气候变暖影响下黄河源区潜在蒸发量预测不确定性研究

Study on the Uncertainty of Predicting Potential Evaporation in the Source Regions of the Yellow River Under the Influence of Climate Warming

蒸发是连接地表能量平衡和水量平衡的重要纽带,高寒区蒸发量对气候变暖尤为敏感。然而,高寒区蒸发预测存在大量不确定因素,其造成流域水文循环变化规律分析、水资源管理面临严峻挑战。因此,以属于高寒区的黄河源区为例,利用5种物理机制不同的蒸发计算模型(P-M、Har、J-H、Mak和P-T)理清模型不确定性对流域潜在蒸发量预测结果的影响;通过耦合蒸发计算模型、GCMs模型、RCPs模型,探究多源不确定性对未来不同时期(近期、中期和远期)潜在蒸发量预测结果不确定性的影响,并利用方差分析方法量化评估各因素独立及交互作用对潜在蒸发量预测结果不确定性的贡献。结果表明:基于太阳辐射和气温的潜在蒸发量模型获得的潜在蒸发量明显大于基于物理机制P-M模型获得的潜在蒸发量,其差值约为150 mm;RCPs不确定性是导致蒸发预测结果不确定性的主导因素,占比高达65%,且多种不确定性因素的交互作用对蒸发预测结果不确定性的贡献在春、冬季节尤为突出。

Evaporation is an essential link between surface energy balance and water balance,and high-cold regions are sensitive to climate change.However,there is a large amount of uncertainty in the evaporation prediction process in the high-cold areas,which poses severe challenges to scientifically analyzing the hydrological cycle changes and water resources management in river basins.Therefore,taking the source area of the Yellow River in the“high-cold region”as an example,this paper used five evaporation calculation models with different physical mechanisms(P-M,Har,J-H,Mak and P-T)to clarify the impact of model uncertainty on the prediction of potential evaporation in the basin.Secondly,by coupling the“evaporation calculation model,GCMs and RCPs”model,the impact of various uncertainties on the uncertainty of potential evaporation prediction in different future periods(short-term,medium-term,and long-term)was explored.The contribution of their independent and interactive effects to the uncertainty of potential evaporation prediction was separated using the variance analysis method.The results show that the potential evaporation model based on solar radiation and temperature is significantly greater than the potential evaporation model based on physical mechanism,and its annual potential evaporation difference is about 150 mm.The uncertainty of RCPs is the main factor leading to the uncertainty of evaporation prediction,accounting for about 65%,and the contribution of the interaction between multiple uncertainty sources to the uncertainty of evaporation prediction is particularly prominent in the“spring and winter”seasons.