271-Antecedent Wetness Conditions Estimation through ERS Scatterometer Data.

Abstract

Soil moisture is widely recognized as a key parameter in environmental processes, including meteorology, hydrology, agriculture and climate changes. From a hydrologic point of view, soil moisture controls the partitioning of rainfall into runoff and infiltration. In particular, the estimation of the Antecedent Wetness Conditions (AWC) is one of the most important issues for storm rainfall-runoff modeling. To this end, the potential of scatterometer on board of ERS satellites has been investigated for an inland region of Italy where the Upper Tiber is located. The satellite soil moisture data used in this study are taken from the ERS/METOP Soil Moisture archive located at http://www.ipf.tuwien.ac.at/radaders-scat/home.htm. First, the Scatterometer-derived Soil Wetness Index (SSWI) data were compared with two soil moisture data sets acquired in an experimental catchment located in the study area with two different methodologies. Then, the reliability of the SSWI to estimate the AWC of a catchment were analyzed through the relationship between the SSWI and the soil potential maximum retention parameter, S, of the Soil Conservation Service-Curve Number (SCS-CN) method for abstraction. At the purpose, several storm events observed in three catchments from 1992 to 2005 were selected. The performance of the SSWI for S estimation was also compared with two Antecedent Precipitation Indices (API) and the Base Flow Index (BFI). The S values obtained by the observed direct runoff volume and rainfall depth were used as benchmark. Results obtained in this study demonstrate the reliability of the SSWI for the wetness condition estimation both at the plot and catchment scale.