Multiscale assessments of hydroclimatic modelling uncertainties under a changing climate

Abstract

Since the 1970s, climate change has led to decreasing water resources in the Sahel. To cope with climate change, reliable modelling of future hydroclimatic evolutions is required. This study uses multiclimate and hydrological modelling approaches to access past and future (1951–2100) hydroclimatic trends on nine headwater catchments of the Niger River Basin. Eight global climate models (GCMs) dynamically downscaled under the CORDEX CMIP5 project were used. The GCM data were bias-corrected with quantile–quantile mapping. Three rainfall–runoff models (IHACRES-CMD, IHACRES-CWI and Sacramento) were calibrated and validated with observed data and used to simulate runoff. The projected future runoff trend from 2061 to 2090 was compared across the three hydrological models to assess uncertainties from hydrological models. Results show that the bias correction positively enhanced the quality of eight GCMs across the nine catchments. An average Nash–Sutcliffe Efficiency (NSE) across the nine catchments was improved from 0.53 to 0.68 and the Kling–Gupta Efficiency (KGE) was enhanced from 0.65 to 0.83. The three hydrological models were calibrated and validated appropriately on the nine catchments. Despite this, high hydrological modelling uncertainties were witnessed with contrasting projected future runoff patterns by the three models. We recommended the use of ensembles of both climate and hydrological models to provide reliable hydroclimatic modelling. HIGHLIGHTS CMIP5 hydroclimatic projections are accrued with biases on the Niger Basin.; Quantile mapping corrected biases in the climate projections.; IHACRES-CWI, IHACRES-CMD and Sacramento hydrological models simulate runoff with high accuracies.; Future runoff patterns on the Niger Basin are highly uncertain.; Ensembles of both climate and hydrological models were recommended for future hydroclimatic projections.;

Keywords

• climate change
• ensembles
• hydrology
• runoff
• uncertainty