Assessing impact of land uses on land salinization in the Yellow River Delta, China using an integrated and spatial statistical model

The key anthropogenic determinants of salinization and their spatially explicit information in the Yellow River Delta. [Display omitted] ► SAR sub-region model captures the spatial dependency in the salinization process and normalizes the interferences of non-anthropogenic factors on land salinity. ► SAR sub-region model provides detail and quantitative assessments, by identifying key anthropogenic determinants, their affected extent on sub-regional scale and affected tendency (positive or negative). ► Oil exploitation, saline aquaculture, crop plantation and fertilization exert main influences on the variability of land salinity pattern. ► Oil exploitation and saline aquaculture are aggregative to salinization, and the influenced areas are distributed in highly saline areas, such as the coastal zones or soil III. ► Agricultural activities are ameliorative to salinization and the most effective alleviation occurred in moderately saline sub-regions. Intensification of agriculture and industry in salinized areas poses a risk of secondary salinization. Thus, comprehensive and spatially explicit assessments are needed to assist government in developing ecologically sound policies. Few assessments have comprehensively quantified the impacts of multiple anthropogenic activities on salinization as environmental interferences and salinity autocorrelation are largely neglected. This study tried to perform such an assessment by identifying the nature of human impacts on salinization from three aspects in the Yellow River Delta (YRD) of China. A versatile GIS-based spatial autoregression (SAR) was applied to nine selected explainable variables in six sub-region models. Sub-region model was verified as an effective tool of normalizing environmental interferences because more useful spatial information was provided compared to the whole region model. GIS-SAR model fit better and performed better in quantifying human activities, compared to the conventional ordinary least square regression (OLSR) model, as SAR can deal with spatial autocorrelation in soil salinity. Among the well-defined key determinants, oil exploitation and saline aquaculture were aggregative to salinization but only in originally highly saline sub-regions, such as coastal zone and Gleyic Solonchaks (coastal saline moisture soil) area. Two agricultural activities, crop plantation and fertilization, were mainly ameliorators in most sub-regions. The most effective salinization alleviation occurred in mo