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蒸散发是农业、气象、水文科学研究的重要参数,是全球水文循环过程的重要组成部分.本文应用改进的DHSVM分布式水文模型,利用光学遥感TM数据反演得到叶面积指数等地表数据,由数字高程模型求得坡度、坡向等地形指数因子,定量估算塔河地区2007年逐日蒸散发.应用BP神经网络建立逐日蒸散发量与逐日径流出口流量的关系,并建立研究区水量平衡方程,共同检验研究结果的准确性.结果表明:该模型可以较好地应用于本研究区.塔河流域年总蒸散量234.01 mm,蒸散发与季节有明显的相关性,夏季蒸散发值最高,日均蒸散发值1.56 mm,秋季、春季日均蒸散发值分别为0.30、0.29 mm,冬季蒸散发值最低.地表覆盖类型对蒸散发值影响明显,阔叶林的蒸散发能力强于针阔混交林,其次为针叶林.
The evapotranspiration is an important parameter of agricultural, meteorological and hydrological research and an important component of the global hydrological cycle.In this paper, an improved DHSVM distributed hydrological model was used to retrieve surface data such as leaf area index The digital elevation model was used to obtain the topographic index factors such as slope and aspect to quantitatively estimate the daily evapotranspiration in Tahe area in 2007. Application of BP neural network to establish the relationship between daily evapotranspiration and daily runoff outlet flow and to establish the water balance equation, The results show that this model can be applied to the study area well.The total annual evapotranspiration in the Tarim River Basin is 234.01 mm, there is a clear correlation between evapotranspiration and seasons, and the summer evapotranspiration value is the highest The average evapotranspiration values were 1.56 mm in autumn and spring, respectively, and the values of evapotranspiration were 0.30,0.29 mm in winter and lowest in winter respectively.The types of surface cover had significant effects on evapotranspiration, Forest, followed by coniferous forest.