La télédétection de la neige dans les Andes comme outil de prévision des débits des rivières du Cuyo

• Published in: Revue de géographie alpine Vol. 103; no. 103-2
• Main Authors: Delbart, Nicolas, Dunesme, Samuel, Lavie, Emilie, Madelin, Malika, Goma, Régis
• Format: Journal Article
• Language: English
• Published: Institut de Géographie Alpine 07.09.2015
• Subjects: Andes; Argentina; discharge; remote sensing; rivers; snow
• ISSN: 0035-1121; 1760-7426
• DOI: 10.4000/rga.2861

In the Argentinian Dry Andes, although the melting of glaciers is seen as a threat for the long-term water availability needed by the piedmont crops, the annual snowmelt is the main source of superficial water and aquifer recharge. In this study, we analyse the link between the seasonal and interannual variations in the discharge measured upstream of the first dams on four rivers (Mendoza, Tunuyán, Diamante, Atuel) of the Argentinian Cuyo region (in the Federal Province of Mendoza) and those of the snow bed extent as mapped by optical remote sensing (MODIS MOD10A2 product) on a weekly basis in the 2001-2014 period, at the scale of each watershed.For the four snow-glacier regime rivers, seasonal variations in the discharge appear directly related to those of the snow bed surface area in each watershed, as shown previously (Masiokas et al., 2006). We observed that the high-water period (September-April) discharge is directly related to the snow extent at the beginning of the snowmelt period, i.e. in September and October, as revealed by a correlation of about 0.8. Moreover, the decreasing trend in the winter snow bed extent from 2001 to 2014 clearly explains the observed decreasing trend in the annual water discharge.Agriculture and human activities in these oases mostly depend on river discharge, which from our results clearly depends on the snow extent. Our research indicates that it is possible to use remote sensing to forecast the average discharge in the September-April period (high-water season) from MOD10A2 images with an average uncertainty of 15%. As MOD10A2 data are freely available ten days after acquisition, it is possible to anticipate in early October the risk of water shortages in the coming summer.