A systematic review of morphological models of salt marshes
Salt marshes are among the most important coastal wetlands and provide critical ecological services, including climate regulation, biodiversity maintenance, and blue carbon sequestration. However, most salt marshes worldwide are shrinking, owing to the effects of natural and human factors, such as c...
| المؤلفون الرئيسيون: | , , , |
|---|---|
| التنسيق: | مقال |
| اللغة: | English |
| منشور في: |
Elsevier
2023-12-01
|
| سلاسل: | Water Science and Engineering |
| الموضوعات: | |
| الوصول للمادة أونلاين: | http://www.sciencedirect.com/science/article/pii/S1674237023000844 |
| _version_ | 1827728371066339328 |
|---|---|
| author | Xin-chen Wang Pei Xin Zeng Zhou Fu-xin Zhang |
| author_facet | Xin-chen Wang Pei Xin Zeng Zhou Fu-xin Zhang |
| author_sort | Xin-chen Wang |
| collection | DOAJ |
| description | Salt marshes are among the most important coastal wetlands and provide critical ecological services, including climate regulation, biodiversity maintenance, and blue carbon sequestration. However, most salt marshes worldwide are shrinking, owing to the effects of natural and human factors, such as climate change and artificial reclamation. Therefore, it is essential to understand the decline in the morphological processes of salt marshes, and accordingly, the likely evolution of these marshes, in order to enable measures to be taken to mitigate this decline. To this end, this study presented an extensive systematic review of the current state of morphological models and their application to salt marshes. The emergence of process-based (PB) and data-driven (DD) models has contributed to the development of morphological models. In morphodynamic simulations in PB models, multiple physical and biological factors (e.g., the hydrodynamics of water bodies, sediment erosion, sediment deposition, and vegetation type) have been considered. The systematic review revealed that PB models have been extended to a broader interdisciplinary field. Further, most DD models are based on remote sensing database for the prediction of morphological characteristics with latent uncertainty. Compared to DD models, PB models are more transparent but can be complex and require a lot of computational power. Therefore, to make up for the shortcomings of each model, future studies could couple PB with DD models that consider vegetation, microorganisms, and benthic animals together to simulate or predict the biogeomorphology of salt marsh systems. Nevertheless, this review found that there is a lack of unified metrics to evaluate model performance, so it is important to define clear objectives, use multiple metrics, compare multiple models, incorporate uncertainty, and involve experts in the field to provide guidance in the further study. |
| first_indexed | 2024-03-10T23:29:22Z |
| format | Article |
| id | doaj.art-0fabc7374d974eeb8f4d3b4d1753e9c6 |
| institution | Directory Open Access Journal |
| issn | 1674-2370 |
| language | English |
| last_indexed | 2024-03-10T23:29:22Z |
| publishDate | 2023-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Water Science and Engineering |
| spelling | doaj.art-0fabc7374d974eeb8f4d3b4d1753e9c62023-11-19T04:34:31ZengElsevierWater Science and Engineering1674-23702023-12-01164313323A systematic review of morphological models of salt marshesXin-chen Wang0Pei Xin1Zeng Zhou2Fu-xin Zhang3College of Water Conservancy and Hydropower Engineering, Hohai University, Nanjing 210098, ChinaState Key Laboratory of Hydrology–Water Resources and Hydraulic Engineering, Hohai University, Nanjing 210098, China; Yangtze Institute for Conservation and Development, Hohai University, Nanjing 210098, China; Corresponding author.Jiangsu Key Laboratory of Coast Ocean Resources Development and Environment Security, Hohai University, Nanjing 210098, ChinaCollege of Water Conservancy and Hydropower Engineering, Hohai University, Nanjing 210098, ChinaSalt marshes are among the most important coastal wetlands and provide critical ecological services, including climate regulation, biodiversity maintenance, and blue carbon sequestration. However, most salt marshes worldwide are shrinking, owing to the effects of natural and human factors, such as climate change and artificial reclamation. Therefore, it is essential to understand the decline in the morphological processes of salt marshes, and accordingly, the likely evolution of these marshes, in order to enable measures to be taken to mitigate this decline. To this end, this study presented an extensive systematic review of the current state of morphological models and their application to salt marshes. The emergence of process-based (PB) and data-driven (DD) models has contributed to the development of morphological models. In morphodynamic simulations in PB models, multiple physical and biological factors (e.g., the hydrodynamics of water bodies, sediment erosion, sediment deposition, and vegetation type) have been considered. The systematic review revealed that PB models have been extended to a broader interdisciplinary field. Further, most DD models are based on remote sensing database for the prediction of morphological characteristics with latent uncertainty. Compared to DD models, PB models are more transparent but can be complex and require a lot of computational power. Therefore, to make up for the shortcomings of each model, future studies could couple PB with DD models that consider vegetation, microorganisms, and benthic animals together to simulate or predict the biogeomorphology of salt marsh systems. Nevertheless, this review found that there is a lack of unified metrics to evaluate model performance, so it is important to define clear objectives, use multiple metrics, compare multiple models, incorporate uncertainty, and involve experts in the field to provide guidance in the further study.http://www.sciencedirect.com/science/article/pii/S1674237023000844MorphologySalt marshPredictive modelingTidal creekTidal flat |
| spellingShingle | Xin-chen Wang Pei Xin Zeng Zhou Fu-xin Zhang A systematic review of morphological models of salt marshes Water Science and Engineering Morphology Salt marsh Predictive modeling Tidal creek Tidal flat |
| title | A systematic review of morphological models of salt marshes |
| title_full | A systematic review of morphological models of salt marshes |
| title_fullStr | A systematic review of morphological models of salt marshes |
| title_full_unstemmed | A systematic review of morphological models of salt marshes |
| title_short | A systematic review of morphological models of salt marshes |
| title_sort | systematic review of morphological models of salt marshes |
| topic | Morphology Salt marsh Predictive modeling Tidal creek Tidal flat |
| url | http://www.sciencedirect.com/science/article/pii/S1674237023000844 |
| work_keys_str_mv | AT xinchenwang asystematicreviewofmorphologicalmodelsofsaltmarshes AT peixin asystematicreviewofmorphologicalmodelsofsaltmarshes AT zengzhou asystematicreviewofmorphologicalmodelsofsaltmarshes AT fuxinzhang asystematicreviewofmorphologicalmodelsofsaltmarshes AT xinchenwang systematicreviewofmorphologicalmodelsofsaltmarshes AT peixin systematicreviewofmorphologicalmodelsofsaltmarshes AT zengzhou systematicreviewofmorphologicalmodelsofsaltmarshes AT fuxinzhang systematicreviewofmorphologicalmodelsofsaltmarshes |