Groundwater nitrate-N Research Articles

Assessment of aquifer specific vulnerability to total nitrate contamination using ensemble learning and geochemical evidence

Henan Province's plain area is the granary of China, yet its regional aquifer is being polluted by industrial wastewater, agricultural pesticide, fertilizer and domestic wastewater. In order to safeguard the security of food and drinking water, and in response to the problem of low prediction accuracy caused by the lack of samples and unevenly distributed groundwater monitoring data, we propose a new way to predict the aquifer vulnerability in large areas by rich small-scale data, so as to identify the pollution risks and to address the issue of sample shortage. In small regions with abundant nitrate data, we employed a Random Forest model to screen key impact indicators, using them as features and nitrate-N concentration as the target variable. Consequently, we established six machine learning prediction models, and then selected the best bagging model (R2 = 0.86) to predict the vulnerability of aquifers in larger regions lacking nitrate data. The predicted results showed that highly vulnerable areas accounted for 20 %, which were mainly affected by aquifer thickness (65.91 %). High nitrate-N concentration implies serious aquifer contamination. Therefore, a long series of groundwater nitrate-N concentration monitoring data in a large scale, the trend and slope of nitrate-N concentration showed a significant correlation with the model prediction results (Spearman's correlation coefficients are 0.75 and 0.58). This study can help identify the risk of aquifer contamination, solve the problem of sample shortage in large areas, thus contributing to the security of food and drinking water.

Quantify the effects of groundwater level recovery on groundwater nitrate dynamics through a quasi-3D integrated model for the vadose zone-groundwater coupled system

Groundwater level (GWL) recovery in some semiarid regions, attributed to mitigation countermeasures for groundwater depletion, potentially causes nitrate accumulated in the vadose zone to be introduced into the aquifer. However, the extent to which GWL recovery affects interactions between the vadose zone and saturated aquifers, migration pathways of soil nitrogen and groundwater nitrate dynamics have not been explicitly determined. This study established a quasi-3D feedback model for the vadose zone-groundwater coupled system in a typical GWL recovery area and quantitatively evaluated the effects of GWL recovery on nitrate-N leaching fluxes via the vadose zone and groundwater nitrate-N dynamics. Within the framework of the integrated model, both the water/contaminant leaching fluxes and the depth to groundwater were exchanged at each flow time step. The obtained results reveal that the temporal changes in nitrate-N leaching fluxes depended on the behaviors of precipitation, farmland irrigation and lithology of the vadose zone, while its spatial patterns were determined by both the GWL undulation and the vertical profiles of nitrate-N content. Furthermore, the GWL recovery caused the magnitude of the nitrate-N leaching fluxes into the aquifer to increase by 44.4%. Along with the GWL recovery, the phreatic aquifer volume increased by 7.47%, and the nitrate-N mass herein increased by 40.06%, which was largely driven by the nitrate-N leaching flux. Consequently, the average groundwater nitrate-N concentration in the GWL recovery region increased by approximately 2.4 mg/L, apart from the artificial recharge route. This finding suggests that the intensified leaching of soil contaminants, given the circumstances of GWL recovery, has a negative effect on groundwater quality. An appropriate groundwater management scheme is therefore urgently required to achieve an optimal balance between GWL recovery and groundwater environment.

Evaluation of groundwater vulnerability to nitrate in shallow aquifer using multi-layer fuzzy inference system within GIS environment

Groundwater aquifer vulnerability to nitrate has become a major concern to all stakeholders involved in managing the quality of water in relation to human health. This paper presents fuzzy inference system (FIS) as an alternative to the conventional overlay index methods for the evaluation of groundwater vulnerability to nitrate pollution in watershed scale within GIS environment. A multilayer FIS model is developed taking advantage of expert knowledge-based DRASTIC system in order to overcome the problem of rule explosion. A case study relating to groundwater vulnerability assessment in shallow aquifer of Kathmandu basin in Nepalis accomplished. The correlations between groundwater vulnerability indices and nitrate-N concentration values were carried out for the validation of vulnerability models. The result shows that the best combination is obtained from fuzzy vulnerability model (r = 0.52) followed by DRASTIC method (r = 0.38). We have also developed a groundwater nitrate-N risk map by integrating groundwater aquifer vulnerability, the nitrate-N distribution map (pollution severity) and the probability of occurrence map based on the limiting threshold value of nitrate-N. Spatial distribution map of nitrate-N shows that nearly 10% of the study area lies within high hazard class which exceeds limiting value of 10 mg/L nitrate-N value, and nearly 50% of the shallow aquifer fall within medium hazard class which has impacted level of nitrate-N, i.e., between 2 mg/L and 10 mg/L. These results also indicate that the northern part of the Kathmandu basin and highly permeable alluvial deposits are dominated by very high vulnerability level, and are also under a threat of high nitrate-N risk. Groundwater aquifer vulnerability and nitrate risk maps are expected to facilitate design and development strategies towards protecting environment and preventing further deterioration of the affected aquifers.

Groundwater nitrate in three distinct hydrogeologic and land-use settings in southwestern Ontario, Canada

Groundwater nitrate is a concern in the Great Lakes Basin (GLB) of North America. Concentrations vary based on hydrogeologic setting and surface contamination pressures. The first objective of this study was to characterize groundwater nitrate trends in a spatial and temporal context across three unique hydrogeologic and land-use settings in the GLB, at research sites in Norfolk, Guelph, and Acton, in southwestern Ontario, Canada. The second objective was to compare groundwater nitrate trends at the sites to determine the potential influence of hydrogeologic setting on seasonal nitrate variability. Groundwater nitrate-N concentrations and additional parameters were measured at 25 monitoring wells at the three sites, once every 2 months from June 2014 to July 2016 (13 sampling events). The dominant land-use pressure at all three sites is agricultural; however, the type of agriculture and the amount of natural and urban land vary. The Guelph site had the highest nitrate concentrations, while the Acton and Norfolk mean concentrations were similar. Seasonally, nitrate was found to be highest during the spring and early summer periods at all three sites. Several monitoring locations had cyclical patterns in nitrate concentrations, while others remained consistent except for isolated peak events. Comparison of multiple years reveals the expression of a relationship between climatic conditions during winter months and nitrate concentrations, indicating the importance of antecedent conditions to groundwater nitrate concentrations. The combination of climatic conditions, land-use pressure, and hydrogeologic setting plays an important role in the characteristics of groundwater nitrate time-series trends.

Horizontal Well Test for Simulating the In Situ Remediation of Nitrate Contaminated Groundwater by Microbial Denitrification

An in situ horizontal well (IHW) fan-shaped test tank was constructed in the laboratory. And nitrate removal rates were analyzed under different hydraulic loads. When the initial concentration of groundwater nitrate-N was 25 mg/L and the hydraulic load increased from 0.78 to 3.90 m3/(m2 day), the results show that the nitrate-N concentration was less than 1.25 mg/L after the denitrification process stabilized. Additionally, the nitrate-N removal rate was over 95%. The concentration of nitrite-N was still below 1 mg/L, and the level of ammonia-N was between 0.5 and 1.00 mg/L. No increase in nitrite-N and ammonia-N concentration occurred during the test. The hydraulic conductivity of the medium in the horizontal well showed little variation, ranging from 34.09 to 31.64 m/day, indicating that there was no blockage caused by microbial growth in the IHW during the test. In addition, no ethanol was detected in the test tank except for the horizontal well, revealing that ethanol did not diffuse into the surrounding aquifer. Therefore, when the concentration of groundwater nitrate contamination is 25 mg/L, the hydraulic load under the IHW test tank condition is 3.90 m3/(m2 day). The IHW test tank had a stable and good biological denitrification effect, and it can provide certain reference significance for in situ remediation of nitrate-contaminated groundwater.

Soil nutrient variability and groundwater nitrate-N in agricultural fields

Landscape may result in uneven nutrient loads within a field. The objective of this study was to determine the influence of landscape on soil carbon and nutrient levels, and on levels of nitrate-N in groundwater. Soil samples were collected in three fields, two transects each, 30 sites in each field. The soil morphology was characterized for the profile, and soil organic carbon and nutrient levels were determined for 0–0.15 and 0.15–0.3 m depths. Each field had wells installed at three of the sites. One field showed a wide range of landscape variability, and significant effects of curvature on soil carbon and nutrient levels. Another field showed no significant effect of slope or curvature on soil carbon and nutrient levels because the nutrient levels were quite variable, including high spikes. The third field had less variable landscape trends but still showed a few significant effects on soil carbon and nutrient levels. Nitrate-N levels remained high in two of the nine wells (20 to 50 mg L−1), suggesting that additions of nitrate-N at the concave or converging sites replaced any losses. Median nitrate-N levels at the other seven well sites were lower, ranging from 8 to 17 mg L−1. Influence of landscape on soil carbon and nutrients was more detectable when the landscape factors were highly variable without excessive variability in soil nutrient properties.

Nitrate-nitrogen contamination in groundwater: Spatiotemporal variation and driving factors under cropland in Shandong Province, China

High groundwater nitrate-N is a serious problem especially in highly active agricultural areas. In study, the concentration and spatialtemporal distribution of groundwater nitrate-N under cropland in Shandong province were assessed by statistical and geostatistical techniques. Nitrate-N concentration reached a maximum of 184.60 mg L-1 and 29.5% of samples had levels in excess of safety threshold concentration (20 mg L-1). The median nitrate-N contents after rainy season were significantly higher than those before rainy season, and decreased with increasing groundwater depth. Nitrate-N under vegetable and orchard area are significantly higher than ones under grain. The kriging map shows that groundwater nitrate-N has a strong spatial variability. Many districts, such as Weifang, Linyi in Shandong province are heavily contaminated with nitrate-N. However, there are no significant trends of NO3--N for most cities. Stepwise regression analysis showed influencing factors are different for the groundwater in different depth. But overall, vegetable yield per unit area, percentages of orchard area, per capita agricultural production, unit-area nitrogen fertilizer, livestock per unit area, percentages of irrigation areas, population per unit area and annual mean temperature are significant variables for groundwater nitrate-N variation.

Nitrogen Source Inventory and Loading Tool: An integrated approach toward restoration of water-quality impaired karst springs

Nitrogen (N) from anthropogenic sources has contaminated groundwater used as drinking water in addition to impairing water quality and ecosystem health of karst springs. The Nitrogen Source Inventory and Loading Tool (NSILT) was developed as an ArcGIS and spreadsheet-based approach that provides spatial estimates of current nitrogen (N) inputs to the land surface and loads to groundwater from nonpoint and point sources within the groundwater contributing area. The NSILT involves a three-step approach where local and regional land use practices and N sources are evaluated to: (1) estimate N input to the land surface, (2) quantify subsurface environmental attenuation, and (3) assess regional recharge to the aquifer. NSILT was used to assess nitrogen loading to groundwater in two karst spring areas in west-central Florida: Rainbow Springs (RS) and Kings Bay (KB). The karstic Upper Floridan aquifer (UFA) is the source of water discharging to the springs in both areas. In the KB study area (predominantly urban land use), septic systems and urban fertilizers contribute 48% and 22%, respectively, of the estimated total annual N load to groundwater 294,400 kg-N/yr. In contrast for the RS study area (predominantly agricultural land use), livestock operations and crop fertilizers contribute 50% and 13%, respectively, of the estimated N load to groundwater. Using overall groundwater N loading rates for the KB and RS study areas, 4.4 and 3.3 kg N/ha, respectively, and spatial recharge rates, the calculated groundwater nitrate-N concentration (2.1 mg/L) agreed closely with the median nitrate-N concentration (1.7 mg/L) from groundwater samples in agricultural land use areas in the RS study area for the period 2010–2014. NSILT results provide critical information for prioritizing and designing restoration efforts for water-quality impaired springs and spring runs affected by multiple sources of nitrogen loading to groundwater. The calculated groundwater N concentration for the KB study area (1.45 mg/L) was approximately three times higher than the median N concentration (0.45 mg/L) for wells located in urban land use areas.

Examining the impacts of increased corn production on groundwater quality using a coupled modeling system.

This study demonstrates the value of a coupled chemical transport modeling system for investigating groundwater nitrate contamination responses associated with nitrogen (N) fertilizer application and increased corn production. The coupled Community Multiscale Air Quality Bidirectional and Environmental Policy Integrated Climate modeling system incorporates agricultural management practices and N exchange processes between the soil and atmosphere to estimate levels of N that may volatilize into the atmosphere, re-deposit, and seep or flow into surface and groundwater. Simulated values from this modeling system were used in a land-use regression model to examine associations between groundwater nitrate-N measurements and a suite of factors related to N fertilizer and groundwater nitrate contamination. Multi-variable modeling analysis revealed that the N-fertilizer rate (versus total) applied to irrigated (versus rainfed) grain corn (versus other crops) was the strongest N-related predictor variable of groundwater nitrate-N concentrations. Application of this multi-variable model considered groundwater nitrate-N concentration responses under two corn production scenarios. Findings suggest that increased corn production between 2002 and 2022 could result in 56% to 79% increase in areas vulnerable to groundwater nitrate-N concentrations ≥ 5 mg/L. These above-threshold areas occur on soils with a hydraulic conductivity 13% higher than the rest of the domain. Additionally, the average number of animal feeding operations (AFOs) for these areas was nearly 5 times higher, and the mean N-fertilizer rate was 4 times higher. Finally, we found that areas prone to high groundwater nitrate-N concentrations attributable to the expansion scenario did not occur in new grid cells of irrigated grain-corn croplands, but were clustered around areas of existing corn crops. This application demonstrates the value of the coupled modeling system in developing spatially refined multi-variable models to provide information for geographic locations lacking complete observational data; and in projecting possible groundwater nitrate-N concentration outcomes under alternative future crop production scenarios.

Field nitrogen budgets and post-harvest soil nitrate as indicators of N leaching to groundwater in a Pacific Northwest dairy grass field

Dairy farms in the U.S. are expected to use farm-field nitrogen (N) budgeting techniques to determine appropriate agronomic manure application rates for crops. As part of nutrient management, post-harvest soil nitrate sampling is often relied upon to indicate the amount of N not used for crop growth during the growing season. A 4–1/2-year study was conducted that quantified the major N inputs, outputs, and residuals (soil and groundwater) at a commercial dairy field overlying a shallow unconfined aquifer in the Pacific Northwest. The purpose of the study was to evaluate the relationships between two indicators, (1) N mass residuals estimated by farm-field N budget and (2) post-harvest soil nitrate residuals, against measured groundwater nitrate-N concentrations following high seasonal recharge. A mass balance mixing-box spreadsheet model that accounts for the hydrogeologic characteristics of the site was used to quantitatively predict the impact of excess farm-field N on underlying shallow groundwater nitrate-N concentrations. Despite intensive sampling of N balance components and post-harvest soil nitrate conditions, the N-budget-predicted groundwater nitrate-N was 37% of the average field-measured early winter groundwater concentration. The post-harvest soil nitrate-predicted groundwater nitrate-N concentration was 140% of that measured in the field. Neither indicator provided a reliable prediction of the groundwater quality response to land application of nutrients using the spreadsheet model in this poorly drained/high water table setting. The mixing-box model provides a basic tool for testing hypothetical nutrient management scenarios in a variety of conditions. However, groundwater nitrate monitoring data are needed to determine actual outcomes.

Hot Spots and Persistence of Nitrate in Aquifers Across Scales

Nitrate-N (NO3 -- N) is one of the most pervasive contaminants in groundwater. Nitrate in groundwater exhibits long-term behavior due to complex interactions at multiple scales among various geophysical factors, such as sources of nitrate-N, characteristics of the vadose zone and aquifer attributes. To minimize contamination of nitrate-N in groundwater, it is important to estimate hot spots (>10 mg/L of NO3 -- N), trends and persistence of nitrate-N in groundwater. To analyze the trends and persistence of nitrate-N in groundwater at multiple spatio-temporal scales, we developed and used an entropy-based method along with the Hurst exponent in two different hydrogeologic settings: the Trinity and Ogallala Aquifers in Texas at fine (2 km × 2 km), intermediate (10 km × 10 km) and coarse (100 km × 100 km) scales. Results show that nitrate-N exhibits long-term persistence at the intermediate and coarse scales. In the Trinity Aquifer, overall mean nitrate-N has declined with a slight increase in normalized marginal entropy (NME) over each decade from 1940 to 2008; however, the number of hot spots has increased over time. In the Ogallala Aquifer, overall mean nitrate-N has increased with slight moderation in NME since 1940; however, the number of hot spots has significantly decreased for the same period at all scales.

Developing a reliable model for aquifer vulnerability

The assessment of aquifer vulnerability to pollution is crucial for planning a sound management strategy of groundwater quality protection and farmland fertilizer use. This study establishes a reliable model for aquifer vulnerability assessment with an excellent performance for predicting groundwater nitrate-N contamination in the Choushui River alluvial fan, Taiwan based on the DRASTIC method. To promote the prediction performance of aquifer vulnerability assessment, discriminant analysis (DA) was applied to determine the weights of factors in the DRASTIC model by comparing the model results with the observed nitrate-N data. Key factors influencing the presence of groundwater nitrate-N pollution were characterized for different concentration thresholds. The results of analysis reveal that the modified DRASTIC model using DA significantly improves prediction performance for aquifer vulnerability assessment, and groundwater protection zones can be determined correctly based on the modified DRASTIC index. Furthermore, the sensitivity of the factors in the modified DRASTIC model indicates that the depth to the groundwater and aquifer media are critical when the nitrate-N concentration is less than 3 mg/L, while the impact of the vadose zone plays a vital role in controlling nitrate-N pollution of over 5 mg/L.

Groundwater Quality and Nitrogen Use Efficiency in Nebraska's Central Platte River Valley

Groundwater nitrate contamination has been an issue in the Platte River Valley of Nebraska since the 1960s, with groundwater nitrate-N concentrations frequently in excess of 10 mg L. This article summarizes education and regulatory efforts to reduce the environmental impact of irrigated crop production in the Platte River Valley. In 1988, a Groundwater Management Area (GWMA) was implemented in the Central Platte Natural Resources District to encourage adoption of improved management practices. Since 1988, there have been steady declines in average groundwater nitrate-N concentrations of about 0.15 mg NO-N L yr in much of the GWMA (from 19 to 15 mg NO-N L). However, N use efficiency (NUE) (partial factor productivity for N [PFP]) has increased very little from 1988 to 2012 (60-65 kg grain kg N), whereas statewide PFP increased from 49 to 67 kg grain kg N in the same period. Although growers are encouraged to credit N from sources besides fertilizer (e.g., soil residual, legumes, irrigation water, and manure), confidence in and use of credits tended to decrease as credits became larger; there was a tendency toward an average N rate regardless of credit-based recommendations. This information, coupled with data from other studies, suggests that much of the decline in groundwater nitrate can be attributed to improved irrigation management-especially conversion from furrow to sprinkler irrigation-and to a lesser extent to improved timing of N application. The development and adoption of improved N management practices, such as fertigation, controlled-release N formulation, and use of crop canopy sensors for in-season N application may be required for further significant NUE gains in these irrigated systems.

Integrating indicator-based geostatistical estimation and aquifer vulnerability of nitrate-N for establishing groundwater protection zones

Summary Groundwater nitrate-N contamination occurs frequently in agricultural regions, primarily resulting from surface agricultural activities. The focus of this study is to establish groundwater protection zones based on indicator-based geostatistical estimation and aquifer vulnerability of nitrate-N in the Choushui River alluvial fan in Taiwan. The groundwater protection zones are determined by univariate indicator kriging (IK) estimation, aquifer vulnerability assessment using logistic regression (LR), and integration of the IK estimation and aquifer vulnerability using simple IK with local prior means (sIKlpm). First, according to the statistical significance of source, transport, and attenuation factors dominating the occurrence of nitrate-N pollution, a LR model was adopted to evaluate aquifer vulnerability and to characterize occurrence probability of nitrate-N exceeding 0.5 mg/L. Moreover, the probabilities estimated using LR were regarded as local prior means. IK was then used to estimate the actual extent of nitrate-N pollution. The integration of the IK estimation and aquifer vulnerability was obtained using sIKlpm. Finally, groundwater protection zones were probabilistically determined using the three aforementioned methods, and the estimated accuracy of the delineated groundwater protection zones was gauged using a cross-validation procedure based on observed nitrate-N data. The results reveal that the integration of the IK estimation and aquifer vulnerability using sIKlpm is more robust than univariate IK estimation and aquifer vulnerability assessment using LR for establishing groundwater protection zones. Rigorous management practices for fertilizer use should be implemented in orchards situated in the determined groundwater protection zones.

Meteorological Influences on Nitrogen Dynamics of a Coastal Onsite Wastewater Treatment System

On-site wastewater treatment systems (OWTS) can contribute nitrogen (N) to coastal waters. In coastal areas with shallow groundwater, OWTS are likely affected by meteorological events. However, the meteorological influences on temporal variability of N exports from OWTS are not well documented. Hydrogeological characterization and seasonal monitoring of wastewater and groundwater quality were conducted at a residence adjacent to the Pamlico River Estuary, North Carolina, during a 2-yr field study (October 2009-2011). Rainfall was elevated during the first study year, relative to the annual mean. In the second year, drought was followed by extreme precipitation from Hurricane Irene. Recent meteorological conditions influenced N speciation and concentrations in groundwater. Groundwater total dissolved nitrogen (TDN) beneath the OWTS drainfield was dominated by nitrate during the drought; during wetter periods, ammonium and organic N were common. Effective precipitation (precipitation [P] minus evapotranspiration [ET]) affected OWTS TDN exports because of its influence on groundwater recharge and discharge. Groundwater nitrate-N concentrations beneath the drainfield were typically higher than 10 mg/L when total biweekly precipitation was less than evapotranspiration (precipitation deficit: P < ET). Overall, groundwater TDN concentrations were elevated above background concentrations at distances >15 m downgradient of the drainfield. Although OWTS nitrate inputs caused elevated groundwater nitrate concentrations between the drainfield and the estuary, the majority of nitrate was attenuated via denitrification between the OWTS and 48 m to the estuary. However, DON originating from the OWTS was mobile and contributed to elevated TDN concentrations along the groundwater flowpath to the estuary.

Nitrate leaching in californian rice fields: a field- and regional-scale assessment.

Irrigated croplands can be a major source of nitrate-N (NO-N) in groundwater due to leaching. In California, where high NO-N levels have been found in some areas of the Central Valley aquifer, the contribution from rice systems has not been determined. Nitrate leaching from rice systems was evaluated from soil cores (0-2 m), from the fate of N fertilizer in replicated microplots, and from about 145 regional groundwater wells. Soil NO-N concentrations were ≤3.3 mg kg (usually <1 mg kg) below the root zone (below 33 cm depth). In pore-water samples, NO-N was observed only below the root zone during the first 2 wk after the onset of flooding in either the growing season or the winter fallow period and was always ≤8.4 mg L. Fertilizer N accounted for 0 to 11.8% of NO-N in pore-water samples below the root zone. One year after application, based on an analysis of soil core samples, on average 2.5% of fertilizer N was recovered as N below the root zone (33-100 cm), possibly due to leaching in permeable soils or via preferential flow through cracks in heavy clay soils. Based on a regional assessment, groundwater samples from wells that are located in proximity to rice fields all had measured median NO-N and NO-N levels below 1 mg L. These results indicate that NO-N leaching from the majority of California rice systems poses little risk to groundwater under current crop management practices.

Coupling of surface water and groundwater nitrate-N dynamics in two permeable agricultural catchments

SUMMARYThe current study investigated the coupling of groundwater and surface water nitrogen (N) dynamics over 3 years, and considered intensive agricultural land-management influences over this period where the risk of N loss to water was considered high. Groundwater N (as nitrate) was monitored monthly in different strata and zones in four hillslopes, two in each of two agricultural catchments ofc. 10 km2, and stream water N flux was monitored sub-hourly in the catchment outlets. Field nutrient sources were connected to surface waterviagroundwater; the groundwater along hillslopes was seen to be influenced spatially and temporally by management, geology and weather as observed in the concentration variability of nitrate in groundwater. Based on spatio-temporal averages of nitrate-N concentration, groundwater status was considered good (at least below a maximum acceptable concentration (MAC) of 11·3 mg/l). However, zones coincident with land-use change (ploughing and reseeding, typical of a management event in intensive landscapes), showed high spatio-temporal variability in nitrate-N concentration, exceeding the MAC temporarily, before recovering. This spatio-temporal variability highlighted the need for insight into these differences when interpreting groundwater quality data from a limited number of basin-scale sampling points and occasions. In both catchments the 3-year mean nitrate-N concentration in stream water was similar to the spatio-temporal mean concentration in groundwater. The magnitude and variability of loads, however, were more related to changes in annual runoff rather than changes in annual groundwater nitrate-N status. In one wet year, nitrate-N loads exceeded 48 kg/ha from an Arable catchment and 45 kg/ha from a grassland catchment (close to double the loss in a dry year).

Letting Wet Spots be Wet: Restoring Natural Bioreactors in the Dissected Glacial Landscape

In this paper, we argue that there is tremendous potential for nitrate-N reductions to occur throughout the Corn Belt region of the USA if we simply let naturally occurring wet spots on the landscape be wet. Geologic and hydrologic data gathered in the Walnut Creek watershed located in south-central Iowa provides compelling evidence that substantial nutrient-processing capacity exists in this dissected glacial landscape. Self-similarity of stratigraphy, sedimentology and hydrology observed at all spatial scales in the watershed suggests that Holocene alluvial fill deposits provide a natural bioreactor for denitrification of upland groundwater nitrate-N; the occurrence of such deposits can be mapped to identify potential nitrogen sinks across the landscape. This approach to identifying potential nitrogen sinks is geology focused and extends potential locations for nutrient processing upstream into the headwater catchments of individual fields.

Probability-based nitrate contamination map of groundwater in Kinmen

Groundwater supplies over 50% of drinking water in Kinmen. Approximately 16.8% of groundwater samples in Kinmen exceed the drinking water quality standard (DWQS) of NO3 (-)-N (10 mg/L). The residents drinking high nitrate-polluted groundwater pose a potential risk to health. To formulate effective water quality management plan and assure a safe drinking water in Kinmen, the detailed spatial distribution of nitrate-N in groundwater is a prerequisite. The aim of this study is to develop an efficient scheme for evaluating spatial distribution of nitrate-N in residential well water using logistic regression (LR) model. A probability-based nitrate-N contamination map in Kinmen is constructed. The LR model predicted the binary occurrence probability of groundwater nitrate-N concentrations exceeding DWQS by simple measurement variables as independent variables, including sampling season, soil type, water table depth, pH, EC, DO, and Eh. The analyzed results reveal that three statistically significant explanatory variables, soil type, pH, and EC, are selected for the forward stepwise LR analysis. The total ratio of correct classification reaches 92.7%. The highest probability of nitrate-N contamination map presents in the central zone, indicating that groundwater in the central zone should not be used for drinking purposes. Furthermore, a handy EC-pH-probability curve of nitrate-N exceeding the threshold of DWQS was developed. This curve can be used for preliminary screening of nitrate-N contamination in Kinmen groundwater. This study recommended that the local agency should implement the best management practice strategies to control nonpoint nitrogen sources and carry out a systematic monitoring of groundwater quality in residential wells of the high nitrate-N contamination zones.

Groundwater denitrification capacity and nitrous oxide flux of former fringing salt marshes filled with human-transported materials

While former salt marsh sites filled with human transported material (HTM) have altered the surface marsh ecosystem, if artificial drainage is absent, subsurface conditions may continue favorable for denitrification, a microbial process reducing nitrogen (N) export to estuaries. We used piezometer networks to evaluate the in situ groundwater denitrification capacity and nitrous oxide (N2O) flux (with 15N-enriched nitrate-N via the push-pull method) in four former fringing salt marshes topped by HTM along the Rhode Island coast, U.S.A. Groundwater at these sites commonly interacted with the buried marsh horizon and the HTM. In situ groundwater denitrification capacity site means ranged from 15.2 to 71.7 μg N kg−1d−1 with no significant differences between sites due to high intrasite variability. The site with the highest and most consistent denitrification capacity also had HTM of the finest texture and highest soluble organic carbon. Three of four sites had minimal N2O flux [mean N2O:(N2O + N2) = 0.082] while the final site had N2O generation rates up to 52.5 μg N kg−1 d−1. The site with the highest N2O contributions also had the lowest ambient groundwater nitrate-N indicating lack of priming for N2O reduction to N2. Former salt marshes with HTM deposits may still have the capacity for substantial groundwater denitrification capacity, similar to that observed in undisturbed salt marshes, but may also contribute substantially to global N2O emissions. For both salt marsh restoration and greenhouse gas mitigation efforts, attention should be given to ensuring that a tidally-driven, fluctuating water table regularly intercepts the buried organic horizons of the filled salt marsh.