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In African countries, the lack of observed rainfall data is a major obstacle for efficient water resources management. The objective of this study is to evaluate satellite rainfall products' ability to estimate river runoff over 12 basins in Morocco using four hydrological models: IHACRES, MISDc, GR4J, and CREST. Satellite products available with a short latency are compared: EUMETSAT H SAF, SM2RAIN-ASCAT, and IMERG. The best results to reproduce river runoff were obtained with SM2RAIN-ASCAT in combination with the IHACRES model, with the highest Kling-Gupta efficiency criterion and probability of detection of extreme runoff. The hydrological model performances differed across catchments and satellite rainfall products, which highlights the need to carefully select hydrological models for a given application. Thus, it is advisable to evaluate satellite rainfall products with different types of hydrological models. This first evaluation over Moroccan basins suggests that SM2RAIN-ASCAT could be a reliable alternative to observed rainfall for hydrological modelling. [ABSTRACT FROM AUTHOR]

Rainfall is the primary input for hydrologic models that simulate the rainfall-runoff processes at basin scale. Because rainfall is highly variable in space and time, accurate hydrological simulations require accurate rainfall data at the best possible resolution. The conventional rain gauge observations in many parts of the world are sparse and unevenly distributed. Satellite-based rainfall products (SRPs) could be an alternative to traditional rain gauge observations and nowadays are available on a global scale at ever increasing spatial and temporal resolution.This study proposes a comprehensive assessment of SRPs for flood modeling in Europe. For this purpose, multiple SRPs (i.e., the Tropical Rainfall Measurement Mission (TRMM) Multi-satellite Precipitation Analysis TMPA; the Climate Prediction Center (CPC) Morphing algorithm, CMORPH, the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks, PERSIANN; the SM2RAIN‐ASCAT rainfall product obtained from ASCAT satellite soil moisture through the SM2RAIN algorithm) will be used to force different lumped hydrologic models (e.g., MISDc, GR4J, HYMOD) over several (+900) basins throughout Europe with different sizes and physiographic characteristics. In particular, this study will allow to: 1) assess the quality of different SRPs for flood modelling and its relationship with climatic/geomorphological conditions; 2) explore the connection between the accuracy of SRPs and their performance in terms of flood modeling taking into account the rainfall-runoff model structure as well. Preliminary results indicated that: 1) satellite rainfall products are not completely reliable for flood forecasting; 2) the hydrological performances of satellite rainfall products depend both on the product and on the selected hydrological model making general guidelines for the optimal use of SRPs in flood modeling difficult to be drawn. To overcome this issue a multimodel-multiproduct approach would help to exploit relative skills of each satellite product-hydrological model configuration and would bring to a more reliable flood forecasting system. [ABSTRACT FROM AUTHOR]

The event runoff coefficient (i.e. the ratio between event runoff and precipitation that originated the runoff) is a key factor for understanding basin response to precipitation events. Runoff coefficient depends on precipitation intensity and duration but also on specific basin geohydrology attributes (including soil type, geology, land cover, topography) and last but not least, antecedent (or pre-storm) conditions (i.e., the amount of water stored in the different hydrological compartments, like the river, groundwater, soil and snowpack). The relation between runoff coefficient and basin pre-storm conditions is critical for flood forecasting, yet, the understanding of where, when and how much basin pre-storm conditions control runoff coefficients is still an open question. Here, we tested the control of basin pre-storm conditions on runoff coefficient for 60620 flood events across 284 basins in Europe. To do so, we derived basin pre-storm conditions from different proxies, namely: antecedent precipitation; surface and root zone soil moisture from hydrological models, reanalyses and land surface models also ingesting satellite observations; pre-storm river discharge, and pre-storm total water storage anomalies. We evaluated the coupling strength between runoff coefficient and pre-storm conditions proxies in relation to five classes of European basins, defined based on land use and soil type (as indexed by the Soil Conservation Service curve number CN), topography, hydrology and long-term climate and tested their ability to explain stormflow volume variability. We found that precipitation explains relatively well the stormflow volumes for both small and large events but not very well the peak discharge, especially for large floods. The runoff coefficient of events shows different distributions for the five different classes and correlates well with deep soil storages (such as root-zone soil moisture and pre-storm total water storage anomalies), pre-storm river discharge, and pre-storm snow water equivalent. Overall, these correlations depend on the class. Poor correlations are found against antecedent precipitation index despite its wide use in the hydrological community. Seasonal and interannual climate variability exert a key role on the coupling strength between runoff coefficient and pre-storm conditions by inducing sharp changes in the correlation with season and climate. These results increase our understanding of the coupling between pre-storm conditions and runoff coefficients. This will aid flood forecasting, hydrological and land surface model calibration, and data assimilation. Furthermore, these findings can help us to better interpret future flood projections in Europe based on expected changes in long and short-term climatic drivers. • Different basin pre-storm proxies explain runoff coefficient variability in Europe • Basin hydrophysioclimatic characteristics control basin pre-storm condition importance • Seasonal and climate variabilities impact basin pre-storm condition importance [ABSTRACT FROM AUTHOR]