The Road to NHDPlus — Advancements in Digital Stream Networks and Associated Catchments

A progression of advancements in Geographic Information Systems techniques for hydrologic network and associated catchment delineation has led to the production of the National Hydrography Dataset Plus (NHDPlus). NHDPlus is a digital stream network for hydrologic modeling with catchments and a suite of related geospatial data. Digital stream networks with associated catchments provide a geospatial framework for linking and integrating water‐related data. Advancements in the development of NHDPlus are expected to continue to improve the capabilities of this national geospatial hydrologic framework. NHDPlus is built upon the medium‐resolution NHD and, like NHD, was developed by the U.S. Environmental Protection Agency and U.S. Geological Survey to support the estimation of streamflow and stream velocity used in fate‐and‐transport modeling. Catchments included with NHDPlus were created by integrating vector information from the NHD and from the Watershed Boundary Dataset with the gridded land surface elevation as represented by the National Elevation Dataset. NHDPlus is an actively used and continually improved dataset. Users recognize the importance of a reliable stream network and associated catchments. The NHDPlus spatial features and associated data tables will continue to be improved to support regional water quality and streamflow models and other user‐defined applications.     

Identification of Putative Geographically Isolated Wetlands of the Conterminous United States

Geographically isolated wetlands (GIWs) are wetlands completely surrounded by uplands. While common throughout the United States (U.S.), there have heretofore been no nationally available, spatially explicit estimates of GIW extent, complicating efforts to understand the myriad biogeochemical, hydrological, and habitat functions of GIWs and hampering conservation and management efforts at local, state, and national scales. We used a 10‐m geospatial buffer as a proxy for hydrological or ecological connectivity of National Wetlands Inventory palustrine and lacustrine wetland systems to nationally mapped and available stream, river, and lake data. We identified over 8.3 million putative GIWs across the conterminous U.S., encompassing nearly 6.5 million hectares of wetland resources (average size 0.79 ± 4.81 ha, median size 0.19 ha). Putative GIWs thus represent approximately 16% of the freshwater wetlands of the conterminous U.S. The water regime for the majority of the putative GIWs was temporarily or seasonally flooded, suggesting a vulnerability to ditching or hydrologic abstraction, sedimentation, or alterations in precipitation patterns. Additional analytical applications of this readily available geospatially explicit mapping product (e.g., hydrological modeling, amphibian metapopulation, or landscape ecological analyses) will improve our understanding of the abundance and extent, effect, connectivity, and relative importance of GIWs to other aquatic systems of the conterminous U.S.     

GIS‐Based Stream Classification in a Mountain Watershed for Jurisdictional Evaluation

This study analyzed stream characteristics in a mountain watershed in southwestern Colorado and developed a three‐level hierarchical classification scheme using national datasets to demonstrate jurisdictional evaluation as “waters of the United States (U.S.)” under U.S. Clean Water Act Section 404 at the watershed scale. The National Hydrography Dataset and USGS StreamStats were used with field observations to classify streams in the 53 km² Cement Creek Watershed based on flow duration (Level 1), stream order (Level 2), and other biophysical metrics (Level 3). Kruskal‐Wallis tests and discriminant analysis showed significant differences among Level 2 classes. Level 3 classification used cluster analysis for stream length, distance to the downstream traditional navigable water (TNW), and the ratio of mean annual flow from the source stream to the TNW. Results showed all perennial and intermittent streams are jurisdictional relatively permanent waters (RPWs), which include over a third of all streams, 64% are intermittent or ephemeral, and almost half are ephemeral first order. All ephemeral reaches are non‐RPWs requiring significant nexus evaluation to determine jurisdiction. These ephemeral first‐order streams can contribute 5% of the annual flow to the TNW at the confluence, while the Cement Creek main stem contributes 21% of the TNW flow. The study demonstrated that the classification provides key biophysical and regulatory information to aid jurisdictional evaluations in mountain watersheds.     

Estimation of Evapotranspiration Across the Conterminous United States Using a Regression With Climate and Land‐Cover Data1

Sanford, Ward E. and David L. Selnick, 2012. Estimation of Evapotranspiration Across the Conterminous United States Using a Regression with Climate and Land‐Cover Data. Journal of the American Water Resources Association (JAWRA) 1‐14. DOI: 10.1111/jawr.12010 Abstract: Evapotranspiration (ET) is an important quantity for water resource managers to know because it often represents the largest sink for precipitation (P) arriving at the land surface. In order to estimate actual ET across the conterminous United States (U.S.) in this study, a water‐balance method was combined with a climate and land‐cover regression equation. Precipitation and streamflow records were compiled for 838 watersheds for 1971‐2000 across the U.S. to obtain long‐term estimates of actual ET. A regression equation was developed that related the ratio ET/P to climate and land‐cover variables within those watersheds. Precipitation and temperatures were used from the PRISM climate dataset, and land‐cover data were used from the USGS National Land Cover Dataset. Results indicate that ET can be predicted relatively well at a watershed or county scale with readily available climate variables alone, and that land‐cover data can also improve those predictions. Using the climate and land‐cover data at an 800‐m scale and then averaging to the county scale, maps were produced showing estimates of ET and ET/P for the entire conterminous U.S. Using the regression equation, such maps could also be made for more detailed state coverages, or for other areas of the world where climate and land‐cover data are plentiful.     

A Fully Distributed Implementation of Mean Annual StreamFlow Regional Regression Equations1

Abstract: Estimates of mean annual streamflow are needed for a variety of hydrologic assessments. Away from gage locations, regional regression equations that are a function of upstream area, precipitation, and temperature are commonly used. Geographic information systems technology has facilitated their use for projects, but traditional approaches using the polygon overlay operator have been too inefficient for national scale applications. As an alternative, the Elevation Derivatives for National Applications (EDNA) database was used as a framework for a fully distributed implementation of mean annual streamflow regional regression equations. The raster “flow accumulation” operator was used to efficiently achieve spatially continuous parameterization of the equations for every 30 m grid cell of the conterminous United States (U.S.). Results were confirmed by comparing with measured flows at stations of the Hydro‐Climatic Data Network, and their applications value demonstrated in the development of a national geospatial hydropower assessment. Interactive tools at the EDNA website make possible the fast and efficient query of mean annual streamflow for any location in the conterminous U.S., providing a valuable complement to other national initiatives (StreamStats and the National Hydrography Dataset Plus).     

Southwestern Intermittent and Ephemeral Stream Connectivity

Ephemeral and intermittent streams are abundant in the arid and semiarid landscapes of the Western and Southwestern United States (U.S.). Connectivity of ephemeral and intermittent streams to the relatively few perennial reaches through runoff is a major driver of the ecohydrology of the region. These streams supply water, sediment, nutrients, and biota to downstream reaches and rivers. In addition, they provide runoff to recharge alluvial and regional groundwater aquifers that support baseflow in perennial mainstem stream reaches over extended periods when little or no precipitation occurs. Episodic runoff, as well as groundwater inflow to surface water in streams support limited naturally occurring riparian communities. This paper provides an overview and comprehensive examination of factors affecting the hydrologic, chemical, and ecological connectivity of ephemeral and intermittent streams on perennial or intermittent rivers in the arid and semiarid Southwestern U.S. Connectivity as influenced and moderated through the physical landscape, climate, and human impacts to downstream waters or rivers is presented first at the broader Southwestern scale, and secondly drawing on a specific and more detailed example of the San Pedro Basin due to its history of extensive observations and research in the basin. A wide array of evidence clearly illustrates hydrologic, chemical, and ecological connectivity of ephemeral and intermittent streams throughout stream networks.     

In search of effective scales for stream management: does agroecoregion,watershed, or their intersection best explain the variance in stream macroinvertebrate communities?

Our lack of understanding of relationships between stream biotic communities and surrounding landscape conditions makes it difficult to determine the spatial scale at which management practices are best assessed. We investigated these relationships in the Minnesota River Basin, which is divided into major watersheds and agroecoregions which are based on soil type, geologic parent material, landscape slope steepness, and climatic factors affecting crop productivity. We collected macroinvertebrate and stream habitat data from 68 tributaries among three major watersheds and two agroecoregions. We tested the effectiveness of the two landscape classification systems (i.e., watershed, agroecoregion) in explaining variance in habitat and macroinvertebrate metrics, and analyzed the relative influence on macroinvertebrates of local habitat versus regional characteristics. Macroinvertebrate community composition was most strongly influenced by local habitat; the variance in habitat conditions was best explained at the scale of intersection of major watershed and agroecoregion (i.e., stream habitat conditions were most homogeneous within the physical regions of intersection of these two landscape classification systems). Our results are consistent with findings of other authors that most variation in macroinvertebrate community data from large agricultural catchments is attributable to local physical conditions. Our results are the first to test the hypothesis and demonstrate that the scale of intersection best explains these variances. The results suggest that management practices adjusted for both watershed and ecoregion characteristics, with the goal of improving physical habitat characteristics of local streams, may lead to better basin-wide water quality conditions and stream biological integrity.     

The Role of Headwater Streams in Downstream Water Quality1

Abstract: Knowledge of headwater influences on the water‐quality and flow conditions of downstream waters is essential to water‐resource management at all governmental levels; this includes recent court decisions on the jurisdiction of the Federal Clean Water Act (CWA) over upland areas that contribute to larger downstream water bodies. We review current watershed research and use a water‐quality model to investigate headwater influences on downstream receiving waters. Our evaluations demonstrate the intrinsic connections of headwaters to landscape processes and downstream waters through their influence on the supply, transport, and fate of water and solutes in watersheds. Hydrological processes in headwater catchments control the recharge of subsurface water stores, flow paths, and residence times of water throughout landscapes. The dynamic coupling of hydrological and biogeochemical processes in upland streams further controls the chemical form, timing, and longitudinal distances of solute transport to downstream waters. We apply the spatially explicit, mass‐balance watershed model SPARROW to consider transport and transformations of water and nutrients throughout stream networks in the northeastern United States. We simulate fluxes of nitrogen, a primary nutrient that is a water‐quality concern for acidification of streams and lakes and eutrophication of coastal waters, and refine the model structure to include literature observations of nitrogen removal in streams and lakes. We quantify nitrogen transport from headwaters to downstream navigable waters, where headwaters are defined within the model as first‐order, perennial streams that include flow and nitrogen contributions from smaller, intermittent and ephemeral streams. We find that first‐order headwaters contribute approximately 70% of the mean‐annual water volume and 65% of the nitrogen flux in second‐order streams. Their contributions to mean water volume and nitrogen flux decline only marginally to about 55% and 40% in fourth‐ and higher‐order rivers that include navigable waters and their tributaries. These results underscore the profound influence that headwater areas have on shaping downstream water quantity and water quality. The results have relevance to water‐resource management and regulatory decisions and potentially broaden understanding of the spatial extent of Federal CWA jurisdiction in U.S. waters.     

Featured Collection Introduction: Connectivity of Streams and Wetlands to Downstream Waters

Connectivity is a fundamental but highly dynamic property of watersheds. Variability in the types and degrees of aquatic ecosystem connectivity presents challenges for researchers and managers seeking to accurately quantify its effects on critical hydrologic, biogeochemical, and biological processes. However, protecting natural gradients of connectivity is key to protecting the range of ecosystem services that aquatic ecosystems provide. In this featured collection, we review the available evidence on connections and functions by which streams and wetlands affect the integrity of downstream waters such as large rivers, lakes, reservoirs, and estuaries. The reviews in this collection focus on the types of waters whose protections under the U.S. Clean Water Act have been called into question by U.S. Supreme Court cases. We synthesize 40+ years of research on longitudinal, lateral, and vertical fluxes of energy, material, and biota between aquatic ecosystems included within the Act's frame of reference. Many questions about the roles of streams and wetlands in sustaining downstream water integrity can be answered from currently available literature, and emerging research is rapidly closing data gaps with exciting new insights into aquatic connectivity and function at local, watershed, and regional scales. Synthesis of foundational and emerging research is needed to support science‐based efforts to provide safe, reliable sources of fresh water for present and future generations.     

Biophysical‐Regulatory Classification and Profiling of Streams Across Management Units and Ecoregions1

Caruso, Brian S. and Joshua Haynes, 2011. Biophysical‐Regulatory Classification and Profiling of Streams Across Management Units and Ecoregions. Journal of the American Water Resources Association (JAWRA) 00(0):1‐22. DOI: 10.1111/j.1752‐1688.2010.00522.x Abstract: Aquatic resources management in the United States (U.S.) under Clean Water Act Section 404 has become more complex after recent Supreme Court decisions and U.S. Army Corps of Engineers and Environmental Protection Agency (USEPA) guidance. Many intermittent/ephemeral and headwater streams may not be jurisdictional if they lack a significant nexus with navigable waters. Streams in semiarid USEPA Region 8 were classified based on hydrologic permanence and stream order using National Hydrography Dataset (NHD) Plus and GIS to provide information across broad spatial scales to aid with jurisdictional determinations (JDs). Four classes were developed for profiling across management units and ecoregions. Based on medium‐resolution NHDPlus data, intermittent streams comprise >¾, and first order streams constitute >½ of the total stream length in Region 8. Mountain states and ecoregions have the largest percentage of perennial first order streams, whereas the Dakotas, plains, and desert ecoregions have the greatest percentages of intermittent first order and intermittent higher order streams. In the Upper Colorado River Basin, >50% of reaches are intermittent first order, and 9% are perennial first order. NHDPlus data can significantly underestimate the length of headwater and intermittent streams, but can still be a valuable tool to help develop stream classes and for regional JD planning and analysis. Refinement of the stream classes using high resolution NHD data and other key catchment parameters can improve their utility for JDs.     

Using GIS to Delineate Headwater Stream Origins in the Appalachian Coalfields of Kentucky

Headwater streams have a significant nexus or physical, chemical, and/or biological connection to downstream reaches. Generally, defined as 1st‐3rd order with ephemeral, intermittent, or perennial flow regimes, these streams account for a substantial portion of the total stream network particularly in mountainous terrain. Due to their often remote locations, small size, and large numbers, conducting field inventories of headwater streams is challenging. A means of estimating headwater stream location and extent according to flow regime type using publicly available spatial data is needed to simplify this complex process. Using field‐collected headwater point of origin data from three control watersheds, streams were characterized according to a set of spatial parameters related to topography, geology, and soils. These parameters were (1) compared to field‐collected point of origin data listed in three nearby Jurisdictional Determinations, (2) used to develop a geographic information system (GIS)‐based stream network for identifying ephemeral, intermittent, and perennial streams, and (3) applied to a larger watershed and compared to values obtained using the high‐resolution National Hydrography Dataset (NHD). The parameters drainage area and local valley slope were the most reliable predictors of flow regime type. Results showed the high‐resolution NHD identified no ephemeral streams and 9 and 65% fewer intermittent and perennial streams, respectively, than the GIS model.     

Spatiotemporal Variability of Snow Depletion Curves Derived from SNODAS for the Conterminous United States, 2004‐2013

Assessment of water resources at a national scale is critical for understanding their vulnerability to future change in policy and climate. Representation of the spatiotemporal variability in snowmelt processes in continental‐scale hydrologic models is critical for assessment of water resource response to continued climate change. Continental‐extent hydrologic models such as the U.S. Geological Survey National Hydrologic Model (NHM) represent snowmelt processes through the application of snow depletion curves (SDCs). SDCs relate normalized snow water equivalent (SWE) to normalized snow covered area (SCA) over a snowmelt season for a given modeling unit. SDCs were derived using output from the operational Snow Data Assimilation System (SNODAS) snow model as daily 1‐km gridded SWE over the conterminous United States. Daily SNODAS output were aggregated to a predefined watershed‐scale geospatial fabric and used to also calculate SCA from October 1, 2004 to September 30, 2013. The spatiotemporal variability in SNODAS output at the watershed scale was evaluated through the spatial distribution of the median and standard deviation for the time period. Representative SDCs for each watershed‐scale modeling unit over the conterminous United States (n = 54,104) were selected using a consistent methodology and used to create categories of snowmelt based on SDC shape. The relation of SDC categories to the topographic and climatic variables allow for national‐scale categorization of snowmelt processes.     

Random forest models to estimate bankfull and low flow channel widths and depths across the conterminous United States

Channel dimensions (width and depth) at varying flows influence a host of instream ecological processes, as well as habitat and biotic features; they are a major consideration in stream habitat restoration and instream flow assessments. Models of widths and depths are often used to assess climate change vulnerability, develop endangered species recovery plans, and model water quality. However, development and application of such models require specific skillsets and resources. To facilitate acquisition of such estimates, we created a dataset of modeled channel dimensions for perennial stream segments across the conterminous United States. We used random forest models to predict wetted width, thalweg depth, bankfull width, and bankfull depth from several thousand field measurements of the National Rivers and Streams Assessment. Observed channel widths varied from <5 to >2000 m and depths varied from <2 to >125 m. Metrics of watershed area, runoff, slope, land use, and more were used as model predictors. The models had high pseudo R² values (0.70–0.91) and median absolute errors within ±6% to ±21% of the interquartile range of measured values across 10 stream orders. Predicted channel dimensions can be joined to 1.1 million stream segments of the 1:100 K resolution National Hydrography Dataset Plus (version 2.1). These predictions, combined with a rapidly growing body of nationally available data, will further enhance our ability to study and protect aquatic resources.     

Application of SPARROW Modeling to Understanding Contaminant Fate and Transport from Uplands to Streams

Understanding spatial variability in contaminant fate and transport is critical to efficient regional water‐quality restoration. An approach to capitalize on previously calibrated spatially referenced regression (SPARROW) models to improve the understanding of contaminant fate and transport was developed and applied to the case of nitrogen in the 166,000 km² Chesapeake Bay watershed. A continuous function of four hydrogeologic, soil, and other landscape properties significant (α = 0.10) to nitrogen transport from uplands to streams was evaluated and compared among each of the more than 80,000 individual catchments (mean area, 2.1 km²) in the watershed. Budgets (including inputs, losses or net change in storage in uplands and stream corridors, and delivery to tidal waters) were also estimated for nitrogen applied to these catchments from selected upland sources. Most (81%) of such inputs are removed, retained, or otherwise processed in uplands rather than transported to surface waters. Combining SPARROW results with previous budget estimates suggests 55% of this processing is attributable to denitrification, 23% to crop or timber harvest, and 6% to volatilization. Remaining upland inputs represent a net annual increase in landscape storage in soils or biomass exceeding 10 kg per hectare in some areas. Such insights are important for planning watershed restoration and for improving future watershed models.     

A Gis‐Based Approach to Watershed Classification for Nebraska Reservoirs1

Abstract: The U.S. Environmental Protection Agency is charged with establishing standards and criteria for assessing lake water quality. It is, however, increasingly evident that a single set of national water quality standards that do not take into account regional hydrogeologic and ecological differences will not be viable as lakes clearly have different inherent capacities to meet such standards. We demonstrate a GIS‐based watershed classification strategy for identifying groups of Nebraska reservoirs that have similar potential capacity to attain a certain level of water quality standard. A preliminary cluster analysis of 78 reservoirs was performed to determine the potential number of Nebraska reservoir groups. Subsequently, a Classification Trees method was used to refine number of classes, describe the structure of reservoir watershed classes, and to develop a predictive model that relates watershed conditions to reservoir classes. Results suggest that Nebraska reservoirs can be represented by nine classes and that soil organic matter content in the watershed is the most important single variable for segregating the reservoirs. The cross‐validation prediction error rate of the Classification Tree model was 26.3%. Because all geospatial data used in this work are available nationally, the method could be adopted throughout the U.S. Hence, this GIS‐based watershed classification approach could provide water resources managers an effective decision‐support tool in managing reservoir water quality.     

REGRESSION MODELS FOR ESTIMATING HERBICIDE CONCENTRATIONS IN U.S. STREAMS FROM WATERSHED CHARACTERISTICS1

ABSTRACT: Regression models were developed for estimating stream concentrations of the herbicides alachlor, atrazine, cyanazine, metolachior, and trilluralin from use‐intensity data and watershed characteristics. Concentrations were determined from samples collected from 45 streams throughout the United States during 1993 to 1995 as part of the U.S. Geological Survey's National Water‐Quality Assessment (NAWQA). Separate regression models were developed for each of six percentiles (10th, 25th, 50th, 75th, 90th, 95th) of the annual distribution of stream concentrations and for the annual time‐weighted mean concentration. Estimates for the individual percentiles can be combined to provide an estimate of the annual distribution of concentrations for a given stream. Agricultural use of the herbicide in the watershed was a significant predictor in nearly all of the models. Several hydrologic and soil parameters also were useful in explaining the variability in concentrations of herbicides among the streams. Most of the regression models developed for estimation of concentration percentiles and annual mean concentrations accounted for 50 percent to 90 percent of the variability among streams. Predicted concentrations were nearly always within an order of magnitude of the measured concentrations for the model‐development streams, and predicted concentration distributions reasonably matched the actual distributions in most cases. Results from application of the models to streams not included in the model development data set are encouraging, but further validation of the regression approach described in this paper is needed.     

ENHANCING FECAL COLIFORM TOTAL MAXIMUM DAILY LOAD MODELS THROUGH BACTERIAL SOURCE TRACKING1

ABSTRACT: Surface water impairment by fecal coliform bacteria is a water quality issue of national scope and importance. In Virginia, more than 400 stream and river segments are on the Commonwealth's 2002 303(d) list because of fecal coliform impairment. Total maximum daily loads (TMDLs) will be developed for most of these listed streams and rivers. Information regarding the major fecal coliform sources that impair surface water quality would enhance the development of effective watershed models and improve TMDLs. Bacterial source tracking (BST) is a recently developed technology for identifying the sources of fecal coliform bacteria and it may be helpful in generating improved TMDLs. Bacterial source tracking was performed, watershed models were developed, and TMDLs were prepared for three streams (Accotink Creek, Christians Creek, and Blacks Run) on Virginia's 303(d) list of impaired waters. Quality assurance of the BST work suggests that these data adequately describe the bacteria sources that are impairing these streams. Initial comparison of simulated bacterial sources with the observed BST data indicated that the fecal coliform sources were represented inaccurately in the initial model simulation. Revised model simulations (based on BST data) appeared to provide a better representation of the sources of fecal coliform bacteria in these three streams. The coupled approach of incorporating BST data into the fecal coliform transport model appears to reduce model uncertainty and should result in an improved TMDL.     

SPARROW Modeling of Nitrogen Sources and Transport in Rivers and Streams of California and Adjacent States,U.S.

The SPARROW (SPAtially Referenced Regressions On Watershed attributes) model was used to evaluate the spatial distribution of total nitrogen (TN) sources, loads, watershed yields, and factors affecting transport and decay in the stream network of California and portions of adjacent states for the year 2002. The two major TN sources to local catchments on a mass basis were fertilizers and manure (51.7%) and wastewater discharge (15.9%). Other sources contributed < 12%. Fertilizer use is widespread in the Central Valley region of California, and also important in several other regions because of the diversity of California agriculture. Precipitation, sand content of surficial soils, wetlands, and tile drains were important for TN movement to stream reaches. Median streamflow in the study area is about 0.04 m³/s. Aquatic losses of nitrogen were found to be most important in intermittent and small to medium sized streams (0.2‐14 m³/s), while larger streams showed less loss, and therefore are important for TN transport. Nitrogen loss in reservoirs was found to be insignificant, possibly because most of the larger ones are located upstream of nitrogen sources. The model was used to show loadings, sources, and tributary inputs to several major rivers. The information provided by the SPARROW model is useful for determining both the major sources contributing nitrogen to streams and the specific tributaries that transport the load.     

REGIONAL CHARACTERISTICS OF NUTRIENT CONCENTRATIONS IN STREAMS AND THEIR APPLICATION TO NUTRIENT CRITERIA DEVELOPMENT1

ABSTRACT: In order to establish meaningful nutrient criteria, consideration must be given to the spatial variations in geographic phenomena that cause or reflect differences in nutrient concentrations in streams. Regional differences in stream nutrient concentrations were illustrated using stream data collected from 928 nonpoint‐source watersheds distributed throughout the country and sampled as part of the U.S. EPA National Eutrophication Survey (NES). Spatial patterns in the differences were compared and found to correspond with an a priori regional classification system based on regional patterns in landscape attributes associated with variation in nutrient concentrations. The classification consists of 14 regions composed of aggregations of the 84 U.S. EPA Level III Ecoregions. The primary distinguishing characteristics of each region and the factors associated with variability in water quality characteristics are presented. The use of the NES and many other extant monitoring data sets to develop regional reference conditions for nutrient concentrations in streams is discouraged on the basis of sample representation. The necessity that all sites used in such an effort be regionally representative and consistently screened for least possible impact is emphasized. These sampling issues are rigorously addressed by the U.S. EPA Environmental Monitoring and Assessment Program (EMAP). A case‐study, using EMAP data collected from the Central and Eastern Forested Uplands, demonstrates how regional reference conditions and draft nutrient criteria could be developed.