Dissolved organic matter in surface runoff in the Loess Plateau of China: The role of rainfall events and land-use

Exploring the chemical characterization of dissolved organic matter (DOM) is important for understanding the fate of laterally transported organic matter in watersheds. We hypothesized that differences in water-extractable organic matter (WEOM) in soils of varying land uses and rainfall events may significantly affect the quality and the quantity of stream DOM. To test our hypotheses, characteristics of rainfall-runoff DOM and WEOM of source materials (topsoil from different land uses and gullies, as well as typical vegetation) were investigated at two adjacent catchments in the Loess Plateau of China, using ultraviolet–visible absorbance and excitation emission matrix fluorescence with parallel factor analysis (PARAFAC). Results indicated that land-use types may significantly affect the chemical composition of soil WEOM, including its aromaticity, molecular weight, and degree of humification. The PARAFAC analysis demonstrated that the soils and stream water were dominated by terrestrial/allochthonous humic-like substances and microbial transformable humic-like fluorophores. Shifts in the fluorescence properties of stream DOM suggested a pronounced change in the relative proportion of allochthonous versus autochthonous material under different rainfall patterns and land uses. For example, high proportions of forestland could provide more allochthonous DOM input. This study highlights the relevance of soils and hydrological dynamics on the composition and fluxes of DOM issuing from watersheds. The composition of DOM in soils was influenced by land-use type. Precipitation patterns influenced the proportion of terrestrial versus microbial origins of DOM in surface runoff. Contributions of allochthonous, terrestrially derived DOM inputs were highest from forested landscapes.     

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.     

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.