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Grantee Research Project Results

2002 Progress Report: Modeling the Impacts of Climate Change on Wetland Ecosystems

EPA Grant Number: R829420E04
Title: Modeling the Impacts of Climate Change on Wetland Ecosystems
Investigators: Aravamuthan, Vibhas , Suhayda, Joseph N. , Singh, Vijay P. , Koppelman, David , Thiagarajan, Ganesh , Ramanujam, Jagannathan , Twilley, Robert
Institution: Louisiana State University - Baton Rouge , University of Louisiana at Lafayette , University of Missouri - Kansas City
Current Institution: Louisiana State University - Baton Rouge , University of Missouri - Kansas City
EPA Project Officer: Chung, Serena
Project Period: June 10, 2002 through June 9, 2004 (Extended to June 9, 2006)
Project Period Covered by this Report: June 10, 2002 through June 9, 2003
Project Amount: $129,210
RFA: EPSCoR (Experimental Program to Stimulate Competitive Research) (2001) RFA Text |  Recipients Lists
Research Category: EPSCoR (The Experimental Program to Stimulate Competitive Research)

Objective:

The overall goal of this research project is to develop a coupled global climate model (GCM) and hydrologic/landscape ecology model for assessing the impact of climate change on the hydrology and ecology of Louisiana wetlands. Because of the complex interaction between the climatologic, hydrologic, and ecologic processes, an integrated approach to study these processes is proposed. The proposed work involves the integration of a GCM, an overland flow hydrologic model, a coastal hydrodynamic model, and a landscape ecology model. The model would address the issue of integrating processes occurring at widely varying spatial and temporal scales. Although the model would be applied to Louisiana wetlands, it would not be site-specific, and should be applicable to other regions with minimal effort. Special attention would be paid to algorithmic development to enable the model to be architecture-independent. This would be achieved by developing the model code using the Fortran 90 language with High Performance Fortran extensions so that the model could be run on both uniprocessor and multiprocessor shared-memory or distributed-memory systems.

A stochastic weather generation model will be developed and calibrated using data archived at the Southern Regional Climate Center at Louisiana State University (LSU). The hydrologic and hydrodynamic components of the model will be calibrated and verified using river-stage and tide gage data collected by the U.S. Geological Survey (USGS) and the U.S. Army Corps of Engineers (USACE). The landscape ecology model will be calibrated using satellite images and aerial photographs.

The model will be used to study the climatological impacts on the hydrology and ecology of coastal Louisiana. The climatological scenarios include global warming caused by increased CO2 emissions and sea-level rise predicted by the GCM. The results of this study should be of interest to a broad spectrum of agencies and individual researchers involved in making scientific and management decisions regarding the protection, planning, and restoration of wetlands. Expected contributions of this study are: improved understanding of the coupled interactions between the climatologic, hydrologic, and ecologic factors at timescales of decades, and a first step towards the development of an effective tool for the management and restoration of ecosystems.

To accomplish the goal of this project, the specific objectives are to: (1) develop a stochastic weather generation model to obtain daily climatological data from monthly means forecasted by a GCM; (2) develop a coastal hydrodynamic and hydrologic model with sub-grid scale features such as rivers and barriers, for predicting tidal circulation in the wetlands; (3) develop a landscape ecology model to predict landscape changes resulting from changes in climatology and hydrology; (4) develop a rational methodology for coupling the various models with diverse time and spatial scales; (5) investigate the sensitivity of the above models to initial conditions, and to changes in model parameters; (6) use the model to quantify hydrological and ecological changes resulting from changes in climate, including an increase in CO2, and an increase in sea level; and (7) improve the understanding of the coupled interactions between the climatologic, hydrologic, and ecological factors at timescales of decades.

Progress Summary:

The project consists of developing several submodels and integrating them together. A summary of our accomplishments is provided below.

Component 1: Stochastic Weather Generation Model

Currently, a stochastic weather generation model, CLIGEN, developed by the Agricultural Research Service, is being adapted to Louisiana conditions. The model has been set up and is working, and preliminary results are being generated. Seventy percent of the work required to set up the model is completed. Integration of the National Center for Atmospheric Research Community Climate System Model 3.0 GCM outputs with a stochastic model currently is underway.

Component 2: Coastal Hydrologic and Hydrodynamic Model

Code development and verification for correctness of the model have been completed. Segments of the model have been parallelized to work under distributed supercomputers. A sediment-transport component has been added, and testing of this model is underway. New solution techniques for solving the algebraic systems of equations have been developed and currently are undergoing testing. Sixty percent of the work required to complete this model sub-component has been achieved.

Component 3: Landscape Ecology Model

Model formulation and coding currently are underway. Forty percent of the work required to complete this model sub-component has been achieved.

Component 4: Coupling of Different Sub-Models

A framework has been developed to couple these models at different spatial and temporal resolutions. The framework involves bringing the hydrodynamic and hydrologic components into sync with the timestep requirements for the ecological model. This involves averaging the hydrodynamic and stochastic model outputs on a daily basis, and using these to drive the landscape ecology submodel. Changes in the landscape in terms of land/water ratios and depth are propagated back to the hydrodynamic model.

Future Activities:

The future activities are to: (1) complete model testing and calibrations of the hydrodynamic and stochastic model components; (2) couple the model components so that they act in unison; (3) improve execution efficiency on parallel and distributed computing platforms; (4) perform model sensitivity to initial and boundary conditions; (5) use the model to quantify hydrological and ecological changes resulting from changes in climate, including an increase in CO2 and an increase in sea level; and (6) perform a 30-year model simulation to understand the impacts of changes in climate on wetland ecosystems.

Journal Articles:

No journal articles submitted with this report: View all 4 publications for this project

Supplemental Keywords:

global climate, coastal ecosystems, ecological modeling, regional climate model, hydrodynamic model, stochastic weather model., RFA, Air, Scientific Discipline, Geographic Area, Ecological Risk Assessment, State, Atmospheric Sciences, Hydrology, climate change, Environmental Monitoring, Global Climate Change, aquatic ecology, coastal ecosystems, global change, global warming, climate variability, fish habitat, land and water resources, climate models, wetlands, Louisiana (LA), watershed

Progress and Final Reports:

Original Abstract
  • 2003 Progress Report
  • 2004 Progress Report
  • Final Report
  • Top of Page

    The perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Conclusions drawn by the principal investigators have not been reviewed by the Agency.

    Project Research Results

    • Final Report
    • 2004 Progress Report
    • 2003 Progress Report
    • Original Abstract
    4 publications for this project

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