A new model was developed to predict head loss in sand media filters. Sand filters with six different media using reclaimed water were used to measure head losses at different flow rates in the laboratory. The parameters influencing head losses were considered to be the uniformity coefficient, the effective diameter, the sand mass, the filtration velocity, the pollution load, and the water viscosity. A dimensional analysis method was used to develop the model. A comparison between the predicted and the measured head losses showed close agreement with a correlation coefficient of 91.7%, reaching a significance level of p < 0.001. The results showed that the model might give satisfactory predictions within the following range of operational and filter structure parameters: uniformity coefficient 1.48–3.31; effective diameter 0.41–2.1 mm; pollution load 0.0169–4.2049 kg, filtration velocity 0.0038–0.0398 m/s.

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.