Terrain attribute soil mapping for predictive continuous soil property maps
Abstract
The current U.S. Soil Survey information is provided in polygon map units with soil property attributes represented with overlapping ranges between map units. The polygon maps do not represent the soil continuum that conforms to the actual landscape and the soil scientist expert knowledge accumulated during the field survey. Geographic Information System (GIS) technologies and software in combination with high resolution spatial data provide an opportunity to generate continuous raster based soil property maps based on terrain attribute soil mapping (TASM) that is compatible with distributed hydrologic modeling. This requires the development of methods to translate Soil Survey Geographic Database (SSURGO) qualitative soil-landscape models to numerical ones. Related to the current SSURGO data is the soil carbon (SC) stock, especially the spatial distribution and stability of SC pools. The recent concerns about climate change, associated with high levels of atmospheric CO2, has brought new interest in the role of the SC pool as a sink for the atmospheric CO 2. Human activities in the Corn Belt and parts of the Great Plains in the United States have reduced the SC stock by half from historic levels. Restoring some of the SC pool would require understanding of its spatial distribution and stability for future predictions. TASM improved the accuracy of predicted continuous soil property maps compared to SSURGO. On average, TASM predicted values for depth to lithic/paralithic contact and depth to till/outwash were within 26 cm and 40 cm of measured values compared to SSURGO with 57 cm and 60 cm, respectively. The Distributed Hydrology Soil Vegetation Model (DHSVM) predicted streamflow without calibration demonstrating the benefits of using the correct soil input information. In addition, the TASM predicted continuous soil depth maps provided a better performance for the DHSVM predicted streamflow compared to SSURGO soil maps, especially for 90 m pixel resolution. SC distribution and stability followed the patterns of soil wetness and was related to soil landscape position. Wetter soils on lower positions and depressions had the highest SC stock. At the beginning of soil incubation the daily CO2 evolved was higher and more intense for the wetter areas indicating a less stable SC pool. The SC pool distribution and stability can be predicted based on soil wetness and landscape position. The management of these areas can potentially increase SC stock. These examples demonstrate the potential benefits of making continuous rater soil maps and property maps using expert knowledge; existing soil information and terrain attribute analysis.
Degree
Ph.D.
Advisors
Owens, Purdue University.
Subject Area
Hydrologic sciences|Soil sciences
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