模拟流域沉积物图谱的新方法

IF 4.3 3区 材料科学 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC
Azadeh Katebikord , Seyed Hamidreza Sadeghi , Vijay P. Singh
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引用次数: 0

摘要

土壤流失管理需要可靠的数据来评估流域的普遍状况。悬浮泥沙浓度(SSC)是土壤流失的指标之一,其数据和相关特性对于流域综合管理至关重要。然而,迄今为止,利用测量数据估算流域尺度上悬浮泥沙浓度的时间变化(即沉积物图(SG))的实用方法还较少受到关注。因此,本研究计划通过对土壤侵蚀过程和泥沙产量进行概念建模来模拟 SG。伊朗西阿塞拜疆省的 Galazchai 流域被选为案例研究对象。为此,首先使用河道纵向剖面图和空间分布旅行时间两种方法绘制了等距直方图。使用修订的通用土壤流失方程 (RUSLE),采用集合和单元自动机方法计算每个等时线段的土壤侵蚀量。随后,使用哈德利方法、WaTEM/SEDEM 方法和新近修改的美国林务局方法对等时线之间的土壤侵蚀进行了路由。最后一种方法是根据当前研究的七个标准化变量开发的。合成 SG 最终由 12 种不同的研究方法组合而成。利用几年来收集的 38 个暴雨事件对建模性能进行了评估。利用相对误差对模拟 SG 和观测 SG 的基准时间、达到峰值的时间、峰值和总沉积物负荷进行了评估。根据评价指标进行的比较表明,空间分布旅行时间法、蜂窝自动机法和修改后的美国林务局法的组合性能更好,在校准和验证阶段的效率系数和归一化效率系数分别为-1.16 至 0.99 和 0.32 至 0.99。然而,没有一个模型能够令人满意地模拟整个沉积物图形。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A new approach to simulate watershed sediment graphs

Soil loss management requires reliable data for assessing the conditions prevailing in a watershed. Suspended sediment concentration (SSC) is one of the indicators of soil loss, and its data and associated properties are essential for integrated watershed management. However, until now, practical methods for estimating the temporal variation of SSC at the watershed scale, i.e., a sediment graph (SG), using measured data have been given less attention. Therefore, the current study was planned to simulate the SG through conceptual modeling of the soil erosion process and sediment yield. The Galazchai Watershed in West Azerbaijan Province, Iran, was selected as a case study. In this regard, the isochrone histograms were initially prepared using two methods of the longitudinal channel profile and spatially distributed travel time. Soil erosion was calculated in each isochrone segment using the Revised Universal Soil Loss Equation (RUSLE), applying the lumped and cellular automata approach. The soil erosion between isochrones was subsequently routed using the Hadley, WaTEM/SEDEM, and newly modified U.S. Forest Service methods. The last method was developed based on seven standardized variables for the current research. Synthetic SGs were ultimately derived from 12 different combinations of the study methods. The modeling performance was assessed using 38 storm events collected over several years. The base time, time to peak, peak value, and total sediment load of the simulated and observed SGs were evaluated using relative error. Comparison based on the evaluation indicators indicated better performance of the combination of the spatially distributed travel time method, cellular automata, and modified U.S. Forest Service method with the coefficient of efficiency and the normalized coefficient of efficiency varying from −1.16 to 0.99 and from 0.32 to 0.99 for the calibration and validation stages, respectively. However, none of the models were simulating satisfactorily the entire sediment graphs.

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来源期刊
CiteScore
7.20
自引率
4.30%
发文量
567
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