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Florisa Melone

Researcher at National Research Council

Publications -  86
Citations -  4860

Florisa Melone is an academic researcher from National Research Council. The author has contributed to research in topics: Water content & Flood forecasting. The author has an hindex of 31, co-authored 86 publications receiving 4365 citations.

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Soil moisture estimation through ASCAT and AMSR-E sensors: An intercomparison and validation study across Europe

TL;DR: In this article, a comprehensive assessment of the reliability of soil moisture estimations from the Advanced SCATterometer (ASCAT) and AMSR-E sensors is carried out by using observed and modelled soil moisture data over 17 sites located in 4 countries across Europe (Italy, Spain, France and Luxembourg).
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Spatial-temporal variability of soil moisture and its estimation across scales

TL;DR: In this paper, the authors used a portable Time Domain Reflectometer (TDRS) to measure the soil moisture at the field and catchment scale. But the accuracy of the measured soil moisture was only 2.38%.
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Soil moisture spatial variability in experimental areas of central Italy

TL;DR: In this article, the authors investigated the soil moisture spatial pattern obtained from spot measurements carried out in different experimental plots located in small basins of Central Italy using a portable time domain reflectometer (TDR) over regular grids whose areas ranging in extension from 9 to 8800 m2.
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Improving runoff prediction through the assimilation of the ASCAT soil moisture product

TL;DR: In this paper, the authors compared the soil wetness index (SWI) derived from the Advanced SCATterometer (ASCAT) sensor onboard of the Metop satellite with the soil moisture temporal pattern derived from a continuous rainfall-runoff model (MISDc) to assess its relationship with modeled data.
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Assimilation of Surface- and Root-Zone ASCAT Soil Moisture Products Into Rainfall–Runoff Modeling

TL;DR: The possibility to efficiently employ coarse resolution satellite soil moisture products for improving flood prediction is proven, mainly if RZSM data are assimilated into the hydrological model.