The Characteristics and Driving Factors of Soil Salinisation in the Irrigated Area on the Southern Bank of the Yellow River in Inner Mongolia: A Assessment of the Donghaixin Irrigation District

Ziyuan Qin, Tangzhe Nie (), Ying Wang, Hexiang Zheng, Changfu Tong, Jun Wang, Rongyang Wang and Hongfei Hou
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Ziyuan Qin: Yinshanbeilu Grassland Eco-Hydrology National Observation and Research Station, China Institute of Water Resources and Hydropower Research, Hohhot 010020, China
Tangzhe Nie: School of Water Conservancy and Electric Power, Heilongjiang University, Harbin 150080, China
Ying Wang: College of Water Conservancy and Civil Engineering, Inner Mongolia Agricultural University, Hohhot 010020, China
Hexiang Zheng: Yinshanbeilu Grassland Eco-Hydrology National Observation and Research Station, China Institute of Water Resources and Hydropower Research, Hohhot 010020, China
Changfu Tong: Yinshanbeilu Grassland Eco-Hydrology National Observation and Research Station, China Institute of Water Resources and Hydropower Research, Hohhot 010020, China
Jun Wang: Yinshanbeilu Grassland Eco-Hydrology National Observation and Research Station, China Institute of Water Resources and Hydropower Research, Hohhot 010020, China
Rongyang Wang: Research Center of Fluid Machinery Engineering and Technology, Jiangsu University, Zhenjiang 212013, China
Hongfei Hou: Yinshanbeilu Grassland Eco-Hydrology National Observation and Research Station, China Institute of Water Resources and Hydropower Research, Hohhot 010020, China

Agriculture, 2025, vol. 15, issue 5, 1-22

Abstract: Soil salinisation is a critical problem in northern China’s arid and semi-arid irrigated regions, posing a substantial impediment to the sustainable advancement of agriculture in these areas. This research utilises the Donghaixin Irrigation District, located on the southern bank of the Yellow River in Inner Mongolia, as a case study. This study examines the spatial distribution and determinants of soil salinisation through macro-environmental variables and micro-ion composition, integrating regression models and groundwater ion characteristics to elucidate the patterns and causes of soil salinisation systematically. The findings demonstrate that soil salinisation in the study region displays notable spatial clustering, with surface water-irrigated regions exhibiting greater salinisation levels than groundwater-irrigated areas. More than 80% of the land exhibits moderate salinity, predominantly characterised by the ions Cl − , HCO 3 − , and SO 4 2− . The hierarchy of ion concentration variation with escalating soil salinity is as follows: Na + > K + > SO 4 2− > Cl − > Mg 2+ > HCO 3 − + CO 3 2− > Ca 2+ . The susceptibility of ions to soil salinisation is ordered as follows: Ca 2+ > Na + > HCO 3 − + CO 3 2− > Mg 2+ > K + > Cl − > SO 4 2− . In contrast to the ordinary least squares (OLS) model, the geographic weighted regression (GWR) model more effectively elucidates the geographical variability of salinity, evidenced by an adjusted R 2 of 0.68, particularly in high-salinity regions, where it more precisely captures the trend of observed values. Ecological driving elements such as organic matter (OM), pH, groundwater depth (GD), total dissolved solids (TDS), digital elevation model (DEM), normalised difference vegetation index (NDVI), soil moisture (SM), and potential evapotranspiration (PET) govern the distribution of salinisation. In contrast, anthropogenic activities affect the extent of salinisation variation. Piper’s trilinear diagram demonstrates that Na cations mainly characterise groundwater and soil water chemistry. In areas irrigated by surface water, the concentration of SO 4 2− is substantially elevated and significantly affected by agricultural practises; conversely, in groundwater-irrigated regions, Cl − and HCO 3 − are more concentrated, primarily driven by evaporation and ion exchange mechanisms.

Keywords: soil salinisation; agricultural irrigation; southern bank of the Yellow River irrigated area; GWR model; driving factors (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2025
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