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This study aims to elucidate the dynamics of fluid topology during drainage and evaporation of wetting and non-wetting fluids via evaluation of their Euler characteristic (EC) and Betti numbers from designed experiments. The results showed that the EC of the non-wetting fluid remained constant at a high wetting fluid saturation and then decreased nonlinearly. However, the EC of the wetting fluid exhibited more complex trends. In the 2-D micromodel, the number of loops decreased monotonously, reached zero, and remained constant for lower saturations, while the number of distinct components fluctuated because of the appearance and disappearance of disconnected clusters. In the 2-D model, the number of distinct components played a significant role; in the 3-D X-ray CT experiment, the number of loops of pendular rings dominated the EC. The findings suggest that the trends observed in the 2-D micromodel may not apply under 3-D conditions. [ABSTRACT FROM AUTHOR]

In the current study, we used micromodel experiments to study three-phase fluid flow in porous media. In contrast to previous studies, we simultaneously observed and measured pore-scale fluid behavior and three-phase constitutive relationships with digital image acquisition/analysis, fluid pressure control, and permeability assays. Our results showed that the fluid layers significantly influenced pore-scale, three-phase fluid displacement as well as water relative permeability. At low water saturation, water relative permeability not only depended on water saturation but also on the distributions of air and diesel. The results also indicate that the relative permeability-saturation model proposed by Parker et al. (1987) could not completely describe the experimental data from our three-phase flow experiments because these models ignore the effects of phase distribution. A simple bundle-of-tubes model shows that the water relative permeability was proportional to the number of apparently continuous water paths before the critical stage in which no apparently continuous water flow path could be found. Our findings constitute additional information about the essential constitutive relationships involved in both the understanding and the modeling of three-phase flows in porous media. [ABSTRACT FROM AUTHOR]

Water resource scarcity increases due to extreme weather events and long-term climate change. Agricultural water utilization efficiency becomes a key issue of water resource and food production nowadays. This study provides a novel method for predicting and controlling the evolution of soil water content in a greenhouse. Our experiment implemented with monitoring instruments installed, collecting air temperature, relative humidity, soil temperature, and soil water content. Cherry tomato, which is one of the most common global greenhouse fruits, was chosen to grow in the potting soil. A well-controlled water content condition in soils can allow for a more appropriate heat balance and protects plant roots systems and reduce the water waste. We used an ensemble-learning method to predict and optimize the irrigation process. The results showed that the machine learning method is more efficient than the widely used Hydrus-1D based on the Richards equation when the soil information is limited. Nevertheless, the quality of the simulation results from the machine learning method is highly dependent on the training period. [ABSTRACT FROM AUTHOR]