PISCO_HyM_GR2M: A Model of Monthly Water Balance in Peru (1981–2020)

Quantification of the surface water offer is crucial for its management. In Peru, low spatial density hydrometric stations makes this task challenging. This work aims to evaluate hydrological performance a monthly balance model in Peru using precipitation and evapotranspiration data from high-resolution meteorological PISCO dataset, which has been developed by National Service Meteorology Hydrology (SENAMHI). A regionalization approach based on Fourier Amplitude Sensitivity Testing (FAST) rainfall-runoff (RR) runoff variability (RV) indices defined 14 calibration regions nationwide. Next, GR2M was used at semi-distributed scale 3594 sub-basins river streams simulate discharges January 1981 March 2020. Model evaluated Kling–Gupta efficiency (KGE), square root transferred Nash–Sutcliffe (NSEsqrt), error (WBE) metrics. The results show very well representation large portion Peruvian (KGE ≥ 0.75, NSEsqrt 0.65, −0.29 < WBE 0.23). Finally, study introduces product continuous discharge rates named PISCO_HyM_GR2M, understand data-scarce sub-basins.