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Hydrological modelling in the High Atlas mountains with the help of remote-sensing data: milestones of the SudMed project

Congress: 2008
Author(s): G. Boulet(1), A. Boudhar(2), L. Hanich(2), B. Duchemin(1), V. Simonneaux(1), P. Maisongrande(1), A. Chehbouni(1), S. Thomas(1), A. Chaponnière(1)
(1) CESBIO (UMR 5126 CNES-CNRS-UPS-IRD), Toulouse, France (2) Faculté des Sciences et Techniques, Marrakech, Maroc

Keyword(s): Morocco, Remote-Sensing, Snowmelt, Climate Change, Hydrological modelling
Article:
AbstractThe sustainable management of water resources worldwide is one of the most important challenges of the 21st century. In the Tensift-Haouz plain, located in central Morocco and characterized by a semi-arid climate, 85% of available water is used for agriculture. Precipitation, which is concentrated over the High-Atlas mountain range, falls in a significant proportion as snow leading to storage until the snowmelt period and a significant contribution to baseflow in the summer. In order to understand the hydrological cycle of the Tensift basin, the sudmed project has developed a research program based on modelling, experimental and remote-sensing monitoring of the High Atlas subbasins. A top-down and a bottom- up strategy have been combined in a modelling approach of medium-range complexity. This approach simulates the largely unobservable subsurface flow processes using input data from the sparse network of climate stations while incorporating as much ancillary available information as possible: noisy streamflow observations, geochemical elements tracing, remotely-sensed land cover and snow area. The bottom-up approach is based on the distributed hydrological model SWAT and uses a simplified land cover map, while the top-down approach uses two global semi-empirical models, GR4J and SRM. In parallel, complex energy-balance models are used to ensure realistic outputs for the simple degree day snowmelt models embedded in the three models. Time series of snow cover derived from SPOT-VEGETATION and MODIS are assimilated into all models to improve the contribution of snowmelt to runoff. The improvement is significant given the lack of distributed climate observations, but its impact on the runoff is relatively minor. The spatialisation of the climatological forcing data remains a pitfall for all studies. An improved spatialisation is developed on the basis of remote-sensing data in the Thermal Infra Red spectrum and outputs of current mesoscale meteorological models. Kriging methods based on a digital elevation model and the available high-resolution TIR data at selected dates are combined with the very low resolution TIR images from geostationary satellites and the outputs of the meteorological models. The climate-change scenarios provided by these models are eventually used to assess the impact of climate change on the hydrological regime of the High Atlas and the availability of water in the foot plain.
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