Dive into the research topics of 'Scale effects of STATSGO VS. SSURGO soil databases on water quality predictions'. In the United States, STATSGO and SSURGO are most commonly available soil databases. This variation was due to the influence of initial nitrogen and phosphorus concentrations in the soil which was varied with soil types in the SSURGO database, whereas they were uniform across the watershed with STATSGO database (as it was only one soil type for the larger scale). Under these conditions, 18% of the cropland received animal manure, and 61%, 14% or 24% of this animal manure was broadcast, incorporated or injected, respectively. 28, No. Site-specific information on planting and harvesting dates and tillage management practices for 2001 were collected for each field within the High Island Creek watershed. 2006-2013 Scientific Research Publishing Inc. All rights reserved. In the United States, STATSGO and SSURGO are most commonly available soil databases. 2006, pp. 4, 2004, pp. 3.5. In contrast, agency leaders and policy makers are typically concerned about decadal or centennial regional trends in water quality at the scale of watersheds, river basins, counties, provinces, states, countries, and continents. This brings up an important issue in developing TMDLs for impaired watersheds where conflicting interests of stakeholders may opt for soil database that support their interests. GIS overlay analysis resulted in 224 and 29 THRUs for SSURGO and STATSGO soil databases, respectively. 39, No. For phosphorus, the STATSGO-based model predictions explained 92% of the variability in observed losses at the outlet of the High Island Creek watershed, compared with 99% for the SSURGO-based predictions. were similar when the percentage of crop land under conservation tillage changed from existing to various scenarios. 296-307. Climatic data such as daily values of precipitation and mean air temperature used in the water quality simulation were the daily averages of data recorded at four weather stations within the study watershed to account for spatial variability. 616-624. Other enhancements included adding the [8] potential evapotranspiration method as an alternative to the Ritchie method [9]; modifying the runoff curve number based on daily soil water conditions; adding a Green-Ampt infiltration model; modeling snowmelt; and accounting for macropore flow. Similar trends were observed with the SSURGO database; however, SSURGO-based predicted nitrate losses were consistently greater than that for STATSGO-based predictions, while SSURGO-based predictions of phosphorus loss was consistently less than from the STATSGO-based predictions. Discharges at the outlet of the watershed were measured using a 1-stage measuring device which was connected to a Campbell Scientific Inc. (CSI, Logan, UT). reminder about moving wetlands and tile drainage over to "integration" branch. CR10 data logger. Home | About SCIRP | Sitemap | Contact Us. Nonpoint source pollution from crop land is a widespread problem in North America. 3, 2008, pp. This study attempts to quantify the effects of spatial resolution of two soil databases on water quality. The unique HRUs with similar watershed characteristics were grouped to form THRUs. Figure 5. 3.4. <> The STATSGO-based predictions accounted for about 77% of the variations in the measured nitrate loadings compared to 82% with SSURGObased predictions. However, evaluation of alternative management practices indicated that STATSGO based predicted annual nitrate losses are consistently higher than that for SSURGO data and vice-versa for predicted phosphorus losses. COMPARISON OF SIMULATION RESULTS USING SSURGO-BASED AND STATSGO-BASED PARAMETERS IN A DISTRIBUTED HYDROLOGIC MODEL, Integration of SSURGO maps and soil parameters within a geographic information system and nonpoint source pollution model system, Spatial variability of digital soil maps and its impact on regional ecosystem modeling, Using SSURGO data to improve Sacramento Model a priori parameter estimates, GIS-based solute transport modeling applications: scale effects of soil and climate data input, Assessment of Soil Erosion Risk within a Subwatershed using GIS and RUSLE with a Comparative Analysis of the use of STATSGO and SSURGO Soil Databases, Darren L. Ficklin, Yuzhou Luo, … Sarah E. Gatzke, View 2 excerpts, cites results and methods, View 3 excerpts, cites background, results and methods, View 3 excerpts, cites background and results, View 5 excerpts, cites background and methods, View 3 excerpts, references methods and background, View 4 excerpts, references background and methods, View 3 excerpts, references background and methods, View 2 excerpts, references background and methods, By clicking accept or continuing to use the site, you agree to the terms outlined in our. in addition to our traditional MUKEY view? endobj Statistical measures such as mean and Root Mean Square Error (RMSE), coefficient of determination (r2) and slope and intercept of the least square regression line between measured and predicted values, and index of agreement (d) [27], were used to evaluate the match between measured and predicted flow and nitrate discharges for the calibration period. Similarly, STATSGO-based annual phosphorus loss was 20% to 25% greater than phosphorus loss predicted using the SSURGO database. 2063- 2071. Currently just a dumping ground for 7/24/2015 meeting STATSGO versus SSURGO as inputs for different water quality-related models. Researchers and watershed managers have been monitoring and/or modeling the transport and fate of agricultural pollutants at different spatial scales. } and Mulla, David J. T1 - scale effects of STATSGO VS. soil! - scale effects of STATSGO VS. SSURGO soil data resolution Matter STATSGO is about 2 ha in High. In Rainfall-Runoff modeling across Wisconsin, ” Transactions of ASAE, Vol %,.! Booktitle = `` Gowda, A. D. Ward, D. a from.! Samplers ( statsgo vs ssurgo ISCO, Lincoln, NE ) Standards and Emerging TMDL '' and... Island Creek watershed poorly drained Basin, ” Transactions of ASAE, Vol far, little is on... 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