Modelling the Effects of Wetland Restoration on Coastal Hydrology: A Case Study of Elkhorn Slough Watershed, California
- Univ. of California, Santa Cruz, CA (United States); Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
- Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
- Univ. of California, Santa Cruz, CA (United States); Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
- San Jose State Univ., Moss Landing, CA (United States); Elkhorn Slough National Estuarine Research Reserve, Moss Landing, CA (United States)
- Elkhorn Slough National Estuarine Research Reserve, Moss Landing, CA (United States)
- Univ. of California, Santa Cruz, CA (United States)
Coastal wetlands, some of the most productive ecosystems on Earth, provide critical ecosystem services, including support of biodiversity, carbon sequestration and flood protection. In recent decades, these ecosystems have experienced extensive coastal wetland loss. Coastal wetland restoration provides a beacon of hope, offering a chance to reclaim these important habitats. However, even with billions of dollars invested worldwide in restoring coastal wetlands, we still lack comprehensive knowledge about the effectiveness of these restoration efforts in recovering wetland ecosystem functions and how future climate change may affect these efforts. The ability to evaluate how these ecosystems will function in the future is vital for examining current investments and developing future protection and management plans. We selected Elkhorn Slough, a tidal estuary, in California, to investigate the impact of wetland restoration and sea level rise (SLR) on coastal hydrology using the process‐based coastal hydrologic model, Advanced Terrestrial Simulator (ATS), informed by site‐specific data. We designed a novel modelling workflow for incorporating wetland restoration features into land cover and soil properties for the model parameterization. The validation results demonstrate a strong agreement between modelled and observed data. We studied the characteristics of coastal watershed hydrology, then focused on the surface water dynamics at two wetland sites within Elkhorn Slough, a reference site and a restored site. Our simulation results indicate that the restored site successfully maintains surface elevation, resulting in reduced surface inundation. We also examined the impact of wetland restoration under expected SLR over the next few decades. The low‐lying Yampah Marsh, the reference site, is likely to be inundated due to future SLR when highest tides arrive, while a higher percentage of Hester Marsh, the restored site, would retain marsh vegetation in coming decades, regardless of tidal conditions. Our study provides important information for examining the outcome of restoration practices that include surface elevation in tidal wetlands under climate changes.
- Research Organization:
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
- Sponsoring Organization:
- National Science Foundation (NSF); USDOE Office of Science (SC), Biological and Environmental Research (BER). Earth & Environmental Systems Science (EESS)
- Grant/Contract Number:
- AC02-05CH11231
- OSTI ID:
- 3008761
- Journal Information:
- Hydrological Processes, Journal Name: Hydrological Processes Journal Issue: 12 Vol. 39; ISSN 0885-6087; ISSN 1099-1085
- Publisher:
- WileyCopyright Statement
- Country of Publication:
- United States
- Language:
- English
Similar Records
Data-model files associated with the manuscript "Modeling the Effects of Wetland Restoration on Coastal Hydrology: A Case Study of Elkhorn Slough Watershed, California"
AmeriFlux US-EKH Elkhorn Slough Hester Marsh
AmeriFlux US-EKP Elkhorn Slough Porter Marsh
Dataset
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Thu Nov 13 23:00:00 EST 2025
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OSTI ID:2588510
AmeriFlux US-EKH Elkhorn Slough Hester Marsh
Dataset
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Tue Dec 03 23:00:00 EST 2024
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OSTI ID:2479624
AmeriFlux US-EKP Elkhorn Slough Porter Marsh
Dataset
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Tue Dec 03 23:00:00 EST 2024
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OSTI ID:2479625