An improved Ia-S relation incorporating antecedent moisture in SCS-CN methodology

Employing a large dataset of 84 small watersheds (area = 0.17 to 71.99 ha) of U.S.A., this paper investigates a number of initial abstraction (I-a )-potential maximum retention (S) relations incorporating antecedent moisture (M) as a function of antecedent precipitation (P-5), and finally suggests an improved relation for use in the popular Soil Conservation Service Curve Number (SCS-CN) methodology for determination of direct runoff from given rainfall. The improved performance of the incorporated M = alpha root P5S and I-a = lambda S-2/(S + M) relations, where lambda is the initial abstraction coefficient, in the SCS-CN methodology exhibits the dependence of I-a on M, which is close to reality; the larger the M, the lesser will be I-a , and vice versa. Such incorporation obviates sudden jumps in the curve number variation with antecedent moisture condition, an unreasonable and undesirable feature of the existing SCS-CN model.