Characterizing the dynamics of soil moisture fields is a key issue in hydrology, offering a strategy to improve our understanding of complex climate-soil-vegetation interactions. Apart from in-situ measurements and hydrological models, soil moisture dynamics can be inferred by analyzing data acquired by sensors aboard satellite platforms. In this work, we investigated the use of the National Oceanic and Atmospheric Administration – Advanced Microwave Sounding Unit (NOAA-AMSU) radiometer for the remote characterization of soil water content. To this aim, a field measurement campaign, lasted about three months, was carried out using a portable time-domain reflectometer (TDR) to get soil water content measures over five different locations within an experimental basin of 32.5 km2, located in the South of Italy. In detail, soil moisture measurements have been carried out systematically at the times of satellite overpasses, over two square areas of 400 m2, a triangular area of 200 m2 and two transects of 60 and 170 m, respectively. Each monitored site is characterized by different land covers and soil textures, to account for spatial heterogeneity of land surface. Afterwards, a more extensive comparison (i.e. analyzing a 5-yr data time series) has been made using soil moisture simulated by a hydrological model. Achieved measured and modeled soil moisture data were compared with two AMSU-based indices: the Surface Wetness Index (SWI) and the Soil Wetness Variation Index (SWVI). Both indices have been filtered to account for soil depth by means of an exponential filter. This allowed to understand the ability of each satellite-based index to account for soil moisture dynamics and to understand its performances under different conditions. As a general remark, the comparison shows a higher ability of the filtered SWI to describe the state of the soil, while the SWVI can capture soil moisture variations with a precision that increases at the higher values of SWVI and it may represent a useful and reliable tool to frequently monitor the soil moisture state for flood forecasting purposes.
How to cite: Manfreda, S., T. Lacava, B. Onorati, N. Pergola, M. Di Leo, M. R. Margiotta, and V. Tramutoli, On the use of AMSU-based products for the description of soil water content at basin scale, Hydrology and Earth System Sciences, 15, 2839-2852, (doi:10.5194/hess-15-2839-2011), 2011. [pdf]