KDE-Based Rainfall Event Separation and Characterization
Rainfall event separation is mainly based on the selection of the minimum inter-event time (MIET). The traditional approach to determining a suitable MIET for estimating the probability density functions is often using the frequency histograms. However, this approach cannot avoid arbitrariness and s...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-02-01
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| Series: | Water |
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| Online Access: | https://www.mdpi.com/2073-4441/15/3/580 |
| _version_ | 1797623023168126976 |
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| author | Shengle Cao Yijiao Diao Jiachang Wang Yang Liu Anita Raimondi Jun Wang |
| author_facet | Shengle Cao Yijiao Diao Jiachang Wang Yang Liu Anita Raimondi Jun Wang |
| author_sort | Shengle Cao |
| collection | DOAJ |
| description | Rainfall event separation is mainly based on the selection of the minimum inter-event time (MIET). The traditional approach to determining a suitable MIET for estimating the probability density functions is often using the frequency histograms. However, this approach cannot avoid arbitrariness and subjectivity in selecting the histogram parameters. To overcome the above limitations, this study proposes a kernel density estimation (KDE) approach for rainfall event separation and characterization at any specific site where the exponential distributions are suitable for characterizing the rainfall event statistics. Using the standardized procedure provided taking into account the Poisson and Kolmogorov–Smirnov (K-S) statistical tests, the optimal pair of the MIET and rainfall event volume threshold can be determined. Two climatically different cities, Hangzhou and Jinan of China, applying the proposed approach are selected for demonstration purposes. The results show that the optimal MIETs determined are 12 h for Hangzhou and 10 h for Jinan while the optimal event volume threshold values are 3 mm for both Hangzhou and Jinan. The KDE-based approach can facilitate the rainfall statistical representation of the analytical probabilistic models of urban drainage/stormwater control facilities. |
| first_indexed | 2024-03-11T09:19:28Z |
| format | Article |
| id | doaj.art-009d04d4460a4172aa6ca38261166836 |
| institution | Directory Open Access Journal |
| issn | 2073-4441 |
| language | English |
| last_indexed | 2024-03-11T09:19:28Z |
| publishDate | 2023-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Water |
| spelling | doaj.art-009d04d4460a4172aa6ca382611668362023-11-16T18:24:41ZengMDPI AGWater2073-44412023-02-0115358010.3390/w15030580KDE-Based Rainfall Event Separation and CharacterizationShengle Cao0Yijiao Diao1Jiachang Wang2Yang Liu3Anita Raimondi4Jun Wang5School of Civil Engineering, Shandong University, Jinan 250061, ChinaSchool of Civil Engineering, Shandong University, Jinan 250061, ChinaSchool of Civil Engineering, Shandong University, Jinan 250061, ChinaSchool of Civil Engineering, Shandong University, Jinan 250061, ChinaDepartment of Civil and Environmental Engineering, Politecnico di Milano, 20133 Milano, ItalySchool of Civil Engineering, Shandong University, Jinan 250061, ChinaRainfall event separation is mainly based on the selection of the minimum inter-event time (MIET). The traditional approach to determining a suitable MIET for estimating the probability density functions is often using the frequency histograms. However, this approach cannot avoid arbitrariness and subjectivity in selecting the histogram parameters. To overcome the above limitations, this study proposes a kernel density estimation (KDE) approach for rainfall event separation and characterization at any specific site where the exponential distributions are suitable for characterizing the rainfall event statistics. Using the standardized procedure provided taking into account the Poisson and Kolmogorov–Smirnov (K-S) statistical tests, the optimal pair of the MIET and rainfall event volume threshold can be determined. Two climatically different cities, Hangzhou and Jinan of China, applying the proposed approach are selected for demonstration purposes. The results show that the optimal MIETs determined are 12 h for Hangzhou and 10 h for Jinan while the optimal event volume threshold values are 3 mm for both Hangzhou and Jinan. The KDE-based approach can facilitate the rainfall statistical representation of the analytical probabilistic models of urban drainage/stormwater control facilities.https://www.mdpi.com/2073-4441/15/3/580rainfall event separationminimum inter-event timeexponential distributionrainfall characteristicskernel density estimation |
| spellingShingle | Shengle Cao Yijiao Diao Jiachang Wang Yang Liu Anita Raimondi Jun Wang KDE-Based Rainfall Event Separation and Characterization Water rainfall event separation minimum inter-event time exponential distribution rainfall characteristics kernel density estimation |
| title | KDE-Based Rainfall Event Separation and Characterization |
| title_full | KDE-Based Rainfall Event Separation and Characterization |
| title_fullStr | KDE-Based Rainfall Event Separation and Characterization |
| title_full_unstemmed | KDE-Based Rainfall Event Separation and Characterization |
| title_short | KDE-Based Rainfall Event Separation and Characterization |
| title_sort | kde based rainfall event separation and characterization |
| topic | rainfall event separation minimum inter-event time exponential distribution rainfall characteristics kernel density estimation |
| url | https://www.mdpi.com/2073-4441/15/3/580 |
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