{"title":"自动校准 SWAT 中旋律搜索的比较实施","authors":"Alireza Borhani Dariane, Reza Bagheri, Mahboobeh Ghasemi, Roza Asadi","doi":"10.1007/s12517-024-11974-9","DOIUrl":null,"url":null,"abstract":"<p>Rainfall-runoff simulation models require calibration to ensure accurate results. The present study assesses the efficacy of the Melody Search algorithm (MeS) in auto-calibration of the SWAT, by comparing it to other commonly used calibration methods in SWAT-CUP, namely, SUF12, GLUE, ParaSol, and PSO. In order to assess the MeS algorithm’s performance, the continuous rainfall-runoff simulation was implemented using daily time-step data from the Taleghan Basin in northern Iran, spanning a 10-year period. The calibration of parameters was established through developing a FORTRAN program. The Nash–Sutcliffe efficiency (NSE) index indicator in SUFI2, GLUE, ParaSol, PSO, and MeS algorithms was found to be 0.647, 0.6, 0.628, 0.625, and 0.66, respectively. Thus, based on these results, the proposed MeS algorithm outperforms all the native calibrating methods in SWAT in all iterations. MeS specifically outperforms all native approaches in reaching a solution after 100 iterations. The results imply that MeS is an algorithm that quickly converges and functions as a reliable calibration technique for SWAT applications.</p>","PeriodicalId":476,"journal":{"name":"Arabian Journal of Geosciences","volume":null,"pages":null},"PeriodicalIF":1.8270,"publicationDate":"2024-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Comparative implementation of melody search in auto-calibrating SWAT\",\"authors\":\"Alireza Borhani Dariane, Reza Bagheri, Mahboobeh Ghasemi, Roza Asadi\",\"doi\":\"10.1007/s12517-024-11974-9\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Rainfall-runoff simulation models require calibration to ensure accurate results. The present study assesses the efficacy of the Melody Search algorithm (MeS) in auto-calibration of the SWAT, by comparing it to other commonly used calibration methods in SWAT-CUP, namely, SUF12, GLUE, ParaSol, and PSO. In order to assess the MeS algorithm’s performance, the continuous rainfall-runoff simulation was implemented using daily time-step data from the Taleghan Basin in northern Iran, spanning a 10-year period. The calibration of parameters was established through developing a FORTRAN program. The Nash–Sutcliffe efficiency (NSE) index indicator in SUFI2, GLUE, ParaSol, PSO, and MeS algorithms was found to be 0.647, 0.6, 0.628, 0.625, and 0.66, respectively. Thus, based on these results, the proposed MeS algorithm outperforms all the native calibrating methods in SWAT in all iterations. MeS specifically outperforms all native approaches in reaching a solution after 100 iterations. The results imply that MeS is an algorithm that quickly converges and functions as a reliable calibration technique for SWAT applications.</p>\",\"PeriodicalId\":476,\"journal\":{\"name\":\"Arabian Journal of Geosciences\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.8270,\"publicationDate\":\"2024-05-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Arabian Journal of Geosciences\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1007/s12517-024-11974-9\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"Earth and Planetary Sciences\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Arabian Journal of Geosciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/s12517-024-11974-9","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Earth and Planetary Sciences","Score":null,"Total":0}
Comparative implementation of melody search in auto-calibrating SWAT
Rainfall-runoff simulation models require calibration to ensure accurate results. The present study assesses the efficacy of the Melody Search algorithm (MeS) in auto-calibration of the SWAT, by comparing it to other commonly used calibration methods in SWAT-CUP, namely, SUF12, GLUE, ParaSol, and PSO. In order to assess the MeS algorithm’s performance, the continuous rainfall-runoff simulation was implemented using daily time-step data from the Taleghan Basin in northern Iran, spanning a 10-year period. The calibration of parameters was established through developing a FORTRAN program. The Nash–Sutcliffe efficiency (NSE) index indicator in SUFI2, GLUE, ParaSol, PSO, and MeS algorithms was found to be 0.647, 0.6, 0.628, 0.625, and 0.66, respectively. Thus, based on these results, the proposed MeS algorithm outperforms all the native calibrating methods in SWAT in all iterations. MeS specifically outperforms all native approaches in reaching a solution after 100 iterations. The results imply that MeS is an algorithm that quickly converges and functions as a reliable calibration technique for SWAT applications.
期刊介绍:
The Arabian Journal of Geosciences is the official journal of the Saudi Society for Geosciences and publishes peer-reviewed original and review articles on the entire range of Earth Science themes, focused on, but not limited to, those that have regional significance to the Middle East and the Euro-Mediterranean Zone.
Key topics therefore include; geology, hydrogeology, earth system science, petroleum sciences, geophysics, seismology and crustal structures, tectonics, sedimentology, palaeontology, metamorphic and igneous petrology, natural hazards, environmental sciences and sustainable development, geoarchaeology, geomorphology, paleo-environment studies, oceanography, atmospheric sciences, GIS and remote sensing, geodesy, mineralogy, volcanology, geochemistry and metallogenesis.