Estimating future daily pan evaporation for Qatar using the Hargreaves model and statistically downscaled global climate model projections under RCP climate change scenarios

Evaporation plays a significant role in the hydrologic cycle, and thus the estimation of evaporative demand is crucial for water resources management and irrigation scheduling. Evaporation is subjected to the effects of global climate change, which can be quantified by the representative concentration pathway (RCP) scenarios. However, forecasts of future daily pan evaporation under RCP climate change scenarios using a temperature-based pan evaporation model and downscaled temperature forecasts for an arid region (e.g., Qatar) have rarely been reported in the literature. The present study provides estimations of future daily pan evaporation in Qatar under four RCP climate change scenarios for the period January 1, 2018 to December 31, 2050. Modelled maximum and minimum daily temperature data from a general circulation model (GCM) within the Coupled Model Intercomparison Project Phase 5 (CMIP5) experimental framework are extracted and downscaled using the Quantiles-matching approach. A pan evaporation model coupling the Hargreaves potential evapotranspiration model and a Class A pan coefficient model is calibrated against observed pan evaporation data and utilized to estimate future daily pan evaporation in the study area using downscaled daily temperature. Various measures of fit are employed to evaluate the performance of the downscaling approach and pan evaporation model, and the results show that the performance of the downscaling approach and pan evaporation method are both satisfactory. The study also finds that the pan evaporation increased fastest under the RCP60 scenario, and the average increase in pan evaporation was roughly 0.01095 mm/day per year. The study provides datasets for future pan evaporation for the period between 2018 and 2050 that can be useful for the development of numerical hydrologic models, management of water resources, and irrigation scheduling.