Soil moisture is widely recognized as a key parameter in the mass and energy balance between the land surface and the atmosphere and, hence, the potential societal benefits of an accurate estimation of soil moisture are immense. Recently, scientific community is making great effort for addressing the estimation of soil moisture over large areas through in situ sensors, remote sensing and modelling approaches. The different techniques used for addressing the monitoring of soil moisture for hydrological applications are briefly reviewed here. Moreover, some examples in which in situ and satellite soil moisture data are successfully employed for improving hydrological monitoring and predictions (e.g., floods, landslides, precipitation and irrigation) are presented. Finally, the emerging applications, the open issues and the future opportunities given by the increased availability of soil moisture measurements are outlined.
[1] In recent years local, national, and international authorities have showed an increasing awareness of flood and inundation hazard, likely due to the large floods which occurred in the past years in many regions of the world. In this context, the estimation of the design flood values to be adopted for flood risk assessment or floodplain management represents a crucial factor. In the case of ungauged or scarcely gauged catchments where a sufficiently long discharge time series is missing, a relevant uncertainty is involved in the flood frequency analysis and a possible solution to reduce this uncertainty is the application of continuous simulation (CS) approaches. Because of the complex structure of this type of approaches and pursuing the parameters parsimony criteria, in the hydrological practice the approaches based on the design storm (DS) estimation are more widely known and applied, mainly for their simplicity. However, one major limit of the DS method is the choice of the ''design soil moisture'' conditions, representing a critical parameter for assessing the initial wetness of the basin. To that end, this study of investigating six subcatchments of the upper Tiber River basin (Central Italy), with drainage area ranging from 13 to 284 km 2 , proposes a procedure based on the application of the CS approach as a tool to define the design soil moisture to be afterwards incorporated into the more simple DS method. For each catchment, the procedure consists of (1) stochastic generation of long synthetic rainfall and temperature series starting from observed hourly data; (2) application of a lumped continuous rainfall-runoff model to generate synthetic discharge series and, hence, to obtain the corresponding flood frequency curves; (3) estimation of the design soil moisture, for each return period, by varying in the DS approach the initial wetness conditions of the catchment so that the peak discharge estimated by the DS method matches the one given by the synthetic flood frequency curve. Moreover, in order to apply the more simple DS approach avoiding the use of the CS one, a preliminary analysis to regionalize the design soil moisture as a function of the geomorphological characteristics and the return period is also shown.Citation: Camici, S., A. Tarpanelli, L. Brocca, F. Melone, and T. Moramarco (2011), Design soil moisture estimation by comparing continuous and storm-based rainfall-runoff modeling, Water Resour. Res., 47, W05527,
Remote sensing of soil moisture has reached a level of good maturity and accuracy for which the retrieved products are ready to use in real-world applications. Due to the importance of soil moisture in the partitioning of the water and energy fluxes between the land surface and the atmosphere, a wide range of applications can benefit from the availability of satellite soil moisture products. Specifically, the Advanced SCATterometer (ASCAT) on board the series of Meteorological Operational (Metop) satellites is providing a near real time (and long-term, 9+ years starting from January 2007) soil moisture product, with a nearly daily (sub-daily after the launch of Metop-B) revisit time and a spatial sampling of 12.5 and 25 km. This study first performs a review of the climatic, meteorological, and hydrological studies that use satellite soil moisture products for a better understanding of the water and energy cycle. Specifically, applications that consider satellite soil moisture product for improving their predictions are analyzed and discussed. Moreover, four real examples are shown in which ASCAT soil moisture observations have been successfully applied toward: 1) numerical weather prediction, 2) rainfall estimation, 3) flood forecasting, and 4) drought monitoring and prediction. Finally, the strengths and limitations of ASCAT soil moisture products and the way forward for fully exploiting these data in real-world applications are discussed.
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