As a result of heterogeneity nature of soils and variation in its hydraulic conductivity over several orders of magnitude for various soil types from fine-grained to coarse-grained soils, predictive methods to estimate hydraulic conductivity of soils from properties considered more easily obtainable have now been given an appropriate consideration. This study evaluates the performance of artificial neural network (ANN) being one of the popular computational intelligence techniques in predicting hydraulic conductivity of wide range of soil types and compared with the traditional multiple linear regression (MLR). ANN and MLR models were developed using six input variables. Results revealed that only three input variables were statistically significant in MLR model development. Performance evaluations of the developed models using determination coefficient and mean square error show that the prediction capability of ANN is far better than MLR. In addition, comparative study with available existing models shows that the developed ANN and MLR in this study performed relatively better.

Bio-cementation is a new sustainable approach that has gained popularity due to its low energy and carbon dioxide footprint compared with those of existing technologies for geotechnical and geoenvironmental engineering applications. Bio-cementation is a soil improvement technique that involves binding the pore space of soil particles with calcium carbonate minerals by microbially induced carbonate precipitation (MICP) and filling the soil pore space. The purpose of this paper is to present the current state of the art and a comprehensive discussion on the development of bio-cementation for soil improvement/reinforcement. Premixing, injection, immersing and surface percolation are identified as four distinct bio-cementation treatment techniques. Furthermore, scholars have reported employing ureolytic bacteria such as Sporosarcina pasteurii, Bacillus sphaericus and Lysinibacillus sphaericus isolated from corals, limestone caves, soils, waste materials, seawater and other sources to accomplish effective bio-cementation. Some of the major issues (bacterial cultivation costs and ammonium production) that impede its industrial potential and promising remedial techniques are also discussed. This state-of-the-art review also discusses the benefits and drawbacks of bio-cementation compared with traditional approaches. The significance of enzyme-induced carbonate precipitation as a soil bio-cementation alternative to MICP is also highlighted. Finally, the sustainable procedure, bio-cementation principles and future implications are discussed.

Microbial-induced carbonate precipitation (MICP) is a promising bioremediation technology for heavy metal immobilisation. This review explores the applications and efficacy of MICP in environmental challenges. It provides a comprehensive overview of the mechanism, primarily through ureolysis, detailing the process from urea hydrolysis to heavy metal precipitation as carbonate minerals. Alternative pathways such as photosynthesis and nitrate reduction are also discussed, highlighting the broad applicability of MICP. The review covers the historical evolution and advancements of MICP as a sustainable solution for heavy metal contamination. Recent studies demonstrate the efficiency of MICP in achieving high removal rates in diverse environments. The sustainable operation, precise targeting of heavy metal species, and versatility of MICP are examined. Challenges such as high copper concentrations, acidic conditions, and cost considerations are addressed. The article provides future directions and solutions to these challenges, including leveraging machine learning for optimal performance and enhancing cost considerations through detailed analyses. This review improves understanding of MICP’s potential, provides a valuable resource for researchers in environmental engineering and the built environment, and encourages innovative approaches within these fields.