Abstract
<abstract> <bold><sc>Abstract.</sc></bold> The transmission of malaria via infected mosquitoes is a biological/ecological system affected by hydrologic variability. In the Sahel of Africa, where malaria vector mosquitoes breed in shallow, temporary pools, topography is a significant environmental factor in the formation and persistence of the breeding habitat. Such breeding pools are commonly several meters to tens of meters in size and host the vast majority of malaria vector mosquitoes. Therefore, high-resolution topography is necessary in order to model breeding habitat productivity mechanistically. This study investigates the role of topography in pool persistence and productivity, and the utility of remote sensing of high-resolution topography for simulating mosquito breeding. Combinations of various synthetic topographic configurations and rainfall scenarios are simulated using a coupled hydrology and entomology model to assess the role of pool catchment size in combination with rainfall variables as a predictor of pool productivity. Rainfall intensity has the strongest influence on pool persistence when compared to duration and frequency. A threshold rainfall frequency exists for a given topographic configuration in order for the pool to persist longer than the development time of larvae and thus for the pool to be productive. In addition, synthetic aperture radar was used to generate high-resolution topography for application in hydrologic and entomology modeling. A digital elevation model generated with radar interferometry does not have enough vertical accuracy (RMS error = 7.7 m) to simulate pools that are tens of meters across and centimeters deep. We conclude that repeat-pass interferometry using two radar images is not a viable method to acquire topography to model pools or confidently delineate pool catchment areas. Additional research is needed to further explore the potential of remote sensing, particularly interferometric methods, as a tool in predicting topographic influences of malaria risk at a high spatial resolution.
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