Exploring efficiency of biochar in enhancing water retention in soils with varying grain size distributions using ANN technique

Recently, incentives have been provided in many countries, including Canada and Denmark, to produce biochar for construction usage. This is done because biochar is carbon negative and can help achieve the emission reduction goal of 2030. This technical note aims to analyze the efficiency of biochar in soils with varying grain size distribution for enhancing water retention capacity (WRC). The combinations of biochar content and grain size distributions corresponding to the maximum and minimum efficiency were explored. Artificial Neural Network (ANN) based model for predicting Soil Water Characteristic Curve (SWCC) as a function of soil suction and grain size distribution was developed. A new factor (the ratio of fine (silt + clay) and coarse (sand) content) was proposed for the interpretation of the efficiency of biochar in soils. The newly developed model is able to predict SWCC reasonably well. Biochar amendment is found to influence both dry and wet sides of soils with a clay content lower than threshold content (6–8%). Beyond threshold content, the influence of biochar appears to reduce. However, in the case of high sand content soils (90%), the NWC value on the drier side is generally higher as compared to soils with lower sand content. Based on sensitivity analysis, it was found that the ratio of fine to sand content is the most influential, while biochar content is the least influential.