工程地质学报2026，Vol.34Issue(2)：837-845,9.DOI:10.13544/j.cnki.jeg.2023-0131
基于多元自适应回归样条的土体含水率剖面时空分布智能预测
INTELLIGENT SPATIOTEMPORAL PREDICTION OF SOIL MOISTURE CONTENT PROFILE USING MULTIVARIATE ADAPTIVE REGRESSION SPLINES
摘要
Abstract
Accurate prediction of soil moisture content is essential for preventing geological disasters and protecting the environment.Recently,numerous artificial intelligence algorithms have been applied to simulate and predict soil moisture content,providing valuable insights into its distribution and migration patterns.In this study,a multiple adaptive regression spline(MARS)data-driven model was developed to predict soil moisture content at various depths for the next 12,24,and 36 hours,using meteorological data along with soil heat and moisture measure-ments.Long-term observations were conducted in Yanjiao,Hebei Province,where fiber-optic sensing technology was employed to collect measured data.Based on these observations,a soil moisture profile prediction model was established.The results demonstrate that the model performs effectively in predicting soil moisture content across different time frames and depths.Furthermore,analysis of the relative importance of influencing factors reveal that soil temperature has a more significant impact on soil moisture content than meteorological factors.Spatiotemporal analysis indicate that shallow soil moisture content is strongly influenced by rainfall and other factors during the monitoring period,exhibiting relatively poor temporal stability.The fluctuation range in shallow layers is consi-derably larger than in deeper layers,resulting in better prediction accuracy during autumn compared to winter.The findings of this study can serve as fundamental data for engineering geology applications and provide a novel methodological approach for soil moisture content prediction.关键词
土体含水率/多元自适应回归样条模型/垂直剖面/时空分布/智能预测Key words
Soil moisture/Multivariate adaptive regression splines/Vertical profile/Spatiotemporal distribution/Intelligent prediction分类
天文与地球科学引用本文复制引用
胡乐乐,朱鸿鹄,程刚,吴冰,刘天翔,李杰,曹鼎峰..基于多元自适应回归样条的土体含水率剖面时空分布智能预测[J].工程地质学报,2026,34(2):837-845,9.基金项目
国家自然科学基金杰出青年科学基金项目(资助号:42225702),国家自然科学基金面上项目(资助号:42461160266).This research is supported by the National Science Fund for Distinguished Young Scholars(Grant No.42225702)and the General Program of Na-tional Natural Science Foundation of China(Grant No.42461160266). （资助号:42225702）
