Rural toilet retrofitting (RTR) is a complex, dynamic system that is affected by many factors and the positive/negative feedback relationships between subsystems and variables. Traditional technologies and management methods face challenges in fundamentally describing and solving problems in RTR. To bridge this gap, this study utilizes system dynamics and causal loop diagrams to explain such problems based on data collected from the stakeholders of the RTR in Jiaozhou from 2018 to 2019. Specifically, this study examines the RTR system from the perspectives of household users, wastewater treatment plants, local governments, grassroots promoters, operation and maintenance personnel, toilet supplier and construction teams, and fecal sludge end users. The factors and processes involved in RTR are identified, and the feedback and relationships among its major stakeholders are established. Results show that the motivation of farmers to engage in RTR is a key variable that affects their final decisions regarding retrofitting and maintaining toilet functions. Meanwhile, the important variables related to the feedback and relationships among the major stakeholders of RTR are mostly focused on policies, subsidies, technology, satisfaction, and cooperation. A scientific analysis method and the updated RTR plan for toilet revolution are then formulated to promote the implementation of RTR in developing countries.

The characteristics of soil moisture content (SMC) distribution in an area are necessarily analyzed for the design and construction of sponge cities. Combining remote sensing data with experimental data, this paper establishes a machine learning model to reveal the characteristics of SMC. Taking Beijing as an example, the SMC distribution was obtained and the characteristics were analyzed after training and validating. When comparing different machine learning methods, it can be concluded that the support vector classifier (SVC) method trained with remote sensing and grayscale data can achieve the highest accuracy (76.69%). The calculation results show that the districts with the highest and lowest SMC value are Xicheng District (19.94%) and Daxing District (11.04%), respectively, in Beijing. The mean SMC value of Beijing is 15.65%. The SMC distribution characteristic in Beijing shows that the soil in the west and north are relatively wet, while the soil in the east and south are relatively dry. Therefore, it is suggested that the timely monitoring of the SMC of vegetation covered areas at the north and west should be carried out. Water conservation facilities also need to be established with the development of city constructions in the south and east areas.

Modeling infiltration into soil and runoff quantitative evaluations is very significant for hydrological applications. In this paper, a flow model of unsaturated soils was established. A computational process of soil water content and runoff prediction was presented that combines an analytical solution with numerical approaches. The solutions have good agreements with the experimental results and other infiltration solutions (Richards numerical solution and classical Green–Ampt solution). We analyzed the effects on cumulative infiltration and runoff under three conditions of rainfall intensity with same average magnitude. These rainfall conditions were (Case 1) decreasing rainfall, (Case 2) steady rainfall, and (Case 3) increasing rainfall, respectively. The results show that the cumulative infiltration in Case 1 is the highest among the three cases. The cumulative runoff under condition of Case 3 is smaller than that of decreasing rainfall at the initial stage, which then becomes larger at the later stage. The time of runoff under the conditions of Case 1 is earliest among the three rainfall conditions, which is about 50% earlier than Case 3. Therefore, project construction for urban flood control should pay more attention to urban flood defense in increasing rainfall weather than other rainfall intensities under the same average magnitude. The approaches presented can be utilized to easily and effectively evaluate infiltration and runoff as a theoretical foundation.

The permeability, heat conductivity, and reaction rate will be varied with the change of natural gas hydrate saturation when thermal fluid is injected into the natural gas hydrate reservoirs. In order to characterize the variation of the physical field parameters with hydrate saturation, DDF-LBM was applied to simulate the hydrate dissociation process by thermal fluid injection under pore-scale modelling. Based on the forced conjugate heat transfer case, the relaxation frequency of the thermal lattice in the pores is corrected. Based on the P-T phase equilibrium relationship of hydrates and considering the heat absorbed by the hydrate reaction, the solid–liquid state of the hydrate lattice is judged in real time, and the dynamic simulation of the heat flow solidification multi-physics field is realized. The simulation results show that the dissociation rate of the hydrates by thermal fluid injection was higher than that by heating the hydrate surface alone and was positively correlated with the hydrate saturation. On the basis of the above results, this paper provided exponential fitting equations between different hydrate saturations and average permeability, effective thermal conductivity, and inherent reaction rate. The fitting results show that saturation has a negative correlation with relative permeability and effective thermal conductivity, and a positive correlation with the inherent reaction rate. The above results can provide a reference basis for accurately describing the heat and mass transfer of natural gas hydrate under the macroscale.

The permeability, heat conductivity and reaction rate will be varied with the change of natural gas hydrate saturation, when thermal fluid injected into the natural gas hydrate reservoirs. In order to characterize the variation of physical field parameters with hydrate saturation, DDF-LBM was applied to simulate the hydrate dissolving process by thermal fluid injection under pore scale modelling. Based on the forced conjugate heat transfer case, the relaxation frequency of the thermal lattice in the pores is corrected. Based on the P-T phase equilibrium relationship of hydrates and considering the heat absorbed by the hydrate reaction, the solid-liquid state of the hydrate lattice is judged in real time, and the dynamic simulation of the heat flow solidification multi-physics field is realized. The simulation results show that the dissolution rate of hydrates by thermal fluid injection was higher than that by heating the hydrate surface alone, and was positively correlated with the hydrate saturation. On the basis of the above results, this paper provided exponential fitting equations between different hydrate saturations and average permeability, effective thermal conductivity, and inherent reaction rate. The fitting results show that saturation has a negative correlation with relative permeability and effective thermal conductivity, and a positive correlation with the inherent reaction rate. The above results can provide a reference basis for accurately describing the heat and mass transfer of natural gas hydrate under macro-scale.