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A new modeling platform was developed to simulate spatially distributed sediment production and transport in agricultural landscapes. The sediment production at the grid scale was computed using the stand-alone Water Erosion Prediction Project-Hillslope Erosion code, while an advection-dispersion equation represented sediment transport. The model's performance was tested in the Water Resources and Erosion watersheds at the Oklahoma and Central Plains Agricultural Research Center, El Reno, OK, USA. Results showed that this modeling approach could capture the complex behavior of sediment under different management practices in the watersheds. The modeling framework provides mechanistic processes to simulate the fate and transport of sediment across the watershed at spatio-temporal scales that are useful in assessing the environmental impacts of management schemes. Therefore, this study is expected to help advance the current approaches to estimating soil erosion by bridging scale differences to capture the large-scale effects of small-scale soil erosion processes. • A new modeling framework was developed for estimating soil erosion. • Sediment production is evaluated in fully distributed settings. • Different sizes of sediment are considered in simulations. • The model provides mechanistic processes in simulating sediment transport. • The model is able to capture changes in land and management practices. [ABSTRACT FROM AUTHOR]

Landslides have long been considered one of the main erosive drivers that sculpt hillslopes over time. Tectonic forces raise slopes that can be sculpted by climate and the degree to which they can be sculpted depends upon the underlying lithology and hillslope geomorphology. Landslides destroy life and property and contribute to the evolution of mountain landscapes by generating and transporting hillslope sediments. In this study, we investigate the dynamics of soil-mantled hillslopes in eastern Oklahoma and western Arkansas, USA, by mapping shallow landslides, evaluating the frequency and magnitude of the landslides, and quantifying the surface geometries. We mapped 185 shallow landslides in a 150 km2 area. The approximate ages of landslides and the frequencies and magnitudes (area, volume and runout) were estimated using historical aerial photographs. The landslide database was then used to compute rate of landslide occurrence and sediment yield. In addition, landslide surface geometries, including slope, curvature and surface roughness, were determined from 10 m NED and 2 m LiDAR elevation data. The hillslope susceptibility studies, derived from elevation data, were augmented by our review of common historical accounts that link landslides in the study region to the 1952 M 5.4 El Reno, Oklahoma earthquake ~300 km away. In light of that case study, we determined the frequency of historical earthquakes that impart >2 kPa dynamic stresses for the study area since 1900 and find an increased potential for dynamic stress perturbation of landslide activity since ~2010. All these characteristics were then evaluated to understand the dynamics of hillslopes and hillslope susceptibility to shallow landslides. Frequency assessment of mapped landslides suggested that frequency of landslides increased significantly during 2005–2016 compared to 1995–2005. On average ~10 shallow landslides occurred every year during 2005–2016. These landslides alone contributed ~1.5 × 105 m3/yr (sediment yield rate: ~0.10 cm/yr) of sediments. Surface roughness values were relatively higher in landslide areas compared to that of surrounding non-landslide areas. The surface roughness index mapped ~84% of observed landslides, and suggests that the index could be used to map hillslope susceptibility to landslides for future planned studies. [ABSTRACT FROM AUTHOR]