A Stochastic Approach for Detecting Catchment Characteristics and Anthropogenic Impacts in the Congo River Basin

Global climate change on the hydrological regime of the Congo River Basin can have impacts on water resource management and planning in the Democratic Republic of Congo (DRC). Meanwhile, the catchment itself changes due to anthropogenic influences. However, it is not easy to prove the link between the hydrology and the forcing. In this context, it might be meaningful to detect the temporal changes of catchments independent from climate change by investigating existing long-term discharge records. This study investigates the anthropogenic impacts on the catchment characteristic independent of the climate change in the Congo River Basin. For this purpose, a stochastic system based on copulas for time series analysis is used. That statistical tool scrutinized the dependence structure of the data and, thus, attributed the catchment behavior by focusing on two statistics aspects:

(1) copula asymmetry, which can capture the nonsymmetric property of discharge data, differs from one catchment to another due to the intrinsic nature of both runoff and catchment;

and (2) copula distances can assist in identifying catchment change by revealing the variability and interdependency of dependence structures.

These measures were calculated for 100 years of daily discharges for the Congo River and these analyses detected epochs of change in the flow sequences