Monitoring soil wetness variations by means of satellite passive microwave observations: the HYDROPTIMET study cases

Abstract

Abstract. Soil moisture is an important component of the hydrological cycle. In the framework of modern flood warning systems, the knowledge of soil moisture is crucial, due to the influence on the soil response in terms of infiltrationrunoff. Precipitation-runoff processes, in fact, are related to catchment's hydrological conditions before the precipitation. Thus, an estimation of these conditions is of significant importance to improve the reliability of flood warning systems. Combining such information with other weatherrelated satellite products (i.e. rain rate estimation) might represent a useful exercise in order to improve our capability to handle (and possibly mitigate or prevent) hydro-geological hazards.Remote sensing, in the last few years, has supported several techniques for soil moisture/wetness monitoring. Most of the satellite-based techniques use microwave data, thanks to the all-weather and all-time capability of these data, as well as to their high sensitivity to water content in the soil. On the other hand, microwave data are unfortunately highly affected by the presence of surface roughness or vegetation coverage within the instantaneous satellite field of view (IFOV). Those problems, consequently, strongly limit the efficiency and the reliability of traditional satellite techniques.Recently, using data coming from AMSU (Advanced Microwave Sounding Unit), flying aboard NOAA (National Oceanic and Atmospheric Administration) satellites, a new methodology for soil wetness estimation has been proposed. The proposed index, called Soil Wetness Variation Index (SWVI), developed by a multi-temporal analysis of AMSU records, seems able to reduce the problems related to vegetation and/or roughness effects. Such an approach has been tested, with promising results, on the analysis of some flooding events which occurred in Europe in the past.Correspondence to: N. Pergola (pergola@imaa.cnr.it)In this study, results achieved for the HYDROPTIMET test cases will be analysed and discussed in detail. This analysis allows us to evaluate the reliability and the efficiency of the proposed technique in identifying different amounts of soil wetness variations in different observational conditions. In particular, the proposed indicator was able to document the actual effects of meteorological events, in terms of space-time evolution of soil wetness changes, for all the analysed HYDROPTIMET test cases. Moreover, in some circumstances, the SWVI was able to identify the presence of a sort of "early" signal in terms of soil wetness variations, which may be regarded as a timely indication of an anomalous value of soil water content. This evidence suggests the opportunity to use such an index in the pre-operational phases of the modern flood warning systems, in order to improve their forecast capabilities and their reliability.

Application of Landsat-8 and ALOS-2 data for structural and landslide hazard mapping in Kelantan, Malaysia

“…Besides, the best soil moisture/wetness information is achievable from L-band microwaves because it comes out from deeper soils. In fact, vegetation is almost transparent and roughness effects are negligible using L-band microwaves for soil wetness mapping/monitoring (Jackson and Schmugge, 1989;Lacava et al, 2005). Soil moisture is one the most important factors in hydrogeological hazards, especially since the soil response is affected by its status of saturation.…”

“…Precipitation and soil moisture variations have an influence on detailed geologic lineament analysis using microwave signal. SAR data are highly sensitive to the water content in the soil because of large contrast between dielectric properties of water and dry soil (Eagleman and Lin, 1976;Jackson and Schmugge, 1989;Lacava et al, 2005). Hence, SAR data acquired during dry seasons contain more useful information for detailed geological structural mapping in tropical environments.…”

Improving flood monitoring by the Robust AVHRR Technique (RAT) approach: the case of the April 2000 Hungary flood

“…It is based on the general Robust AVHRR Technique (RAT), recently changed to the Robust Satellite Techniques (RST) approach (Tramutoli 1998(Tramutoli , 2005 already successfully applied to forest-fire detection (Cuomo et al 2001), volcanic eruption , Di Bello et al 2004) seismic-area monitoring , 2005, Corrado et al 2005, cloud detection (Cuomo et al 2004) and hydrologic risk evaluation (Lacava et al 2005a(Lacava et al ,b,c, 2006. In this work, the RAT approach is applied to the real-time mapping of flooded areas for the first time.…”

Analysis of Soil Wetness Variations Using AMSR-E Data in Huaihe River Basin

“…Passive microwave data present a potential for floodwaterlogging monitoring and soil moistures estimation because of the ability of the microwave signal to penetrate through cloud and provide a daily coverage and because they are sensitive to the water and near soil surface [3][4][5][6][7]. AMSR-E (Advanced Microwave Scanning Radiometer-Earth Observing System) instrument on the NASA Earth Observing System (EOS) Aqua satellite provides the higher spatial resolution than SSM/I data.…”