Space–time soil wetness variations monitoring by a multi-temporal microwave satellite records analysis

Abstract

In the last few years, remote sensing observations have become a useful tool for providing hydrological information, including the quantification of the main physical characteristics of the catchment, such as topography and land use, and of its variables, like soil moisture or snow cover. Moreover, satellite data have also been largely used in the framework of hydro-meteorological risk mitigation. Recently, an innovative Soil Wetness Variation Index (SWVI) has been proposed, using data acquired by the microwave radiometer AMSU (Advanced Microwave Sounding Unit) which flies aboard NOAA (National Oceanic and Atmospheric Administration) satellites. SWVI is based on a general approach for multi-temporal satellite data analysis (RAT – Robust AVHRR Techniques). This approach exploits the analysis of long-term multi-temporal satellite records in order to obtain a former characterization of the measured signal, in term of expected value and natural variability, providing a further identification of signal anomalies by an automatic, unsupervised change-detection step. Such an approach has already demonstrated, in several studies carried out on extreme flooding events which occurred in Europe in the past few years, its capability in reducing spurious effects generated by natural/observational noise. In this paper, the proposed approach is applied to the analysis of the flooding event which occurred in Europe (primarily in NW Spain) in June 2000. Results obtained, in terms of reliability as well as efficiency in space–time monitoring of soil wetness variation, are presented. Future prospects, in terms of exportability of the methodology on the new dedicated satellite missions, like ESA-SMOS and NASA-HYDROS, are also discussed.