Record Display for the EPA National Library Catalog

RECORD NUMBER: 265 OF 4230

OLS Field Name OLS Field Data
Main Title Application of Topographically Distributed Models of Energy, Water and Carbon Balance over the Columbia River Basin: A Framework for Simulating Potential Climate Change Effects at the Regional Scale.
Author Turner, D. P. ; Marks, D. G. ;
CORP Author ManTech Environmental Technology, Inc., Research Triangle Park, NC.;Environmental Protection Agency, Research Triangle Park, NC. Neurotoxicology Div.
Publisher 1993
Year Published 1993
Report Number EPA-68-C6-0006; EPA/600/A-94/018;
Stock Number PB94-141561
Additional Subjects Temperature ; Climatic changes ; Solar radiation ; Models ; Columbia River Basin ; Energy ; Carbon ; Water balance ; Productivity ; Estimates ; Regions ; Vegetation ; Evaportranspiration ; Soil properties ; Soil water ; Moisture content ; Time series analysis ; Meteorological data ;
Holdings
Library Call Number Additional Info Location Last
Modified
Checkout
Status
NTIS  PB94-141561 Most EPA libraries have a fiche copy filed under the call number shown. Check with individual libraries about paper copy. NTIS 05/14/1994
Collation 16p
Abstract
The investigation of many issues relating to global change is dependent on spatially distributed models of land surface processes. These models may originate as point models, and the methodology for 'scaling up' to the regional level remains a significant research issue. Here, the authors describe an approach to running a carbon and water balance model (Forest -BGC) over a gridded digital elevation surface for the Columbia River Basin. Estimates were made at each 1 sq km grid point at a daily time step over a two week period (May 1-15, 1990) for climate variables required by the model including solar radiation, minimum and maximum air temperature and precipitation. The daily time series for the climate drivers was developed from interpolations of regional meteorological data. To initialize the run, surfaces for vegetation properties including biome type and leaf area index (LAI), as well as soil factors including water holding capacity and carbon content, were also prepared. The spatial distribution of vegetation type from land cover maps derived in part from satellite remote sensing.