The rate of soil detachment by water flow indicates soil erosion intensity directly. The exact relation between soil detachment rate and actual sediment load in water flow, however, is still unclear, and the existing relationships have not been adequately tested. The aims of the present study were to investigate the response of soil detachment rate to sediment load using rill flume data with loessial soil and to quantitatively examine the soil detachment equations in the WEPP and EUROSEM soil erosion models. Six slopes were combined with seven flow discharges to measure detachment rates under seven sediment loads using a rill flume with a soil-feeding hopper. Significant differences were found among the soil detachment rate by different sediment loads in low sediment load levels, but an insensitive response of soil detachment rate to sediment load was found under high levels of sediment load. The soil detachment rate was proved to be negatively linearly correlated with sediment load. The rill detachment equation in the WEPP model predicted the soil detachment rate by rill flow very well under our experiment condition. The soil detachment equation in the EUROSEM model underestimated the detachment rates under controlled conditions, but removing the setting velocity from the equation greatly improved prediction. Further experiments that could reflect the dynamic convective detachment and deposition process need to be conducted to compare with the present examination results and to further understand rill erosion processes.

The increasing generation of solid waste is recognized as one of the leading environmental and economic challenges. Optimal waste management, particularly in the agricultural and industrial sectors, necessitates innovative approaches for the efficient management of vital resources, including soil and water. One practical solution is the production of morpho-genetic porous carbon (MGPC) as a type of activated biochar, which has wide applications due to its porous structure, chemical and thermal stability, and high specific surface area. In this study, biochar was prepared with eight types of waste, including rice straw, vineyard prunings, palm prunings, sawdust, vinasse, poultry slaughterhouse waste, paper mill waste, and tissue paper production waste. Biochar production was carried out through a pyrolysis process under low-oxygen conditions and at a temperature of 400 °C. Biochar was converted into MGPC at a temperature of 800 °C using KOH and H ₃ PO ₄ as activators at three different levels and CO ₂ at a single level. Then, using data obtained from the Brunauer–Emmet–Teller (BET) test, the game theory approach, and the Condorcet algorithm for evaluation, 64 MGPC samples were analyzed. BET analysis was performed to measure the specific surface area and pore structure. The data obtained from this analysis were extensively reported, encompassing approximately 40 criteria. However, only 12 criteria were selected, while about 28 criteria were excluded from the Condorcet algorithm due to the incompleteness of some of their data. This study investigated the process of biochar and MGPC production using agricultural and industrial wastes, with an emphasis on the role of game theory in promoting environmentally sound decision-making and optimizing MGPC applications. From 64 prepared samples, by examining their physical properties and environmental impacts, five priority samples, i.e., rice straw-KOH-level 2, sawdust-KOH-level 2, palm tree pruning waste-KOH-level 2, vineyard pruning waste-KOH-level 2, and tissue factory waste-KOH-level 2, with respective surface areas of 1071.47, 672.04, 860.54, 667.49, and 133.45 m ² g ⁻¹ and t-plot micropore volumes of 0.29, 0.24, 0.17, 0.19, and 0.02 cm ³ g ⁻¹ . were prioritized using the Condorcet algorithm. They were identified as suitable candidates for advanced applications in soil and water conservation due to their favorable porous structures and highly performed BET properties. The present study shows that innovative methods for producing MGPC can improve the performance and properties of porous materials for various applications. Graphical

Investigating the spatial distribution characteristics of the interaction between soil salinity and moisture is crucial in revealing moisture–salinity interaction in semi-arid farmland. The sampling of soil was performed on the second (S1), fifth (S2), eighth (S3), eleventh (S4), and fourteenth (S5) days after the erosive rainfall. The multifractal method was used to analyze spatial distribution parameters of soil moisture and salinity under the different stages. The findings showed that the soil moisture content decreased from 22.44% to 12.73%, while the salinity increased from 0.71 to 1.18 g kg^–1 after the rainfall. As the amount of moisture in the soil decreased, the variability in the distribution of moisture initially increased from S1 to S3 and then decreased, while the salinity content also decreased. The spatial distribution of soil moisture and salinity content showed a strong correlation at S3 to S4 (with the relative water content of soil ranging from 0.52 to 0.75), indicating a significant coupling effect in these stages. However, the distribution of soil salinity was not uniform under high moisture content conditions (S1 to S2), as it was leached unevenly by rainfall, and under low moisture content conditions (S5), it precipitated, resulting in a low correlation between the spatial distribution of soil moisture and salinity content. This research has provided insight into the coupling dynamics of soil moisture and salinity content, revealing the mechanisms governing their spatial distribution in dryland agricultural regions.