An empirical approach for computing surface runoff concentration time

Abstract

This article examines data from the Shihuiyao, Nierji, Tongmeng, Jiangqiao, and Dalai hydrological stations in the Nen River basin to understand the hydrological processes occurring in the catchments. Daily precipitation and runoff data from 1955 to 1973 were combined using the smoothed minima trial method to determine the surface runoff concentration time. Then, a genetic algorithm was used to optimize the parameters and obtain an optimal empirical formula. An improved empirical formula was implemented with the genetic algorithm and optimized parameters then incorporated variable average rainfall intensity, correlation between basin area, surface runoff average concentration time, and average rainfall intensity. Finally, an optimized empirical formula (using genetic algorithm to optimize the parameters) and improved empirical formula (incorporating variable average rainfall intensity) were tested by using the daily precipitation and runoff data from the Baishan and Hongshi hydrological stations of the Second Songhua River. The results show that an optimized and improved formula can be used to more accurately estimate hydrologic conditions in the Nen River. Therefore, the improved formula is an efficient method for calculating surface runoff concentration time. Surface runoff concentration time is an important basis for differentiating source waters, which include surface runoff and underground runoff.