A hybrid mathematical model for estimation of runoff uncertainty influenced by climate drivers

Quantifying the runoff uncertainty influenced by the climate drivers is essential for water resources management. Runoff in the Tarim River Basin (TRB) originated from the ice and snow meltwater is, thus, sensitive to climate change due to its inherent uncertainties. In this paper, a hybrid mathematical model for uncertainty estimation combing the water-heat coupling model, sensitivity coefficient, uncertainty measurement indices, and an improving standard uncertainty method was proposed to quantify the runoff uncertainty influenced by climate drivers in the TRB from 1965 to 2015. The results showed that the runoff uncertainty in the TRB varies at different time scales and bears strong uncertainty in summer and autumn. In addition, runoff is sensitive to climate change, and when the annual precipitation, annual average temperature, and annual potential evapotranspiration factors change by 1%, the annual runoff changes by 2.8857%, 1.6559%, and −1.8857%, respectively, while the contribution rate of temperature to runoff changes gradually increases. When the changes in precipitation and temperature have the fluctuation uncertainties of 5.76–6.96% and 22.26–66.72%, the runoff fluctuation uncertainties influenced by climate drivers in the Hotan River Basin, Yarkand River Basin, Aksu River Basin, and Kaikong River Basin are 14.31%, 15.03%, 18.23%, and 5.93%, respectively. The proposed hybrid mathematical model can provide a quantitative analysis reference for the runoff uncertainty under climate change in inland river basins in the arid region of Northwest China.