Abstract
The susceptibility of a catchment to flooding is affected by its soil moisture prior to an extreme rainfall event. While soil moisture is routinely observed by satellite instruments, results from previous work on the assimilation of remotely sensed soil moisture into hydrologic models have been mixed. This may have been due in part to the low spatial resolution of the observations used. In this study, the remote sensing aspects of a project attempting to improve flow predictions from a distributed hydrologic model by assimilating soil moisture measurements are described. Advanced Synthetic Aperture Radar (ASAR) Wide Swath data were used to measure soil moisture as, unlike low resolution microwave data, they have sufficient resolution to allow soil moisture variations due to local topography to be detected, which may help to take into account the spatial heterogeneity of hydrological processes. Surface soil moisture content (SSMC) was measured over the catchments of the Severn and Avon rivers in the South West UK. To reduce the influence of vegetation, measurements were made only over homogeneous pixels of improved grassland determined from a land cover map. Radar backscatter was corrected for terrain variations and normalized to a common incidence angle. SSMC was calculated using change detection.To search for evidence of a topographic signal, the mean SSMC from improved grassland pixels on low slopes near rivers was compared to that on higher slopes. When the mean SSMC on low slopes was 30–90%, the higher slopes were slightly drier than the low slopes. The effect was reversed for lower SSMC values. It was also more pronounced during a drying event. These findings contribute to the scant information in the literature on the use of high resolution SAR soil moisture measurement to improve hydrologic models.
Highlights
One factor that affects the susceptibility of a catchment to flooding is its soil moisture condition prior to an extreme rainfall event
In order to search for evidence of a topographic signal in the remotely sensed relative surface soil moisture content (SSMC), we compared the mean relative SSMC from improved grassland pixels on low slopes
From the plot it can be seen that (a) when SSMC on low slopes (SSMCL) approaches 100%, there is little difference between the mean relative SSMC of the low and higher slopes, (b) when SSMCL is 30 - 90%, the higher slopes are slightly drier than the low slopes
Summary
One factor that affects the susceptibility of a catchment to flooding is its soil moisture condition prior to an extreme rainfall event. There appears to be scant information in the literature relating to the use of high resolution SAR soil moisture measurement to improve rainfall-runoff estimation. ASAR WS data have been used to study soil moisture variations at high resolution in an alpine valley (Greifeneder et al 2014); to validate soil moisture measurements from passive microwave sensors at a number of Irish sites (Pratola et al, 2014); and to map surface soil moisture over parts of Tunisia (Zribi et al, 2014). The object of this paper is to detect whether a topographic signal can be seen in high resolution remotely sensed soil moisture data Such a signal may be useful information for a hydrologic model to be able to account for spatial heterogeneity in hydrological processes in relation to flood-producing rainfall-runoff events A subsequent paper will investigate whether the assimilation of these data into a hydrologic model is able to improve runoff prediction
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