A hydro-economic modeling framework for optimal management of groundwater nitrate pollution from agriculture

La contaminación difusa por nitratos de las aguas subterráneas, la cual es principalmente originada por la agricultura, es una creciente preocupación en casi cualquier parte del mundo. Esto ha provocado el desarrollado de normativas; en Europa, en 1991 se estableció la Directiva de Nitratos y el año 2000 la Directiva Europea Marco del Agua (DMA). La DMA establece que las masas de agua deben alcanzar el buen estado en el año 2015, además reconoce el rol que la economía puede tener en alcanzar los objetivos ecológicos y ambientales. En este trabajo se presenta un modelo hidro-económico que sugiere la gestión óptima de fertilizantes para controlar la contaminación por nitratos de las agua subterráneas. El modelo holístico de optimización determina la distribución espacio-temporal de la tasa de aplicación de fertilizantes que maximiza los beneficios netos en la agricultura, limitada por los requerimientos de calidad en el agua subterránea en diferentes puntos de control. El modelo relaciona la aplicación de fertilizantes con las concentraciones de nitratos en el agua subterránea mediante el uso de modelos agronómicos, de simulación del flujo y transporte en el agua subterránea, con los cuales se generan soluciones unitarias que son integradas en matrices de respuesta (RM). Las RM dentro del modelo de gestión permiten simular la evolución de la concentración de nitratos en el agua subterránea mediante superposición en diferentes puntos de control a largo del tiempo, debido a la emisión de contaminantes en diferentes zonas distribuidas en el espacio y variables en el tiempo. Los beneficios de la agricultura se determinan a través de funciones de producción y el precio de los cultivos. El modelo desarrollado se aplicó a un acuífero sintético. Se obtuvo la aplicación óptima de fertilizantes para problemas con diferentes condiciones iniciales, horizontes de planeación y tiempos de recuperación.Peña Haro, S. (2010). A hydro-economic modeling framework for optimal management of groundwater nitrate pollution from agriculture [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/7483Palanci

Stochastic hydro-economic modeling for optimal management of agricultural groundwater nitrate pollution under hydraulic conductivity uncertainty

[EN] In decision-making processes, reliability and risk aversion play a decisive role. This paper presents a framework for stochastic optimization of control strategies for groundwater nitrate pollution from agriculture under hydraulic conductivity uncertainty. The main goal is to analyze the influence of uncertainty in the physical parameters of a heterogeneous groundwater diffuse pollution problem on the results of management strategies, and to introduce methods that integrate uncertainty and reliability in order to obtain strategies of spatial allocation of fertilizer use in agriculture. A hydro-economic modeling approach is used for obtaining the allocation of fertilizer reduction that complies with the maximum permissible concentration in groundwater while minimizes agricultural income losses. The model is based upon nonlinear programming and groundwater flow and mass transport numerical simulation, condensed on a pollutant concentration response matrix. The effects of the hydraulic conductivity uncertainty on the allocation of nitrogen reduction among agriculture pollution sources are analyzed using four formulations: Monte Carlo simulation with pre-assumed parameter field, Monte Carlo optimization, stacking management, and mixed-integer stochastic model with predefined reliability. The formulations were tested in an illustrative example for 100 hydraulic conductivity realizations with different variance. The results show a high probability of not meeting the groundwater quality standards when deriving a policy from just a deterministic analysis. To increase the reliability several realizations can be optimized at the same time. By using a mixed-integer stochastic formulation, the desired reliability level of the strategy can be fixed in advance. The approach allows deriving the trade-offs between the reliability of meeting the standard and the net benefits from agricultural production. In a risk-averse decision making, not only the reliability of meeting the standards counts, but also the probability distribution of the maximum pollutant concentrations. A sensitivity analysis was carried out to assess the influence of the variance of the hydraulic conductivity fields on the strategies. The results show that the larger the variance, the greater the range of maximum nitrate concentrations and the worst case (or maximum value) that could be reached for the same level of reliability. © 2011 Elsevier Ltd.The study has been partially supported by the European Community 7th Framework Project GENESIS (226536) on groundwater systems and from the Plan Nacional I+D+I 2008-2011 of the Spanish Ministry of Science and Innovation (subprojects CGL2009-13238-C02-01 and CGL2009-13238-C02-02). The authors thank the anonymous reviewers for their suggestions for improving the paper.Peña Haro, S.; Pulido-Velazquez, M.; Llopis Albert, C. (2011). Stochastic hydro-economic modeling for optimal management of agricultural groundwater nitrate pollution under hydraulic conductivity uncertainty. Environmental Modelling and Software. 26(8):999-1008. https://doi.org/10.1016/j.envsoft.2011.02.010S999100826

Stochastic hydro-economic model for groundwater quality management using Bayesian networks

A strong normative development in Europe, including the Nitrate Directive (1991) and the Water Framework Directive (WFD) (2000), has been promulgated. The WFD states that all water bodies have to reach a good quantitative and chemical status by 2015. It is necessary to consider different objectives, often in conflict, for tackling a suitable assessment of the impacts generated by water policies aimed to reduce nitrate pollution in groundwater. For that, an annual lumped probabilistic model based on Bayesian networks (BNs) has been designed for hydro-economic modelling of groundwater quality control under uncertain conditions. The information introduced in the BN model comes from different sources such as previous groundwater flow and mass transport simulations, hydro-economic models, stakeholders and expert opinion, etc. The methodology was applied to the El Salobral-Los Llanos aquifer unit within the 'Easter Mancha' groundwater body, which is one of the largest aquifers in Spain (7,400 km(2)), included in the Júcar River Basin. Over the past 30 years, socioeconomic development within the region has been mainly depending on intensive use of groundwater resources for irrigating crops. This has provoked a continuous groundwater level fall in the last two decades and significant streamflow depletion in the connected Júcar River. This BN model has proved to be a robust Decision Support System for helping water managers in the decision making process.The authors gratefully acknowledge the contributions of the following people and organizations. The study has been partially supported by the European Community 7th Framework Project GENESIS (226536) on groundwater systems and from the subprogram Juan de la Cierva (2010, 2011) of the Spanish Ministry of Science and Innovation as well as from the Plan Nacional I + D + i 2008-2011 of the Spanish Ministry of Science and Innovation (subprojects CGL2009-13238-C02-01 and CGL2009-13238-C02-02). Finally, thanks to the Jucar River Basin Authority (CHJ), IDR of Univ. of Castilla-La Mancha, the Junta Central de Regantes de la Mancha Oriental, and all the different stakeholders who have collaborated on the data and information provided in this research.Molina, J.; Pulido-Velazquez, M.; Llopis Albert, C.; Peña Haro, S. (2013). Stochastic hydro-economic model for groundwater quality management using Bayesian networks. Water Science and Technology. 67(3):579-586. https://doi.org/10.2166/wst.2012.598S57958667

A hydro-economic modelling framework for optimal management of groundwater nitrate pollution from agriculture

A hydro-economic modelling framework is developed for determining optimal management of groundwater nitrate pollution from agriculture. A holistic optimization model determines the spatial and temporal fertilizer application rate that maximizes the net benefits in agriculture constrained by the quality requirements in groundwater at various control sites. Since emissions (nitrogen loading rates) are what can be controlled, but the concentrations are the policy targets, we need to relate both. Agronomic simulations are used to obtain the nitrate leached, while numerical groundwater flow and solute transport simulation models were used to develop unit source solutions that were assembled into a pollutant concentration response matrix. The integration of the response matrix in the constraints of the management model allows simulating by superposition the evolution of groundwater nitrate concentration over time at different points of interest throughout the aquifer resulting from multiple pollutant sources distributed over time and space. In this way, the modelling framework relates the fertilizer loads with the nitrate concentration at the control sites. The benefits in agriculture were determined through crop prices and crop production functions. This research aims to contribute to the ongoing policy process in the Europe Union (the Water Framework Directive) providing a tool for analyzing the opportunity cost of measures for reducing nitrogen loadings and assessing their effectiveness for maintaining groundwater nitrate concentration within the target levels. The management model was applied to a hypothetical groundwater system. Optimal solutions of fertilizer use to problems with different initial conditions, planning horizons, and recovery times were determined. The illustrative example shows the importance of the location of the pollution sources in relation to the control sites, and how both the selected planning horizon and the target recovery time can strongly influence the limitation of fertilizer use and the economic opportunity cost for meeting the environmental standards. There is clearly a trade-off between the time horizon to reach the standards (recovery time) and the economic losses from nitrogen use reductions. (C) 2009 Elsevier B.V. All rights reserved.The authors thank the Editor, Geoff Syme, and two anonymous reviewers for their detailed and helpful comments on improving the paper. Support for this research was provided by the Mexican Ministry of Science and Technology (CONACyT).Peña Haro, S.; Pulido-Velazquez, M.; Sahuquillo Herráiz, A. (2009). A hydro-economic modelling framework for optimal management of groundwater nitrate pollution from agriculture. Journal of Hydrology. 373(1-2):193-203. doi:10.1016/j.jhydrol.2009.04.024S1932033731-

Influence of soil and climate heterogeneity on the performance of economic instruments for reducing nitrate leaching from agriculture

Economic instruments can be used to control groundwater nitrate pollution due to the intensive use of fertilizers in agriculture. In order to test their efficiency on the reduction of nitrate leaching, we propose an approach based on the combined use of production and pollution functions to derive the impacts on the expected farmer response of these instruments. Some of the most important factors influencing nitrate leaching and crop yield are the type of soil and the climatic conditions. Crop yield and nitrate leaching responses to different soil and climaticconditions were classified by means of a cluster analysis, and crops located in different areas but with similar response were grouped for the analysis. We use a spatial economic optimization model to evaluate the potential of taxes on nitrogen fertilizers, water prices, and taxes on nitrate emissions to reduce nitrate pollution, as well as their economic impact in terms of social welfare and farmers' net benefits. Themethod was applied to theMancha Oriental System(MOS) in Spain, a large area with different soil types and climatic conditions.We divided the study area into zones of homogeneous crop production and nitrate leaching properties. Results how spatially different responses of crop growth and nitrate leaching, proving howthe cost-effectiveness of pollution control instruments is contingent upon the spatial heterogeneities of the problem.The study has been supported by the European Community 7th Framework Project GENESIS (226536) on groundwater.Peña Haro, S.; García Prats, A.; Pulido-Velazquez, M. (2014). Influence of soil and climate heterogeneity on the performance of economic instruments for reducing nitrate leaching from agriculture. Science of the Total Environment. 499:510-519. https://doi.org/10.1016/j.scitotenv.2014.07.029S51051949

Integrated assessment of the impact of climate and land use changes on groundwater quantity and quality in the Mancha Oriental system (Spain)

[EN] 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 pollution) to climate and land use changes, with decreasing groundwater recharge and an increase in nitrate concentrations. The sequential modeling chain has been proven to be a valuable assessment tool for supporting the development of sustainable management strategies.This study was partially funded by the EU FP7 GENESIS project (no. 226.536) on groundwater systems, the Plan Nacional de I+D+I 2008-2011 of the Ministry of Science and Innovation of Spain (projects CGL2009-13238-C02-01/02 on climate change impacts and adaptation), and the IMPADAPT project (CGL2013-48424-C2-1-R) with Spanish MINECO (Ministerio de Economia y Competitividad) and Feder funds. 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Sci., 15, 333–344, https://doi.org/10.5194/hess-15-333-2011, 2011.Zheng, C. and Wang, P. P.: MT3DMS: a modular three-dimensional multispecies transport model for simulation of advection, dispersion, and chemical reactions of contaminants in groundwater systems; documentation and user's guide SERDP-99-1, Washington, DC, US Army Corps of Engineers, 1999

Recerca i tecnologia en enginyeria gràfica i disseny a la Universitat Politècnica de Catalunya

Els temps canvien cada vegada més ràpidament, i a la universitat això encara es nota més. L’històric departament d‘Expressió Gràfica a l’Enginyeria (EGE) de la Universitat Politècnica de Catalunya, garant d’una docència de Grau, Màster i Doctorat de qualitat i adaptada a les necessitats de la societat, emprèn l’any 2020 amb una proposta de canvi de nom per adaptar-se al nous coneixements que estan esdevenint la seva matèria principal, al voltant de l’enginyeria gràfica i el disseny. Les àrees de recerca del centenar de professors que formen el departament són àmplies i variades, i sempre en col·laboració en diversos grups tant de la pròpia UPC com d’altres universitats. Una recerca avançada, de caràcter pluridisciplinari, on s'apliquen creativitat i innovació com a eines de coneixement, implicats en un territori ampli, i situats als diferents campus de la UPC. En els capítols d’aquest llibre podeu veure una petita mostra d’aquesta recerca tecnològica en camps ben variats.Postprint (published version

Towards harmonization of image velocimetry techniques for river surface velocity observations

Since the turn of the 21st Century, image based velocimetry techniques have become an increasingly popular approach for determining open-channel flow in a range of hydrological settings across Europe, and beyond. Simultaneously, a range of large-scale image velocimetry algorithms have been developed, equipped with differing image pre-processing, and analytical capabilities. Yet in operational hydrometry, these techniques are utilised by few competent authorities. Therefore, imagery collected for image velocimetry analysis, along with validation data is required both to enable inter-comparisons between these differing approaches and to test their overall efficacy. Through benchmarking exercises, it will be possible to assess which approaches are best suited for a range of fluvial settings, and to focus future software developments. Here we collate, and describe datasets acquired from six countries across Europe and Asia, consisting of videos that have been subjected to a range of pre-processing, and image velocimetry analysis (Perks et al., 2019, https://doi.org/10.4121/uuid:34764be1-31f9-4626-8b11-705b4f66b95a). Validation data is available for 12 of the 13 case studies presented enabling these data to be used for validation and accuracy assessment

Performance assessment of nitrate leaching models for highly vulnerable soils used in low-input farming based on lysimeter data

[EN] The agricultural sector faces the challenge of ensuring food security without an excessive burden on the environment. Simulationmodels provide excellent instruments for researchers to gainmore insight into relevant processes and best agricultural practices and provide tools for planners for decision making support. The extent to which models are capable of reliable extrapolation and prediction is important for exploring new farming systems or assessing the impacts of future land and climate changes. A performance assessmentwas conducted by testing six detailed state-of-the-artmodels for simulation of nitrate leaching (ARMOSA, COUPMODEL, DAISY, EPIC, SIMWASER/STOTRASIM, SWAP/ANIMO) for lysimeter data of the Wagna experimental field station in Eastern Austria, where the soil is highly vulnerable to nitrate leaching. Three consecutive phases were distinguished to gain insight in the predictive power of themodels: 1) a blind test for 2005 2008 in which only soil hydraulic characteristics, meteorological data and information about the agricultural management were accessible; 2) a calibration for the same period in which essential information on field observations was additionally available to the modellers; and 3) a validation for 2009 2011 with the corresponding type of data available as for the blind test. A set of statistical metrics (mean absolute error, root mean squared error, index of agreement,model efficiency, root relative squared error, Pearson's linear correlation coefficient) was applied for testing the results and comparing the models. None of the models performed good for all of the statistical metrics. Models designed for nitrate leaching in high-input farming systems had difficulties in accurately predicting leaching in low-input farming systems that are strongly influenced by the retention of nitrogen in catch crops and nitrogen fixation by legumes. An accurate calibration does not guarantee a good predictive power of the model. Nevertheless all models were able to identify years and crops with high- and low-leaching rates.This research was made possible by the GENESIS project of the EU 7th Framework Programme (Project No. 226536; FP7-ENV-2008-1). We are grateful for the experimental data provided by Joanneum Raum (Graz, Austria). The modelling team of Democritus University of Thrace would like to thank Per-Erik Jansson (Royal Institute of Technology, Stockholm, Sweden) for his valuable help during the application of Coup Model.Groenendijk, P.; Heinen, M.; Klammler, G.; Fank, J.; Kupfersberger, H.; Pisinaras, V.; Gemitzi, A.... (2014). Performance assessment of nitrate leaching models for highly vulnerable soils used in low-input farming based on lysimeter data. Science of the Total Environment. 499:463-480. https://doi.org/10.1016/j.scitotenv.2014.07.002S46348049