Response of soil aggregate disintegration to the different content of organic carbon and its fractions during splash erosion

Aggregate disintegration is a critical process in soil splash erosion. However, the effect of soil organic carbon (SOC) and its fractions on soil aggregates disintegration is still not clear. In this study, five soils with similar clay contents and different contents of SOC have been used. The effects of slaking and mechanical striking on splash erosion were distinguished by using deionized water and 95% ethanol as raindrops. The simulated rainfall experiments were carried out in four heights (0.5, 1.0, 1.5 and 2.0 m). The result indicated that the soil aggregate stability increased with the increases of SOC and light fraction organic carbon (LFOC). The relative slaking and the mechanical striking index increased with the decreases of SOC and LFOC. The reduction of macroaggregates in eroded soil gradually decreased with the increase of SOC and LFOC, especially in alcohol test. The amount of macroaggregates (>0.25 mm) in deionized water tests were significantly less than that in alcohol tests under the same rainfall heights. The contribution of slaking to splash erosion increased with the decrease of heavy fractions organic carbon. The contribution of mechanical striking was dominant when the rainfall kinetic energy increased to a range of threshold between 9 J m⁻² mm⁻¹ and 12 m⁻² mm⁻¹. This study could provide the scientific basis for deeply understanding the mechanism of soil aggregates disintegration and splash erosion.     

Development of Land Resources in Transitional Zones Based on Ecological Security Pattern: A Case Study in China

Land use based on landscape ecological security pattern provides a scientific basis for alleviating conflicts between land conservation and human use, ensuring concomitant economic development and ecological integrity. The majority of studies by Chinese researchers have been focused on the carrying capacity and land development intensity, and less attention has been paid to the ecological security pattern of the landscape in Mianzhu in the transitional zone between the Chengdu Plain region and the Longmen Mountains, western China. However, land resources are undergoing significant changes resulting from land use associated with rapid economic development and demographic growth. In this study, we constructed a minimum cumulative resistance model in Mianzhu in the transitional zone, and the land space was divided into optimized development areas, key development areas, restricted development areas, and prohibited development areas according to the landscape ecological security pattern based on the model surface. These land use types covered 7218.39 ha, 17,974.75 ha, 21,545.39 ha, and 77,791.46 ha, respectively. We also examined land use changes over the last 20 years and quantitatively analyzed the relationships between land use changes and geographic factors based on remote sensing and geographic information system. The information obtained from this research ultimately impacts future policies and plans regarding land resources and can be used to promote the sustainable use of land resources in the region.

     

Parallelized combined finite-discrete element (FDEM) procedure using multi-GPU with CUDA

This paper focuses on the efficiency of finite discrete element method (FDEM) algorithmic procedures in massive computers and analyzes the time-consuming part of contact detection and interaction computations in the numerical solution. A detailed operable GPU parallel procedure was designed for the element node force calculation, contact detection, and contact interaction with thread allocation and data access based on the CUDA computing. The emphasis is on the parallel optimization of time-consuming contact detection based on load balance and GPU architecture. A CUDA FDEM parallel program was developed with the overall speedup ratio over 53 times after the fracture from the efficiency and fidelity performance test of models of in situ stress, UCS, and BD simulations in Intel i7-7700K CPU and the NVIDIA TITAN Z GPU. The CUDA FDEM parallel computing improves the computational efficiency significantly compared with the CPU-based ones with the same reliability, providing conditions for achieving larger-scale simulations of fracture.