Radar remote sensing of the source areas from the Coët-Dan catchment

Abstract

Abstract:As interest shifts to the development of models for predicting runo quality, identi®cation of the source areas for runo becomes increasingly important. Active microwave remote sensing has a unique potential for surveying source areas at the catchment scale. Thresholding of the back-scattering coecient was initially proposed but proved unsatisfactory when applied to the ERS-1 SAR multitemporal images acquired during winter 1992 over the CoeÈ t-Dan catchment, concomitantly with ground observations. Dierence images may, instead, allow the wettest part of the catchment to be identi®ed provided that the two images encompass a marked hydrological event. A saturation plot could not however be obtained for each date; the use of a pair of images may be further limited by the residual speckle (although carefully ®ltered using the multitemporal information) and a slight inaccuracy in the SAR image calibration. It is therefore argued that considering the whole temporal back-scatter pro®le would be, at present, a safer approach to the remote sensing of saturated areas. The back-scatter temporal standard deviation appears, in this light, as a possible good indicator of the local saturation likelihood during the period of study: it is based on the fact that saturation develops on parts of the catchment that are wetter than the others through lateral recharge. Possible applications within the TOPMODEL framework are discussed. #

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“…This spatial organization seems to correspond to saturated areas as predicted by Verhoest et al (1998) and Gineste et al (1998). This spatial organization seems to correspond to saturated areas as predicted by Verhoest et al (1998) and Gineste et al (1998).…”

“…However, the results indicate that there is a marginally stronger correlation between PC2 and soil moisture change than for either PC1 or the ratio image. This confirms the potential for mapping saturated areas with imaging radar as put forth by Merot et al (1994), Gineste et al (1998), and Grayson and Blö schl (2001). Further examination of PC2 shows a spatial organization that is extremely similar to that of the ratio image, with dark linear features corresponding to the derived drainage network (Figure 5b).…”

“…Gineste et al (1998) demonstrated that a ''saturation potential index'' based on the temporal backscatter standard deviation from a set of 15 ERS images could be used along with a topographic index and compared with field observations to determine saturation area extent. Gineste et al (1998) demonstrated that a ''saturation potential index'' based on the temporal backscatter standard deviation from a set of 15 ERS images could be used along with a topographic index and compared with field observations to determine saturation area extent.…”

Advances in the use of observed spatial patterns of catchment hydrological response

“…Troch et al [95] noted that analysis of individual SAR scenes from operational satellites were too poorly correlated with surface soil moisture to be a useful surrogate, but Verhoest et al [100] and Gineste et al [41] showed that multitemporal analysis of many SAR images could provide information on areas of the landscape that were continuously wet, providing a useful surrogate for saturated areas. This is an excellent example of where substantial analysis of pattern data was needed to derive a usable surrogate pattern.…”

Assessment of SAR-retrieved soil moisture uncertainty induced by uncertainty on modeled soil surface roughness

“…Models employed in these disciplines quite often require spatially distributed soil moisture as input. As the microwave backscattered signal from a bare soil surface is partly influenced by the soil moisture content (Ulaby et al, , 1996(Ulaby et al, , 1982b, radar remote sensing can be used to meet these high spatial resolution requirements (Gineste et al, 1998;Verhoest et al, 1998;Western et al, 2004). Currently, only active microwave sensors, more specifically Synthetic Aperture Radars (SARs), are able to capture soil moisture patterns at high resolutions of about 10 m to 100 m (Moran et al, 2004).…”