High-resolution drought monitoring with Sentinel-1 and ASCAT: A case-study over Mozambique

Résumé fourni par la source

This study investigates the potential of active microwave remote sensing to develop high-resolution drought indicators based on surface soil moisture (SSM) in Mozambique. A 500-meter resolution SSM product is derived from Sentinel-1 C-band radar backscatter using a change detection model (SSM s1 ) and validated with state-of-the-art products including ASCAT, ERA5-Land, and SMAP. Results show that SSM s1 provides consistent moisture information with greater spatial resolution compared to existing datasets. Two drought indicators are derived from SSM s1 : the soil water deficiency index (SWDI s1 ) using SSM s1 with auxiliary soil properties from Soilgrids, and the Z-score s1 , combining ASCAT long-term climatology with Sentinel-1 spatial resolution to develop an anomaly-based indicator. Both SWDI s1 and Z-score s1 are compared against precipitation and vegetation anomalies in six regions of Mozambique. Precipitation anomalies show low regional variability and often fail to capture drought dynamics during the dry season, yet correlate with Surface Soil Moisture (SSM) anomalies during the rainy season. The vegetation indicator detects drought with a temporal delay compared to both SWDI and Z-score s1 , suggesting that SSM provide information on earlier drought development, prior to observable vegetation anomalies. The results highlight the complementary strengths of these datasets and suggest their combined use in early warning systems. Combining information from precipitation, vegetation, and SSM s1 enables complete monitoring of drought development. This research contributes to the development of strategies to monitor droughts and the improvement of early warning systems to improve the resilience of smallholder farmers as communities in Mozambique often rely on rain-fed agriculture.

Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.