Exploring Moisture Sources for the Congo River Basin in Space and Time

Precipitationsheds have been defined as the evaporative moisture source regions that eventually fall as precipitation in an area of interest (Keys et. al 2012). Outlining these regions is a vital step in understanding annual, seasonal, and sub-seasonal moisture source regions to better assess effects of land-use and climate change. In this study, researching the Congo River Basin’s precipitationshed provides insight into the land and ocean evaporative origins for the world’s second largest rainforest. This is crucial to understanding when the rainforest relies more heavily on specific regions and how these patterns could influence policy change.

This study utilized the Water Accounting Model 2 Layers (WAM-2layers) for the year of 2018 to analyze spatial and temporal moisture sources for the Congo River Basin. In doing so, seasonal oscillations north-south were observed for both precipitation and their evaporation sources. From here, the total evaporation sources for the year were plotted in absolute and relative amounts, identifying hotspots of annual moisture. Notably, it was found that this region is substantially dependent on terrestrial sources throughout the year, and particularly of interest were the levels of self-dependency for the year. This study observed that between 22-36% of the basin’s precipitation each month came from its own evaporation, strikingly peaking in the dry season. An exploratory approach in this project began to qualitatively link evaporation spikes to precipitation spikes, then using satellite images to identify the evaporative hotspots. The desire here was to link the WAM-2layers products to observable phenomena in the atmosphere leading to larger precipitation events, and for future research to dive deeper into the dynamics at hand. This study confirmed the Congo River Basin’s notable dependency on itself to provide moisture on an annual scale, particularly in seasons with less available moisture. Future research could investigate how projected deforestation levels may impact this terrestrial dependency.