Biochar has been globally recognized as a soil amendment to ameliorate the degraded soil structures. We investigated the different biochar percentages contributed to the changes in soil water retention, soil infiltration, and water-holding capacity of one dimensional scale. Besides, infiltration models were compared, and an improved genetic algorithm (GA) combined with multi-objective optimization and elitist strategy was proposed to upgrade the modified van-Genuchten (VG) model. Results indicated that observed cumulative infiltration displayed reductions by 14.06%, 46.62%, and 71.78% for the soil mixed with 5%, 10%, and 15% biochar, respectively, relative to the pure soil. The Kostiakov model was more effective than the Philip model in predicting cumulative infiltration. Furthermore, the constructed modified VG model based on the inversed hydraulic parameters was capable of predicting soil moisture at suction less than 2070 kPa (i.e., 1.38 times wilting point) but caused an underestimation beyond it. This research has the potential to replace the soil water retention curve (SWRC) measurement by one-dimensional infiltration experiment with parameters inversed from the improved GA combined with a modified VG model. It is time-saving and efficient during the SWRC study.

生物炭已被全球公认为改善土壤结构退化的土壤改良剂。我们调查了不同生物炭百分比对土壤持水量，土壤入渗量和一维尺度持水量变化的影响。此外，比较了渗透模型，并提出了一种结合多目标优化和精英策略的改进遗传算法（GA），对改进的van-Genuchten（VG）模型进行了升级。结果表明，相对于纯净土壤，与5％，10％和15％生物炭混合的土壤，观察到的累积入渗量分别减少了14.06％，46.62％和71.78％。在预测累积渗透方面，Kostiakov模型比Philip模型更有效。此外，基于反水力参数构造的改进的VG模型能够预测吸力小于2070 kPa（即萎缩点的1.38倍）的土壤水分，但会导致超出这一范围的低估。这项研究有可能用一维渗透实验代替土壤保水曲线（SWRC）的测量，该实验用改进的遗传算法和改进的VG模型反演的参数进行。在SWRC研究期间，这既省时又高效。这项研究有可能用一维渗透实验代替土壤保水曲线（SWRC）的测量，该实验用改进的遗传算法和改进的VG模型反演的参数进行。在SWRC研究期间，这既省时又高效。这项研究有可能用一维渗透实验代替土壤保水曲线（SWRC）的测量，该实验用改进的遗传算法和改进的VG模型反演的参数进行。在SWRC研究期间，这既省时又高效。