Bernard T. Nolan

Workgroup Report: Drinking-Water Nitrate and Health-Recent Findings and Research Needs

Human alteration of the nitrogen cycle has resulted in steadily accumulating nitrate in our water resources. The U.S. maximum contaminant level and World Health Organization guidelines for nitrate in drinking water were promulgated to protect infants from developing methemoglobinemia, an acute condition. Some scientists have recently suggested that the regulatory limit for nitrate is overly conservative; however, they have not thoroughly considered chronic health outcomes. In August 2004, a symposium on drinking-water nitrate and health was held at the International Society for Environmental Epidemiology meeting to evaluate nitrate exposures and associated health effects in relation to the current regulatory limit. The contribution of drinking-water nitrate toward endogenous formation of N-nitroso compounds was evaluated with a focus toward identifying subpopulations with increased rates of nitrosation. Adverse health effects may be the result of a complex interaction of the amount of nitrate ingested, the concomitant ingestion of nitrosation cofactors and precursors, and specific medical conditions that increase nitrosation. Workshop participants concluded that more experimental studies are needed and that a particularly fruitful approach may be to conduct epidemiologic studies among susceptible subgroups with increased endogenous nitrosation. The few epidemiologic studies that have evaluated intake of nitrosation precursors and/or nitrosation inhibitors have observed elevated risks for colon cancer and neural tube defects associated with drinking-water nitrate concentrations below the regulatory limit. The role of drinking-water nitrate exposure as a risk factor for specific cancers, reproductive outcomes, and other chronic health effects must be studied more thoroughly before changes to the regulatory level for nitrate in drinking water can be considered.

Nitrate in Groundwater of the United States, 1991−2003

An assessment of nitrate concentrations in groundwater in the United States indicates that concentrations are highest in shallow, oxic groundwater beneath areas with high N inputs. During 1991-2003, 5101 wells were sampled in 51 study areas throughout the U.S. as part of the U.S. Geological Survey National Water-Quality Assessment (NAWQA) program. The well networks reflect the existing used resource represented by domestic wells in major aquifers (major aquifer studies), and recently recharged groundwater beneath dominant land-surface activities (land-use studies). Nitrate concentrations were highest in shallow groundwater beneath agricultural land use in areas with well-drained soils and oxic geochemical conditions. Nitrate concentrations were lowest in deep groundwater where groundwater is reduced, or where groundwater is older and hence concentrations reflect historically low N application rates. Classification and regression tree analysis was used to identify the relative importance of N inputs, biogeochemical processes, and physical aquifer properties in explaining nitrate concentrations in groundwater. Factors ranked by reduction in sum of squares indicate that dissolved iron concentrations explained most of the variation in groundwater nitrate concentration, followed by manganese, calcium, farm N fertilizer inputs, percent well-drained soils, and dissolved oxygen. Overall, nitrate concentrations in groundwater are most significantly affected by redox conditions, followed by nonpoint-source N inputs. Other water-quality indicators and physical variables had a secondary influence on nitrate concentrations.

Root Zone Water Quality Model (RZWQM2): Model Use, Calibration, and Validation

The Root Zone Water Quality Model (RZWQM2) has been used widely for simulating agricultural management effects on crop production and soil and water quality. Although it is a one-dimensional model, it has many desirable features for the modeling community. This article outlines the principles of calibrating the model component by component with one or more datasets and validating the model with independent datasets. Users should consult the RZWQM2 user manual distributed along with the model and a more detailed protocol on how to calibrate RZWQM2 provided in a book chapter. Two case studies (or examples) are included in this article. One is from an irrigated maize study in Colorado to illustrate the use of field and laboratory measured soil hydraulic properties on simulated soil water and crop production. It also demonstrates the interaction between soil and plant parameters in simulated plant responses to water stresses. The other is from a maize-soybean rotation study in Iowa to show a manual calibration of the model for crop yield, soil water, and N leaching in tile-drained soils. Although the commonly used trial-and-error calibration method works well for experienced users, as shown in the second example, an automated calibration procedure is more objective, as shown in the first example. Furthermore, the incorporation of the Parameter Estimation Software (PEST) into RZWQM2 made the calibration of the model more efficient than a grid (ordered) search of model parameters. In addition, PEST provides sensitivity and uncertainty analyses that should help users in selecting the right parameters to calibrate.

Predicting Unsaturated Zone Nitrogen Mass Balances in Agricultural Settings of the United States

Unsaturated zone N fate and transport were evaluated at four sites to identify the predominant pathways of N cycling: an almond [Prunus dulcis (Mill.) D.A. Webb] orchard and cornfield (Zea mays L.) in the lower Merced River study basin, California; and corn-soybean [Glycine max (L.) Merr.] rotations in study basins at Maple Creek, Nebraska, and at Morgan Creek, Maryland. We used inverse modeling with a new version of the Root Zone Water Quality Model (RZWQM2) to estimate soil hydraulic and nitrogen transformation parameters throughout the unsaturated zone; previous versions were limited to 3-m depth and relied on manual calibration. The overall goal of the modeling was to derive unsaturated zone N mass balances for the four sites. RZWQM2 showed promise for deeper simulation profiles. Relative root mean square error (RRMSE) values for predicted and observed nitrate concentrations in lysimeters were 0.40 and 0.52 for California (6.5 m depth) and Nebraska (10 m), respectively, and index of agreement (d) values were 0.60 and 0.71 (d varies between 0 and 1, with higher values indicating better agreement). For the shallow simulation profile (1 m) in Maryland, RRMSE and d for nitrate were 0.22 and 0.86, respectively. Except for Nebraska, predictions of average nitrate concentration at the bottom of the simulation profile agreed reasonably well with measured concentrations in monitoring wells. The largest additions of N were predicted to come from inorganic fertilizer (153-195 kg N ha(-1) yr(-1) in California) and N fixation (99 and 131 kg N ha(-1) yr(-1) in Maryland and Nebraska, respectively). Predicted N losses occurred primarily through plant uptake (144-237 kg N ha(-1) yr(-1)) and deep seepage out of the profile (56-102 kg N ha(-1) yr(-1)). Large reservoirs of organic N (up to 17,500 kg N ha(-1) m(-1) at Nebraska) were predicted to reside in the unsaturated zone, which has implications for potential future transfer of nitrate to groundwater.

Identification of key climatic factors regulating the transport of pesticides in leaching and to tile drains

BACKGROUND Key climatic factors influencing the transport of pesticides to drains and to depth were identified. Climatic characteristics such as the timing of rainfall in relation to pesticide application may be more critical than average annual temperature and rainfall. The fate of three pesticides was simulated in nine contrasting soil types for two seasons, five application dates and six synthetic weather data series using the MACRO model, and predicted cumulative pesticide loads were analysed using statistical methods. RESULTS Classification trees and Pearson correlations indicated that simulated losses in excess of 75th percentile values (0.046 mg m(-2) for leaching, 0.042 mg m(-2) for drainage) generally occurred with large rainfall events following autumn application on clay soils, for both leaching and drainage scenarios. The amount and timing of winter rainfall were important factors, whatever the application period, and these interacted strongly with soil texture and pesticide mobility and persistence. Winter rainfall primarily influenced losses of less mobile and more persistent compounds, while short-term rainfall and temperature controlled leaching of the more mobile pesticides. CONCLUSIONS Numerous climatic characteristics influenced pesticide loss, including the amount of precipitation as well as the timing of rainfall and extreme events in relation to application date. Information regarding the relative influence of the climatic characteristics evaluated here can support the development of a climatic zonation for European-scale risk assessment for pesticide fate.

Modeling groundwater nitrate concentrations in private wells in Iowa

Contamination of drinking water by nitrate is a growing problem in many agricultural areas of the country. Ingested nitrate can lead to the endogenous formation of N-nitroso compounds, potent carcinogens. We developed a predictive model for nitrate concentrations in private wells in Iowa. Using 34,084 measurements of nitrate in private wells, we trained and tested random forest models to predict log nitrate levels by systematically assessing the predictive performance of 179 variables in 36 thematic groups (well depth, distance to sinkholes, location, land use, soil characteristics, nitrogen inputs, meteorology, and other factors). The final model contained 66 variables in 17 groups. Some of the most important variables were well depth, slope length within 1 km of the well, year of sample, and distance to nearest animal feeding operation. The correlation between observed and estimated nitrate concentrations was excellent in the training set (r-square=0.77) and was acceptable in the testing set (r-square=0.38). The random forest model had substantially better predictive performance than a traditional linear regression model or a regression tree. Our model will be used to investigate the association between nitrate levels in drinking water and cancer risk in the Iowa participants of the Agricultural Health Study cohort.

Variations in Pesticide Leaching Related to Land Use, Pesticide Properties, and Unsaturated Zone Thickness

Pesticide leaching through variably thick soils beneath agricultural fields in Morgan Creek, Maryland was simulated for water years 1995 to 2004 using LEACHM (Leaching Estimation and Chemistry Model). Fifteen individual models were constructed to simulate five depths and three crop rotations with associated pesticide applications. Unsaturated zone thickness averaged 4.7 m but reached a maximum of 18.7 m. Average annual recharge to ground water decreased from 15.9 to 11.1 cm as the unsaturated zone increased in thickness from 1 to 10 m. These point estimates of recharge are at the lower end of previously published values, which used methods that integrate over larger areas capturing focused recharge in the numerous detention ponds in the watershed. The total amount of applied and leached masses for five parent pesticide compounds and seven metabolites were estimated for the 32-km2 Morgan Creek watershed by associating each hectare to the closest one-dimensional model analog of model depth and crop rotation scenario as determined from land-use surveys. LEACHM parameters were set such that branched, serial, first-order decay of pesticides and metabolites was realistically simulated. Leaching is predicted to be greatest for shallow soils and for persistent compounds with low sorptivity. Based on simulation results, percent parent compounds leached within the watershed can be described by a regression model of the form e(-depth) (a ln t1/2-b ln K OC) where t1/2 is the degradation half-life in aerobic soils, K OC is the organic carbon normalized sorption coefficient, and a and b are fitted coefficients (R2 = 0.86, p value = 7 x 10(-9)).

Modeling nitrate at domestic and public-supply well depths in the Central Valley, California

Aquifer vulnerability models were developed to map groundwater nitrate concentration at domestic and public-supply well depths in the Central Valley, California. We compared three modeling methods for ability to predict nitrate concentration >4 mg/L: logistic regression (LR), random forest classification (RFC), and random forest regression (RFR). All three models indicated processes of nitrogen fertilizer input at the land surface, transmission through coarse-textured, well-drained soils, and transport in the aquifer to the well screen. The total percent correct predictions were similar among the three models (69-82%), but RFR had greater sensitivity (84% for shallow wells and 51% for deep wells). The results suggest that RFR can better identify areas with high nitrate concentration but that LR and RFC may better describe bulk conditions in the aquifer. A unique aspect of the modeling approach was inclusion of outputs from previous, physically based hydrologic and textural models as predictor variables, which were important to the models. Vertical water fluxes in the aquifer and percent coarse material above the well screen were ranked moderately high-to-high in the RFR models, and the average vertical water flux during the irrigation season was highly significant (p < 0.0001) in logistic regression.

Dietary Nitrate and the Epidemiology of Cardiovascular Disease: Report From a National Heart, Lung, and Blood Institute Workshop

In view of continuing unanswered questions regarding the geographical and demographic distribution of cardiovascular disease, and recent discoveries about the effects of dietary nitrate on cardiovascular physiology, the National Heart, Lung, and Blood Institute (NHLBI) convened a workshop to

Spatial Variability of Groundwater Recharge and its Effect on Shallow Groundwater Quality in Southern New Jersey

ity in the Glassboro, NJ area (Fig. 1). The Darcian method was used to estimate groundwater recharge Point estimates of groundwater recharge at 48 sediment-coring from water-retention parameters and unsaturated hylocations vary substantially ( 18.5–1840 cm yr 1) in a 930-km2 area of southern New Jersey. Darcian estimates of steady, long-term recharge draulic conductivity on the basis of sediment texture made at depth in the unsaturated zone were estimated using pedoand moisture content data obtained near the water table transfer functions of soil texture and interpolated (mapped) with at 48 locations in the study area. The recharge estimates nonparametric methods to assess aquifer vulnerability in the area. were geostatistically analyzed to evaluate the spatial The probability of exceeding the median recharge (29.1 cm yr 1) is variability of measured sediment properties, to map relow in the southwestern and northeastern portions of the study area charge with respect to land use, and to derive statistical and high in the eastern and southeastern portions. Estimated recharge distributions of recharge at specific locations in the study is inversely related to measured percentage clay and positively related area. The recharge estimates were compared with soils to the percentage of well-drained soils near wells. Spatial patterns of and topographic data to determine whether recharge recharge estimates, exceedance probabilities, and clay content indicate could be accurately predicted from landscape characterthat sediment texture controls recharge in the study area. Relations with land elevation and a topographic wetness index were statistically istics. Finally, recharge estimates were compared with insignificant. Nitrate concentration and atrazine (6-chloro-N2-ethylconcentrations of NO3 and atrazine to evaluate potential N4-isopropyl-1,3,5-triazine-2,4-diamine) percentage detection in sameffects on the quality of shallow, recently recharged ples of shallow groundwater (typically 10 m) are higher for low groundwater. In this study, “shallow groundwater” rerecharge sites ( 29.1 cm yr 1) than for high recharge sites ( 29.1 cm fers to depths 10 m. The depth of the screened interval yr 1) in agricultural and urban areas. Differences between high and below water in observation wells in the area is about low recharge sites in these areas are highly significant for NO3 concen3 m. The objectives of the study were to tration, but not for atrazine concentration. • evaluate the spatial variability of point estimates of ground-water recharge, • map recharge with respect to land use, and N contamination is considered the • compare recharge estimates with NO3 and atrazine single greatest threat to water quality (Corwin et concentrations in shallow groundwater. al., 1997). Preventing contamination of groundwater is crucial in areas where it is a major source of public and domestic supply. Knowing where an aquifer is vulneraMATERIALS AND METHODS ble to surface-derived contaminants would help managDescription of Study Area ers prioritize scarce resources for alternative management practices, monitoring, and cleanup. The study area (Fig. 1) comprises about 930 km within the Coastal Plain Physiographic province of southern New Jersey. Aquifer vulnerability studies at large spatial scales Population in the area has increased from about 50 000 people have used index methods, such as DRASTIC and SEEPin 1940 to about 250 000 in 2000. Groundwater withdrawals AGE (Navulur and Engel, 1996), or overlays made with from the surficial, Kirkwood-Cohansey aquifer system, which geographic information systems (GISs) (Nolan et al., consists of highly permeable unconsolidated sands and gravels, 1997). Both DRASTIC and SEEPAGE underestimated have recently increased to meet the growing demand for drinkcontamination potential by describing areas with high ing water. As of 1986, the Glassboro area comprised 21% NO3 concentration as low risk (Navulur and Engel, urban land, 26% agricultural land, and 39% undeveloped land 1996). Index and overlay methods provide only limited (Stackelberg et al., 1997). understanding of processes controlling the transport of The outcrop of the Kirkwood Formation, a confining unit water and chemicals in the unsaturated zone. Alternaabout 30 m thick, underlies the aquifer and forms the northwest boundary of the study area. Aquifer thickness increases tively, deterministic models can simulate water and to about 75 m at the southeastern boundary (Zapecza, 1989). chemical fluxes, but the spatial variability of sediment Unsaturated zone sediment in the study area consists mainly properties at field scales and above limits accuracy and of the Cohansey Sand, which was deposited during the Mioimposes large uncertainty on model predictions. cene Age on inner shelf, nearshore, and beach areas during In the current study, we used a combined determinisslow retreat of the sea. Sediments in the Cohansey Sand genertic–geostatistical approach to assess aquifer vulnerabilally are coarser at shallower depths, which is consistent with similarly deposited formations in the New Jersey Coastal Plain B.T. Nolan, U.S. Geological Survey, 413 National Center, Reston, (Zapecza, 1989). The Bridgeton Formation overlies the CoVA 20192; A.L. Baehr and L.J. Kauffman, U.S. Geological Survey, West Trenton, NJ. Received 27 Nov. 2002. Original Research Paper. Abbreviations: CCDF, conditional cumulative distribution function; *Corresponding author (btnolan@usgs.gov). DEM, digital elevation model; DO, dissolved oxygen; GIS, geographic information system; IGF, Indicative Goodness of Fit; IK, indicator Published in Vadose Zone Journal 2:677–691 (2003).  Soil Science Society of America kriging; KED, Kriging with external drift; MLR, multiple linear regression; PTF, pedotransfer function. 677 S. Segoe Rd., Madison, WI 53711 USA