Optimizing Sampling Strategies for Riverine Nitrate Using High-Frequency Data in Agricultural Watersheds.

Understanding linked hydrologic and biogeochemical processes such as nitrate loading to agricultural streams requires that the sampling bias and precision of monitoring strategies be known. An existing spatially distributed, high-frequency nitrate monitoring network covering ∼40% of Iowa provided direct observations of in situ nitrate concentrations at a temporal resolution of 15 min. Systematic subsampling of nitrate records allowed for quantification of uncertainties (bias and precision) associated with estimates of various nitrate parameters, including: mean nitrate concentration, proportion of samples exceeding the nitrate drinking water standard (DWS), peak (>90th quantile) nitrate concentration, and nitrate flux. We subsampled continuous records for 47 site-year combinations mimicking common, but labor-intensive, water-sampling regimes (e.g., time-interval, stage-triggered, and dynamic-discharge storm sampling). Our results suggest that time-interval sampling most efficiently characterized all nitrate parameters, except at coarse frequencies for nitrate flux. Stage-triggered storm sampling most precisely captured nitrate flux when less than 0.19% of possible 15 min observations for a site-year were used. The time-interval strategy had the greatest return on sampling investment by most precisely and accurately quantifying nitrate parameters per sampling effort. These uncertainty estimates can aid in designing sampling strategies focused on nitrate monitoring in the tile-drained Midwest or similar agricultural regions.

Antecedent moisture controls on stream nitrate flux in an agricultural watershed.

Evaluating nitrate-N fluxes from agricultural landscapes is inherently complex due to the wide range of intrinsic and dynamic controlling variables. In this study, we investigate the influence of contrasting antecedent moisture conditions on nitrate-N flux magnitude and dynamics in a single agricultural watershed on intra-annual and rainfall-event temporal scales. High temporal resolution discharge and nitrate concentration data were collected to evaluate nitrate-N flux magnitude associated with wet (2009) and dry (2012) conditions. Analysis of individual rainfall events revealed a marked and consistent difference in nitrate-N flux response attributed to wet/dry cycles. Large-magnitude dilutions (up to 10 mg N L) persisted during the wet antecedent conditions (2009), consistent with a dominant baseflow contribution and excess groundwater release in relation to precipitation volume (discharge > > precipitation). Smaller-magnitude concentrations (<7 mg N L) were observed during the drought conditions of 2012, consistent with a quickflow-dominated response to rain events and infiltration/storage of precipitation resulting in discharge < precipitation. Nitrate-N loads and yields from the watershed were much higher (up to an order of magnitude) in the wet year vs. the dry year. Our results suggest that the response of nitrate-N loading to rain events is highly dependent on intra-annual antecedent moisture conditions and subsurface hydrologic connectivity, which together dictate the dominant hydrologic pathways for stream recharge. Additionally, the results of our study indicate that continued pronounced wet/dry cycles may become more dominant as the short-term driver of future nitrate-N exports.