A Decision Support System has been set up as the result of a fruitful cooperation between several public and research institutions in the framework of a large cooperation program. The DSS aims to compare spatially and temporally sectorial water demands of the Haouz-Mejjate plain (Morocco) in regard to available surface and groundwater resources. It is composed of a tool for satellite estimation of Agricultural Water Demand (SAMIR), a tool for integrated water resources planning (WEAP) and a groundwater model (MODFLOW) each of them relying on a common Geographical Information System not described here. The DSS is operating on a monthly time scale. Agricultural water demand accounts for about 80 % of the total demand. In areas where groundwater abstraction is difficult to quantify by direct methods, multitemporal remote sensing associated to the FAO methodology is a simple and efficient alternative to estimate Evapotranspiration (ET). In this work, a monthly estimate of ET from irrigated areas is derived from freely available MODIS NDVI for the 2001–2009 period. An important part of the paper deals with the validation of these estimates with eddy covariance flux measurements installed on different irrigated crops of the region. Results are satisfactory with a minus 6.5 % error per year on the monthly time scale. This preprocessing allows to dichotomize irrigated versus non-irrigated areas, and then, to estimate groundwater abstraction in subareas distinguishing by their operating modes: traditional, dam or privately irrigated. A dynamic linkage between MODFLOW and WEAP transfers the results of one model as input data to the other. The model restitutes both spatial and temporal variations in head charges and allows the calculation of the ground water balance. After calibration, piezometric validation is acceptable for the majority of the 21 head control points.
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Fraction Cover of vegetation
Basal Crop Coefficient
Normalized Difference Vegetation Index
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This study was realized within the framework of the Joint International Laboratory TREMA, AGIRE project and ACSAD/BGR cooperation. The Tensift Basin Agency (Agence de Bassin Hydraulique du Tensift), which is a stakeholder in the two projects, played a key role in joining stakeholders. TREMA ‘Remote sensing and water resources in semi-arid environment’ involves the collaboration of CESBIO (Centre d’Etudes Spatiales de la Biosphère, Toulouse, France) the Cadi Ayyad University, Marrakech, Morocco, the Agriculture Office (Office de Mise en Valeur Agricole), thanks to the financial support of IRD (Institut de Recherche pour le Développement, France). AGIRE (Program to support the integrated management of water resources) involves the Ministry of Water and the Environment of the Kingdom of Morocco, the German International Cooperation (GIZ) and four Moroccan Basin Agencies. We are very grateful with each of these institutions for sharing their data and experience in this project. The Arab Center for the Studies of Arid Zones and Dry Lands (ACSAD) and the Federal Institute for Geosciences and Natural Resources, Germany (BGR) were the igniters of the WEAP-MODFLOW modeling through several workshops. Thanks to the Federal Institute for Geosciences and Natural Resources and Jack Sieber (SEI) for their technical support on WEAP. This study was also financially supported by Resamed project (Aquifer Recharge in the Mediterranean Area). We are grateful to the CNES (Centre National d’Etudes Spatiales, France) for its financial support during this work and for providing SPOT/LANDSAT images and facilitating the import of scientific equipment, the DMN (Direction de la Météorologie National, Morocco) for providing us with the outputs of the ALADIN model. Final thanks to Ian Timms for correcting the English version of the manuscript.
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Le Page, M., Berjamy, B., Fakir, Y. et al. An Integrated DSS for Groundwater Management Based on Remote Sensing. The Case of a Semi-arid Aquifer in Morocco. Water Resour Manage 26, 3209–3230 (2012). https://doi.org/10.1007/s11269-012-0068-3
- Decision support system
- Remote sensing