Mosquito-borne diseases like Rift Valley Fever and Malaria that cause serious health threat to human and livestock populations are known to correlate with the tremendous increase of associated mosquito vectors following periods of widespread and heavy rainfall. In the Barkedji area, Senegal, rainfall occur only during the July–October wet season, and mosquito breeding sites are provided by relatively small temporary ponds, which account for the vast majority of the water surfaces during the rainy season. Given that rain fed ponds play a key role in the epidemiology of the mosquito-borne diseases, we have developed an approach allowing to model the flooding/drying dynamics of rain fed ponds in the Barkedji area by combining the detection of ponds using optical remote sensing techniques, field data on a small set of monitored ponds and modeling of both the pond profile, shapes and the flooding/drying dynamics at the single-pond level for each pond in the entire region.As a result, we have computed on output the daily flooding/drying dynamics for each of the 1345 rain fed ponds detected in Barkedji area as a function of the daily rainfall in input. As dry and fluctuating ponds are less productive in mosquitoes, the ponds are characterizes in terms of flooding-drying fluctuations and of resistance to dryness by computing the total number of time per year a pond dries out and the pond lifetime, respectively. And, clusters of ponds with identical behavior, i.e., clusters of temporary, semi-permanent and permanent ponds, were subsequently identified.As a perspective, we show how this work can be used for modelling mosquito population dynamics and addressing the issues of associated impacts of climate change.