Academic Journal
A multiple spatial scales water use simulation for capturing its spatial heterogeneity through cellular automata model.
| Τίτλος: | A multiple spatial scales water use simulation for capturing its spatial heterogeneity through cellular automata model. |
|---|---|
| Συγγραφείς: | Zhang, Jiayu, Liu, Dedi, Wang, Jiaoyang, Yue, Feng, Liang, Hanxu, Peng, Zhengbo, Guan, Wei |
| Πηγή: | Hydrology & Earth System Sciences; 2025, Vol. 29 Issue 23, p7149-7172, 24p |
| Θεματικοί όροι: | Cellular automata, Multiscale modeling, Spatial variation, Uncertainty (Information theory), Water demand management, Climate change, Water management |
| Γεωγραφικοί όροι: | China |
| Περίληψη: | Reliable water use simulation is essential for sustainable water resource planning, especially under intensifying pressures from climate change, population growth, and socio-economic transitions. While previous studies have extensively explored water availability as supply side modeling across multiple spatial scales for its spatial heterogeneity, the water demand side remains relatively underdeveloped – often constrained by fixed spatial scales and coarse statistical data that assume spatial homogeneity. This mismatch between supply side and demand side limits the ability of existing models to accurately represent spatial heterogeneity in water use and brings uncertainty into water resource allocation strategies. To address this mismatch, we propose a novel multi-scale water use simulation framework by integrating cellular automata (CA) model with Generalized Likelihood Uncertainty Estimation (GLUE). The CA model captures the spatial heterogeneity of water use through the grid-based update rules. Two update rules are adopted – probability rule (i.e., capturing stochastic transitions via distribution fitting) and linear rule (i.e., modeling neighborhood-weighted evolution). To evaluate the impacts of spatial scale on water use heterogeneity, simulations are conducted at three spatial scales: 1 km, appropriate scale, and prefecture scale across 341 prefectures in China. Results show that both the update rule and spatial scale significantly affect spatial heterogeneity and uncertainty of water use. The probability rule can capture the broader variability but results in higher Root Mean Squared Error (RMSE) and Relative Error (RE) while the linear rule brings more stable performance with lower errors. While the 1 km scale increases uncertainty due to sensitivity to local fluctuations, and the prefecture scale suppresses spatial details, the appropriate scale offers the best trade-off between stability and spatial heterogeneity. The uncertainty quantified by GLUE, expresses as confidence intervals, varies across prefectures and spatial scales. Overall, the proposed framework offers a flexible tool for multi-scale water use simulation and highlights the critical role of spatial heterogeneity, thereby supporting adaptive water resource planning and management. [ABSTRACT FROM AUTHOR] |
| Copyright of Hydrology & Earth System Sciences is the property of Copernicus Gesellschaft mbH and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Βάση Δεδομένων: | Complementary Index |
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| Items | – Name: Title Label: Title Group: Ti Data: A multiple spatial scales water use simulation for capturing its spatial heterogeneity through cellular automata model. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Zhang%2C+Jiayu%22">Zhang, Jiayu</searchLink><br /><searchLink fieldCode="AR" term="%22Liu%2C+Dedi%22">Liu, Dedi</searchLink><br /><searchLink fieldCode="AR" term="%22Wang%2C+Jiaoyang%22">Wang, Jiaoyang</searchLink><br /><searchLink fieldCode="AR" term="%22Yue%2C+Feng%22">Yue, Feng</searchLink><br /><searchLink fieldCode="AR" term="%22Liang%2C+Hanxu%22">Liang, Hanxu</searchLink><br /><searchLink fieldCode="AR" term="%22Peng%2C+Zhengbo%22">Peng, Zhengbo</searchLink><br /><searchLink fieldCode="AR" term="%22Guan%2C+Wei%22">Guan, Wei</searchLink> – Name: TitleSource Label: Source Group: Src Data: Hydrology & Earth System Sciences; 2025, Vol. 29 Issue 23, p7149-7172, 24p – Name: Subject Label: Subject Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Cellular+automata%22">Cellular automata</searchLink><br /><searchLink fieldCode="DE" term="%22Multiscale+modeling%22">Multiscale modeling</searchLink><br /><searchLink fieldCode="DE" term="%22Spatial+variation%22">Spatial variation</searchLink><br /><searchLink fieldCode="DE" term="%22Uncertainty+%28Information+theory%29%22">Uncertainty (Information theory)</searchLink><br /><searchLink fieldCode="DE" term="%22Water+demand+management%22">Water demand management</searchLink><br /><searchLink fieldCode="DE" term="%22Climate+change%22">Climate change</searchLink><br /><searchLink fieldCode="DE" term="%22Water+management%22">Water management</searchLink> – Name: SubjectGeographic Label: Geographic Terms Group: Su Data: <searchLink fieldCode="DE" term="%22China%22">China</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Reliable water use simulation is essential for sustainable water resource planning, especially under intensifying pressures from climate change, population growth, and socio-economic transitions. While previous studies have extensively explored water availability as supply side modeling across multiple spatial scales for its spatial heterogeneity, the water demand side remains relatively underdeveloped – often constrained by fixed spatial scales and coarse statistical data that assume spatial homogeneity. This mismatch between supply side and demand side limits the ability of existing models to accurately represent spatial heterogeneity in water use and brings uncertainty into water resource allocation strategies. To address this mismatch, we propose a novel multi-scale water use simulation framework by integrating cellular automata (CA) model with Generalized Likelihood Uncertainty Estimation (GLUE). The CA model captures the spatial heterogeneity of water use through the grid-based update rules. Two update rules are adopted – probability rule (i.e., capturing stochastic transitions via distribution fitting) and linear rule (i.e., modeling neighborhood-weighted evolution). To evaluate the impacts of spatial scale on water use heterogeneity, simulations are conducted at three spatial scales: 1 km, appropriate scale, and prefecture scale across 341 prefectures in China. Results show that both the update rule and spatial scale significantly affect spatial heterogeneity and uncertainty of water use. The probability rule can capture the broader variability but results in higher Root Mean Squared Error (RMSE) and Relative Error (RE) while the linear rule brings more stable performance with lower errors. While the 1 km scale increases uncertainty due to sensitivity to local fluctuations, and the prefecture scale suppresses spatial details, the appropriate scale offers the best trade-off between stability and spatial heterogeneity. The uncertainty quantified by GLUE, expresses as confidence intervals, varies across prefectures and spatial scales. Overall, the proposed framework offers a flexible tool for multi-scale water use simulation and highlights the critical role of spatial heterogeneity, thereby supporting adaptive water resource planning and management. [ABSTRACT FROM AUTHOR] – Name: Abstract Label: Group: Ab Data: <i>Copyright of Hydrology & Earth System Sciences is the property of Copernicus Gesellschaft mbH and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.5194/hess-29-7149-2025 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 24 StartPage: 7149 Subjects: – SubjectFull: China Type: general – SubjectFull: Cellular automata Type: general – SubjectFull: Multiscale modeling Type: general – SubjectFull: Spatial variation Type: general – SubjectFull: Uncertainty (Information theory) Type: general – SubjectFull: Water demand management Type: general – SubjectFull: Climate change Type: general – SubjectFull: Water management Type: general Titles: – TitleFull: A multiple spatial scales water use simulation for capturing its spatial heterogeneity through cellular automata model. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Zhang, Jiayu – PersonEntity: Name: NameFull: Liu, Dedi – PersonEntity: Name: NameFull: Wang, Jiaoyang – PersonEntity: Name: NameFull: Yue, Feng – PersonEntity: Name: NameFull: Liang, Hanxu – PersonEntity: Name: NameFull: Peng, Zhengbo – PersonEntity: Name: NameFull: Guan, Wei IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 12 Text: 2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 10275606 Numbering: – Type: volume Value: 29 – Type: issue Value: 23 Titles: – TitleFull: Hydrology & Earth System Sciences Type: main |
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