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Evaluating the capabilities of watershed-scale models in estimating sediment yield at field-scale

机译:评价流域尺度模型在田间尺度上估算泥沙产量的能力

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摘要

Many watershed model interfaces have been developed in recent years for predicting field-scale sediment loads. They share the goal of providing data for decisions aimed at improving watershed health and the effectiveness of water quality conservation efforts. The objectives of this study were to: 1) compare three watershed-scale models (Soil and Water Assessment Tool (SWAT), Field_SWAT, and the High Impact Targeting (HIT) model) against calibrated field-scale model (RUSLE2) in estimating sediment yield from 41 randomly selected agricultural fields within the River Raisin watershed; 2) evaluate the statistical significance among models; 3) assess the watershed models' capabilities in identifying areas of concern at the field level; 4) evaluate the reliability of the watershed-scale models for field-scale analysis. The SWAT model produced the most similar estimates to RUSLE2 by providing the closest median and the lowest absolute error in sediment yield predictions, while the HIT model estimates were the worst. Concerning statistically significant differences between models, SWAT was the only model found to be not significantly different from the calibrated RUSLE2 at α = 0.05. Meanwhile, all models were incapable of identifying priorities areas similar to the RUSLE2 model. Overall, SWAT provided the most correct estimates (51%) within the uncertainty bounds of RUSLE2 and is the most reliable among the studied models, while HIT is the least reliable. The results of this study suggest caution should be exercised when using watershed-scale models for field level decision-making, while field specific data is of paramount importance.
机译:近年来,已经开发了许多流域模型接口来预测田间规模的沉积物负荷。他们的共同目标是为旨在改善流域健康和水质保护工作有效性的决策提供数据。这项研究的目的是:1)将三个流域尺度模型(土壤和水评估工具(SWAT),Field_SWAT和高影响目标(HIT)模型)与校正后的尺度模型(RUSLE2)进行比较,以估算沉积物赖辛河流域内随机选择的41个农田的产量; 2)评估模型之间的统计显着性; 3)评估分水岭模型在现场层面确定关注区域的能力; 4)评估分水岭规模模型用于现场规模分析的可靠性。通过在沉积物产量预测中提供最接近的中位数和最低的绝对误差,SWAT模型得出的结果与RUSLE2最相似,而HIT模型的估计则最差。关于模型之间的统计学差异,SWAT是唯一在α= 0.05时与校准的RUSLE2没有显着差异的模型。同时,所有模型都无法识别与RUSLE2模型类似的优先领域。总体而言,SWAT在RUSLE2的不确定性范围内提供了最正确的估计(51%),并且在所研究的模型中是最可靠的,而HIT则最不可靠。这项研究的结果表明,在使用分水岭规模的模型进行田间水平决策时应谨慎行事,而田间特定数据至关重要。

著录项

  • 来源
    《Journal of Environmental Management》 |2013年第30期|228-236|共9页
  • 作者单位

    Department of Biosystems & Agricultural Engineering, Michigan State University, East Lansing, Ml 48824, USA;

    Department of Biosystems & Agricultural Engineering, Farrall Agriculture Engineering Hall, 524 S. Shaw Lane, Room 225, Michigan State University,East Lansing MI 48824, USA;

    Department of Biosystems & Agricultural Engineering, Michigan State University, East Lansing, Ml 48824, USA;

    Department of Biosystems & Agricultural Engineering, Michigan State University, East Lansing, Ml 48824, USA;

    Department of Civil & Environmental Engineering, Michigan State University, East Lansing, MI 48824, USA;

  • 收录信息 美国《科学引文索引》(SCI);美国《化学文摘》(CA);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    SWAT; Field_SWAT; High impact targeting; RUSLE2; Sediment; Field-scale; Models comparison;

    机译:扑打;Field_SWAT;高影响力定位;RUSLE2;沉淀;现场规模型号比较;

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