Published Paper
2352-1864
Environmental Technology & Innovation
Projecting spatiotemporal dynamics of soil salinity using hybrid machine learning and Landsat OLI: The Red River Delta in Vietnam as a testbed for vulnerable deltas globally
Huu Duy Nguyen, Dinh Kha Dang, Thi Thanh Huyen Dinh, et al
DOI:
Keywords:
Soil Salinity, Red River Delta, Vietnam, Machine Learning, Climate Change, Agriculture
Huu Duy Nguyen, Dinh Kha Dang, Thi Thanh Huyen Dinh, et al (2025), "Projecting spatiotemporal dynamics of soil salinity using hybrid machine learning and Landsat OLI: The Red River Delta in Vietnam as a testbed for vulnerable deltas globally", Environmental Technology & Innovation, 40, pp. 104649, DOI: doi.org/10.1016/j.eti.2025.104649
Abstract
Soil salinization is a major driver of global land degradation, yet monitoring remains difficult due to its complex spatiotemporal dynamics and climate change. The Red River Delta (RRD), Vietnam, suffers severe salinity that undermines agriculture and food security, making it an ideal testbed for deltaic studies. Unlike prior research focusing on single time points, this study integrates historical salinity data with climate projections to model long-term dynamics. Given field data, we applied hybrid machine learning approaches: XGB (XGBoost) optimized with Sandpiper Hunting Optimization (XGB-SHO), Northern Goshawk Optimization (XGB-NGO), Electromagnetic Search Optimization (XGB-ESOA), Monkey Gorilla Optimization (XGB-MGO), and Grey Wolf Optimization (XGB-GWO). This addressed spatial heterogeneity and filled missing data. Objectives included: (i) simulating soil salinity (2005–2025); (ii) projecting dynamics to 2035 under climate scenarios; and (iii) assessing cropland impacts. XGB-NGO performed best (R²=0.886), followed by XGB-SHO/ESOA (0.881) and XGB-MGO/GWO (0.876). Projections indicate intensifying salinity (EC>4 mS/cm) in coastal/estuarine areas due to sea-level rise. Cropland declines from 2,796.3 km² (86.2%) in 2005 to 2,424.0 km² (74.7%) in 2035 (−13.3%), while aquaculture expands from 68.5 km² (2.1%) to 179.0 km² (5.5%) (+161%). Salinity-affected cropland declines under RCP 4.5 (18.02 km²) and RCP 8.5 (19.0 km²) by 2035 via land conversion. Findings stress integrating climate scenarios into adaptive soil-water management and prioritizing tailored agricultural strategies. Using RRD as a testbed, this study offers transferable insights for deltas worldwide. • Soil salinity has transformed agriculture in the Red River Delta (RRD) • XGB-NGO model achieved highest accuracy (R² = 0.886) for soil salinity prediction • Coastal zones face highest salinity risk, with EC levels exceeding 9 mS/cm by 2035 • Climate change and sea level rise increase soil salinity impact on agriculture


