No abstract

No abstract

No abstract

No abstract

Significant anthropogenic and biophysical changes have caused fluctuations in the soil salinization area of the Keriya Oasis in China. The Driver-Pressure-State-Impact-Response (DPSIR) sustainability framework and Bayesian networks (BNs) were used to integrate information from anthropogenic and natural systems to model the trend of secondary soil salinization. The developed model predicted that light salinization (vegetation coverage of around 15-20%, soil salt 5-10 g/kg) of the ecotone will increase in the near term but decelerate slightly in the future, and that farmland salinization will decrease in the near term. This trend is expected to accelerate in the future. Both trends are attributed to decreased water logging, increased groundwater exploitation, and decreased ratio of evaporation/precipitation. In contrast, severe salinization (vegetation coverage of around 2%, soil salt ≥20 g/kg) of the ecotone will increase in the near term. This trend will accelerate in the future because decreased river flow will reduce the flushing of severely salinized soil crust. Anthropogenic factors have negative impacts and natural causes have positive impacts on light salinization of ecotones. In situations involving severe farmland salinization, anthropogenic factors have persistent negative impacts.

Groundwater levels and salinity are significant contributors to soil salinisation in irrigated areas. In this study, spatial and temporal variations of groundwater levels and salinity in the Ili River Irrigation Area in the western arid zone of China were analysed using a geostatistical approach. Results showed that: (1) groundwater salinity varied widely, with a maximum of 30.70 g/L and minimum of 0.20 g/L, while maximum groundwater level was 31.10 m and minimum was 0.54 m. The abundance of major ions in groundwater was in the order:Groundwater salinity had a good positive correlation with EC, Cl − , Na + , HCO 3 − and Mg 2+ (correlation coefficient >0.90); (2) a Gaussian model was the most suitable semivariogram model to describe groundwater levels for four measurement periods, while a Spherical model was most suitable semivariogram model to describe groundwater salinity in March, September and November, and an Exponential model was most suitable variogram model for June. RA relatively strong spatial and temporal structure existed for groundwater levels and salinity due to very low nugget effects. The nugget-to-sill ratio indicated that groundwater levels and salinity in the study area have relatively strong spatial dependence. The groundwater levels and salinity showed an east-west, north-south U-shaped distribution in each measurement period; (3) maps of kriged groundwater levels and salinity showed that deeper groundwater was found in southern parts, with more shallow groundwater in northern parts of the study area. Higher groundwater salinity was found in central parts, with lower salinity in marginal parts of the study area. It is clear that substantial soil salinisation has taken place in central parts of the study area, and more attention should be paid to these areas to prevent future problems.

No abstract

No abstract