Application of a Coupled Vegetation Competition and Groundwater Simulation Model to Study Effects of Sea Level Rise and Storm Surges on Coastal Vegetation
Global climate change poses challenges to areas such as low-lying coastal zones, where sea level rise (SLR) and storm-surge overwash events can have long-term effects on vegetation and on soil and groundwater salinities, posing risks of habitat loss critical to native species. An early warning sys...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Published: |
MDPI
2015
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| Subjects: | |
| Online Access: | http://www.mdpi.com/2077-1312/3/4/1149 http://www.mdpi.com/2077-1312/3/4/1149 http://eprints.usm.my/38347/1/Application_of_a_Coupled_Vegetation_Competition_and_Groundwater.pdf |
| Summary: | Global climate change poses challenges to areas such as low-lying coastal zones,
where sea level rise (SLR) and storm-surge overwash events can have long-term effects on
vegetation and on soil and groundwater salinities, posing risks of habitat loss critical to native species. An early warning system is urgently needed to predict and prepare for the
consequences of these climate-related impacts on both the short-term dynamics of salinity
in the soil and groundwater and the long-term effects on vegetation. For this purpose, the
U.S. Geological Survey’s spatially explicit model of vegetation community dynamics along
coastal salinity gradients (MANHAM) is integrated into the USGS groundwater model
(SUTRA) to create a coupled hydrology–salinity–vegetation model, MANTRA. In MANTRA,
the uptake of water by plants is modeled as a fluid mass sink term. Groundwater salinity,
water saturation and vegetation biomass determine the water available for plant transpiration.
Formulations and assumptions used in the coupled model are presented. MANTRA is
calibrated with salinity data and vegetation pattern for a coastal area of Florida Everglades
vulnerable to storm surges. A possible regime shift at that site is investigated by simulating
the vegetation responses to climate variability and disturbances, including SLR and storm
surges based on empirical information. |
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