Estimating WEPP Cropland Erodibility Values From Soil Properties
نویسندگان
چکیده
Highlights Very fine sand is the single most important variable for predicting rill and interrill erodibility values. Slope steepness property critical shear erosion. Erodibility prediction equations with best goodness-of-fits have both soil texture mineralogy terms. Equations to predict from texture, organic carbon, cation exchange, slope, taxonomy are proposed. Abstract. In late 1980s, USDA Agricultural Research Service, along other federal agencies multiple universities, collaborated develop a new physically based erosion model, Water Erosion Prediction Project (WEPP) Model. The WEPP model was intended replace Universal Soil Loss Equation include estimates upland runoff erosion, sediment delivery first order channels, routing through downstream channel network. technology estimated raindrop splash sheet flow (interrill erosion) concentrated (rill erosion). To make these estimates, required values (Ki). (Kr), (ðc) Core team determined that they needed estimate three measurable properties wide range of conditions. relationships between variables properties, field study carried out using rainfall simulation measure 36 soils. Sites were identified on croplands Washington Georgia Maine California, USA measurement. Concurrently, Conservation Service (SCS) detailed surveys laboratory analyses all sites provide large database physical, chemical, engineering properties. Correlation regression SCS This article provides summary procedures, data analyses, subsequent predictive developed. finalized in User Summary used sand, very clay, carbon contents cropland erodibility, but Coefficient Determination (r2) 0.55 or less. More complex developed mineralogical, geomorphic r2 up 0.81. Most better included terms clay mineralogy, often additional chemical A set simplified only readily available exchange capacity, slope steepness, taxonomic derived use within Model, r2Â greater than 0.5 estimating
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ژورنال
عنوان ژورنال: Journal of the ASABE
سال: 2023
ISSN: ['2769-3287', '2769-3295']
DOI: https://doi.org/10.13031/ja.15218