Shiyang Yin

Geostatistical interpolation model selection based on ArcGIS and spatio-temporal variability analysis of groundwater level in piedmont plains, northwest China

Abstract Based on the geo-statistical theory and ArcGIS geo-statistical module, datas of 30 groundwater level observation wells were used to estimate the decline of groundwater level in Beijing piedmont. Seven different interpolation methods (inverse distance weighted interpolation, global polynomial interpolation, local polynomial interpolation, tension spline interpolation, ordinary Kriging interpolation, simple Kriging interpolation and universal Kriging interpolation) were used for interpolating groundwater level between 2001 and 2013. Cross-validation, absolute error and coefficient of determination (R2) was applied to evaluate the accuracy of different methods. The result shows that simple Kriging method gave the best fit. The analysis of spatial and temporal variability suggest that the nugget effects from 2001 to 2013 were increasing, which means the spatial correlation weakened gradually under the influence of human activities. The spatial variability in the middle areas of the alluvial–proluvial fan is relatively higher than area in top and bottom. Since the changes of the land use, groundwater level also has a temporal variation, the average decline rate of groundwater level between 2007 and 2013 increases compared with 2001–2006. Urban development and population growth cause over-exploitation of residential and industrial areas. The decline rate of the groundwater level in residential, industrial and river areas is relatively high, while the decreasing of farmland area and development of water-saving irrigation reduce the quantity of water using by agriculture and decline rate of groundwater level in agricultural area is not significant.

Natural and anthropogenic factors affecting the shallow groundwater quality in a typical irrigation area with reclaimed water, North China Plain

In this study, the hydrochemical characteristics of shallow groundwater were analyzed to get insight into the factors affecting groundwater quality in a typical agricultural dominated area of the North China Plain. Forty-four shallow groundwater samples were collected for chemical analysis. The water type changes from Ca·Na-HCO3 type in grass land to Ca·Na-Cl (+NO3) type and Na (Ca)-Cl (+NO3+SO4) type in construction and facility agricultural land, indicating the influence of human activities. The factor analysis and geostatistical analysis revealed that the two major factors contributing to the groundwater hydrochemical compositions were the water-rock interaction and contamination from sewage discharge and agricultural fertilizers. The major ions (F, HCO3) and trace element (As) in the shallow groundwater represented the natural origin, while the nitrate and sulfate concentrations were related to the application of fertilizer and sewage discharge in the facility agricultural area, which was mainly affected by the human activities. The values of pH, total dissolved solids, electric conductivity, and conventional component (K, Ca, Na, Mg, Cl) in shallow groundwater increased from grass land and cultivated land, to construction land and to facility agriculture which were originated from the combination sources of natural processes (e.g., water-rock interaction) and human activities (e.g., domestic effluents). The study indicated that both natural processes and human activities had influences on the groundwater hydrochemical compositions in shallow groundwater, while anthropogenic processes had more contribution, especially in the reclaimed water irrigation area.