A - Papers appearing in refereed journals
Shi, W., Huang, M., Gongadze, K. and Wu, L. 2017. A modified SCS-CN method incorporating storm duration and antecedent soil moisture estimation for runoff prediction. Water Resources Management. 31, pp. 1713-1727.
|Authors||Shi, W., Huang, M., Gongadze, K. and Wu, L.|
In one of the widely used methods to estimate surface runoff - Soil Conservation Service Curve Number (SCS-CN), the antecedent moisture condition (AMC) is categorized into three AMC levels causing irrational abrupt jumps in estimated runoff. A few improved SCS-CN methods have been developed to overcome several in-built inconsistencies in the soil moisture accounting (SMA) procedure that lies behind the SCS-CN method. However, these methods still inherit the structural inconsistency in the SMA procedure. In this study, a modified SCS-CN method was proposed based on the revised SMA procedure incorporating storm duration and a physical formulation for estimating antecedent soil moisture (V 0 ). The proposed formulation for V 0 estimation has shown a high degree of applicability in simulating the temporal pattern of soil moisture in the experimental plot. The modified method was calibrated and validated using a dataset of 189 storm-runoff events from two experimental watersheds in the Chinese Loess Plateau. The results indicated that the proposed method, which boosted the model efficiencies to 88% in both calibration and validation cases, performed better than the original SCS-CN and the Singh et al. (2015) method, a modified SCS-CN method based on SMA. The proposed method was then applied to a third watershed using the tabulated CN value and the parameters of the minimum infiltration rate (f c ) and coefficient (β) derived for the first two watersheds. The root mean square error between the measured and predicted runoff values was improved from 6 mm to 1 mm. Moreover, the parameter sensitivity analysis indicated that the potential maximum retention (S) parameter is the most sensitive, followed by f c . It can be concluded that the modified SCS-CN method, may predict surface runoff more accurately in the Chinese Loess Plateau.
|Year of Publication||2017|
|Journal||Water Resources Management|
|Journal citation||31, pp. 1713-1727|
|Digital Object Identifier (DOI)||doi:10.1007/s11269-017-1610-0|
|Open access||Published as non-open access|
|Funder||Natural Environment Research Council|
|Funder project or code||Modelling and managing critical zone relationships between soil, water and ecosystem processes across the Loess Plateau|
|02 Mar 2017|
|Publication process dates|
|Accepted||22 Feb 2017|
|Copyright license||CC BY|
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