Comparing Meteorological Data Sets in the Evaluation of Climate Change Impact on Hydrological Indicators: A Case Study on a Mexican Basin

Abstract

This study evaluates the choice of the meteorological data set in the simulation of the streamflow of a Mexican basin, in the bias correction of climate simulations, and in the climate change impact on hydrological indicators. The selected meteorological data sets come from stations, two interpolated data sets and one reanalysis data set. The climate simulations were taken from the five-member ensemble from the second generation Canadian Earth System Model (CanESM2) under two representative concentration pathways (RCPs), for a reference period (1981–2000) and two future periods (2041–2060 and 2081–2100). The selected lumped hydrological model is GR4J, which is a daily lumped four-parameter rainfall-runoff model. Firstly, the results show that GR4J can be calibrated and validated with the meteorological data sets to simulate daily streamflow; however, the hydrological model leads to different hydrological responses for the basin. Secondly, the bias correction procedure obtains a similar relative climate change signal for the variables, but the magnitude of the signal strongly varies with the source of meteorological data. Finally, the climate change impact on hydrological indicators also varies depending on the meteorological data source, thus, for the overall mean flow, this uncertainty is greater than the uncertainty related to the natural variability. On the other hand, mixed results were found for high flows. All in all, the selection of meteorological data source should be taken into account in the evaluation of climate change impact on water resources.