíz, V.; García-López, S.; Solera Solera, A.; Paredes Arquiola, J. (2019). Contribution of decision support systems to water management improvement in basins with high evaporation in Mediterranean climates. Hydrology Research. 50(4):1020-1036. https://doi.org/10.2166/nh.2019.014S10201036504Alcamo J. , HenrichT. & RoschT.2000World Water in 2025 – Global Modelling and Scenario Analysis for the World Commission on Water for the 21st Century. Report A0002, Centre for Environmental System Research, University of Kassel, Germany.ALCAMO, J., FLÖRKE, M., & MÄRKER, M. (2007). Future long-term changes in global water resources driven by socio-economic and climatic changes. Hydrological Sciences Journal, 52(2), 247-275. doi:10.1623/hysj.52.2.247Allen R. G. , PereiraL. S., RaesD. & SmithM.2006Crop Evapotranspiration. Guidelines for Computing Crop Water Requirements (FAO Irrigation and Drainage Paper 56). Food and Agricultural Organization of the United Nations, Rome, Italy. http://www.fao.org/docrep/009/x0490s/x0490s00.htm (accessed 10 September 2018).Andreu, J., Capilla, J., & Sanchís, E. (1996). AQUATOOL, a generalized decision-support system for water-resources planning and operational management. Journal of Hydrology, 177(3-4), 269-291. doi:10.1016/0022-1694(95)02963-xAndreu J. , SoleraA., CapillaJ. & FerrerJ.2007Modelo SIMGES de simulación de la gestión de recursos hídricos, incluyendo utilización conjunta. Versión 3.03.01. Manual de usuario (Model SIMGES simulation of water resources management, including conjunctive use. 3.03.01 version. User Manual). Polytechnic University of Valencia, Valencia, Spain.Condon, L. E., & Maxwell, R. M. (2013). Implementation of a linear optimization water allocation algorithm into a fully integrated physical hydrology model. Advances in Water Resources, 60, 135-147. doi:10.1016/j.advwatres.2013.07.012EC (European Commission) 2012 A Blueprint to Safeguard Europe's Water Resources. European Commission, 14.11.2012 COM (2012) 673 final, Brussels, Belgium.González-Zeas D. 2012 Impacto del cambio climático sobre los usos del agua en Europa (Impact of Climate Change on Water Uses in Europe). PhD thesis, University of Madrid, Madrid, Spain.Junta de Andalucía. Consejería de Medio Ambiente y Ordenación del Territorio. 2016Plan Hidrológico del Guadalete Barbate (2015–2021) (Hydrological Plan of the Guadalete Barbate 2015–2021). http://www.juntadeandalucia.es (accessed 25 May 2018).Li, P., Qian, H., & Wu, J. (2018). Conjunctive use of groundwater and surface water to reduce soil salinization in the Yinchuan Plain, North-West China. International Journal of Water Resources Development, 34(3), 337-353. doi:10.1080/07900627.2018.1443059Paredes, J., Andreu, J., & Solera, A. (2010). A decision support system for water quality issues in the Manzanares River (Madrid, Spain). Science of The Total Environment, 408(12), 2576-2589. doi:10.1016/j.scitotenv.2010.02.037Pedro-Monzonís, M., Jiménez-Fernández, P., Solera, A., & Jiménez-Gavilán, P. (2016). The use of AQUATOOL DSS applied to the System of Environmental-Economic Accounting for Water (SEEAW). Journal of Hydrology, 533, 1-14. doi:10.1016/j.jhydrol.2015.11.034Tabari, M. M. R., & Soltani, J. (2012). Multi-Objective Optimal Model for Conjunctive Use Management Using SGAs and NSGA-II Models. Water Resources Management, 27(1), 37-53. doi:10.1007/s11269-012-0153-7Singh, A. (2013). Irrigation Planning and Management Through Optimization Modelling. Water Resources Management, 28(1), 1-14. doi:10.1007/s11269-013-0469-ySingh, A. (2014). Conjunctive use of water resources for sustainable irrigated agriculture. Journal of Hydrology, 519, 1688-1697. doi:10.1016/j.jhydrol.2014.09.049Singh, A. (2014). Simulation–optimization modeling for conjunctive water use management. Agricultural Water Management, 141, 23-29. doi:10.1016/j.agwat.2014.04.003Sophocleous, M. (2002). Interactions between groundwater and surface water: the state of the science. Hydrogeology Journal, 10(1), 52-67. doi:10.1007/s10040-001-0170-8Strosser P. , RoussardJ. & GrandmouginB.2007EU Water Saving Potential. ENV.D.2/ETU/2007/0001r. Final Report. 247. http://ec.europa.eu (accessed 2 July 2018).Hassan, S. M. T., Lubczynski, M. W., Niswonger, R. G., & Su, Z. (2014). Surface–groundwater interactions in hard rocks in Sardon Catchment of western Spain: An integrated modeling approach. Journal of Hydrology, 517, 390-410. doi:10.1016/j.jhydrol.2014.05.02

Efecto del cambio climático en la calidad del agua de la Cuenca del Júcar

This study analyses the effect of climate change on water quality in the Júcar River Basin from future estimations of hydrological inputs and water temperature (WT). For this purpose, a large-scale water quality model was used to estimate the ecological status of all the water bodies, based on the concentrations of BDO5, P, NH4+ and NO3– for the future horizons 2020, 2050 and 2080. In this study, a greater number of water bodies with higher pollution levels (80-100% failures) were obtained in the horizons 2050 and 2080, which are located in the middle and lower parts of the basin. In addition, the degradation of BDO5 and the NH4+ is highly dependent on WT, highlighting the importance of considering this variable in the model.En este estudio se analiza el efecto del cambio climático en la calidad del agua de la cuenca del Júcar a partir de estimaciones futuras de aportaciones hidrológicas y temperatura del agua (Ta). Para ello, se utilizó un modelo de calidad de aguas a escala de cuenca con el que se estimó el estado ecológico de todas las masas de agua, basándose en las concentraciones de DBO5, P, NH4+ y NO3- para los horizontes futuros 2020, 2050 y 2080. De este análisis se obtuvo un incremento del número de masas con altos niveles de contaminación (80-100% incumplimientos) en los horizontes 2050 y 2080, localizadas sobre todo en la parte media y baja de la cuenca. Además, la degradación de la DBO5 y el NH4+ es muy dependiente de la temperatura del agua, poniendo de manifiesto la importancia de considerar esta variable en el modelo

Optimization of the Scarcity State Indicator in the Jucar river basin

[ES] Los indicadores de estado de escasez ayudan a evitar pérdidas económicas, sociales y ambientales que causan las sequías en las cuencas mediterráneas como la cuenca del río Júcar. El presente trabajo pretende optimizar la obtención del Indicador de Estado de Escasez (IEE) para reproducir las situaciones de escasez acontecidas en un sistema de recursos hídricos (RRHH). La metodología consiste en utilizar un modelo de gestión RRHH, Aquatool-Simges, para definir los períodos de escasez y su magnitud. A continuación, se calculan las variables del IEE y se aplica un algoritmo evolutivo para optimizar su ponderación. Los resultados muestran un incremento del 13.7% y del 78.8% del peso de las variables VE07 y EA03 respectivamente. Además, se obtiene un 62% de acierto del método para predecir estados de normalidad en la cuenca. Se puede concluir que esta propuesta de optimización del IEE presenta buenos resultados, aunque muestran una anticipación a los escenarios de escasez y falsos positivos que se solventarán en futuros estudios.[EN] Scarcity status indicators help to avoid economic, social and environmental losses caused by droughts in Mediterranean basins such as the Jucar River basin. The aim of this work is to optimize the Scarcity State Indicator (SSI) in order to reproduce the scarcity periods occurring in a water resource system (WRS). The methodology used consists of using an WRS model, Aquatool-Simges, to define the scarcity periods and their magnitude. Then we computed the SSI variables and applied an evolutionary algorithm to optimize their weighting. The results show an increase of 13.7% and 78.8% in the weight of variables VE07 and EA03 respectively. In addition, a 62% success rate is obtained from the method for predicting states of normality in the basin. It can be concluded that this proposal for optimization of the EEI presents good results, although they show an anticipation of the scenarios of scarcity and false positives that will be solved in future studies.Los autores agradecen a la Agencia Española de Investigación (MINECO) el apoyo económico al proyecto ERAS (CTM2016-77804-P, incluyendo fondos EU-FEDER). Además, también valoramos el apoyo de la Comunidad Europea que ha financiado el proyecto IMPREX (H2020-WATER-2014–2015, 641811).Palop-Donat, C.; Paredes-Arquiola, J.; Andreu, J. (2020). Optimización del indicador de escasez en la cuenca del río Júcar. Ingeniería del agua. 24(2):129-140. https://doi.org/10.4995/ia.2020.12275OJS129140242Alcamo, J., Acosta-Michlik, L., Carius, A., Eierdanz, F., Klein, R., Krömker, D., Tänzler, D. 2008. A new approach to quantifying and comparing vulnerability to drought. Regional Environmental Change, 8(4), 137-149. https://doi.org/10.1007/s10113-008-0065-5Alcamo, J., Döll, P., Henrichs, T., Kaspar, F., Lehner, B., Rösch, T., Siebert, S. 2003. Global estimates of water withdrawals and availability under current and future "business-as-usual" conditions. Hydrological Sciences Journal, 48(3), 339-348. https://doi.org/10.1623/hysj.48.3.339.45278Andreu, J., Capilla, J., Sanchís, E. 1996. AQUATOOL, a generalized decision-support system for water-resources planning and operational management. Journal of Hydrology, 177(3-4), 269-291. https://doi.org/10.1016/0022-1694(95)02963-XBoletín Oficial del Estado (BOE). Instrucción de Planificación Hidrológica., 2008.CEDEX. 2017. Evaluación del impacto del Cambio Climático en los recursos hídricos y sequías en España. Recuperado de http://publicacionesoficiales.boe.es/CHJ. 2015. Plan Hidrológico del Júcar 2015-2021. Recuperado de https://www.chj.es/Descargas/ProyectosOPH/Consulta publica/PHC-2015-2021/PHJ1521_Memoria_151126.pdfCHJ. 2018. Plan Especial de Sequía Demarcación Hidrográfica del Júcar.EC, European Commission. 2012. Communication from the commission to the European parliament, the council, the European economic and social committee and the committee of the regions a Blueprint to Safeguard Europe's Water Resources. Recuperado de https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:52012DC0673EC, European Commission. 2007. Addressing the challenge of water scarcity and droughts in the European Union. Official Journal of the European Union, (COM/2007), 1-14. https://doi.org/10.1017/CBO9781107415324.004Estrela, T., Sancho, T. A. 2016. Drought management policies in Spain and the european union: From traditional emergency actions to drought management plans. Water Policy, 18, 153-176. https://doi.org/10.2166/wp.2016.018Estrela, T., Vargas, E. 2012. Drought Management Plans in the European Union. The Case of Spain. Water Resources Management, 26(6), 1537-1553. https://doi.org/10.1007/s11269-011-9971-2EU. 2000. Directive 2000/60/EC of the European Parliament and of the Council establishing a framework for the Community action in the field of water policy. Recuperado de http://ec.europa.eu/environment/water/water-framework/index_en.htmlFalkenmark, M. 1989. The Massive Water Scarcity Now Threatening Africa: Why Isn't It Being Addressed? Ambio, 18, 112-118. https://www.jstor.org/stable/4313541Guttman, N. B. 1998. Comparing the palmer drought index and the standardized precipitation index. Journal of the American Water Resources Association, 34(1), 113-121. https://doi.org/10.1111/j.1752-1688.1998.tb05964.xIPCC. 2007. AR4 Climate Change 2007: Impacts, Adaptation, and Vulnerability - IPCC. Recuperado el 2 de Mayo, 2019, de https://www.ipcc.ch/report/ar4/wg2/IPCC. 2014. AR5 Climate Change 2014: Impacts, Adaptation, and Vulnerability - IPCC. Recuperado el 2 de Mayo, 2019 dehttps://www.ipcc.ch/report/ar5/wg2/Kampragou, E., Apostolaki, S., Manoli, E., Froebrich, J., Assimacopoulos, D. 2011. Towards the harmonization of water-related policies for managing drought risks across the EU. Environmental Science and Policy, 14(7), 815-824. https://doi.org/10.1016/j.envsci.2011.04.001Lerma, N., Paredes-Arquiola, J., Andreu, J., Solera, A. 2013. Development of operating rules for a complex multireservoir system by coupling genetic algorithms and network optimization. Hydrological Sciences Journal, 58(4), 797-812. https://doi.org/10.1080/02626667.2013.779777Liu, J., Yang, H., Gosling, S. N., Kummu, M., Flörke, M., Hanasaki, N., Zheng, C. 2017. Water scarcity assessments in the past, present, and future. Earth's Future, 5(6), 545-559. https://doi.org/10.1002/2016EF000518MAAM. 2014. Plan Nacional De Adaptación al Cambio Climático. Madrid, España.Mckee, T. B., Doesken, N. J., Kleist, J. 1993. The relationship of drought frequency and duration to time scales. In Eighth Conference on Applied Climatology. Recuperado de https://climate.colostate.edu/pdfs/relationshipofdroughtfrequency.pdfOrtega-Gómez, T., Pérez-Martín, M. A., Estrela, T. 2018. Improvement of the drought indicators system in the Júcar River Basin, Spain. Science of the Total Environment, 610-611, 276-290. https://doi.org/10.1016/j.scitotenv.2017.07.250Pedro-Monzonís, M., Solera, A., Ferrer, J., Estrela, T., Paredes-Arquiola, J. 2015. A review of water scarcity and drought indexes in water resources planning and management. Journal of Hydrology, 527, 482-493. https://doi.org/10.1016/j.jhydrol.2015.05.003Pérez-Blanco, C. D., Gómez, C. M. 2014. Drought management plans and water availability in agriculture: A risk assessment model for a Southern European basin. Weather and Climate Extremes, 4, 11-18. https://doi.org/10.1016/j.wace.2014.02.003Quiring, S. M., Papakryiakou, T. N. 2003. An evaluation of agricultural drought indices for the Canadian prairies. Agricultural and Forest Meteorology, 118, 49-62. https://doi.org/10.1016/S0168-1923(03)00072-8Rijsberman, F. R. 2006. Water scarcity: Fact or fiction? Agricultural Water Management, 80(1-3 SPEC. ISS.), 5-22.https://doi.org/10.1016/j.agwat.2005.07.001Sánchez-Quispe, S. 2000. Gestión de Recursos Hídricos con decisiones basadas en Estimación del Riesgo. Universitat Politécnica de Valéncia.Zaniolo, M., Giuliani, M., Castelletti, A. F., Pulido-Velazquez, M. 2018. Automatic design of basin-specific drought indexes for highly regulated water systems. Hydrology and Earth System Sciences, 22(4), 2409-2424. https://doi.org/10.5194/hess-22-2409-201