Improving soil wetness variations monitoring from passive microwave satellite data: The case of April 2000 Hungary flood

European Journal of Remote Sensing

Brocca

Coviello

et al. 2012

Self Cite

The monitoring of soil moisture (SM) can be performed through remote sensing technologies. Among the operational microwave radiometers potentially able to provide information about SM and its variability in the space-time domain, in this work the capability of the AMSU (Advanced Microwave Sounding Unit) sensor has been investigated. In particular, SM information, achieved implementing two different AMSU-based indices, has been compared with both in situ measured and modeled observations for several sites spread out all over Italy. The results indicate that the AMSU sensor can be considered as a useful tool to provide quite reliable information about SM variability, mainly if its high temporal resolution is taken into account.

Section: Methodsmentioning

confidence: 99%

Soil moisture variability estimation through AMSU radiometer

European Journal of Remote Sensing

Brocca

Coviello

et al. 2012

Self Cite

“…The same site observed under the same observational conditions (same month of year, same time of day), in fact, is expected to have the same roughness and quite similar vegetation cover, so that the possible emissivity variations observed can mainly be attributed to moisture variations in the soil (Lacava et al, 2005).…”

Section: The Soil Wetness Variation Index (Swvi)mentioning

confidence: 97%

“…In order to try to overcome (or reduce) the problems related to vegetation and/or roughness effects, a new technique has already been suggested (Lacava et al, 2005). It is based on a general data analysis strategy, the RAT (Robust AVHRR Techniques - Tramutoli, 1998) approach.…”

Section: The Soil Wetness Variation Index (Swvi)mentioning

confidence: 99%

“…A new technique for soil wetness monitoring has recently been proposed (Lacava et al, 2005). It is based on a multitemporal analysis of data acquired from AMSU (Advanced Microwave Sensor Unit) sensor.…”

Section: Introductionmentioning

confidence: 99%

“…The new approach proposed, which seems able to overcome the above mentioned problems related to soil roughness and vegetation, has been applied with good results for the analysis of some flooding events which affected European countries in the past (Lacava, 2004;Lacava et al, 2004 and2005). In this study, the results obtained by the analysis of the study cases selected within the INTERREG IIIB Medocc "HYDROPTIMET" project will be presented and discussed in a possible operational scenario.…”

Section: Introductionmentioning

confidence: 99%

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

Nat. Hazards Earth Syst. Sci.

Greco

Leo

et al. 2005

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.

A multi‐temporal analysis of AMSR‐E data for flood and discharge monitoring during the 2008 flood in Iowa

Temimi

Lakhankar

et al. 2011

Hydrological Processes

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The objective of this work is to demonstrate the potential of using passive microwave data to monitor flood and discharge conditions and to infer watershed hydraulic and hydrologic parameters. The case study is the major flood in Iowa in summer 2008. A new Polarisation Ratio Variation Index (PRVI) was developed based on a multi-temporal analysis of 37 GHz satellite imagery from the Advanced Microwave Scanning Radiometer (AMSR-E) to calculate and detect anomalies in soil moisture and/or inundated areas. The Robust Satellite Technique (RST) which is a change detection approach based on the analysis of historical satellite records was adopted. A rating curve has been developed to assess the relationship between PRVI values and discharge observations downstream. A time-lag term has been introduced and adjusted to account for the changing delay between PRVI and streamflow. Moreover, the Kalman filter has been used to update the rating curve parameters in near real time. The temporal variability of the b exponent in the rating curve formula shows that it converges toward a constant value. A consistent 21-day time lag, very close to an estimate of the time of concentration, was obtained. The agreement between observed discharge downstream and estimated discharge with and without parameters adjustment was 65 and 95%, respectively. This demonstrates the interesting role that passive microwave can play in monitoring flooding and wetness conditions and estimating key hydrologic parameters