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Spatial Scale Resolution of Prognostic Hydrological Models: Simulation Performance and Application in Climate Change Impact Assessment

机译:水文预报模型的空间尺度分辨率:模拟性能及其在气候变化影响评估中的应用

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In this paper, long-term hydrological response of a watershed to climate change was investigated taking into account the spatial scale effect on the performance of hydrological models. A water balance model was used in which variations of soil moisture, snow budget, deep infiltration and interactions with groundwater resources were modeled. Four various combinations of sub-catchment delineation, altitudinal discretization and division into square-shaped grids were tested for semi-distributed water balance modeling of a basin located in southwest of Iran, namely Roodzard Basin, with arid and semiarid climate based on Koppen-Geiger climate classification. The results showed improvement in the model performances when spatial variations of the meteorological data and topographic characteristics of the basin were incorporated in the modeling process. The effects of spatial scale resolution dependency were evaluated in projecting streamflow for various climate change scenarios. The results showed that finer resolution of grid cells in the semi-distributed model does not necessarily result in more accurate estimation of monthly streamflows and altitudinal discretization provides almost same accuracy as the results of grid-based models. Moreover, probability distribution of projections obtained from water balance models for A2 and B2 of Special Report on Emissions Scenarios (SRES) scenarios presented less coefficient of variation and skewness compared with historical observations.
机译:本文考虑了空间尺度对水文模型性能的影响,研究了流域对气候变化的长期水文响应。使用水平衡模型,对土壤湿度,降雪预算,深层渗透以及与地下水资源的相互作用进行建模。对子集水区划定,高度离散和划分为方形网格的四种不同组合进行了测试,以对伊朗西南部的一个盆地(即Roodzard盆地)的半分布式水平衡模型进行建模,该干旱和半干旱气候基于Koppen-Geiger气候分类。当在建模过程中纳入气象数据的空间变化和盆地的地形特征时,结果表明模型性能得到了改善。在各种气候变化情景的预测流量中,评估了空间尺度分辨率依赖性的影响。结果表明,在半分布式模型中,网格单元的更精细分辨率不一定会导致对每月流量的更准确估计,并且高度离散化提供的精度几乎与基于网格的模型相同。此外,从排放情景特别报告(SRES)情景A2和B2的水平衡模型获得的预测的概率分布与历史观测值相比,呈现出较小的变异系数和偏度。

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