Satellite inspired hydrology in an uncertain future: a H SAF and HEPEX workshop

Bucket-type hydrological models such as the HBV model are widely popular, because of their relatively low data and computational demands. This is the case of the snow routine in the HBV model. While this approach usually results in good simulations, improvements are possible. We explored and tested different alternatives to the design of the snow routine of HBV-light such as considering a...

Improving sharpness/reliability of hydrological forecasts is key to increase the value of a warning service. Hydrological data assimilation is one possible way to increase the accuracy (and possibly reliability). Various studies in assimilation of various ECVs (water level, discharge, soil moisture) show that accuracy can be indeed be improved. Here, we show results from the H2020 IMPREX...

Event-based hydrological modelling disregards some hydrological processes that during an event resulted neglectable. A reliable initial condition of model is fundamental for discharges prediction and, consequently, for flood risk mitigation. Satellite observations can be exploited to estimate soil moisture and these can be used to enhance the predictions of hydrological models.
The aim of...

The objective of this study is to evaluate the potential of assimilating flood extent information derived from satellite Earth observation into a flood forecasting chain for reducing predictive uncertainty. A recent promising study introduces a DA framework based on probabilistic flood maps derived from SAR images considering uncertain rainfall. In our study, we carry out an identical twin...

A consortium led by the RHEA Group, working with the Ugandan Ministry of Water and Environment and local Non-Governmental Organizations (NGOs, AgriTechTalk Uganda and Mercy Corps) has developed a Drought and Flood Mitigation Service (DFMS), funded as part of the UK Space Agency’s International Partnership Programme.

DFMS is using satellite Earth observation (EO) data alongside meteorological...