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A physically guided and interpretable SWAT-BiLSTM framework with Bayesian optimization for bias correction in daily streamflow forecasting.

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Title: A physically guided and interpretable SWAT-BiLSTM framework with Bayesian optimization for bias correction in daily streamflow forecasting.
Authors: Jin L; School of Civil and Hydraulic Engineering, Huazhong University of Science and Technology, Wuhan 430074, China; Hubei Provincial Key Laboratory of Construction and Management in Hydropower Engineering, and Engineering Research Center of Eco-environment in Three Gorges Reservoir Region, Ministry of Education, China Three Gorges University, Yichang 443002, China. Electronic address: lina_jin@hust.edu.cn., Peng T; Hubei Provincial Key Laboratory of Construction and Management in Hydropower Engineering, and Engineering Research Center of Eco-environment in Three Gorges Reservoir Region, Ministry of Education, China Three Gorges University, Yichang 443002, China. Electronic address: pengtao306@163.com., Jiang Z; School of Civil and Hydraulic Engineering, Huazhong University of Science and Technology, Wuhan 430074, China. Electronic address: zqjzq@hust.edu.cn., Jia X; School of Civil and Hydraulic Engineering, Huazhong University of Science and Technology, Wuhan 430074, China., Wang J; School of Civil and Hydraulic Engineering, Huazhong University of Science and Technology, Wuhan 430074, China., Li Z; School of Civil and Hydraulic Engineering, Huazhong University of Science and Technology, Wuhan 430074, China., Zhang C; School of Civil and Hydraulic Engineering, Huazhong University of Science and Technology, Wuhan 430074, China., Lu Q; School of Civil and Hydraulic Engineering, Huazhong University of Science and Technology, Wuhan 430074, China., Luo Z; School of Civil and Hydraulic Engineering, Huazhong University of Science and Technology, Wuhan 430074, China.
Source: Journal of contaminant hydrology [J Contam Hydrol] 2026 Jul; Vol. 281, pp. 104952. Date of Electronic Publication: 2026 Apr 19.
Publication Type: Journal Article
Journal Info: Publisher: Elsevier Country of Publication: Netherlands NLM ID: 8805644 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1873-6009 (Electronic) Linking ISSN: 01697722 NLM ISO Abbreviation: J Contam Hydrol Subsets: MEDLINE
Database: MEDLINE Ultimate
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PubType: Academic Journal
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  Data: A physically guided and interpretable SWAT-BiLSTM framework with Bayesian optimization for bias correction in daily streamflow forecasting.
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  Data: <searchLink fieldCode="AU" term="%22Jin+L%22">Jin L</searchLink>; School of Civil and Hydraulic Engineering, Huazhong University of Science and Technology, Wuhan 430074, China; Hubei Provincial Key Laboratory of Construction and Management in Hydropower Engineering, and Engineering Research Center of Eco-environment in Three Gorges Reservoir Region, Ministry of Education, China Three Gorges University, Yichang 443002, China. Electronic address: lina_jin@hust.edu.cn.<br /><searchLink fieldCode="AU" term="%22Peng+T%22">Peng T</searchLink>; Hubei Provincial Key Laboratory of Construction and Management in Hydropower Engineering, and Engineering Research Center of Eco-environment in Three Gorges Reservoir Region, Ministry of Education, China Three Gorges University, Yichang 443002, China. Electronic address: pengtao306@163.com.<br /><searchLink fieldCode="AU" term="%22Jiang+Z%22">Jiang Z</searchLink>; School of Civil and Hydraulic Engineering, Huazhong University of Science and Technology, Wuhan 430074, China. Electronic address: zqjzq@hust.edu.cn.<br /><searchLink fieldCode="AU" term="%22Jia+X%22">Jia X</searchLink>; School of Civil and Hydraulic Engineering, Huazhong University of Science and Technology, Wuhan 430074, China.<br /><searchLink fieldCode="AU" term="%22Wang+J%22">Wang J</searchLink>; School of Civil and Hydraulic Engineering, Huazhong University of Science and Technology, Wuhan 430074, China.<br /><searchLink fieldCode="AU" term="%22Li+Z%22">Li Z</searchLink>; School of Civil and Hydraulic Engineering, Huazhong University of Science and Technology, Wuhan 430074, China.<br /><searchLink fieldCode="AU" term="%22Zhang+C%22">Zhang C</searchLink>; School of Civil and Hydraulic Engineering, Huazhong University of Science and Technology, Wuhan 430074, China.<br /><searchLink fieldCode="AU" term="%22Lu+Q%22">Lu Q</searchLink>; School of Civil and Hydraulic Engineering, Huazhong University of Science and Technology, Wuhan 430074, China.<br /><searchLink fieldCode="AU" term="%22Luo+Z%22">Luo Z</searchLink>; School of Civil and Hydraulic Engineering, Huazhong University of Science and Technology, Wuhan 430074, China.
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  Data: <searchLink fieldCode="JN" term="%228805644%22">Journal of contaminant hydrology</searchLink> [J Contam Hydrol] 2026 Jul; Vol. 281, pp. 104952. <i>Date of Electronic Publication: </i>2026 Apr 19.
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  Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22Elsevier%22">Elsevier </searchLink><i>Country of Publication: </i>Netherlands <i>NLM ID: </i>8805644 <i>Publication Model: </i>Print-Electronic <i>Cited Medium: </i>Internet <i>ISSN: </i>1873-6009 (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2201697722%22">01697722 </searchLink><i>NLM ISO Abbreviation: </i>J Contam Hydrol <i>Subsets: </i>MEDLINE
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RecordInfo BibRecord:
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      – Type: doi
        Value: 10.1016/j.jconhyd.2026.104952
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      – Code: eng
        Text: English
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        StartPage: 104952
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      – TitleFull: A physically guided and interpretable SWAT-BiLSTM framework with Bayesian optimization for bias correction in daily streamflow forecasting.
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            – D: 01
              M: 07
              Text: 2026 Jul
              Type: published
              Y: 2026
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            – Type: issn-electronic
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              Value: 281
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            – TitleFull: Journal of contaminant hydrology
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