Abstract

The hydrology and ecology of hosts, vectors, and parasites combine to determine how aquatic diseases spread, with the long-term absence of water serving as a strict lower constraint. However, the relationship between spatio-temporal patterns of hydrological ephemerality and the spread of waterborne diseases is unclear and challenging to explain. To describe, categorise, and predict river network ephemerality in a spatially explicit framework, it is consequently necessary to use restricted biophysical and hydroclimate data from places with otherwise sparse data. Here, we create a brand-new method for classifying and predicting large-scale ephemerality that is applicable to epidemiology, maintains a mechanistic connection to catchment hydrologic processes, and is based on monthly discharge data, water and energy availability, and remote-sensing measures of vegetation. In particular, in light of the background of we extract a useful collection of catchment covariates from Burkina Faso in sub-Saharan Africa, including the aridity index, Budyko framework annual runoff estimation, and hysteretical relationships between precipitation and vegetation.