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This study consisted to land cover datasets evaluation and prediction, detection of climate change via trend analysis on the hydro-climatic datasets and hydrological modeling using different models over two baseline periods in the Mono River basin in West Africa. The results revealed CILSS data set as the most accurate with increase of cropland and decrease of savanna and forest whereas significant positive and negative trends were detected on hydro-climatic datasets. The hydrological modeling outputs showed discharge predictions with good evaluation efficiencies over pre-dam period (1964 – 1986) and more and less acceptable during post-dam period (1988-2010). Finally, water balance components spatio-temporal variation depended on land-use type change, climate conditions and to the reservoir.

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