A generalized relation between initial abstraction and potential maximum retention in SCS‐CN‐based model

Abstract

Abstract Soil Conservation Service curve number (SCS‐CN) method estimates direct surface runoff from given amount of rainfall. The initial abstraction coefficient (λ), which largely depends on the climatic conditions, is taken as a constant value of 0.2 in the method and it is perhaps the most ambiguous parameter to be considered for modification. Though the Mishra and Singh (MS) [14] model allows variation in λ and, in turn, initial abstraction Ia, it obviates its dependence on the antecedent moisture M. In fact, larger the antecedent moisture, lesser will be the initial abstraction, and vice versa. This study presents a modification to the initial abstraction (Ia)‐potential maximum retention (S) relationship of the existing SCS‐CN method and MS model for M. In an application to a large set of data from 84 small watersheds of U.S.A., the proposed modified model for varying λ is found to perform much better than the existing one and other considered variations. The proposed method advantageously obviates sudden jumps in the curve number with antecedent moisture condition, an unreasonable and undesirable feature of the existing SCS‐CN model. Finally, a better one‐parameter model is also suggested for field applications.