Assessing the accuracy of SM2RAIN (Soil Moisture to Rainfall) products in poorly gauged countries: the case of Burkina Faso in the West African Sahel.

Effects of climate change and variability in West African countries are heightening the vulnerability of local populations, which heavily rely on agriculture and natural resources through ecosystem services. Developing effective water management strategies for mitigation of these impacts requires knowledge of weather, especially rainfall, built upon continuous long-term records (in both time and space). Yet, most West African countries are poorly gauged, with a low density of reliable gauging stations, hampering applications such as water planning and weather forecasting. Recently, some daily global precipitation products have been developed, providing rainfall estimates derived from soil moisture observations using the innovative SM2RAIN (Soil Moisture to Rain) bottom-up inversion algorithm, hence treating the soil as a natural rain gauge. Since these products are gridded, they also provide continuous spatial information regarding rainfall. In this study, the accuracy of such three typical SM2RAIN products (SM2RAIN-CCI, GPM+SM2RAIN, SM2RAIN-ASCAT) at depicting rainfall estimates in Burkina Faso (West Africa, area of 272,200 km²) at 10 synoptic stations over the period 2007-2017 (9 years), at the daily, dekadal (10-days accumulation), monthly and annual timescales. The results reveal that at the daily timescale, all products performance is poor to moderate (KGE: 0.18 to 0.36). At higher time scales, however, both products performed satisfactorily to very good (dekadal: KGE: 0.61 to 0.79; monthly: KGE: 0.63 to 0.91; annual: KGE: 0.44 to 0.81), with SM2RAIN-CCI being consistently superior. Overall, SM2RAIN-CCI presented the lowest volumetric hit and miss bias at all stations, whereas SM2RAIN-GPM presented the lowest false bias. Also, SM2RAIN-CCI featured the highest ability at picturing the timing of occurrence of daily rainfall events (probability of detection, false alarm ratio, threat score) for various thresholds in the range of 0 to 25 mm. Finally, the ability of these products at picturing observed rainfall extremes have been evaluated through various ETCCDI climate indices, at which SM2RAIN-CCI and SM2RAIN-GPM presented equal performance, SM2RAIN-ASCAT being less good. These results provide a quantitative assessment of the SM2RAIN approach in the context of Burkina Faso and might help in the selection of an optimal product for further applications.

Keywords: ASCAT, Burkina Faso, CCI, GPM, rainfall, Sahel, SM2RAIN.