EFFECT OF DIGITAL ELEVATION MODEL RESOLUTION ON EMPIRICAL ESTIMATION OF SOIL LOSS AND SEDIMENT TRANS

来源 :International Journal of Sediment Research | 被引量 : 0次 | 上传用户:dysongbo
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The horizontal accuracy of topographic data represented by digital elevation model (DEM) resolution brings about uncertainties in landscape process modeling with raster GIS. This paper presents a study on the effect of topographic variability on cell-based empirical estimation of soil loss and sediment transport. An original DEM of 10m resolution for a case watershed was re-sampled to three realizations of higher grid sizes for a comparative examination. Equations based on the USLE are applied to the watershed to calculate soil loss from each cell and total sediment transport to streams. The study found that the calculated total soil loss from the watershed decreases with the increasing DEM resolution with a linear correlation as spatial variability is reduced by cell aggregation. The USLE topographic factors (LS) extracted from applied DEMs represent spatial variability, and determine the estimations as shown in the modeling results. The commonly used USGS 30m DEM appears to be able to reflect essentia The horizontal accuracy of topographic data represented by digital elevation model (DEM) resolution brings about uncertainties in landscape process modeling with raster GIS. This paper presents a study on the effect of topographic variability on cell-based empirical estimation of soil loss and sediment transport. An original DEM of 10m resolution for a case watershed was re-sampled to three realizations of higher grid sizes for a comparative examination. Equations based on the USLE are applied to the watershed to calculate soil loss from each cell and total sediment transport to streams. The study found that the calculated total soil loss from the watershed decreases with the increasing DEM resolution with a linear correlation as spatial variability is reduced by cell aggregation. The USLE topographic factors (LS) extracted from applied DEMs represent spatial variability, and determine the estimations The commonly used USGS 30m DEM appears to be able t o reflect essentia
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