The effects of digital elevation model resolution on the calculation and predictions of topographic wetness indices.

Other · Thu Dec 01 04:00:00 EST 2011

OSTI ID:1030960

One of the largest exports in the Southeast U.S. is forest products. Interest in biofuels using forest biomass has increased recently, leading to more research into better forest management BMPs. The USDA Forest Service, along with the Oak Ridge National Laboratory, University of Georgia and Oregon State University are researching the impacts of intensive forest management for biofuels on water quality and quantity at the Savannah River Site in South Carolina. Surface runoff of saturated areas, transporting excess nutrients and contaminants, is a potential water quality issue under investigation. Detailed maps of variable source areas and soil characteristics would therefore be helpful prior to treatment. The availability of remotely sensed and computed digital elevation models (DEMs) and spatial analysis tools make it easy to calculate terrain attributes. These terrain attributes can be used in models to predict saturated areas or other attributes in the landscape. With laser altimetry, an area can be flown to produce very high resolution data, and the resulting data can be resampled into any resolution of DEM desired. Additionally, there exist many maps that are in various resolutions of DEM, such as those acquired from the U.S. Geological Survey. Problems arise when using maps derived from different resolution DEMs. For example, saturated areas can be under or overestimated depending on the resolution used. The purpose of this study was to examine the effects of DEM resolution on the calculation of topographic wetness indices used to predict variable source areas of saturation, and to find the best resolutions to produce prediction maps of soil attributes like nitrogen, carbon, bulk density and soil texture for low-relief, humid-temperate forested hillslopes. Topographic wetness indices were calculated based on the derived terrain attributes, slope and specific catchment area, from five different DEM resolutions. The DEMs were resampled from LiDAR, which is a laser altimetry remote sensing method, obtained from the USDA Forest Service at Savannah River Site. The specific DEM resolutions were chosen because they are common grid cell sizes (10m, 30m, and 50m) used in mapping for management applications and in research. The finer resolutions (2m and 5m) were chosen for the purpose of determining how finer resolutions performed compared with coarser resolutions at predicting wetness and related soil attributes. The wetness indices were compared across DEMs and with each other in terms of quantile and distribution differences, then in terms of how well they each correlated with measured soil attributes. Spatial and non-spatial analyses were performed, and predictions using regression and geostatistics were examined for efficacy relative to each DEM resolution. Trends in the raw data and analysis results were also revealed.

• Research Organization: USDA Forest Service-Savannah River, New Ellenton, SC
• Sponsoring Organization: USDOE; USDOE EM Office of Program and Site Support (EM-50)
• DOE Contract Number: AI09-00SR22188
• OSTI ID: 1030960
• Report Number(s): 11-12-T; na
• Country of Publication: United States
• Language: English

Related Subjects

09 BIOMASS FUELS
60 APPLIED LIFE SCIENCES
BIOFUELS
BIOMASS
BULK DENSITY
CARBON
DISTRIBUTION
Digital Elevation Models
Topographic Wetness Index
Downslope Index
Variable Source Areas
Soils
Biofuels
Resolution
Geographic Information System
Prediction Map
Basin Delineation
EXPORTS
GEOLOGIC SURVEYS
LASERS
MANAGEMENT
NITROGEN
NUTRIENTS
OPTICAL RADAR
REMOTE SENSING
RESOLUTION
SATURATION
SOILS
TEXTURE
WATER QUALITY