Investigation of Climate Change Adaptation Impacts on Optimization of Water Allocation Using a Coupled SWAT-bi Level Programming Model
Abstract One way to deal with the future effects of climatic changes on the water resources and to cope with water shortages in basins is to have a clear understanding of the future climate change trends. To this end, this study proposes an integrated hydrological-water transfer and supply (HWTS) framework including a coupled SWAT-Bi level programming model to investigate future optimal water supply between different sectors with regard to transaction right. Indeed, Soil & Water Assessment Tool (SWAT) is applied to project the rate of streamflow under Representative Concentration Pathway scenarios of RCP2.6&RCP4.5 and future periods (2020–2040 & 204(Abbas et al. 2015)2060). In addition, a case study of the Hamoun wetland in southeastern of Iran is considered for calibration and validation of real historical data (2000–2016) and then simulation of future streamflow patterns (2020–2060). Next, simulated streamflow data extracted by SWAT is entered as the input of market based bi-level optimization model so that upper-level manager seeks optimization of the available water level in the reservoirs while the lower-level decision maker tries to minimize the economic loss due to water shortage between different sectors regarding transaction right. However, after solving the model with the Improved Particle Swarm Optimization (IBPSO) technique, the final results show that although not much economic profit will be made, but considering specific management strategies such as demand reduction schemes to conserve more water, the imbalance between supply and demand can be significantly improved..
Medienart: |
Artikel |
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Erscheinungsjahr: |
2021 |
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Erschienen: |
2021 |
Enthalten in: |
Zur Gesamtaufnahme - volume:41 |
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Enthalten in: |
Wetlands - 41(2021), 3 vom: 28. Feb. |
Sprache: |
Englisch |
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Beteiligte Personen: |
He, Yuan [VerfasserIn] |
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Links: |
Volltext [lizenzpflichtig] |
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Themen: |
Bi-level programming model |
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Anmerkungen: |
© Society of Wetland Scientists 2021 |
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doi: |
10.1007/s13157-021-01434-5 |
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funding: |
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Förderinstitution / Projekttitel: |
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PPN (Katalog-ID): |
OLC2124054929 |
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520 | |a Abstract One way to deal with the future effects of climatic changes on the water resources and to cope with water shortages in basins is to have a clear understanding of the future climate change trends. To this end, this study proposes an integrated hydrological-water transfer and supply (HWTS) framework including a coupled SWAT-Bi level programming model to investigate future optimal water supply between different sectors with regard to transaction right. Indeed, Soil & Water Assessment Tool (SWAT) is applied to project the rate of streamflow under Representative Concentration Pathway scenarios of RCP2.6&RCP4.5 and future periods (2020–2040 & 204(Abbas et al. 2015)2060). In addition, a case study of the Hamoun wetland in southeastern of Iran is considered for calibration and validation of real historical data (2000–2016) and then simulation of future streamflow patterns (2020–2060). Next, simulated streamflow data extracted by SWAT is entered as the input of market based bi-level optimization model so that upper-level manager seeks optimization of the available water level in the reservoirs while the lower-level decision maker tries to minimize the economic loss due to water shortage between different sectors regarding transaction right. However, after solving the model with the Improved Particle Swarm Optimization (IBPSO) technique, the final results show that although not much economic profit will be made, but considering specific management strategies such as demand reduction schemes to conserve more water, the imbalance between supply and demand can be significantly improved. | ||
650 | 4 | |a SWAT model | |
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700 | 1 | |a Mahdi, Moudi |0 (orcid)0000-0001-5129-203X |4 aut | |
700 | 1 | |a Huang, Ping |4 aut | |
700 | 1 | |a Xie, Guangming |4 aut | |
700 | 1 | |a Galoie, Majid |4 aut | |
700 | 1 | |a Shafi, Mohsin |4 aut | |
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