An overall optimization and solution framework for urban historical and future DRIF under climate change
The estimation and application of Intensity-Duration-Frequency (IDF) curves depend on the assumption of stationarity of the rainfall series, which is that the intensity and frequency of extreme hydrological events remain unchanged in the future. Climate change will have a significant impact on the c...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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IWA Publishing
2022-09-01
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| Series: | Water Supply |
| Subjects: | |
| Online Access: | http://ws.iwaponline.com/content/22/9/7297 |
| _version_ | 1811192785443749888 |
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| author | XingChen Ding WeiHong Liao Hao Wang Hao Wang XiaoHui Lei JiaLi Yang |
| author_facet | XingChen Ding WeiHong Liao Hao Wang Hao Wang XiaoHui Lei JiaLi Yang |
| author_sort | XingChen Ding |
| collection | DOAJ |
| description | The estimation and application of Intensity-Duration-Frequency (IDF) curves depend on the assumption of stationarity of the rainfall series, which is that the intensity and frequency of extreme hydrological events remain unchanged in the future. Climate change will have a significant impact on the collection and utilization of rainwater and its spatial characteristics. When the Gray-Green infrastructure is designed, if only historical precipitation is adopted to calculate the urban design rainstorm intensity formula (DRIF) and the total annual runoff control rate, it may be difficult to meet the demand of future precipitation changes on the city's ability to accommodate rainfall. Therefore, it is very important to study the impact of climate change on the IDF curve. This study proposes an overall optimization solution framework for historical and future DRIF. The impact of the extreme value on the IDF curve during the historical period is analyzed. The calculation method of the IDF curve in the future period is established. The changes of the rainstorm intensity in the historical and future period (SSP1-2.6,SSP2-4.5,SSP3-7.0,SSP5-8.5) were analyzed for the 15 durations and eight return periods in Beijing, China. The results of this study show that the nondominated sorting and local search (NSLS) has the best accuracy in fitting the statistical samples of precipitation for different durations. The best methods to judge and process the extreme value of the statistical sample are Z-score and average value of series greater than critical value (AVG). Under the four SSP scenarios, the estimated IDF value is larger than the observed value in the historical period. The results of the equivalent return period calculated using the DRIF show that the the four SSP scenarios are smaller than the historical period for the return period greater than five years. Taking 120 min of short-duration precipitation as an example, the 100-year equivalent return periods of the observation under the four SSP scenarios are 35-, 20-, 54-, and 17-years, respectively. The research can provide valuable reference for the design and planning of the drainage facility under climate change.
HIGHLIGHTS
The best methods to judge and process the extreme value of IDF are Z-Score and average value of series greater than critical value (AVG).;
Under the four SSP (SSP1-2.6, SSP2-4.5, SSP3-7.0, SSP5-8.5) scenarios, the estimated IDF value is larger than the observed value in the historical period.; |
| first_indexed | 2024-04-11T23:58:21Z |
| format | Article |
| id | doaj.art-42e89f92050f4b97ac395b66260d190e |
| institution | Directory Open Access Journal |
| issn | 1606-9749 1607-0798 |
| language | English |
| last_indexed | 2024-04-11T23:58:21Z |
| publishDate | 2022-09-01 |
| publisher | IWA Publishing |
| record_format | Article |
| series | Water Supply |
| spelling | doaj.art-42e89f92050f4b97ac395b66260d190e2022-12-22T03:56:18ZengIWA PublishingWater Supply1606-97491607-07982022-09-012297297731810.2166/ws.2022.293293An overall optimization and solution framework for urban historical and future DRIF under climate changeXingChen Ding0WeiHong Liao1Hao Wang2Hao Wang3XiaoHui Lei4JiaLi Yang5 College of Resources and Civil Engineering, Northeastern University, Shenyang 110819, China State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing 100038, China Faculty of Architecture, Civil and Transportation Engineering, Beijing University of Technology, Beijing 100124, China State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing 100038, China State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing 100038, China School of Hydropower and Information Engineering, Huazhong University of Science and Technology, Wuhan 430074, China The estimation and application of Intensity-Duration-Frequency (IDF) curves depend on the assumption of stationarity of the rainfall series, which is that the intensity and frequency of extreme hydrological events remain unchanged in the future. Climate change will have a significant impact on the collection and utilization of rainwater and its spatial characteristics. When the Gray-Green infrastructure is designed, if only historical precipitation is adopted to calculate the urban design rainstorm intensity formula (DRIF) and the total annual runoff control rate, it may be difficult to meet the demand of future precipitation changes on the city's ability to accommodate rainfall. Therefore, it is very important to study the impact of climate change on the IDF curve. This study proposes an overall optimization solution framework for historical and future DRIF. The impact of the extreme value on the IDF curve during the historical period is analyzed. The calculation method of the IDF curve in the future period is established. The changes of the rainstorm intensity in the historical and future period (SSP1-2.6,SSP2-4.5,SSP3-7.0,SSP5-8.5) were analyzed for the 15 durations and eight return periods in Beijing, China. The results of this study show that the nondominated sorting and local search (NSLS) has the best accuracy in fitting the statistical samples of precipitation for different durations. The best methods to judge and process the extreme value of the statistical sample are Z-score and average value of series greater than critical value (AVG). Under the four SSP scenarios, the estimated IDF value is larger than the observed value in the historical period. The results of the equivalent return period calculated using the DRIF show that the the four SSP scenarios are smaller than the historical period for the return period greater than five years. Taking 120 min of short-duration precipitation as an example, the 100-year equivalent return periods of the observation under the four SSP scenarios are 35-, 20-, 54-, and 17-years, respectively. The research can provide valuable reference for the design and planning of the drainage facility under climate change. HIGHLIGHTS The best methods to judge and process the extreme value of IDF are Z-Score and average value of series greater than critical value (AVG).; Under the four SSP (SSP1-2.6, SSP2-4.5, SSP3-7.0, SSP5-8.5) scenarios, the estimated IDF value is larger than the observed value in the historical period.;http://ws.iwaponline.com/content/22/9/7297climate changecmip6equivalent return periodextreme precipitationidfoutliers |
| spellingShingle | XingChen Ding WeiHong Liao Hao Wang Hao Wang XiaoHui Lei JiaLi Yang An overall optimization and solution framework for urban historical and future DRIF under climate change Water Supply climate change cmip6 equivalent return period extreme precipitation idf outliers |
| title | An overall optimization and solution framework for urban historical and future DRIF under climate change |
| title_full | An overall optimization and solution framework for urban historical and future DRIF under climate change |
| title_fullStr | An overall optimization and solution framework for urban historical and future DRIF under climate change |
| title_full_unstemmed | An overall optimization and solution framework for urban historical and future DRIF under climate change |
| title_short | An overall optimization and solution framework for urban historical and future DRIF under climate change |
| title_sort | overall optimization and solution framework for urban historical and future drif under climate change |
| topic | climate change cmip6 equivalent return period extreme precipitation idf outliers |
| url | http://ws.iwaponline.com/content/22/9/7297 |
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