Digital hydrologic networks depicting surface-water pathways and their associated drainage catchments provide a key component to hydrologic analysis and modeling. Collectively, they form common spatial units that can be used to frame the descriptions of aquatic and watershed processes. In addition, they provide the ability to simulate and route the movement of water and associated constituents throughout the landscape. Digital hydrologic networks have evolved from derivatives of mapping products to detailed, interconnected, spatially referenced networks of water pathways, drainage areas, and stream and watershed characteristics. These properties are important because they enhance the ability to spatially evaluate factors that affect the sources and transport of water-quality constituents at various scales. SPAtially Referenced Regressions On Watershed attributes (SPARROW), a process-based/statistical model, relies on a digital hydrologic network in order to establish relations between quantities of monitored contaminant flux, contaminant sources, and the associated physical characteristics affecting contaminant transport. Digital hydrologic networks modified from the River Reach File (RF1) and National Hydrography Dataset (NHD) geospatial datasets provided frameworks for SPARROW in six regions of the conterminous United States. In addition, characteristics of the modified RF1 were used to update estimates of mean-annual streamflow. This produced more current flow estimates for use in SPARROW modeling.

We applied the SPARROW model to estimate phosphorus transport from catchments to stream reaches and subsequent delivery to major receiving water bodies in the Southeastern United States (U.S.). We show that six source variables and five land-to-water transport variables are significant (p<0.05) in explaining 67% of the variability in long-term log-transformed mean annual phosphorus yields. Three land-to-water variables are a subset of landscape characteristics that have been used as transport factors in phosphorus indices developed by state agencies and are identified through experimental research as influencing land-to-water phosphorus transport at field and plot scales. Two land-to-water variables – soil organic matter and soil pH – are associated with phosphorus sorption, a significant finding given that most state-developed phosphorus indices do not explicitly contain variables for sorption processes. Our findings for Southeastern U.S. streams emphasize the importance of accounting for phosphorus present in the soil profile to predict attainable instream water quality. Regional estimates of phosphorus associated with soil-parent rock were highly significant in explaining instream phosphorus yield variability. Model predictions associate 31% of phosphorus delivered to receiving water bodies to geology and the highest total phosphorus yields in the Southeast were catchments with already high background levels that have been impacted by human activity.

Defining the oxic-suboxic interface is often critical for determining pathways for nitrate transport in groundwater and to streams at the local scale. Defining this interface on a regional scale is complicated by the spatial variability of reaction rates. The probability of oxic groundwater in the Chesapeake Bay watershed was predicted by relating dissolved O2 concentrations in groundwater samples to indicators of residence time and/or electron donor availability using logistic regression. Variables that describe surficial geology, position in the flow system, and soil drainage were important predictors of oxic water. The probability of encountering oxic groundwater at a 30 m depth and the depth to the bottom of the oxic layer were predicted for the Chesapeake Bay watershed. The influence of depth to the bottom of the oxic layer on stream nitrate concentrations and time lags (i.e., time period between land application of nitrogen and its effect on streams) are illustrated using model simulations for hypothetical basins. Regional maps of the probability of oxic groundwater should prove useful as indicators of groundwater susceptibility and stream susceptibility to contaminant sources derived from groundwater.

The myriad hydrologic and biogeochemical processes taking place in watersheds occurring across space and time are integrated and reflected in the quantity and quality of water in streams and rivers. Collection of high‐frequency water quality data with sensors in surface waters provides new opportunities to disentangle these processes and quantify sources and transport of water and solutes in the coupled groundwater‐surface water system. A new approach for separating the streamflow hydrograph into three components was developed and coupled with high‐frequency nitrate data to estimate time‐variable nitrate loads from chemically dilute quick flow, chemically concentrated quick flow, and slowflow groundwater end‐member pathways for periods of up to 2 years in a groundwater‐dominated and a quick‐flow‐dominated stream in central Wisconsin, using only streamflow and in‐stream water quality data. The dilute and concentrated quick flow end‐members were distinguished using high‐frequency specific conductance data. Results indicate that dilute quick flow contributed less than 5% of the nitrate load at both sites, whereas 89 ± 8% of the nitrate load at the groundwater‐dominated stream was from slowflow groundwater, and 84 ± 25% of the nitrate load at the quick‐flow‐dominated stream was from concentrated quick flow. Concentrated quick flow nitrate concentrations varied seasonally at both sites, with peak concentrations in the winter that were 2–3 times greater than minimum concentrations during the growing season. Application of this approach provides an opportunity to assess stream vulnerability to nonpoint source nitrate loading and expected stream responses to current or changing conditions and practices in watersheds.

The one-dimensional approach is reasonable for a prismatic channel in a relatively narrow floodplain but may not be appropriate for sinuous rivers with several tributaries in broad floodplains. Uncertainty in the flood-inundation polygons increases with distance from the main channel for which water-surface slopes are simulated. Two-dimensional models are increasingly used for simulating floodplain inundation because of the variability in topography across the floodplain, particularly in wide floodplains with numerous tributaries.