Submitted to: Transactions of the ASABE
Publication Type: Peer reviewed journal
Publication Acceptance Date: 2/3/2008
Publication Date: 4/30/2008
Citation: Renschler, C.S., Flanagan, D.C. 2008. Site-specific decision-making based on RTK GPS survey and six alternative elevation data sources: soil erosion prediction. Transactions of the American Society of Agricultural and Biological Engineers. 51(2):413-424. Interpretive Summary: It is becoming more and more important to be able to estimate soil erosion and sediment loss from landscape areas. In order to do this in an efficient way, digital geographic elevation information can be used, from a variety of sources. One source is elevation data that is derived from existing paper maps, while newer methods use multiple satellite signals to determine the elevation at a position on the Earth’s surface (Global Positioning System – GPS). Many farmers already have simple GPS systems for monitoring grain yields across a field. This paper provides information on predicting soil erosion from a small agricultural watershed using a variety of digital elevation information, from less accurate to more accurate sources. Ultimately we wanted to see how detailed (and expensive) a GPS system is needed to make satisfactory soil erosion predictions for small watersheds. We found that all of the systems could reasonably outline the watershed boundary and locate the channels. The more precise measurements provided more precise soil erosion estimates across a range of scales. However, we also found that erosion model elevation input data based on contour lines from paper maps can provide sufficiently accurate data to predict runoff and sediment yield from a small watershed and to identify specific locations within the watershed with hillslope erosion problems. Information presented here impacts farmers, land managers, soil conservationists, engineers and others involved in assessing runoff and sediment loss from watersheds. The work impacts recommendations for the type of data or GPS needed. Low-cost systems can be useful in estimating watershed sediment yield and locating potentially high hillslope erosion regions. More precise and expensive GPS systems are needed if more precise erosion predictions are required at small spatial scales (down to 0.01 ha).
Technical Abstract: Soil erosion modeling requires substantial and accurate data to obtain meaningful results for decision-making in soil and water conservation practices. Today's precision farming equipment based on Global Positioning Systems (GPS), enables landowners to gather spatially distributed topographic data in Real Time Kinematic (RTK) mode that has the potential to be used in addition or as substitute for commonly available topographic data sources. In contrast to highly accurate commercial photogrammetric surveys, the United States Geological Survey (USGS) provides nationwide coverage of topographic contour lines and Digital Elevation Models (DEM) at no cost. The latter ones are considered insufficiently accurate in their topographical representation to be able to meaningfully apply detailed process-based soil erosion assessment tools at the field scale. This comprehensive accuracy test uses results of the spatially distributed soil erosion assessment with the Water Erosion Prediction Project (WEPP) model supported by Geographic Information Systems (GIS) and discusses the usefulness of the available data sets from a decision-maker's perspective. The impact of the accuracy of six alternative topographical data sources on predicting soil erosion rates using WEPP is compared to erosion predictions using elevation measurements from a survey-grade RTK GPS with cm accuracy. The results show that the more precise topographic measurements with a photogrammetric survey and Differential GPS units yield more precise soil loss predictions at all scales ranging from individual raster cells (0.01 ha) and hillslope areas (0.5 ha) to small watersheds (>4 ha). The results also demonstrate that DEMs based on contour lines from commonly available data can be as good as the most accurate data sets to predict runoff and sediment yields for a 30 ha watershed and to indicate the hillslope areas of concern with known soil loss problems successfully.