Hydrological sensitivity of the Adour‐Garonne river basin to climate change

Abstract

[1] Output atmospheric fields from seven global climate models (GCMs) were extracted over a domain covering the Adour-Garonne basin in southwestern France in order to calculate precipitation and temperature anomalies for the decade 2050-2060 relative to the present climate. These anomalies showed a general trend of increasing precipitation in wintertime and decreasing precipitation in summertime, together with an increase in the annual average temperature of approximately 2°C. The anomalies were used to create seven modified climate-forcing data sets, which were then used to drive the SAFRAN-ISBA-MODCOU (SIM) hydrometeorological modeling system. The river discharge simulated by the SIM model under each modified climate for the 2050-2060 decade was compared to the discharge simulated for the 1985-1995 reference decade. The results show a slight decrease in the low river flow, on the order of 11% ± 8% on average for all of the climate-forcing data sets and the hydrometric stations. However, there was a significant impact on the snowpack in terms of reduced snow cover depth and duration. These changes provoked a discharge decrease in the spring and a large increase in winter due to the additional liquid precipitation. Considering the large range in climate conditions of the period studied, it appears that the hydrological sensitivity of the river basin is greater when applying the same climate modification to a wet year as opposed to a dry year. Finally, a transient climate forcing covering the 1985-2095 period provokes a general tendency to decrease the river discharge for all seasons.

Comparison of past and future Mediterranean high and low extremes of precipitation and river flow projected using different statistical downscaling methods

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Safran-Isba-Modcou (SIM) : Un outil pour le suivi hydrométéorologique opérationnel et les études

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An interdisciplinary modelling framework for selecting adaptation measures at the river basin scale in a global change scenario

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