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a Dep. of Soil and Atmospheric Sciences, Univ. of Missouri-Columbia, 302 Anheuser-Busch Natural Resources Building, Columbia, MO 65211
b USDA-ARS, Univ. of Missouri, Columbia,Columbia, MO 65211
c Dep. of Biological Engineering, Univ. of Missouri, Columbia, 269 Agricultural Engineering Building, Columbia, MO 65211
* Corresponding author (hb91d{at}mizzou.edu)
Saturated hydraulic conductivity (Ksat) is an essential parameter for understanding soil hydrology. This study evaluated the Ksat of in situ monoliths and intact cores and compared the results with other studies for Missouri claypan soils. These Ksat values were used as runoff-model inputs to assess the impact of Ksat variation on simulated runoff. Lateral in situ Ksat of the topsoil was determined on 250 by 500 by 230 mm deep monoliths. These values were compared with the Ksat of 76 by 76 mm diam. intact cores with and without bentonite to seal macropores. Mean (± SD) lateral in situ Ksat was 72 ± 0.7 mm h-1 and mean intact core Ksat without bentonite was 312 ± 58 mm h-1. The mean intact core Ksat without bentonite was significantly larger than the lateral in situ Ksat (P = 0.03). The lateral in situ Ksat was not different from core Ksat with bentonite (71 ± 1.1 mm h-1). The intact core Ksat with bentonite differed from previous studies by 10 times. This was attributed to the variations in soil depth to claypan, macropore presence, and methodology. The impact of using an effective hydraulic conductivity (Keff) computed from measured Ksat on intact cores without bentonite underestimated the Water Erosion Prediction Project (WEPP) simulated runoff by 28% for a measured runoff event of 40 mm. The core Ksat with bentonite was correlated with measured runoff from long-term erosion-runoff plots. A quadratic regression explained 95% of the variability between measured and simulated runoff.
Abbreviations: EC, electrical conductivity Keff, effective hydraulic conductivity Ksat, saturated hydraulic conductivity REV, representative elementary volume SAR, Na adsorption ratio WEPP, Water Erosion Prediction Project
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