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Soil erosion prediction for shaping conservation policy and practice.

机译：水土流失预测，以形成保护政策和实践。

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摘要

Scientific evidence guides public policy for improving the management of soil and water resources. With stronger scientific evidence, more informed public policy will lead to desired outcomes. The studies described in this dissertation use the Water Erosion Prediction Project (WEPP) computer model to address two soil erosion modeling issues. First, a statewide analysis of soil erosion in Iowa resulting from different corn stover removal rates is modeled to produce maps of soil erosion risk under various management scenarios. The results indicate that no-till is an effective practice for soil erosion control on sloping soils when maximum amounts of corn stover are removed from the field. However, maintaining adequate levels of soil organic carbon may be more of a constraint for stover harvesting than soil erosion on flat soils. Modifications to the WEPP user interface are needed to simplify soil erosion modeling with corn stover removal and site specific conditions. The second soil erosion modeling issue addressed in this dissertation is uncertainty of soil erosion and sediment load delivery predictions. The paper in Chapter 3 of this dissertation demonstrates a novel stochastic approach for explicitly quantifying prediction uncertainty using WEPP. Uncertainty of sediment load predictions is explicitly calculated using Monte Carlos simulation with stochastic climate variable inputs. Scientists, environmentals and farmers commented in focus group interviews that the stochastic analysis results helped them to better understand the uncertainty of soil erosion and sediment delivery predictions used to design control measures.
机译：科学证据指导公共政策改善土壤和水资源的管理。有了更强大的科学证据，更加明智的公共政策将导致预期的结果。本文所描述的研究使用水蚀预测项目（WEPP）计算机模型来解决两个土壤侵蚀建模问题。首先，对全州因玉米秸秆去除率不同而造成的爱荷华州土壤侵蚀进行了全州分析，以模拟各种管理方案下的土壤侵蚀风险图。结果表明，当从田间移走最大数量的玉米秸秆时，免耕是控制坡地土壤侵蚀的有效方法。然而，保持土壤有机碳的适当水平可能比秸秆在平坦土壤上的侵蚀更受秸秆收获的限制。需要对WEPP用户界面进行修改，以简化去除玉米秸秆和特定地点条件下的土壤侵蚀模型。本文研究的第二个土壤侵蚀模型问题是土壤侵蚀和泥沙输送预测的不确定性。本论文第三章中的论文演示了一种新颖的随机方法，该方法可以使用WEPP明确量化预测不确定性。使用带有随机气候变量输入的蒙特卡洛斯模拟显式计算了沉积物负荷预测的不确定性。科学家，环境人员和农民在焦点小组访谈中评论说，随机分析结果有助于他们更好地理解用于设计控制措施的土壤侵蚀和沉积物输送预测的不确定性。

著录项

  • 作者

    Newman, James Kenneth.;

  • 作者单位

    Iowa State University.;

  • 授予单位 Iowa State University.;
  • 学科 Engineering Agricultural.;Environmental Sciences.
  • 学位 Ph.D.
  • 年度 2010
  • 页码 118 p.
  • 总页数 118
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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