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Evaluation of spatial and temporal variability of snow cover in a large mountainous basin in Iran

机译:伊朗大山区流域积雪的时空变化评估

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Determination of snow characteristics in mountainous basins is difficult due to the complex spatial and temporal variability of snow cover. Accurate representation of snow cover variations in space and time is an important factor in snowmelt modeling, hydrological forecasts, water resources planning, and drought management. This study demonstrates how remotely sensed data can complement the measurements of ground hydro-meteorological data to simulate the spatial and temporal variations of snow cover characteristics in a mountainous basin. In this paper, we studied Karun basin, located in the south west of Iran, because of its importance in accumulating large snow reserves, and subsequently contributing snowmelt to the total runoff. Snow cover variability was simulated by extraction of maps of snow cover indices using remotely sensed data. Contribution of snowmelt to the runoff was determined using a seasonal water balance model as well as estimations based on indirect approaches by modeling variables such as critical temperature, which is an important variable in snow studies. Agreement between indirect approaches used in this paper is an encouraging result that shows the reliability of the procedure where snow data is scarce. The results of correlation analysis between topographic and meteorological variables with snow cover indices suggested that elevation is the single most important variable on large-scale snow variability.
机译:由于积雪的时空复杂性,很难确定山区的积雪特征。积雪的时空变化的准确表示是融雪模型,水文预报,水资源规划和干旱管理中的重要因素。这项研究表明,遥感数据如何补充地面水文气象数据的测量,以模拟山区流域积雪特征的时空变化。在本文中,我们研究了位于伊朗西南部的卡伦盆地,因为它在积聚大量积雪中起着重要的作用,并随后将融雪促进了总径流量。通过使用遥感数据提取积雪指数图来模拟积雪变异性。使用季节性水平衡模型以及基于间接方法的估算来确定融雪对径流的贡献,该估算是通过对诸如临界温度等变量进行建模,而临界温度是雪研究中的重要变量。本文使用的间接方法之间的一致性是一个令人鼓舞的结果,表明了在积雪数据稀缺的情况下该程序的可靠性。积雪指数与地形和气象变量之间的相关性分析结果表明,海拔高度是大规模积雪变异性中最重要的单个变量。

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