Increasing detail of distributed runoff modeling using fuzzy logic in curve number

Abstract

The Soil Conservation Service Curve Number runoff model is widely used in runoff prediction and has been incorporated into many software packages for watershed modeling. The Curve Number (CN) is the key parameter in the model, but it is largely dependent on Hydrologic Soil Group (HSG) classifications which may induce aggregation of detailed soil information. However, little attention and efforts have been paid to reduce such aggregation effect for retaining those valuable soil information to derive more detailed CN. This study proposed to integrate fuzzy logic to derive detailed CN. Membership of a given soil to each HSG is first calculated based on soil properties and HSG classification criteria; then, detailed and continuous CN is derived using the membership as weight for CN of each soil-cover complex. The proposed approach was incorporated into an automation system and its further effects on runoff modeling were examined. A case study shows fuzzy CN possesses more spatial details and leads to obvious spatial differences of simulated runoff. The developed system could also be used to detect inconsistency of HSG placements.