Groundwater pumping effects on contaminant loading management in agricultural regions.

Groundwater pumping changes the behavior of subsurface water, including the location of the water table and characteristics of the flow system, and eventually affects the fate of contaminants, such as nitrate from agricultural fertilizers. The objectives of this study were to demonstrate the importance of considering the existing pumping conditions for contaminant loading management and to develop a management model to obtain a contaminant loading design more appropriate and practical for agricultural regions where groundwater pumping is common. Results from this study found that optimal designs for contaminant loading could be determined differently when the existing pumping conditions were considered. This study also showed that prediction of contamination and contaminant loading management without considering pumping activities might be unrealistic. Motivated by these results, a management model optimizing the permissible on-ground contaminant loading mass together with pumping rates was developed and applied to field investigation and monitoring data from Icheon, Korea. The analytical solution for 1-D unsaturated solute transport was integrated with the 3-D saturated solute transport model in order to approximate the fate of contaminants loaded periodically from on-ground sources. This model was further expanded to manage agricultural contaminant loading in regions where groundwater extraction tends to be concentrated in a specific period of time, such as during the rice-growing season, using a method that approximates contaminant leaching to a fluctuating water table. The results illustrated that the simultaneous management of groundwater quantity and quality was effective and appropriate to the agricultural contaminant loading management and the model developed in this study, which can consider time-variant pumping, could be used to accurately estimate and to reasonably manage contaminant loading in agricultural areas.

Prediction of groundwater contamination with multivariate regression and probabilistic capture zones.

Probabilistic capture zones are combined with a regression model and used as buffer zones around wells for Tobit regression analysis to predict contaminant concentration of groundwater in an agricultural region. A backward transport equation, which is a mathematical model based on the physical processes of solute transport, is used to delineate probabilistic capture zones. The probabilistic capture zone defines the area where contaminant discharge can have a direct influence, with pertinent probability, on the quality of groundwater pumped from a well. Tobit regression analysis is used to find the relationship between independent regression variables and a dependent variable, which is contaminant concentration in this study. The capture zone and the regression are combined into a model, and its applicability for prediction of nitrate concentration is tested in a small agricultural basin in Chuncheon, Korea, which is occupied mainly by vegetation fields, orchards, and small barns. Three cases of Model 1, Model 2, and Model 3 are compared in which buffer zones are circles, capture zones with probability over 0.1, and capture zones divided into sections with different probabilities, respectively. The resulting regression model describes nitrate concentration in terms of selected independent variables. When the concentrations are calculated with the model, the best fit with the observed concentrations was in Model 3. This result supports the applicability of the method proposed in this study to prediction of contaminant concentration of groundwater.

Factors affecting the spatial pattern of nitrate contamination in shallow groundwater.

The elevated level of nitrate in groundwater is a serious problem in Korean agricultural areas. To control and manage groundwater quality, the characterization of groundwater contamination and identification of the factors affecting the nitrate concentration of groundwater are significant. The characterization of groundwater contamination at a hydrologically complex agricultural site in Yupori, Chuncheon (Korea) was undertaken by analyzing the hydrochemical data of groundwater within a statistical framework. Multivariate statistical tools such as cluster analyses and Tobit regression were applied to investigate the spatial variation of nitrate contamination and to analyze the factors affecting the NO3-N concentration in a shallow groundwater system. The groundwater groups from the cluster analysis were consistent with the land use pattern of the study area. The clustered group of a gentle-slope area with lower elevations showed higher NO3-N contamination of groundwater than groups on a hillside with higher elevations. Tobit regression results indicated that the agricultural activity in the vegetable fields and barns were the major factors affecting the elevated NO3-N concentration while the land slopes and elevations were negatively correlated with the NO3-N concentration. This shows that topographic characteristics such as land slopes and elevations should be considered to evaluate the land use impact on shallow groundwater quality.

Identification of the source of nitrate contamination in ground water below an agricultural site, Jeungpyeong, Korea.

This study applied hydrogeological characterization and isotope investigation to identify source locations and to trace a plume of ground water contaminated by nitrate. Most of the study site is agricultural fields with the remainder being residential. A poultry farm is also within the study area, so that potential point and nonpoint sources were present. Estimates of seasonal ground water recharge from irrigation and precipitation, leakage of sewage, and the regional ground water flow were linked to the seasonal changes in isotopic values. Ground water recharge largely occurred in spring and summer following precipitation or irrigation, depending on the locations. Natural and fertilized soils were identified as nonpoint sources of nitrate contamination in this area, while septic and animal wastes were identified as small point sources. The seasonal changes in the relative impact of these sources on ground water contamination were related to such factors as source distribution, the aquifer confining condition, precipitation rate, infiltration capacity, recharge rate, and the land use pattern.