Estimating the groundwater table threshold for mitigating soil salinization in the Songnen Plain of China

Abstract

Study region

The Songnen Plain is a key part of China’s largest plain, situated in northeastern China.

Study focus

Soil salinization has become one of the largest ecological issues in the Songnen Plain, and regulating groundwater levels is a crucial strategy for mitigating it. To address this, a comprehensive framework is developed to estimate the groundwater table threshold for soil salinization by integrating field sampling, remote sensing big data, and machine learning models.

New hydrological insights for the region

The soil salinity inversion model, which utilizes a random forest algorithm, achieves the highest accuracy (R² = 0.75, d = 0.94, RPD = 2.05), outperforming SVM, LightGBM, and XGBoost algorithms. From 2020–2023, areas with mild salinization accounted for 9.3 % of the total area, while moderate salinization accounted for 3.2 %, severe salinization accounted for 4.0 %, and saline soil areas accounted for 0.6 %. A probabilistic model further identifies groundwater depth thresholds for salinization: 2.3 m for sandy soil, 3.1 m for loamy soil, and 1.1 m for silty soil. Based on current groundwater depths, it is anticipated that 15.5 % of the Songnen Plain area will continue to be affected by soil salinization or remain at risk of potential salinization.