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Scope of Projects

Everglades regional: Sulfer & MeHg

Everglades subregional: WCA2A Wading Bird Suitability

Florida Coastal Everglades LTER

Everglades regional: SERES project

Spain Segura Basin: Ecological Economics

Everglades regional: CERP ASR

Everglades regional: CERP Decomp

Everglades WCA-1: unique restoration

Louisiana Davis Pond: restoration prototype

Everglades regional: cal/val (ELM v. 2.8)

Everglades regional: cal/val (ELM v. 2.5)

Florida Coastal Everglades (FCE) Long Term Ecological Research (LTER) project

FCE LTER We are collaborating on multi-decadal research and modeling in the coastal Everglades as part of the FCE LTER program. The regional 500 m resolution application of Everglades Landscape Model (ELM) serves as a framework in a multi-modelling approach to understanding ecological (esp. nutrient and salinity) gradients in the southern Everglades, with a current focus on the evolution of socio-ecological dynamics in south Florida that may occur with long term climate change. See our FCE Modeling and Scenarios group's summary for more information on our modeling-research progress and plans.

The target audience for this page is the scientific community interested in Everglades hydro-ecological dynamical responses to future scenarios.

The Model Documentation report on the ELM v2.8.4 historical (calibration/validation) performance assessment (including data, code, model performance assessment, and user's guide) is found in the Publications link. (Note: Code changes from ELM v2.8.4 to v2.8.6 and v2.9.0 do not effect any results related to this project).

Note: That report is separate from the documentation of the ELM applications that support the FCE Climate & Sea Level Rise project, which is the topic of this web page.

Here we document the assumptions and results of applying ELM v2.9.0 for this FCE Climate Change and Sea Level Rise project.

FCE Climate Change and Sea Level Rise: Summary of Our Scenario Analyses

Over the past several years, a collaboration organized by Florida Atlantic University and several government agencies involved multi-stakeholder workshops to develop plausible scenarios of future climate change and sea level rise (SLR) in south Florida. As part of this effort, the South Florida Water Management Model (SFWMM) was run under a variety of such future scenarios (Obeysekera et al. 2014). Daily flows through water control structures from those SFWMM runs drove the managed flows of the ELM, which explicitly integrates dynamic flux equations of hydrology, nutrients, plants, and soils (Fitz et al. 2011, Fitz and Paudel 2012). As detailed in Obeysekera et al. (2014), the 36-year Baseline future run assumed 2010 initial conditions, to which two future scenarios were compared: (a) a 10% decrease in precipitation, an increase of 1.5 degrees C and associated 7% increase in potential ET, and a 50-cm rise in sea level and (b) a 10% increase in precipitation, an increase of 1.5 degrees C and associated 7% increase in potential ET, and a 50-cm rise in sea level.

In the encroaching marine-influenced subregion: water depths and salinities increased under both scenarios along a topographic-influenced gradient; phosphorus accumulation rates generally increased under both scenarios, due to higher phosphorus concentrations in marine sources; and peat accretion rates generally decreased under both scenarios due to interactions between changing habitat types, altered nutrient availability, increased salinity, and subsequent decreases in plant productivity. Freshwater habitat (e.g., sawgrass marsh) area decreased by more than 25% under both scenarios and was largely replaced by mangroves and, in the increased rainfall scenario, open water as well. Adaptive planning efforts that foster upward peat accretion may help support both mangrove and freshwater marsh habitats. We infer that ecological effects related to sea level rise may occur in extremely oligohaline water, that topography will control the incursion of this zone as sea level rises, and that differences in freshwater availability will have ecologically significant effects within the oligohaline zone.

We published this manuscript (Flower et al. 2017) on the project and results.

See also this April 2017 (26 Mb) PowerPoint presentation of some of the principal results from the project.

Documentation of FCE Climate & SLR Project results

This section links to documentation of model assumptions, inputs, and outputs for the Climate_Base, decRFincET, and incRFincET simulation runs.

Timeline of updates to this page.

  • May 15, 2017 -- Posted results of the climate change & SLR analyses, refined from year-ago simulations.
  • Jan 21, 2016 -- Posted results of the climate change & SLR analyses, with the habitat succession module operating.
  • Dec 02, 2014 -- Posted results of the climate change & SLR analyses, without the habitat succession module operating.

    Page Contents - Major headings

  • SFWMM and ELM simulations for project
  • Input data common to all simulations
  • Input data on water management infrastructure
  • Perfomance Measures used to evaluate project simulations
  • Results: 3 scenarios: 2 climate change & SLR scenario runs compared to the 2010 Base scenario run   

    SFWMM and ELM simulations for project

    Table of SFWMM, ELM simulation runs

    Whereas we previously posted results of the above 2014 and 2016 simulations, for simplicity we now only include the latest (2017) simulations, which most acurately/effectively represent the interactions among hydrology, soils, and vegetation under these future scenarios.   

    Input data common to all simulations

    Note: The changes to rainfall and potential ET were made by modifying two parameters that applied globally across space and time. Initial sea level increase was made by alterations to tidal boundary condition time series data. Please see the below "Summary table of input data for simulations".


    Input data on water management infrastructure

    For detailed hydrologic assumptions used by the SFWMM (whose managed water control structure flows drive these ELM simulations), please see Obeysekera et al. 2014).

    Water management infrastructure data (no changes among the 3 simulations)


    Perfomance Measures

    (Below is the same file summary used in the CERP Decomp PIR1 project, and does not include what Decomp team referred to as ELM supplementary metrics). Performance Measures are quantitative metrics used to make relative comparisons among baseline and alternative simulations.


    Results: comparisons among 3 future scenarios

    For evaluations of the FCE Climate & SLR project, we made relative comparisons of the 2010 Base to the two climate and SLR scenarios. Note that is important to understand that none of these future projections should be considered accurate predictions of a highly uncertain future, but RELATIVE comparisons among simulations provide a useful understanding of the possible range of hydro-ecological responses to plausible future climate and sea level changes.

    The 2010 Base assumes current water management infrastructure and operations (i.e., no Comprehensive Everglades Restoration Plan or other restoration projects), projecting how the system may respond over a 36-yr future period if there were no changes to those existing water management practices.

    Both future climate scenarios also assumed current water management infrastructure and operations, projecting how the system may respond over a 36-yr future period if there were no changes to those existing water management practices, but under altered climate and sea level dynamics.

    For highly dynamic hydro-ecological variables, Performance Measures include difference maps of:
    a) landscape Period of Simulation mean ("MeanPOS" in variable's name), and
    b) landscape seasonal "snapshots" which are end-of-season 30d averages ("MeanRAW" in variable's name) for three example years:

    In addition to the Performance Measures described above (for CERP Decomp PIR1 project), for this project we provide a larger suite of hydro-ecological metrics. Included are difference-maps for

    decRFincET scenario

    incRFincET scenario

    Raw output files (Climate_Base, decRFincET, incRFincET (outdated, example-only))

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