利用机器学习预测华北地区冬小麦农田氮淋失

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Abstract Winter wheat is the main cereal crop in Northern China, and excessive nitrogen (N) fertilization and irrigation are employed in recent years to ensure a high grain yield. A high amount of N was lost via leaching, which exacerbated the risk of non-point source pollution and further increased the resource waste. It is highly necessary to clarify the characteristics and influencing factors of N leaching loss during the winter wheat season in the region. The literature on N leaching loss from the winter wheat production in Northern China, published from 2000 to 2023 was screened, and linear, multiple-factor regression models, as well as random forest and XGBoost models were established in the study. The research showed that the N leaching during the winter wheat season was mainly affected by the fertilizer rate and irrigation water, as well as soil properties (pH, clay and sand content), and was effectively inhibited by crop straw incorporation. Multiple variable combinations were constructed based on the results of importance analysis and stepwise regression. Grid search method, Bayesian and the combination of Bayesian and Early stopping were used to optimize the model parameters. The models constructed through Random Forest, based on all influential variables and based on the influential variables screened by stepwise, had the R² of 0.628 and 0.708, respectively, and the R² for the corresponding models constructed through XGBoost were 0.745 and 0.722, respectively. This indicates that the prediction effects of N leaching based on Random Forest and XGBoost were much better than the linear and multiple-factor regression models. The influence of multiple factors on N leaching was comprehensively considered in the machine learning models, and the effects of prediction were better when choosing the influential variables screened by empirical statistical methods as independent variables. The results of this study can provide technical support for reducing the N leaching in the winter wheat production in Northern China.

Key words： winter wheat nitrogen leaching machine learning XGBoost grid search bayesian optimization

Received: 30 May 2024

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X592

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	LI Tao-yu
	XU Xiu-chun
	YANG Xuan
	CUI Bin
	CHEN Heng-ai
	ZHAO Xiao-ying
	YUAN Ning
	MENG Fan-qiao

Cite this article:

LI Tao-yu,XU Xiu-chun,YANG Xuan等. Prediction of nitrogen leaching from winter-wheat production in North China based on random forest and XGBoost[J]. CHINA ENVIRONMENTAL SCIENCECE, 2025, 45(1): 343-354.

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http://www.zghjkx.com.cn/EN/ OR http://www.zghjkx.com.cn/EN/Y2025/V45/I1/343

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