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By Hugo Melo

Assessing Flood Hydrology In Data Scarce Tropical Regions

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A robust hydrological assessment can be a challenging task in regions where a lack of data, of a sufficient quality, is available to fully validate both hydrological assessments. This level of uncertainty is heightened in studies of flood hydrology for tropical regions, where spatiotemporal variation in rainfall can be significant and the associated timing can be challenging to determine. In 2014, SRK undertook a hydrological assessment as part of a multi-disciplinary Feasibility Study for an open pit phosphate mine situated within the Republic of Congo. Due to the progression of the pit through the main floodplain of the Tchivouba catchment, characterising the flood hydrology in this data scarce region was key to ensuring the accuracy of the resulting water management design.

A bottom up approach was applied, with the baseline hydro-meteorological monitoring network reviewed and improved, establishing a stronger representation of rainfall-runoff response in the area. A detailed review of climatic influences in the region was performed, with remotely sensed TRMM data (Tropical Rainfall Measuring Mission) used to support the analysis. A quasidistributed hydrological model (below) was built using a gridded ModClark transform and SCS-CN loss methodology (Soil Conservation Services - Curve number) to better represent the spatial variability in catchment characteristics influencing runoff processes. The model required developing unique site specific design hyetographs. Uncertainty within the modelling was reduced by validating simulated outputs in response to measured events.

This study highlighted the many issues associated with hydrological analysis in areas with little data, and explored solutions to what is a common problem for many studies in tropical regions. It is by no means a definitive study, however it explored the application and limitations of advanced techniques available for hydrologists working as consultants with limited time and resources, to determine the magnitude, timing and impacts of flooding events.