In this paper, the authors studied the impact of human activities on the groundwater environment to reduce the impacts such activities for sustainable groundwater use. The authors took the monthly water table depth data of 32 long-term observation wells in the Daxing District of Beijing from 1986 to 2016 as samples. The authors used seven interpolation methods in the statistics module of ArcGIS by comparing the average error (ME) and root mean square error (RMSE) between the measured and predicted values so that the authors can select the best interpolation method. Using the geostatistical variogram model variation, the authors analyzed the nugget effect through time in the study area. On the basis of the set pair analysis, the main factors causing the increase in groundwater exploitation intensity were quantitatively evaluated and identified. The results were as follows. (1) After comparing the simulation accuracy of the seven interpolation methods for water table depth, ordinary Kriging interpolation was selected as the best interpolation model for the study area. (2) The spatial correlation of the water table depth gradually weakened, and the nugget effect from 2006 to 2016 was 25.92% (>25%). The data indicated that human groundwater exploitation activities from 2006 to 2016 greatly influenced the spatial correlation of the water table depth. (3) The average mining intensity of groundwater from 2006 to 2016 was medium (Level II), and a bleak gradual deterioration trend was observed. The evaluation results of the subtraction set pair potentials in 2010 and 2013, the years of key regulation of groundwater exploitation intensity, are partial negative potential and negative potential, respectively. In 2010, three indicators had partial negative potential: industrial product, tertiary industry product, and irrigated field area. In 2013, five indicators were in negative potential: irrigated area, vegetable area, facility agricultural area, fruit tree area, and the number of wells. Herein, the spatial and temporal variations in the water table depth of the study area are analyzed using a geostatistical method. Moreover, the influence of each water part on the groundwater exploitation intensity is further diagnosed and evaluated based on set pair analysis. The obtained results can provide a theoretical and methodological reference for the sustainable utilization of groundwater in regions where groundwater is the main water supply source, providing a basis for industrial regulation policies in the region.

Increased urbanization has caused problems such as increasing water consumption and the continuous deterioration of the groundwater environment. It is necessary to consider the groundwater quality in the water resource optimization system and increase the rate of reclaimed water development to reduce the amount of groundwater exploitation and achieve sustainable development of water resources. This study used the Daxing District, a region of Beijing’s southern plain, as an example to evaluate water quality by analyzing water quality data of surface and groundwater from 2012 to 2016 and actual water-use schemes from 2006 to 2016. Three groundwater extraction modes were set up based on NO₃–N concentrations, water resources were optimized under three extraction modes, and water resource optimization schemes were determined based on the improved connection entropy. The results show that (1) the surface water quality was poor, and the proportion of V₄ type water in the indexes of NH₃–N and chemical oxygen demand (COD) was the largest. The surface water can only be used for agricultural irrigation. The pollution sources contributing most to NH₃–N and COD were domestic and agricultural pollution sources. (2) The groundwater quality was good. The NO₃–N index was primarily type I–III water, accounting for 95.20% of the total samples. Severe NH₃–N pollution areas were mainly in the northern region, and most regional groundwater can be used for various purposes. (3) Taking 2016 as an example, three groundwater exploitation modes were set to optimize water resource allocation, and the results showed that the rate of groundwater development and NO₃–N pollution decreased significantly after optimization. (4) Connection entropy is an evaluation method that combines connection numbers and entropy, including identify, difference, and opposition entropy. As connection entropy being a kind of complete entropy, which can reflect the difference of the system in different states, based on the improved connection entropy, the connection entropies of optimal water resource allocation and actual water-use schemes were calculated. The connection entropy of groundwater exploitation mode 3 was less than that of groundwater exploitation modes 1 and 2 and actual water-use schemes from 2006 to 2016. Therefore, exploitation mode 3’s water resource optimization scheme was recommended. In the paper, satisfactory results have been obtained. As a kind of complete entropy, connection entropy has great research value in dealing with complex hydrological problems. This study’s research methods and outcomes can provide methodological and theoretical lessons for water management in freshwater-deficient areas.