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- Title
A Method For Estimating Excess Rainfall Intensity (ERI) of Combined Sewer Overflow (CSO) Based on Peak Over Threshold (POT) Sampling And The Generalized Pareto Distribution (GPD).
- Authors
Liu, Xingpo; Zang, Wenke; Zhou, Yuwen
- Abstract
Combined sewer overflow (CSO) posed a great threat to the urban aquatic environment of many Chinese cities during the wet weather. For CSO from the specific interceptor well, the drainage capacity of the adjacent downstream interceptor sewer can be viewed as one of the critical thresholds. In this study, the generalized Pareto distribution (GPD) combined with peak over threshold (POT) sampling was used to characterize the excess rainfall intensity (ERI) of CSO events, which is significant for evaluating the severity and intensity of CSO events. First, the 10-year rainfall series were divided into different rainfall events, and the maximum rainfall intensity for the specific rainfall duration (30 min used in this study) over the drainage capacity of interceptor sewers (i.e., ERI) was calculated and sampled from each rainfall event, and its statistic characteristics were analyzed. Moreover, the empirical frequency of excess rainfall intensity (ERI) was calculated by the Weibull formula. Finally, GPD was used for fitting the empirical frequency distribution and its shape, scale parameters were optimized based on the Markov chain Monte Carlo (MCMC) algorithm. It was concluded that: (1) POT sampling combining rainfall event division was appropriate for ERI estimation of CSO events; (2) The Coefficient of skewness (Cs) of ERI was greater than zero for the studied scenarios, which showed that its distribution was right-skewed; (3) The kurtosis of the ERI was greater than three for the studied scenarios, which indicated that its distribution was thick-tailed; (4) GPD was suitable for modeling the theoretical frequency distribution of ERI.
- Subjects
COMBINED sewer overflows; PARETO distribution; MARKOV chain Monte Carlo; RAINFALL frequencies; DISTRIBUTION (Probability theory); KURTOSIS
- Publication
Water Resources Management, 2024, Vol 38, Issue 3, p1045
- ISSN
0920-4741
- Publication type
Article
- DOI
10.1007/s11269-023-03708-5