Nguyen Thi Thuy Hang, Hidetaka Chikamori, Cong-Thanh Tran, Tri Nguyen-Quang
{"title":"利用优化研究气候危机背景下水库的适应性运行","authors":"Nguyen Thi Thuy Hang, Hidetaka Chikamori, Cong-Thanh Tran, Tri Nguyen-Quang","doi":"10.1021/acsestwater.4c00389","DOIUrl":null,"url":null,"abstract":"This study investigates the climate change impacts on the performance of the Thac Mo reservoir in Vietnam throughout the release duration from December to June of the following year. The adaptative optimization operating rules during two periods, 2029–2064 and 2064–2099, were analyzed. Precipitation and temperature of three shared socioeconomic pathway (SSP) scenarios (SSP1–P2.6, SSP2–4.5, and SSP5–8.5) of the Coupled Model Intercomparison Project Phase 6 (CMIP6) derived from the global climate model (GCM) Meteorological Research Institute Earth System Model version 2.0 (MRI-ESM2–0) were used for inflow prediction. Due to the decreased inflow, the current operating rule would almost lead to a decrease in hydropower production of two periods of SSP1–P2.6, SSP2–4.5, and SSP5–8.5 scenarios of −3.9, 0.7, −7.6, −6.7, −6.3, and 7.0% and an increase in water scarcity, with the respective amount of water deficit by 20.4, 6.8, 33.2, 31.3, 30.2, and 28.3% compared to the base period (1987–2022). The improved power production of 7.1, 7.1, 7.3, 6.2, 6.9, and 6.8% and reduced water shortage of −40.2, −42.7, −37.2, −43.4, −40.8, and −39.0% can be achieved by applying the nondominated sorting genetic algorithm II (NSGA-II) optimization technique under different periods and scenarios. This approach has the potential to mitigate climate change effects on future reservoir operations.","PeriodicalId":7078,"journal":{"name":"ACS Es&t Water","volume":"9 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Using Optimization to Investigate the Adaptive Operation of Reservoirs under the Context of Climate Crisis\",\"authors\":\"Nguyen Thi Thuy Hang, Hidetaka Chikamori, Cong-Thanh Tran, Tri Nguyen-Quang\",\"doi\":\"10.1021/acsestwater.4c00389\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This study investigates the climate change impacts on the performance of the Thac Mo reservoir in Vietnam throughout the release duration from December to June of the following year. The adaptative optimization operating rules during two periods, 2029–2064 and 2064–2099, were analyzed. Precipitation and temperature of three shared socioeconomic pathway (SSP) scenarios (SSP1–P2.6, SSP2–4.5, and SSP5–8.5) of the Coupled Model Intercomparison Project Phase 6 (CMIP6) derived from the global climate model (GCM) Meteorological Research Institute Earth System Model version 2.0 (MRI-ESM2–0) were used for inflow prediction. Due to the decreased inflow, the current operating rule would almost lead to a decrease in hydropower production of two periods of SSP1–P2.6, SSP2–4.5, and SSP5–8.5 scenarios of −3.9, 0.7, −7.6, −6.7, −6.3, and 7.0% and an increase in water scarcity, with the respective amount of water deficit by 20.4, 6.8, 33.2, 31.3, 30.2, and 28.3% compared to the base period (1987–2022). The improved power production of 7.1, 7.1, 7.3, 6.2, 6.9, and 6.8% and reduced water shortage of −40.2, −42.7, −37.2, −43.4, −40.8, and −39.0% can be achieved by applying the nondominated sorting genetic algorithm II (NSGA-II) optimization technique under different periods and scenarios. This approach has the potential to mitigate climate change effects on future reservoir operations.\",\"PeriodicalId\":7078,\"journal\":{\"name\":\"ACS Es&t Water\",\"volume\":\"9 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-09-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACS Es&t Water\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1021/acsestwater.4c00389\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Es&t Water","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1021/acsestwater.4c00389","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Using Optimization to Investigate the Adaptive Operation of Reservoirs under the Context of Climate Crisis
This study investigates the climate change impacts on the performance of the Thac Mo reservoir in Vietnam throughout the release duration from December to June of the following year. The adaptative optimization operating rules during two periods, 2029–2064 and 2064–2099, were analyzed. Precipitation and temperature of three shared socioeconomic pathway (SSP) scenarios (SSP1–P2.6, SSP2–4.5, and SSP5–8.5) of the Coupled Model Intercomparison Project Phase 6 (CMIP6) derived from the global climate model (GCM) Meteorological Research Institute Earth System Model version 2.0 (MRI-ESM2–0) were used for inflow prediction. Due to the decreased inflow, the current operating rule would almost lead to a decrease in hydropower production of two periods of SSP1–P2.6, SSP2–4.5, and SSP5–8.5 scenarios of −3.9, 0.7, −7.6, −6.7, −6.3, and 7.0% and an increase in water scarcity, with the respective amount of water deficit by 20.4, 6.8, 33.2, 31.3, 30.2, and 28.3% compared to the base period (1987–2022). The improved power production of 7.1, 7.1, 7.3, 6.2, 6.9, and 6.8% and reduced water shortage of −40.2, −42.7, −37.2, −43.4, −40.8, and −39.0% can be achieved by applying the nondominated sorting genetic algorithm II (NSGA-II) optimization technique under different periods and scenarios. This approach has the potential to mitigate climate change effects on future reservoir operations.