The use of global gridded datasets in a hydrological model for a scarce-data Andean watershed

Abstract

Global gridded climatological (GGC) datasets including precipitation, temperature, pressure, and circulation indices, among others are becoming more and more precise, accessible and common in climate and hydrological research. In this study, we evaluate these datasets as an alternative input to supply the lack of measured climatological data in a Chilean Andean watershed in order to develop a monthly water balance model. A conceptual model was carried out for the simulation of stream-flows in the mountainous area of the Polcura River basin in south-central Chile. Based on 18 years of simulation and four model performance assessments, we concluded that from GGC datasets it is possible to reproduce observed flows and the snow-rain regime with "good" performance, being an adequate alternative to supply the lack of measured data, but taking the following considerations i) the GGC rainfall datasets in the Andean area are undervalued; this effect is transferred to the simulated flows, and must be fixed through an amplification coefficient (a calibration parameter), ii) due to the nature of the GGC datasets and to the orographic effect produced by the Andean mountains, the rainfall amounts are damped during the rainy season which result in a sub-estimation of the simulated flows during the winter, and limits the model scope to applications where peak flows are dispensable, and iii) the simulated snow-melt minimum and mean flows are close to the observed flows, which suggest that the GGC datasets are an adequate alternative for estimating the evapotranspiration and snow-melting amounts.