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Curve Number Estimation Accuracy on Disturbed and Undisturbed Soils

机译:受扰动土与未扰动土的曲线数估计精度

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摘要

Estimates of the USDA-NRCS runoff curve number (CN) are generally based on a soil map and observed land cover. Because the CN method is increasingly applied to disturbed and urbanized land, the objective of this work was to collect effective saturated hydraulic conductivities, K_(sat), and sorptivities, S_o, from a range of land use types, use the results to estimate a CN, and compare these CNs with CN estimates made from soil survey information and corresponding land cover. A total of 331 double ring infiltration tests were conducted over the 15 sites. Based on land use and site history, the test sites were classified into categories of engineered, urban altered, rural altered, rural unaltered, and prairie. Measured K_(sat) values were skewed so the medians of these data were a better predictor of central tendency. The prairie and rural unaltered median K_(sat) values were closer to soil map estimates than the other categories (between 0.0 and 91% different from soil survey). Two empirical methods developed in Hawaii using sprinkle infiltration tests were used to estimate CN values from infiltration data; method 1 used only K_(sat) as the predictor and method 2 used K_(sat) and S_o. Results from these two methods were not statistically different at 12 of the 15 sites (α = 0.05). When comparing these methods to CN values developed from soils data and land cover (method 3), better overall agreement existed between method 1 and method 3. The median CN value from method 1 was the best predictor for the mean CN based on measured runoff data for an urban altered land use site (0.6% different), whereas method 3 was the best predictor for the mean CN based on measured runoff data for a prairie land use (0.0% different).
机译:USDA-NRCS径流曲线数(CN)的估算通常基于土壤图和观测到的土地覆盖。由于CN方法越来越多地应用于受干扰和城市化的土地,因此这项工作的目的是从各种土地利用类型中收集有效的饱和水导率K_(sat)和吸水率S_o,使用结果估算CN,并将这些CN与从土壤调查信息和相应的土地覆被中得出的CN估算值进行比较。在这15个地点进行了331次双环渗透测试。根据土地使用和场地历史,将测试场地分为工程,城市改造,农村改造,农村未改变和草原等类别。测量的K_(sat)值是偏斜的,因此这些数据的中位数可以更好地预测中心趋势。草原和农村未改变的中位数K_(sat)值比其他类别更接近土壤图估计值(与土壤调查值之间介于0.0到91%之间)。夏威夷使用洒水渗透试验开发了两种经验方法,用于根据渗透数据估算CN值。方法1仅使用K_(sat)作为预测变量,方法2使用K_(sat)和S_o。这两种方法的结果在15个位点中的12个位点没有统计学差异(α= 0.05)。将这些方法与从土壤数据和土地覆盖物得出的CN值(方法3)进行比较时,方法1和方法3之间存在更好的总体一致性。方法1的CN值中位数是基于测得径流数据的平均CN的最佳预测指标对于城市改变后的土地利用地点(差异为0.6%),而方法3是基于测得的草原土地利用径流数据的平均CN的最佳预测指标(差异为0.0%)。

著录项

  • 来源
    《Journal of hydrologic engineering》 |2016年第2期|04015059.1-04015059.12|共12页
  • 作者单位

    Center for Watershed Protection, 3290 North Ridge Rd., Suite 290, Ellicott City, MD 21043;

    Dept. of Biological and Agricultural Engineering, Kansas State Univ., 129 Seaton Hall, Manhattan, KS 66502;

    Dept. of Biosystems and Agricultural Engineering, Oklahoma State Univ., 111 Agricultural Hall, Stillwater, OK 74078;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Curve number;

    机译:曲线数;

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