High-quality groundwater bodies with relatively stable water volumes, good water quality, and a high resistance to pollution are widely distributed throughout the world. They play an important role in, among other things, the domestic water supply, economic development, and maintaining the integrity of the geological environment and ecological balance. However, with rapid socio-economic development, increasing human demand for water has resulted in increasing pressure on, and unreasonable use of, groundwater bodies. Consequently, groundwater systems throughout the world are subject to varying degrees of pollution and destruction, one result of which is an increasing disequilibrium between the supply of and demand for water resources.
The field of international hydrogeology is concerned with evaluation of groundwater vulnerability, which is considered a basic task in the development and protection of groundwater resources. Currently, groundwater vulnerability is thought to result from characteristics of the groundwater system itself and anthropogenic factors; research into groundwater vulnerability can support groundwater protection. GIS, together with the contraposed index method, is the most popular tool for calculating groundwater vulnerability indices. Because the hydrogeological environment is not under the complete control of human activities, a thorough understanding of groundwater vulnerability and the causes of its variation is necessary for environmental managers to enact preventive and pollution control measures.
This study was based on the DRASTIC model. Groundwater parameters for 3 years (1991, 2000, and 2010) were used to calculate the distribution of groundwater vulnerability in the lower reaches of the plain of the Liaohe River, using ArcGIS. Groundwater nitrogen concentration was used as a response index to test the reliability of results. Using the mapping and spatial statistical analysis functions in GS⁺, ArcGIS, and Geoda095i, we evaluated and analyzed the spatial distribution, variation, and spatial correlation patterns of groundwater vulnerability in the tested area. Results showed that:1) Overall groundwater vulnerability initially decreased but then showed a trend of increase from 1991 to 2010, and high-vulnerability areas were distributed from the regions around Shenyang to the south coast. 2) From 1991 to 2010, groundwater vulnerability showed a strong positive autocorrelation (Moran's I), the degree of which showed a slight downward trend. 3) Over the study period, marked changes have occurred in local spatial autocorrelation of groundwater vulnerability and its significance levels. 4) Groundwater vulnerability in the study area was influenced by a combination of structural and random factors. While the random factors have gradually increased over time, structural factors remain important. This study highlights the causes of variation in groundwater vulnerability and the mechanisms that drive its spatial structure in the study area and can provide a reference for policy makers to support development of groundwater pollution control and protection plans.