{"title":"伊朗大坝水库的热分层和混合现象","authors":"Roohollah Noori , Mojtaba Noury , Maryam Khalilzadeh Poshtegal , Masoud Sadrinasab , Mehran Mahdian , Rabin Bhattarai , Mohammad Moradi , Soroush Abolfathi","doi":"10.1016/j.wsee.2024.07.002","DOIUrl":null,"url":null,"abstract":"<div><p>Although numerical water quality models offer valuable insights into thermal stratification (TSn) and mixing dynamics in lakes, they are often resource and time consuming, limiting their applications for investigating a large number of lakes over a wide geographical area. An alternative approach is using well-known thermal classification systems, which require minimum data to provide acceptable information on TSn and mixing patterns in lakes. This study investigates the TSn and mixing regimes in 198 dam reservoirs located in Iran, using Lewis’s method for analysis. The results highlight that all 198 investigated reservoirs in Iran can be represented by six out of eight possible thermal classifications. The majority of the northeastern reservoirs are categorized as “warm monomictic”. For the reservoirs located in the north and northwest regions, all six thermal classes are observed. However, in the southern part of Iran, only the reservoirs of “continuous warm polymictic”, “warm monomictic”, and “discontinuous cold polymictic” types are located. Our findings reveal that 35.4%, 21.2%, 17.2%, 13.1%, 6.6%, and 5.6% of the investigated reservoirs were classified as “warm monomictic”, “discontinuous cold polymictic”, “continuous cold polymictic”, “dimictic”, “discontinuous warm polymictic”, and “continuous warm polymictic”, respectively. Our results can provide authorities with initial insights for further in-depth studies and decision-making into water quality management in Iran and enhancement strategies for the reservoirs in the country.</p></div>","PeriodicalId":101280,"journal":{"name":"Watershed Ecology and the Environment","volume":"6 ","pages":"Pages 138-145"},"PeriodicalIF":0.0000,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S258947142400010X/pdfft?md5=07f021f91d4850a093b7d32e60605b02&pid=1-s2.0-S258947142400010X-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Thermal stratification and mixing of dam reservoirs in Iran\",\"authors\":\"Roohollah Noori , Mojtaba Noury , Maryam Khalilzadeh Poshtegal , Masoud Sadrinasab , Mehran Mahdian , Rabin Bhattarai , Mohammad Moradi , Soroush Abolfathi\",\"doi\":\"10.1016/j.wsee.2024.07.002\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Although numerical water quality models offer valuable insights into thermal stratification (TSn) and mixing dynamics in lakes, they are often resource and time consuming, limiting their applications for investigating a large number of lakes over a wide geographical area. An alternative approach is using well-known thermal classification systems, which require minimum data to provide acceptable information on TSn and mixing patterns in lakes. This study investigates the TSn and mixing regimes in 198 dam reservoirs located in Iran, using Lewis’s method for analysis. The results highlight that all 198 investigated reservoirs in Iran can be represented by six out of eight possible thermal classifications. The majority of the northeastern reservoirs are categorized as “warm monomictic”. For the reservoirs located in the north and northwest regions, all six thermal classes are observed. However, in the southern part of Iran, only the reservoirs of “continuous warm polymictic”, “warm monomictic”, and “discontinuous cold polymictic” types are located. Our findings reveal that 35.4%, 21.2%, 17.2%, 13.1%, 6.6%, and 5.6% of the investigated reservoirs were classified as “warm monomictic”, “discontinuous cold polymictic”, “continuous cold polymictic”, “dimictic”, “discontinuous warm polymictic”, and “continuous warm polymictic”, respectively. Our results can provide authorities with initial insights for further in-depth studies and decision-making into water quality management in Iran and enhancement strategies for the reservoirs in the country.</p></div>\",\"PeriodicalId\":101280,\"journal\":{\"name\":\"Watershed Ecology and the Environment\",\"volume\":\"6 \",\"pages\":\"Pages 138-145\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S258947142400010X/pdfft?md5=07f021f91d4850a093b7d32e60605b02&pid=1-s2.0-S258947142400010X-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Watershed Ecology and the Environment\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S258947142400010X\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Watershed Ecology and the Environment","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S258947142400010X","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Thermal stratification and mixing of dam reservoirs in Iran
Although numerical water quality models offer valuable insights into thermal stratification (TSn) and mixing dynamics in lakes, they are often resource and time consuming, limiting their applications for investigating a large number of lakes over a wide geographical area. An alternative approach is using well-known thermal classification systems, which require minimum data to provide acceptable information on TSn and mixing patterns in lakes. This study investigates the TSn and mixing regimes in 198 dam reservoirs located in Iran, using Lewis’s method for analysis. The results highlight that all 198 investigated reservoirs in Iran can be represented by six out of eight possible thermal classifications. The majority of the northeastern reservoirs are categorized as “warm monomictic”. For the reservoirs located in the north and northwest regions, all six thermal classes are observed. However, in the southern part of Iran, only the reservoirs of “continuous warm polymictic”, “warm monomictic”, and “discontinuous cold polymictic” types are located. Our findings reveal that 35.4%, 21.2%, 17.2%, 13.1%, 6.6%, and 5.6% of the investigated reservoirs were classified as “warm monomictic”, “discontinuous cold polymictic”, “continuous cold polymictic”, “dimictic”, “discontinuous warm polymictic”, and “continuous warm polymictic”, respectively. Our results can provide authorities with initial insights for further in-depth studies and decision-making into water quality management in Iran and enhancement strategies for the reservoirs in the country.