Modified SCS curve number method for predicting subsurface drainage flow

被引:0
|
作者
Yuan, Yongping [1 ]
Mitchell, J. Kent [1 ]
Hirschi, Michael C. [1 ]
Cooke, Richard A. C. [1 ]
机构
[1] USDA-ARS-NSL, P.O. Box 1157, Oxford, MS 38655, United States
关键词
Drainage; -; Infiltration; Rain; Runoff; Watersheds;
D O I
暂无
中图分类号
学科分类号
摘要
Agricultural fields in Central Illinois are predominantly drained by subsurface drainage systems, which often are in depressional areas. The prediction of outflow from drainage systems is a challenge. The SCS curve number (SCS-CN) method is a popular method for evaluating direct runoff from rainfall. The concept behind this method can be applied to subsurface drainage flow. The SCS-CN method was modified through theoretical analogy and term redevelopment to estimate subsurface drainage flow from rainfall. The analogical theory is that when accumulated subsurface drainage flow is plotted versus accumulated infiltration, subsurface drainage flow starts after some infiltration has accumulated and the relationship becomes asymptotic to a line of 45° slope, just as the generalized SCS rainfall-runoff relationship. Procedures are introduced for modification of the SCS-CN method and determination of curve numbers for subsurface drainage flow. In the process of defining curve numbers for drainage flow, it was found that the curve number varied not only with season but also with rainfall amount. In addition, the curve number varied with previous rainfall condition as with the traditional SCS-CN method. The best previous rainfall adjustment is based on the 10-day previous rainfall for subsurface flow prediction. The curve number is sensitive to the fraction of initial abstraction (k). However, this does not mean that predicted flows resulting from different k values are significantly different, since the equation for flow prediction changes when k is changed; in fact, the predicted flow is not sensitive to the fraction of initial abstraction to potential maximum retention of the watershed. The modified SCS-CN method was applied to estimate subsurface drainage flow for five drainage monitoring stations in the Little Vermilion River (LVR) watershed in East-Central Illinois. Predicted subsurface flows using the modified SCS-CN method were compared with observed subsurface flows. Statistical tests showed that the predicted subsurface flows using the modified SCS-CN method were not significantly different from the observed subsurface flows. Validation performed on two of the sites using modified curve number relationships from the other sites showed that the predicted subsurface drainage flows were not significantly different from the observed subsurface drainage flows.
引用
收藏
页码:1673 / 1682
相关论文
共 50 条
  • [21] Derivation of Soil Moisture Recovery Relation Using Soil Conservation Service (SCS) Curve Number Method
    Kim, Jungho
    Johnson, Lynn E.
    Cifelli, Rob
    Choi, Jeongho
    Chandrasekar, V.
    WATER, 2018, 10 (07)
  • [22] Improving runoff risk estimates: Formulating runoff as a bivariate process using the SCS curve number method
    Shaw, Stephen B.
    Walter, M. Todd
    WATER RESOURCES RESEARCH, 2009, 45
  • [23] Estimating runoff from rainfall using the SCS curve number procedure
    Vali-Khodjeini, A
    PROCEEDINGS OF THE INTERNATIONAL SYMPOSIUM ON COMPREHENSIVE WATERSHED MANAGEMENT (ISWM-'98), 1998, : 303 - 310
  • [24] Calibration of the curve number of the SCS model for the region of the north coast of Peru
    Alberca, Jhon
    Mejia, Jesus
    Guevara-Perez, Edilberto
    INGENIERIA UC, 2022, 29 (02): : 124 - 135
  • [26] Monitoring subsurface drainage flow at remote locations
    Workman, SR
    Higgins, SF
    Shearer, SA
    APPLIED ENGINEERING IN AGRICULTURE, 2001, 17 (06) : 783 - 786
  • [27] ASSESSMENT OF LAND-USE CHANGE EFFECT ON A DESIGN STORM HYDROGRAPH USING THE SCS CURVE NUMBER METHOD
    Stathis, Dimitrios
    Sapountzis, Marios
    Myronidis, Dimitrios
    FRESENIUS ENVIRONMENTAL BULLETIN, 2010, 19 (9A): : 1928 - 1934
  • [28] An analytical solution of Richards' equation providing the physical basis of SCS curve number method and its proportionality relationship
    Hooshyar, Milad
    Wang, Dingbao
    WATER RESOURCES RESEARCH, 2016, 52 (08) : 6611 - 6620
  • [29] Effects of Different Retention Parameter Estimation Methods on the Prediction of Surface Runoff Using the SCS Curve Number Method
    Tessema, Selome M.
    Lyon, Steve W.
    Setegn, Shimelis G.
    Mortberg, Ulla
    WATER RESOURCES MANAGEMENT, 2014, 28 (10) : 3241 - 3254
  • [30] Effects of Different Retention Parameter Estimation Methods on the Prediction of Surface Runoff Using the SCS Curve Number Method
    Selome M. Tessema
    Steve W. Lyon
    Shimelis G. Setegn
    Ulla Mörtberg
    Water Resources Management, 2014, 28 : 3241 - 3254