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Modeling infiltration using time-to-ponding and a storm generator approach.

机译:使用响应时间和风暴生成器方法对渗透进行建模。

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摘要

Soil productivity is largely determined by the biological, physical, and chemical properties and processes in concert with climate and resource management inputs. Mathematical or physical models are effective for describing the influences of soil erosion and management systems on long-term productivity. Research on developing and applying a functional model of infiltration into a soil profile under rainfall or irrigation conditions is important in both hydrology and agriculture. To provide a rational basis for infiltration prediction during rainfall or irrigation, a nonlinear model was used in this study to calculate cumulative infiltration based on time-to-ponding approach. The cumulative infiltration amount at ponding is a function of water application rate, saturated conductivity, saturated soil water content, antecedent soil water content, and macroscopic capillary length. Soil management practices such as crop types, tillage methods and surface residue cover also influence soil properties and infiltration capacity.; To make this infiltration model functional for strategic applications where it is difficult to obtain or use short-period rainfall data, a relatively simple storm generator was used to generate daily precipitation and to disaggregate it into a discrete number of storms of varying intensity patterns. The generated outcome distribution of rainfall was used as input to the physically based time-to-ponding model.; A field study was conducted on a loamy sand (Eutric Glossoboralf) soil in Michigan with corn and potatoes under various tillage, surface residue, and wheel traffic conditions to determine values of the soil properties needed for the infiltration model. Time-to-ponding was observed for various water application rates using a sprinkling infiltrometer under a variety of soil management situations. Time to ponding curves were established for each management combination of crop, tillage and wheel traffic conditions.; The time-to-ponding approach appears to be a good infiltration predictor under complex rainfall patterns and different soil management conditions. Using the ponding curves, with known soil hydraulic properties, the point source (or localized) runoff are predictable under any type of rainfall or irrigation patterns. This point source runoff is a critical input for the assessment of water erosion.
机译:土壤生产力在很大程度上取决于生物学,物理和化学特性以及与气候和资源管理投入相一致的过程。数学或物理模型对于描述土壤侵蚀和管理系统对长期生产力的影响是有效的。在降雨或灌溉条件下,开发并应用渗入土壤剖面的功能模型的研究在水文和农业方面均十分重要。为了为降雨或灌溉过程中的入渗量预测提供合理的基础,本研究使用非线性模型基于时间响应方法计算累积入渗量。积水时的累积入渗量是施水量,饱和电导率,饱和土壤含水量,前期土壤含水量和宏观毛细管长度的函数。诸如作物类型,耕作方法和地表残留物覆盖等土壤管理措施也会影响土壤特性和渗透能力。为了使该渗透模型在难以获取或使用短期降雨数据的战略应用中起作用,使用了一个相对简单的风暴发生器来产生日降水量并将其分解为不同强度模式的离散风暴。降雨产生的结果分布被用作基于物理的响应时间模型的输入。在密歇根州的玉米,马铃薯在各种耕作,地表残渣和轮流条件下,对玉米和马铃薯的壤土(Eutric Glossoboralf)土壤进行了野外研究,以确定入渗模型所需的土壤特性值。在各种土壤管理情况下,使用洒水式渗透计观察到各种水施用量的响应时间。为作物,耕作和轮式交通状况的每种管理组合确定了思考时间。在复杂的降雨模式和不同的土壤管理条件下,响应时间方法似乎是很好的入渗预测指标。使用具有已知土壤水力特性的积水曲线,可以在任何类型的降雨或灌溉模式下预测点源(或局部)径流。该点源径流是评估水蚀的关键输入。

著录项

  • 作者

    Chou, Tien-Yin.;

  • 作者单位

    Michigan State University.;

  • 授予单位 Michigan State University.;
  • 学科 Hydrology.; Agriculture Soil Science.; Engineering Agricultural.
  • 学位 Ph.D.
  • 年度 1990
  • 页码 186 p.
  • 总页数 186
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 水文科学(水界物理学);土壤学;农业工程;
  • 关键词

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