An Alternative Statistical Model for Predicting Salinity Variations in Estuaries Article Swipe
Ronghui Ye
,
Jun Kong
,
Chengji Shen
,
Jinming Zhang
,
Weisheng Zhang
·
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.3390/su122410677
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.3390/su122410677
Accurate salinity prediction can support the decision-making of water resources management to mitigate the threat of insufficient freshwater supply in densely populated estuaries. Statistical methods are low-cost and less time-consuming compared with numerical models and physical models for predicting estuarine salinity variations. This study proposes an alternative statistical model that can more accurately predict the salinity series in estuaries. The model incorporates an autoregressive model to characterize the memory effect of salinity and includes the changes in salinity driven by river discharge and tides. Furthermore, the Gamma distribution function was introduced to correct the hysteresis effects of river discharge, tides and salinity. Based on fixed corrections of long-term effects, dynamic corrections of short-term effects were added to weaken the hysteresis effects. Real-world model application to the Pearl River Estuary obtained satisfactory agreement between predicted and measured salinity peaks, indicating the accuracy of salinity forecasting. Cross-validation and weekly salinity prediction under small, medium and large river discharges were also conducted to further test the reliability of the model. The statistical model provides a good reference for predicting salinity variations in estuaries.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/su122410677
- https://www.mdpi.com/2071-1050/12/24/10677/pdf?version=1608610704
- OA Status
- gold
- Cited By
- 4
- References
- 40
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3115445300
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W3115445300Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.3390/su122410677Digital Object Identifier
- Title
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An Alternative Statistical Model for Predicting Salinity Variations in EstuariesWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2020Year of publication
- Publication date
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2020-12-21Full publication date if available
- Authors
-
Ronghui Ye, Jun Kong, Chengji Shen, Jinming Zhang, Weisheng ZhangList of authors in order
- Landing page
-
https://doi.org/10.3390/su122410677Publisher landing page
- PDF URL
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https://www.mdpi.com/2071-1050/12/24/10677/pdf?version=1608610704Direct link to full text PDF
- Open access
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- OA status
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goldOpen access status per OpenAlex
- OA URL
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https://www.mdpi.com/2071-1050/12/24/10677/pdf?version=1608610704Direct OA link when available
- Concepts
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Salinity, Estuary, Environmental science, Discharge, Statistical model, Hydrology (agriculture), Reliability (semiconductor), Statistics, Oceanography, Geology, Mathematics, Drainage basin, Geography, Geotechnical engineering, Physics, Cartography, Power (physics), Quantum mechanicsTop concepts (fields/topics) attached by OpenAlex
- Cited by
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4Total citation count in OpenAlex
- Citations by year (recent)
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2025: 1, 2024: 2, 2022: 1Per-year citation counts (last 5 years)
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40Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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