Monitoring Flood and Discharge Variations in the Large Siberian Rivers From a Multi-Satellite Technique

• Published in: Surveys in Geophysics
• Main Authors: Papa, Fabrice, Prigent, Catherine, Rossow, William B.
• Other Authors: City College of New York CUNY (CCNY), City University of New York New York (CUNY), Laboratoire d'Etude du Rayonnement et de la Matière en Astrophysique (LERMA), École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire de Paris, Université Paris sciences et lettres (PSL)-Université de Cergy Pontoise (UCP), Université Paris-Seine-Université Paris-Seine-Centre National de la Recherche Scientifique (CNRS)
• Format: Article in Journal/Newspaper
• Language: English
• Published: HAL CCSD 2008
• Subjects: [PHYS.ASTR]Physics [physics]/Astrophysics [astro-ph]; Arctic; permafrost
• Online Access: https://hal.archives-ouvertes.fr/hal-03785234; https://doi.org/10.1007/s10712-008-9036-0

International audience Using a multi-satellite method, employing passive and active microwave along with visible and infrared observations developed to estimate monthly inundation extent at global scale, this study investigates the response of river discharge to seasonal flood change in the large Siberian watersheds. The seasonal cycle and variations of inundation extent over the Ob, the Yenissey, and the Lena basins for the period 1993-2000 show different spatial and temporal behaviors due to different climate and permafrost conditions. Using in-situ discharges collected at the outlets of the three basins, we analyze and quantify the relationships between the river streamflow and the monthly satellite-derived inundation extent during the spring/summer periods. Furthermore, we analyze extreme (high/low) streamflow cases for some years and the associated inundation conditions for the three watersheds and link these cases with other climatic parameters such as the snow water equivalent, temperatures, and precipitation. The results of this study demonstrate that the monthly multi-satellite-derived inundation dataset brings a new useful tool for better understanding both the streamflow processes and the description of the snow-inundation-runoff relations in data scarce areas like the remote Arctic river basins.