<![CDATA[Monitoring and mapping surface water dynamics is a key element in studying and modelling their roles in any hydrological system. However, the fast and accurate extraction of these surfaces is a major challenge due to the spatio-temporal variety of surface water bodies. Through its spatial and temporal capabilities and the synoptic view it offers, remote sensing becomes a very powerful tool in this kind of problem. In recent years, Sentinel 2 optical and Sentinel 1 radar data have shown their effectiveness in the study of natural resources and water surfaces in particular. In this context, this study has taken advantage of remote sensing data to detect and extract surface water bodies. The approach adopted in this work is to use indices derived from high-resolution satellite images for the period 2015-2020. For this, this study used a series of Sentinel 2 MSI (Multi-Spectral Imager) multi-spectral images and Sentinel 1 synthetic radar images. These images are acquired over the Merdja Sidi Abed dam located in western Algeria and allowed us to derive spectral indices by combining several bands such as: Normalised Difference Vegetation Index (NDVI), Modified Normalised Difference Water Index (MNDWI), and the radar backscatter coefficient (????0). The automatic extraction of the dam extent shows a significant degradation of the surface, which has fallen from 815 ha in 2015 to 28 ha in 2020. The signal sensitivity of radar sensors such as Sentinel 1 and the better spatial (10 m) and temporal (5 days) resolution of the Sentinel 2 MSI sensor are very practical ways to track water bodies over time.]]>
