STREAMFLOW PREDICTION BASED ON DATA-SCARCE RIVER-AQUIFER DYNAMICS ESTIMATED BY A SIMPLIFIED MODELLING FRAMEWORK IN A DRYLAND CATCHMENT

Código

XXVI-SBRH0322

Autores

ARTHUR TONÉ, Alexandre Cunha Costa, Mário Ubirajara Gonçalves Barros, IRAN EDUARDO LIMA NETO

Tema

F - Processos Hidrológicos e Monitoramento Integrado de Recursos Hídricos

Resumo

Water security relies on accurately representing hydrological processes in river-aquifer dynamics, including aquifer recharge driven by rainfall, hyporheic flow, and lateral tributary inflows. River?aquifer studies often overlook these processes, however. Using a parsimonious numerical model, we accurately calculated these processes in a data-scarce region, at scales relevant to water management. This model was developed based on a conceptual model of river-aquifer dynamics in dryland regions. The numerical model's performance measures (Kling-Gupta efficiency, Nash? Sutcliffe efficiency, and percent bias) showed that it effectively estimated river and groundwater flow using a simple modeling approach, requiring only minimal calibration (three parameters). Notably, the data required for the model are often available in regions with scarce data availability. Hyporheic flow is crucial for the water balance in dryland rivers. In contrast, subcatchment runoff demonstrated minimal influence compared to inflow and groundwater fluxes, suggesting a greater dependence on river volume and stage than on intraseasonal rainfall. This study provides valuable tools for similar areas that require viable management solutions to be developed.