Temporal variability of nitrate concentration in groundwater affected by intensive agricultural activities in a rural area of Hongseong, South Korea

Ki, Min-Gyu; Koh, Dong‐Chan; Yoon, Heesung; Kim, Hyun-Su

doi:10.1007/s12665-015-4637-7

Cited by 28 publications

(7 citation statements)

References 41 publications

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“…Hence, to determine the sustainable management of groundwater, the evaluation of connected pressure at the different scales are vigorously essential [ 4 , 5 ]. Nitrate (NO 3 -) is the high pollutant in groundwater [ 6 , 7 ]; furthermore, NO 3 -concentration growth continues, with amplification of agricultural operations owing to the overuse of nitrogen fertilizers [ 8 , 9 , 10 ], manure management, and crop cultivation practices that move into the farming field [ 11 , 12 ]. Accordingly, the consumption of water polluted through nitrate can be connected to health problems, for example, cancers in adults via drinking water and skin contact [ 13 , 14 ].…”

Section: Introductionmentioning

confidence: 99%

Comparative Analysis of Artificial Intelligence Models for Accurate Estimation of Groundwater Nitrate Concentration

Band

Janizadeh

Pal

et al. 2020

Sensors

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Prediction of the groundwater nitrate concentration is of utmost importance for pollution control and water resource management. This research aims to model the spatial groundwater nitrate concentration in the Marvdasht watershed, Iran, based on several artificial intelligence methods of support vector machine (SVM), Cubist, random forest (RF), and Bayesian artificial neural network (Baysia-ANN) machine learning models. For this purpose, 11 independent variables affecting groundwater nitrate changes include elevation, slope, plan curvature, profile curvature, rainfall, piezometric depth, distance from the river, distance from residential, Sodium (Na), Potassium (K), and topographic wetness index (TWI) in the study area were prepared. Nitrate levels were also measured in 67 wells and used as a dependent variable for modeling. Data were divided into two categories of training (70%) and testing (30%) for modeling. The evaluation criteria coefficient of determination (R2), mean absolute error (MAE), root mean square error (RMSE), and Nash–Sutcliffe efficiency (NSE) were used to evaluate the performance of the models used. The results of modeling the susceptibility of groundwater nitrate concentration showed that the RF (R2 = 0.89, RMSE = 4.24, NSE = 0.87) model is better than the other Cubist (R2 = 0.87, RMSE = 5.18, NSE = 0.81), SVM (R2 = 0.74, RMSE = 6.07, NSE = 0.74), Bayesian-ANN (R2 = 0.79, RMSE = 5.91, NSE = 0.75) models. The results of groundwater nitrate concentration zoning in the study area showed that the northern parts of the case study have the highest amount of nitrate, which is higher in these agricultural areas than in other areas. The most important cause of nitrate pollution in these areas is agriculture activities and the use of groundwater to irrigate these crops and the wells close to agricultural areas, which has led to the indiscriminate use of chemical fertilizers by irrigation or rainwater of these fertilizers is washed and penetrates groundwater and pollutes the aquifer.

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Section: Introductionmentioning

confidence: 99%

Comparative Analysis of Artificial Intelligence Models for Accurate Estimation of Groundwater Nitrate Concentration

Band

Janizadeh

Pal

et al. 2020

Sensors

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“…From the early 2000s, the domestic sewage disposal service has significantly improved, particularly in rural areas in the country, and therefore, the unmanaged discharge of domestic wastewater has declined (Kim, 2007;Wakida & Lerner, 2005). In addition, the mixed effects of increased irrigation (pumping) of deeper, cleaner groundwater (Hosono et al, 2013;Ki et al, 2015), increased dilution of groundwater caused by higher rainfall (Kim, Chung, Tans, & Yoon, 2016), and enhanced denitrification due to changes in climate (Barclay & Walter, 2015;Cheong et al, 2012) should also be considered as possible causes of nitrate decline.…”

Section: Nitrate Levels and Groundwater Usagementioning

confidence: 99%

“…Consequently, there is a need to consolidate these data to examine the long‐term and nationwide trends in water quality. Although previous studies have investigated temporal changes in nitrate concentrations in Korean groundwater, these studies did not consider the entire country nor did they consider long term (decadal) temporal scales (Kaown, Hyun, Bae, Oh, & Lee, ; Ki, Koh, Yoon, & Kim, ). Here, we explore the changes in nitrate levels in Korean groundwater based on an analysis of the nationwide groundwater monitoring data for 2001–2013.…”

Section: Introductionmentioning

confidence: 99%

Unexpected nationwide nitrate declines in groundwater of Korea

Lee

Park

Jeon

2017

Hydrological Processes

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Elevated levels of nitrate in groundwater are an important concern for health and the environment. The overapplication of nitrogen fertilizer to croplands is one of the major sources of high nitrate content in groundwater. In this study, we analyse the nitrate concentrations in Korean groundwater based on data from groundwater quality monitoring wells (n = 1,022–2,072), which were sampled twice annually over a recent 13‐year analysis period (2001–2013). We report that groundwater nitrate levels are decreasing, despite steadily increasing groundwater use. The maximum nitrate concentration decreased from 168.91 to 48.11 mg/L, whereas the mean values also show a gradual decreasing trend. Non‐parametric Mann–Kendall tests on nitrate concentrations also confirm the decreasing trend. The nitrate decrease is more clearly evident in agricultural groundwater as compared to domestic and drinking groundwaters. This decrease of nitrate in groundwater coincides with a large decline in nitrogen fertilizer application due to reduced cropland areas, more sustainable agricultural practices, and progressive improvement of sewage disposal services. This study proposes that the long‐term adoption of best practices in agriculture has had a positive impact on groundwater nitrate control.

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“…When groundwater is pumped, its quality before and after pumping may change with the seasons. As groundwater pumping continues, the quality may change, which is caused by mixing from different aquifers, inflow of surface water from rivers or reservoirs [1][2][3][4], seawater intrusion [5][6][7], and so on. Also, groundwater quality may change temporally due to hydrologic processes, including seasonally varying rainfall and irrigation patterns [8][9][10][11].…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Seasonal Groundwater Quality Changes Associated with Groundwater Pumping and Level Fluctuations in an Agricultural Area, Korea

Lee

et al. 2020

Water

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This study was conducted to evaluate seasonal groundwater quality due to groundwater pumping and hydrochemical characteristics with groundwater level fluctuations in an agricultural area in Korea. Groundwater levels were observed for about one year using automatic monitoring sensors, and groundwater uses were estimated based on the monitoring data. Groundwater use in the area is closely related to irrigation for rice farming, and rising groundwater levels occur during the pumping, which may be caused by the irrigation water of rice paddies. Hydrochemical analysis results for two separate times (17 July and 1 October 2019) show that the dissolved components in groundwater decreased overall due to dilution, especially at wells in the alluvial aquifer and shallow depth. More than 50% of the samples were classified as CaHCO3 water type, and changes in water type occurred depending on the well location. Water quality changes were small at most wells, but changes at some wells were evident. In addition, the groundwater quality was confirmed to have the effect of saltwater supplied during the 2018 drought by comparison with seawater. According to principal component analysis (PCA), the water quality from July to October was confirmed to have changed due to dilution, and the effect was strong at shallow wells. In the study areas where rice paddy farming is active in summer, irrigation water may be one of the important factors changing the groundwater quality. These results provide a qualitative and quantitative basis for groundwater quality change in agricultural areas, particularly rice paddies areas, along with groundwater level and usage.

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Temporal variability of nitrate concentration in groundwater affected by intensive agricultural activities in a rural area of Hongseong, South Korea

Cited by 28 publications

References 41 publications

Comparative Analysis of Artificial Intelligence Models for Accurate Estimation of Groundwater Nitrate Concentration

Comparative Analysis of Artificial Intelligence Models for Accurate Estimation of Groundwater Nitrate Concentration

Unexpected nationwide nitrate declines in groundwater of Korea

Evaluation of Seasonal Groundwater Quality Changes Associated with Groundwater Pumping and Level Fluctuations in an Agricultural Area, Korea

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