水资源保护2025，Vol.41Issue(4)：10-18,41,10.DOI:10.3880/j.issn.1004-6933.2025.04.002
基于机器学习的Budyko框架流域时变特征参数估计
Estimation of watershed time-varying feature parameter in Budyko Framework based on machine learning
摘要
Abstract
To analyze the spatiotemporal changes of watershed characteristic parameter in the Budyko Framework in the middle reaches of the Yellow River and capture the impact of different factors on the watershed characteristic parameter,multiple linear regression(MLR),gradient boosting(GB),and random forest(RF)models were constructed based on runoff,meteorological,and human activity data from eight sub-basins in the middle reaches of the Yellow River.The watershed characteristic parameter ω in the Fu Baopu equation was simulated.By cross validation,select the model with the best performance,identify the main control factors that significantly affect ω,and further incorporate the optimal model into the water heat coupling equilibrium equation to construct a time-varying Budyko framework,quantifying the contribution of climate change and underlying surface changes to runoff.The results showed that among the three models,the RF model outperformed the MLR and GB models in simulating ω.From 1980 to 2019,the ω values of each sub-basin showed an increasing trend,mainly controlled by human activities such as impermeable area,population,and regional GDP.Potential evapotranspiration is an important controlling factor in climate factors.The change of underlying surface is the main driving factor for runoff changes in most sub-basins of the middle reaches of the Yellow River,but the impact of climate change on the Qinhe River sub-basin is slightly stronger than the change of underlying surface.关键词
Budyko框架/流域特征参数/多元线性回归模型/梯度提升模型/随机森林模型/黄河中游Key words
Budyko Framework/watershed characteristic parameter/multiple linear regression model/gradient boosting model/random forest model/middle reaches of the Yellow River分类
天文与地球科学引用本文复制引用
薛联青,陈雨欣,刘远洪,杨明杰..基于机器学习的Budyko框架流域时变特征参数估计[J].水资源保护,2025,41(4):10-18,41,10.基金项目
国家重点研发计划项目(2023YFC3206800) （2023YFC3206800）
新疆生产建设兵团科技合作项目(2022BC001) （2022BC001）
国家自然科学基金项目(51779074) （51779074）
