Scientific and operational value of alternative datasets in hydrological science

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Applied hydrological science strongly relies on hydrometeorological information, and especially on measurements of precipitation end temperature. However, time series of relevant hydrometeorological variables are plagued with problems such as short temporal horizons, missing data, errors, and various biases. This limits, sometimes severely, the ability to adequately represent the spatial and temporal variability of the hydrological processes at the basin scale. New datasets have been proposed to palliate the lack of direct observations and the less than optimal coverage in time and space. Available datasets consists of the traditional station-based data and of three alternative datasets: gridded datasets, reanalyses of observations and dynamically generated data. The scientists and industrial partners involved in this project propose to: Investigate the scientific and operational value of alternative datasets in hydrological science. More precisely, this project intends to address the following specific objectives: