Rainfall-Runoff Database for Facilitating Improved Adaptation Strategies to Climate Extremes

Global freshwater availability is extensively governed by streamflow availability. However, in the recent past, the streamflow in many world rivers is showing a greater variability as a response to extremes, such as floods, which in turn is challenging to water managers due to lack of sufficient information. Reliable flood forecasting system, exploiting also satellite information, can help decision-makers to take actions for addressing both disaster risk and water resources management.

In this study, a framework for a comprehensive rainfall-runoff database was developed to study the catchment response to a variety of rainfall events. The core of the framework is the hydrological model, MISDc (Modello Idrologico Semi-Distribuito in continuo), forced with satellite Global Precipitation Measurement (GPM) precipitation data and soil moisture Advanced SCATterometer (ASCAT) backscatter observations. The resulting rainfall-runoff database stores pre-simulated events classified on the basis of the rainfall amount, initial wetness conditions, and initial discharge. The system was developed and tested at several gauged river sections along the upper Tiber river (central Italy) and the Po river (North Italy), and it demonstrated to be an effective tool to assess possible streamflow scenarios assuming different soil moisture conditions and rainfall volumes for the following days. This activity is part of the European Space Agency Digital Thin Earth Hydrology project aimed to develop what-if scenarios for flood risk assessment.