Evaluation of the ERS Scatterometer-Derived Soil Water Index to Monitor Water Availability and Precipitation Distribution at Three Different Scales in China.

In this paper, the capability of the European Remote Sensing Satellite (ERS) scatterometer-derived soil water index (SWI) data to disclose water availability and precipitation distribution in China is investigated. Monthly averaged SWI data for the years 1992–2000 are analyzed to evaluate the use of the SWI as an index to monitor water availability and water stress at three different scales in China and to investigate if it reflects general precipitation distribution characteristics in China. Monthly averaged in situ relative soil moisture from Chinese meteorological gauge stations, as well as monthly precipitation data from the Global Precipitation Climatology Centre (GPCC), are employed to perform comparisons with SWI on local, regional, and countrywide scales. First, since soil moisture is highly affected by the precipitation, area-averaged SWI is compared with in situ relative soil moisture and GPCC precipitation data in one local area. Second, area-averaged SWI and GPCC precipitation data are used to perform comparisons in three regions of China. Finally, the relationship between SWI and GPCC precipitation data in China is investigated on a countrywide scale. Such multiscale analyses with SWI data have not been performed before, and SWI has never been investigated in detail for China. ERS-derived SWI data in China for the years 1992–2000 are evaluated to be a good indicator for water availability on local, regional, and countrywide scales. SWI and SWI anomaly data correlate well with precipitation and in situ soil moisture data. SWI has furthermore been demonstrated to reflect extreme events such as droughts and floods in China, occurring during the investigated period between 1992 and 2000. Additionally, the SWI allows one to monitor increasing soil moisture resulting from snowmelt, which cannot be deduced from precipitation data. The freely available 15-yr (1992–2007) time series SWI data are thus a valuable tool to overcome the scarcity of in situ soil moisture observations, which are usually not available on regional and countrywide scales. [ABSTRACT FROM AUTHOR]