Abstract. Climate and land use change (global change) impacts on groundwater systems cannot be studied in isolation. Land use and land cover (LULC) changes have a great impact on the water cycle and contaminant production and transport. Groundwater flow and storage are changing in response not only to climatic changes but also to human impacts on land uses and demands, which will alter the hydrologic cycle and subsequently impact the quantity and quality of regional water systems. Predicting groundwater recharge and discharge conditions under future climate and land use changes is essential for integrated water management and adaptation. In the Mancha Oriental system (MOS), one of the largest groundwater bodies in Spain, the transformation from dry to irrigated lands during the last decades has led to a significant drop of the groundwater table, with the consequent effect on stream-aquifer interaction in the connected Jucar River. Understanding the spatial and temporal distribution of water quantity and water quality is essential for a proper management of the system. On the one hand, streamflow depletion is compromising the dependent ecosystems and the supply to the downstream demands, provoking a complex management issue. On the other hand, the intense use of fertilizer in agriculture is leading to locally high groundwater nitrate concentrations. In this paper we analyze the potential impacts of climate and land use change in the system by using an integrated modeling framework that consists in sequentially coupling a watershed agriculturally based hydrological model (Soil and Water Assessment Tool, SWAT) with a groundwater flow model developed in MODFLOW, and with a nitrate mass-transport model in MT3DMS. SWAT model outputs (mainly groundwater recharge and pumping, considering new irrigation needs under changing evapotranspiration (ET) and precipitation) are used as MODFLOW inputs to simulate changes in groundwater flow and storage and impacts on stream-aquifer interaction. SWAT and MODFLOW outputs (nitrate loads from SWAT, groundwater velocity field from MODFLOW) are used as MT3DMS inputs for assessing the fate and transport of nitrate leached from the topsoil. Three climate change scenarios have been considered, corresponding to three different general circulation models (GCMs) for emission scenario A1B that covers the control period, and short-, medium-and long-term future periods. A multi-temporal analysis of LULC change was carried out, helped by the study of historical trends (from remote-sensing images) and key driving forces to explain LULC transitions. Markov chains and European scenarios and projections were used to quantify trends in the future. The cellular automata technique was applied for stochastic modeling future LULC maps. Simulated values of river discharge, crop yields, groundwater levels and nitrate concentrations fit well to the observed ones. The results show the response of groundwater quantity and quality (nitrate polPublished by Copernicus Publications on behalf of the European Geosc...

Corresponding author: mapuve@hma.upv.es (Pulido-Velazquez, M.)*, anloni@upv.es 6 (Lopez-Nicolas,A.), hecmasor@upv.es (Macian-Sorribes, H.) 7 8 ABSTRACT 9In this paper we present an innovative framework for an economic risk analysis of 10 drought impacts on irrigated agriculture. It consists on the integration of three 11 components: stochastic time series modelling for prediction of inflows and future 12 reservoir storages at the beginning of the irrigation season; statistical regression for the 13 evaluation of water deliveries based on projected inflows and storages; and econometric 14 modelling for economic assessment of the production value of agriculture based on 15 irrigation water deliveries and crop prices. Therefore, the effect of the price volatility 16 can be isolated from the losses due to water scarcity in the assessment of the drought 17 impacts. Monte Carlo simulations are applied to generate probability functions of 18 inflows, which are translated into probabilities of storages, deliveries, and finally, 19 production value of agriculture. The framework also allows the assessment of the value 20 of mitigation measures as reduction of economic losses during droughts. 21 The approach was applied to the Jucar river basin, a complex system affected by 22 multiannual severe droughts, with irrigated agriculture as the main consumptive 23 demand. Probability distributions of deliveries and production value were obtained for 24 each irrigation season. In the majority of the irrigation districts, drought causes a 25 significant economic impact. The increase of crop prices can partially offset the losses 26 Confidential manuscript submitted to J. Hydrology 2 from the reduction of production due to water scarcity in some districts. Emergency 27 wells contribute to mitigating the droughts' impacts on the Jucar river system. 28

The management of large‐scale water resource systems with surface and groundwater resources requires considering stream‐aquifer interactions. Optimization models applied to large‐scale systems have either employed deterministic optimization (with perfect foreknowledge of future inflows, which hinders their applicability to real‐life operations) or stochastic programming (in which stream‐aquifer interaction is often neglected due to the computational burden associated with these methods). In this paper, stream‐aquifer interaction is integrated in a stochastic programming framework by combining the Stochastic Dual Dynamic Programming (SDDP) optimization algorithm with the Embedded Multireservoir Model (EMM). The resulting extension of the SDDP algorithm, named Combined Surface‐Groundwater SDDP (CSG‐SDDP), is able to properly represent the stream‐aquifer interaction within stochastic optimization models of large‐scale surface‐groundwater resource systems. The algorithm is applied to build a hydroeconomic model for the Jucar River Basin (Spain), in which stream‐aquifer interactions are essential to the characterization of water resources. Besides the uncertainties regarding the economic characterization of the demand functions, the results show that the economic efficiency of the operating policies under the current system can be improved by better management of groundwater and surface resources.

Abstract. Climate and land use change (global change) impacts on groundwater systems cannot be studied in isolation, as various and complex interactions in the hydrological cycle take part. Land-use and land-cover (LULC) changes have a great impact on the water cycle and contaminant production and transport. Groundwater flow and storage are changing in response not only to climatic changes but also to human impacts on land uses and demands (global change). Changes in future climate and land uses will alter the hydrologic cycles and subsequently impact the quantity and quality of regional water systems. Predicting the behavior of recharge and discharge conditions under future climatic and land use changes is essential for integrated water management and adaptation. In the Mancha Oriental system in Spain, in the last decades the transformation from dry to irrigated lands has led to a significant drop of the groundwater table in one of the largest groundwater bodies in Spain, with the consequent effect on stream-aquifer interaction in the connected Jucar River. Streamflow depletion is compromising the related ecosystems and the supply to the downstream demands, provoking a complex management issue. The intense use of fertilizer in agriculture is also leading to locally high groundwater nitrate concentrations. Understanding the spatial and temporal distribution of water availability and water quality is essential for a proper management of the system. In this paper we analyze the potential impact of climate and land use change in the system by using an integrated modelling framework consisting of the sequentially coupling of a watershed agriculturally-based hydrological model (SWAT) with the ground-water model MODFLOW and mass-transport model MT3D. SWAT model outputs (mainly groundwater recharge and pumping, considering new irrigation needs under changing ET and precipitation) are used as MODFLOW inputs to simulate changes in groundwater flow and storage and impacts on stream-aquifer interaction. SWAT and MODFLOW outputs (nitrate loads from SWAT, groundwater velocity field from MODFLOW) are used as MT3D inputs for assessing the fate and transport of nitrate leached from the topsoil. Results on river discharge, crop yields, groundwater levels and groundwater nitrate concentrations obtained from simulation fit well to the observed values. Three climate change scenarios have been considered, corresponding to 3 different GCMs for emission scenario A1B, covering the control period, and short, medium and long-term future periods. A multi-temporal analysis of LULC change was carried out, helped by the study of historical trends by remote sensing images and key driving forces to explain LULC transitions. Markov chains and European scenarios and projections have been used to quantify trends in the future. The cellular automata technique was applied for stochastic modeling future LULC maps. The results show the sensitivity of groundwater quantity and quality (nitrate pollution) to climate and land use changes, and the need to implement adaptation measures in order to prevent further groundwater level declines and increasing nitrate concentrations. The sequential modelling chain has been proved to be a valuable assessment and management tool for supporting the development of sustainable management strategies.

Coordinated and efficient operation of water resource systems becomes essential to deal with growing demands and uncertain resources in water‐stressed regions. System analysis models and tools help address the complexities of multireservoir systems when defining operating rules. This paper reviews the state of the art in developing operating rules for multireservoir water resource systems, focusing on efficient system operation. This review focuses on how optimal operating rules can be derived and represented. Advantages and drawbacks of each approach are discussed. Major approaches to derive optimal operating rules include direct optimization of reservoir operation, embedding conditional operating rules in simulation‐optimization frameworks, and inferring rules from optimization results. Suggestions on which approach to use depend on context. Parametrization–simulation–optimization or rule inference using heuristics are promising approaches. Increased forecasting capabilities will further benefit the use of model predictive control algorithms to improve system operation. This article is categorized under: Engineering Water > Water, Health, and Sanitation Engineering Water > Methods