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ORIGINAL RESEARCH

Groundwater Nitrate Spatial and Temporal Patterns and Correlations

Influence of Natural Controls and Nitrogen Management

^a Div. of Plant Science, Univ. of Missouri, Columbia, MO 65211
^b Dep. of Soil Science, North Carolina State Univ., Raleigh, NC 27695-7619
^c Dep. of Crop Science, North Carolina State Univ., Raleigh, NC 27695-7620
^d Dep. of Statistics, North Carolina State Univ., Raleigh, NC 27695-8203
^* Corresponding author (hongn{at}missouri.edu)

Received 1 May 2006.

To use shallow groundwater NO₃–N concentration as an indicator of groundwater quality requires understanding its patterns, correlations, and controls across space and time. Within a study comparing variable-rate and uniform N management, our objectives were to determine groundwater NO₃–N patterns and correlations at various spatial and temporal scales and their association with natural controls and N management. Experiments in a random, complete block design were conducted in a 2-yr crop rotation in North Carolina that included one variable-rate and two uniform N management treatments to wheat (Triticum aestivum L.) and corn (Zea mays L.). We measured groundwater NO₃–N and depth every 2 wk at 60 well nests, sampling the 0.9- to 3.7-m depth. Field-mean NO₃–N varied with time from 5.5 to 15.3 mg NO₃–N L^–1. These variations were correlated primarily with concurrent changes in water table elevation and depth. Mean NO₃–N exhibited two preferred states: high when the water table was shallow and low when the water table was deep. Temporal NO₃–N fluctuations greatly exceeded treatment effects. Treatments appeared to affect NO₃–N temporal covariance structure. Groundwater NO₃–N spatial patterns and correlations were associated mostly with saturated hydraulic conductivity and water table fluctuations and appeared influenced by subsurface lateral flow. When treatment effects became consistently significant later in the study, they overrode natural controls, and NO₃–N was spatially uncorrelated or exhibited shorter spatial correlation ranges and patterns associated predominantly with treatments.

Abbreviations: AR(1), first-order autoregressive covariance model • CS, compound symmetry covariance model • FA, remote sensing informed, in-season, uniform, field-average N management • Go, Goldsboro soil series • K_sat, saturated hydraulic conductivity • Ly, Lynchburg soil series • No, Norfolk soil series • RYE, uniform realistic yield expectation N management • SOM, soil organic matter • SS, remote sensing informed, in-season, site-specific, variable-rate N management • VR-N, variable-rate N management • WTD, water table depth • WTE, water table elevation