Heuristic Knowledge-base Approach to Runoff Estimation in Midwestern States Using a SCS Curve Number Method

by Jaewan Yoon, (A.M.ASCE), North Dakota State Univ, Fargo, United States,
G. Padmanabhan, (A.M.ASCE), North Dakota State Univ, Fargo, United States,



Document Type: Proceeding Paper

Part of: Computing in Civil Engineering

Abstract: The applications of the Knowledge-Based engineering has emerged as a potential technique for incorporating human expertise and some degree of intelligent judgment into decision-supporting procedures. An Expert Knowledge Base (EKB) methodology to estimate the volume and hydrograph of direct surface runoff from rain events using Soil Conservation Service (SCS) Curve Number method is developed and discussed here. The EKB approach is designed to determine runoff curve numbers even if only limited information on watershed characteristics is available, estimate rainfall intensity of the geographic location for specific duration and return period, and to use the curve number and rainfall intensity estimates for calculating runoff volume, peak runoff and time-to-peak. Rainfall intensity estimation is performed based on four regional rainfall parameters corresponding to a given geographic location. Currently, regional parameters of 1566 towns across twelve Midwestern states including Illinois, Indiana, Iowa, Kansas, Michigan, Minnesota, Missouri, Nebraska, North Dakota, Ohio, South Dakota, Wisconsin are compiled in the knowledge base.

Subject Headings: Knowledge-based systems | Runoff curve number | Algorithms | Rainfall-runoff relationships | Rainfall intensity | Parameters (statistics) | Rain water | Decision support systems | North America | United States | South Carolina | Michigan | Kansas | Illinois | Indiana | Iowa

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