论文部分内容阅读
基于HIMS（Hydro-Informatic Modeling System）,构建了黑河上游山区的分布式水文模型,取得了较高的模拟与验证精度,并在不同的气候变化情景下模拟分析黑河上游山区莺落峡水文站径流,结果表明：①HIMS在黑河上游山区具有适应性,日过程模型率定期和验证期Nash-Suttcliffe效率系数均达0.80,月过程模型率定期和验证期均高达0.97;②莺落峡站年径流量与气温呈负相关关系,与降水量呈正相关关系,气温升高和降水量减少都会减少年径流量;③降水不变情景下,气温对不同月份径流量影响不同,气温降低2℃时会加剧径流年内分配不均的程度;而在气温不变的情景下,月径流量均随降水增加而增加,但径流量年内分配格局未受到降水变化的显著影响;④不同气候变化情景下年径流量差异明显,对年径流量最不利的气候变化情景是气温升高2℃,降水减少20%;最有利的情景是气温降低1℃,降水增加20%。“,”The Heihe River Basin is the second largest inland basin in China’s northwest arid region and is suffering from a number of severe water-related environmental problems because of drought, water shortages, global climate change and human activity. These problems are now constraining economic and social sustainable development. This paper constructed a distributed hydrological model based on the Hydro-Informatic Modeling System. The model achieved high accuracy during both simulation and verification. We simulated runoff for the Yingluo Valley hydrological station in the upper reaches of the Heihe River Basin under different climate change scenarios to quantitatively analyze the impact of future precipitation and temperature change on runoff. These data show that the a distributed hydrological model of the upper Heihe River based on the Hydro-Informatic Modeling System is suitable; both calibration and validation period Nash-Suttcliffe efficiency coefficient of day process model reached 0.80; both calibration and validation period Nash-Suttcliffe efficiency coefficient of month process model reached as high as 0.97. Annual runoff of the Yingluo Valley hydrological station and temperature were negativly correlated. Rising temperature causes earlier snowmelt time and increased evaporation. Annual runoff and precipitation were positively correlate, because precipitation is the direct source of runoff. If the amount of precipitation is constant, temperature influences runoff differently in different months because of temperature’s double effect on snowmelt time and evaporation. A temperature decrease of 2 ℃ will exacerbate the situation of the unequal distribution of runoff in one year. If the temperature is constant, monthly runoff will increase with increasing precipitation; but precipitation has little influence on runoff distribution patterns over one year. Annual runoff differences are obvious under different climate change scenarios. A temperature rise of 2 ℃ and precipitation fall by 20% is the most unfavorable condition for annual runoff. The most advantageous situation is that temperature falls 1 ℃ and at the same time precipitation increases 20%.