# To reduce soil salinity: the role of irrigation and water management in global arid regions across development phases

**Authors:** Haiyang Shi  
**arXiv:** [2204.02029](https://arxiv.org/abs/2204.02029)  
**Date:** 2022-04-05  
**Summary page:** https://www.summarizepaper.com/en/arxiv-id/2204.02029v1/

## Key points

- Reducing soil salinization in croplands through optimized irrigation and water management is crucial for achieving land degradation neutralization.
- Bayesian network analysis was employed to compare the spatial-temporal response of salinity to various water management strategies in ten large arid river basins.
- Managers in basins at more advanced phases of development successfully implemented drip and groundwater irrigation methods, effectively controlling salinity by lowering groundwater levels.
- A Bayesian network (BN) model was constructed using Netica software to analyze the causality between different factors influencing soil salinity reduction.
- Sensitivity analysis using mutual information (MI) was conducted to evaluate the influence of different factors on soil salinity.
- The study highlights the importance of optimized irrigation and water management practices in mitigating soil salinization in arid croplands.
- It emphasizes the need for implementing advanced irrigation methods, such as drip and groundwater irrigation, in basins at more advanced development stages.
- Economic development and policy interventions are significant for improving irrigation systems, reducing salinity levels, and enhancing agricultural incomes in basins still relying on conventional flood irrigation.

## Summary

Reducing soil salinization in croplands through optimized irrigation and water management is crucial for achieving land degradation neutralization. Bayesian network analysis was then employed to compare the spatial-temporal response of salinity to various water management strategies in ten large arid river basins. The findings revealed that managers in basins at more advanced phases of development successfully implemented drip and groundwater irrigation methods which effectively controlled salinity by lowering groundwater levels. To further analyze the causality between different factors influencing soil salinity reduction, a Bayesian network (BN) model was constructed using Netica software. Sensitivity analysis using mutual information (MI) was conducted to evaluate the influence of different factors on soil salinity. This analysis provided insights into which factors have a greater impact on reducing soil salinity. Overall, this study highlights the importance of optimized irrigation and water management practices in mitigating soil salinization in arid croplands. It emphasizes the need for implementing advanced irrigation methods, such as drip and groundwater irrigation, in basins at more advanced development stages. Additionally, it underscores the significance of economic development and policy interventions to improve irrigation systems, reduce salinity levels, and enhance agricultural incomes in basins still relying on conventional flood irrigation.