Search

Permeability, essential for water retention, requires careful consideration in hydraulic engineering projects. Determining soil permeability is challenging due to spatial and temporal variability, complicating the application of classical formulas. In this context, a study investigating deep seepage was conducted on sandy loam and clay loam soils in Tri Ton and Phu Tan. This investigation involved quantifying the amount of water retained in the soil through laboratory cylinders and rice fields with water levels set at 5 cm and 10 cm. The findings of the research indicate a direct proportionality between the permeability coefficient and soil moisture in both soil types. Notably, porosity showed no discernible correlation with permeability coefficient at both 5 cm and 10 cm water levels for sandy loam soils, which restrict fluid flow despite the high pore volume and the permeability coefficient in sandy loam soil is K = 8.67 × 10−5 cm/s at 5 cm and 10 cm water levels, respectively K = 8.46 × 10−5 cm/s The infiltration of sandy loam was 4–5 times lower than laboratory rates at 5 cm and 10 cm water levels. While the permeability of clayey loam in rice fields was 0.6–2.2 times lower than laboratory values and the permeability coefficient at 5 cm and 10 cm water levels are K = 1.12 × 10−5 cm/s and K = 3.22 × 10−5 cm/s respectively. Furthermore, the infiltration equation for each treatment in rice fields for the two soil types was also built. The research suggests a robust connection between permeability and both porosity and moisture levels.

Abstract In the present study, the waste part of the banana tree was used as a precursor, and copper chloride salt was used as an impregnating agent for the preparation of adsorbent to remove both cyanide and phenol from synthetic wastewater. Initially, thermogravimetric analysis was used to determine the rate of carbonization of the material with temperature, and thus, the optimum temperature (370 °C) and time of carbonization (35 min) were assessed. Different samples of adsorbents were prepared next by varying the weight ratio of pseudo-stem of waste banana tree to copper salt from 1:1 to 30:1. All the samples were then tested for removal of both the pollutants, and the ratio (20:1) corresponding to maximum removal of both the pollutants was considered as optimum. Therefore, further studies were conducted with the adsorbent prepared at optimum ratio, temperature and time and such adsorbent was termed as copper impregnated activated banana tree (CIABT). One variable at a time approach was followed to find out the most effective condition based on the maximum removal of pollutants. Maximum removal of 95.99 ± 1.03% and 97.33 ± 0.04% was achieved for cyanide (initial concentration: 100 ppm) and phenol (initial concentration: 450 ppm), respectively, at an optimum contact time of 150 min, the particle size of 90 μ, the adsorbent dosage of 10 g/L, pH 8.0 using CIABT at 25 °C. Hybrid artificial neural network–particle swarm optimization were employed for modelling-optimization of removal of both the pollutants while achieving 91.4–99.99% and 86.43–99.99% removal of cyanide and phenol, respectively, from simulated wastewater.