Uncertainty-based parameter estimation for urban pollutant buildup and washoff simulation using a multiple pattern inverse modeling approach

Qian Wang, Rui Zou, Alvi Khalid and Tao Yang

Mathematics and Computers in Simulation (MATCOM), 2020, vol. 175, issue C, 140-152

Abstract: Reliable model parameter estimation for stormwater runoff water quality modeling has always been a challenge, especially in ungauged areas. Insufficient local observations can increase parameter uncertainty, leading to modeling outputs of limited credibility. This paper proposes an event-based multiple pattern inverse modeling approach to estimate regional-scale parameters characterizing the buildup and washoff processes in urban watersheds. The approach explicitly accounts for system uncertainties by simultaneously using a wide range of storm events. A genetic algorithm was employed to solve the inverse models. The solution populations that minimize the error between the observed and predicted values were then filtered into distinct parameter groups using a K-means clustering algorithm. Each identified parameter group may be used to represent the buildup and washoff processes.

Keywords: Buildup/washoff model; Regional parameter identification; Nutrient load estimation; Impervious surface; Multiple pattern inverse modeling; Uncertainty (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:matcom:v:175:y:2020:i:c:p:140-152

DOI: 10.1016/j.matcom.2019.07.009

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