大型灌区土壤水盐运移模拟研究进展

doi:10.12118/j.issn.1000-6060.2023.717

Abstract

Abstract:

Soil salinization is a manifestation of land degradation caused by the combined effect of natural processes and human activities. This issue is particularly common in irrigation districts, where various factors exacerbated by frequent human interventions influence soil salinity. To prevent soil salinization, it is essential to have a comprehensive understanding of soil water-salt transport mechanisms in irrigation districts with frequent human activities. After reviewing the factors that influence soil water-salt transport in irrigation districts and the characteristics and applications of water-salt transport model, we propose a potential direction for simulating water-salt transport in irrigation areas. The formation of salinization in irrigation areas is closely related to natural factors such as climatic aridity, terrain, seasonal soil freeze-thaw cycles, groundwater salinity, and parent material of soils, as well as anthropogenic factors such as irrational irrigation practices, agricultural methodologies, and fertilization regimes. To understand the process of water-salt transport, soil water-salt transport models are effective tools. The commonly used models for water-salt transport include water-salt balance models, physical models, and statistical models. They are mainly used to optimize irrigation water-saving regimes and drainage management for salinity control at the field scale. However, applying these models at the regional scale presents challenges due to the difficulty of obtaining observational data to calibrate and validate models that involve soil water-salt transport processes and crop growth. The rapid development of modern large-scale irrigation districts has changed the spatiotemporal distribution of soil water-salt transport. However, the continuous improvements of the model and the rapid development of computer technology have provided possibilities for investigating the spatiotemporal evolution mechanisms of water-salt transport in large-scale irrigation districts. Future models should focus on strengthening the soil water-salt transport mechanisms based on ecological safety. It is recommended to develop a multi-process water-salt transport model that is coupled with a climate model or an economic model.

Key words: irrigation districts, soil salinization, soil water-salt transport model, climate model, economical model, ecological safety

MENG Huimin, ZHAN Chesheng, HU Shi, LIN Zhonghui. Research progress on simulation of soil water-salt transport in large-scale irrigation districts[J].Arid Land Geography, 2024, 47(9): 1566-1576.

Figures/Tables 5

Fig. 1

Tab. 1

Comparison of common soil water-salt transport models"

模型名称	类型	尺度	优点	缺点
HYDRUS	物理模型	田间	能较好刻画不同介质中水与溶质的迁移转化过程	局限于田间或对室内土柱的模拟应用
SHAW	物理模型	田间	能够模拟冻融期土壤水盐运移过程	土壤盐分的模拟效果较差
SWAP	物理模型	田间	能够考虑饱和-非饱和带水盐运移情况和水盐胁迫对作物生长的影响	不能定量描述空间变异性复杂的土壤水盐动态
UNSATCHEM	物理模型	田间	能够模拟变饱和度的土壤水流和盐分运移过程	模型参数较多，忽略了土壤大孔隙中的优先流流动、滞后现象
LEACHC	物理模型	田间	能够模拟预测土壤层主要离子浓度、pH值、钠吸附比等	忽略了植物对肥料和溶质的吸收过程，可能影响土壤溶液中离子的化学平衡和反应
COMSOL	物理模型	田间	能够较好地模拟土壤中主要盐离子的动态变化过程	未考虑土壤中碳酸钙的沉淀溶解过程
DRAINMOD	水盐平衡模型	田间	能够描述农田盐分输出及盐分累积过程，计算简便	不能模拟作物对浅层地下水利用时造成的盐分累积过程
BP神经网络	统计模型	区域	具有良好的非线性映射能力	需要大量的实测数据
模糊神经网络模型（FNN）	统计模型	区域	模型模拟预测精度较高	模型的自我调整能力和适应能力较差
自组织径向基函数（RBF）	统计模型	区域	非线性逼近能力强	模型训练时间较长、结构较复杂
快速反向传播网络模型（FBP）	统计模型	区域	模型训练速度快，结构较简单	模型容易陷入局部最优解，在处理非线性问题时可能受限
SaltMod	水盐平衡模型	区域	模型参数少	不能模拟不同灌溉水质及井渠结合灌溉情景，不适合短期盐分预测
SahysMod	水盐平衡模型	区域	综合SaltMod和SGMP模型优势，考虑了土壤空间变异性和种植制度的不同引起的灌溉与排水的差异性	未考虑植物体吸盐量，不适合短期盐分预测
SWAT	物理模型	流域	能够模拟流域内主要盐离子的运移过程	不能模拟基于物理的、空间分布的地下水流动和溶质运移过程

Tab. 1

Fig. 2

Fig. 3

Fig. 4

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Research progress on simulation of soil water-salt transport in large-scale irrigation districts

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