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The impact of digital elevation model and land use spatial information on Hydrologic Simulation Program-FORTRAN-predicted stream flow and sediment uncertainty

机译:数字高程模型和土地利用空间信息对水文模拟程序(FORTRAN预测的水流和泥沙不确定性)的影响

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摘要

The Hydrologic Simulation Program-FORTRAN (HSPF) model is widely used to develop management strategies for water resources. The spatial resolution of the input data used to parameterize the HSPF model may lead to uncertainty in model outputs. In this study, we evaluated the impact of the spatial resolution of the digital elevation model (DEM) and land use data on uncertainty in HSPF-predicted flow and sediment. The resolution of DEMs can affect stream length, watershed area, and average slope, while the resolution of land use data can influence the distribution of land use information. Results showed that DEMs and land use maps with finer resolutions generated higher flow volumes and sediment loads. There was a non-linear relationship between changes in resolution of the DEM and land use data and changes in the uncertainty of predicted flow and sediment loads. Relative error was used to describe model uncertainty and the probability density function was used to estimate these uncertainties. The best-fit distributions of uncertainty in modeled flow and sediment related to DEM and land use data resolution were the generalized Pareto distribution and the Johnson SB distribution, respectively. The results of this study provide useful information for better understanding and estimating uncertainties in the HSPF model.
机译:水文模拟程序FORTRAN(HSPF)模型被广泛用于开发水资源管理策略。用于参数化HSPF模型的输入数据的空间分辨率可能导致模型输出的不确定性。在这项研究中,我们评估了数字高程模型(DEM)和土地利用数据的空间分辨率对HSPF预测的流量和泥沙不确定性的影响。 DEM的分辨率会影响河流长度,流域面积和平均坡度,而土地利用数据的分辨率会影响土地利用信息的分布。结果表明,DEM和具有更高分辨率的土地利用图产生了更高的流量和沉积物负荷。 DEM分辨率和土地利用数据的变化与预测流量和泥沙负荷的不确定性变化之间存在非线性关系。相对误差用于描述模型不确定性,而概率密度函数用于估计这些不确定性。与DEM和土地利用数据分辨率相关的模拟流量和泥沙不确定性的最佳拟合分布分别是广义Pareto分布和Johnson SB分布。这项研究的结果为更好地理解和评估HSPF模型中的不确定性提供了有用的信息。

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