Streamflow Hydrology Estimate Using Machine Learning (SHEM)

Continuity and accuracy of near real‐time streamflow gauge (streamgage) data are critical for flood forecasting, assessing imminent risk, and implementing flood mitigation activities. Without these data, decision makers and first responders are limited in their ability to effectively allocate resources, implement evacuations to save lives, and reduce property losses. The Streamflow Hydrology Estimate using Machine Learning (SHEM) is a new predictive model for providing accurate and timely proxy streamflow data for inoperative streamgages. SHEM relies on machine learning (“training”) to process and interpret large volumes (“big data”) of historic complex hydrologic information. Continually updated with real‐time streamflow data, the model constructs a virtual dataset index of correlations and groups (clusters) of relationship correlations between selected streamgages in a watershed and under differing flow conditions. Using these datasets, SHEM interpolates estimated discharge and time data for any indexed streamgage that stops transmitting data. These estimates are continuously tested, scored, and revised using multiple regression analysis processes and methodologies. The SHEM model was tested in Idaho and Washington in four diverse watersheds, and the model's estimates were then compared to the actual recorded data for the same time period. Results from all watersheds revealed a high correlation, validating both the degree of accuracy and reliability of the model.     

Factors Affecting Stream Nutrient Loads: A Synthesis of Regional SPARROW Model Results for the Continental United States1

Preston, Stephen D., Richard B. Alexander, Gregory E. Schwarz, and Charles G. Crawford, 2011. Factors Affecting Stream Nutrient Loads: A Synthesis of Regional SPARROW Model Results for the Continental United States. Journal of the American Water Resources Association (JAWRA) 47(5):891‐915. DOI: 10.1111/j.1752‐1688.2011.00577.x Abstract: We compared the results of 12 recently calibrated regional SPARROW (SPAtially Referenced Regressions On Watershed attributes) models covering most of the continental United States to evaluate the consistency and regional differences in factors affecting stream nutrient loads. The models – 6 for total nitrogen and 6 for total phosphorus – all provide similar levels of prediction accuracy, but those for major river basins in the eastern half of the country were somewhat more accurate. The models simulate long‐term mean annual stream nutrient loads as a function of a wide range of known sources and climatic (precipitation, temperature), landscape (e.g., soils, geology), and aquatic factors affecting nutrient fate and transport. The results confirm the dominant effects of urban and agricultural sources on stream nutrient loads nationally and regionally, but reveal considerable spatial variability in the specific types of sources that control water quality. These include regional differences in the relative importance of different types of urban (municipal and industrial point vs. diffuse urban runoff) and agriculture (crop cultivation vs. animal waste) sources, as well as the effects of atmospheric deposition, mining, and background (e.g., soil phosphorus) sources on stream nutrients. Overall, we found that the SPARROW model results provide a consistent set of information for identifying the major sources and environmental factors affecting nutrient fate and transport in United States watersheds at regional and subregional scales.     

Introduction to SWAT+, A Completely Restructured Version of the Soil and Water Assessment Tool

SWAT+ is a completely restructured version of the Soil and Water Assessment Tool (SWAT) that was developed to face present and future challenges in water resources modeling and management and to meet the needs of the worldwide user community. It is expected to improve code development and maintenance; support data availability, analysis, and visualization; and enhance the model's capabilities in terms of the spatial representation of elements and processes within watersheds. The most important change is the implementation of landscape units and flow and pollutant routing across the landscape. Also, SWAT+ offers more flexibility than SWAT in defining management schedules, routing constituents, and connecting managed flow systems to the natural stream network. To test the basic hydrologic function of SWAT+, it was applied to the Little River Experimental Watershed (Georgia) without enhanced overland routing and compared with previous models. SWAT+ gave similar results and inaccuracies as these models did for streamflow and water balance. Taking full advantage of the new capabilities of SWAT+ regarding watershed discretization and landscape and river interactions is expected to improve simulations in future studies. While many capabilities of SWAT have already been enhanced in SWAT+ and new capabilities have been added, the model will continue to evolve in response to advancements in scientific knowledge and the demands of the growing worldwide user community. Editor's note: This paper is part of the featured series on SWAT Applications for Emerging Hydrologic and Water Quality Challenges. See the February 2017 issue for the introduction and background to the series.     

A Spatially Explicit Model for Mapping Headwater Streams

Headwater streams are the primary sources of water in a drainage network and serve as a critical hydrologic link between the surrounding landscape and larger, downstream surface waters. Many states, including North Carolina, regulate activity in and near headwater streams for the protection of water quality and aquatic resources. A fundamental tool for regulatory management is an accurate representation of streams on a map. Limited resources preclude field mapping every headwater stream and its origin across a large region. It is more practical to develop a model for headwater streams based on a sample of field data that can then be extrapolated to a larger area of interest. The North Carolina Division of Water Quality has developed a cost‐effective method for modeling and mapping the location, length, and flow classification (intermittent and perennial) of headwater streams. We used a multiple logistic regression approach that combined field data and terrain derivatives for watersheds located in the Triassic Basins ecoregion. Field data were collected using a standard methodology for identifying headwater streams and origins. Terrain derivatives were generated from digital elevation models interpolated from bare‐earth Light Detection and Range data. Model accuracies greater than 80% were achieved in classifying stream presence and absence, stream length and perennial stream length, but were not as consistent in predicting intermittent stream length.     

A CyberGIS Integration and Computation Framework for High‐Resolution Continental‐Scale Flood Inundation Mapping

We present a Digital Elevation Model‐based hydrologic analysis methodology for continental flood inundation mapping (CFIM), implemented as a cyberGIS scientific workflow in which a 1/3rd arc‐second (10 m) height above nearest drainage (HAND) raster data for the conterminous United States (CONUS) was computed and employed for subsequent inundation mapping. A cyberGIS framework was developed to enable spatiotemporal integration and scalable computing of the entire inundation mapping process on a hybrid supercomputing architecture. The first 1/3rd arc‐second CONUS HAND raster dataset was computed in 1.5 days on the cyberGIS Resourcing Open Geospatial Education and Research supercomputer. The inundation mapping process developed in our exploratory study couples HAND with National Water Model forecast data to enable near real‐time inundation forecasts for CONUS. The computational performance of HAND and the inundation mapping process were profiled to gain insights into the computational characteristics in high‐performance parallel computing scenarios. The establishment of the CFIM computational framework has broad and significant research implications that may lead to further development and improvement of flood inundation mapping methodologies.     

The Impact of Asynchronicity on Event‐Flow Estimation in Basin‐Scale Hydrologic Model Calibration1

Abstract: The calibration of basin‐scale hydrologic models consists of adjusting parameters such that simulated values closely match observed values. However, due to inevitable inaccuracies in models and model inputs, simulated response hydrographs for multiyear calibrations will not be perfectly synchronized with observed response hydrographs at the daily time step. An analytically derived formula suggests that when timing errors are significant, traditional calibration approaches may generally underestimate the total event‐flow volume. An event‐adaptive time series is developed and incorporated into the Nash‐Sutcliffe Efficiency objective function to diagnose the potential impact of event‐flow synchronization errors. Test sites are the 50 km² Subwatershed I of the Little River Experimental Watershed (LREWswI) in southeastern Georgia, and the 610 km² Little Washita River Experimental Watershed (LWREW) in southwestern Oklahoma, with the Soil and Water Assessment Tool used as the hydrologic model. Results suggest that simulated surface runoff generation is 55% less for LREWswI when the daily time series is used compared with when the event‐adaptive technique is used. Event‐flow generation may also be underestimated for LWREW, but to a lesser extent than it may be for LREWswI, due to a larger portion of the event flow being lateral flow.     

Assessing Retrospective National Water Model Streamflow with Respect to Droughts and Low Flows in the Colorado River Basin

Streamflow monitoring in the Colorado River Basin (CRB) is essential to ensure diverse needs are met, especially during periods of drought or low flow. Existing stream gage networks, however, provide a limited record of past and current streamflow. Modeled streamflow products with more complete spatial and temporal coverage (including the National Water Model [NWM]), have primarily focused on flooding, rather than sustained drought or low flow conditions. Objectives of this study are to (1) evaluate historical performance of the NWM streamflow estimates (particularly with respect to droughts and seasonal low flows) and (2) identify characteristics relevant to model inputs and suitability for future applications. Comparisons of retrospective flows from the NWM to observed flows from the United States Geological Survey stream gage network over 22 years in the CRB reveal a tendency for underestimating low flow frequency, locations with low flows, and the number of years with low flows. We found model performance to be more accurate for the Upper CRB and at sites with higher precipitation, snow percent, baseflow index, and elevations. Underestimation of low flows and variable model performance has important implications for future applications: inaccurate evaluations of historical low flows and droughts, and less reliable performance outside of specific watershed/stream conditions. This highlights characteristics on which to focus future model development efforts.     

Continental‐Scale River Flow Modeling of the Mississippi River Basin Using High‐Resolution NHDPlus Dataset

As a key component of the National Flood Interoperability Experiment (NFIE), this article presents the continental scale river flow modeling of the Mississippi River Basin (MRB), using high‐resolution river data from NHDPlus. The Routing Application for Parallel computatIon of Discharge (RAPID) was applied to the MRB with more than 1.2 million river reaches for a 10‐year study (2005‐2014). Runoff data from the Variable Infiltration Capacity (VIC) model was used as input to RAPID. This article investigates the effect of topography on RAPID performance, the differences between the VIC‐RAPID streamflow simulations in the HUC‐2 regions of the MRB, and the impact of major dams on the streamflow simulations. The model performance improved when initial parameter values, especially the Muskingum K parameter, were estimated by taking topography into account. The statistical summary indicates the RAPID model performs better in the Ohio and Tennessee Regions and the Upper and Lower Mississippi River Regions in comparison to the western part of the MRB, due to the better performance of the VIC model. The model accuracy also increases when lakes and reservoirs are considered in the modeling framework. In general, results show the VIC‐RAPID streamflow simulation is satisfactory at the continental scale of the MRB.     

Nonstationarity: Flood Magnification and Recurrence Reduction Factors in the United States1

Vogel, Richard M., Chad Yaindl, and Meghan Walter, 2011. Nonstationarity: Flood Magnification and Recurrence Reduction Factors in the United States. Journal of the American Water Resources Association (JAWRA) 47(3):464‐474. DOI: 10.1111/j.1752‐1688.2011.00541.x Abstract: It may no longer be reasonable to model streamflow as a stationary process, yet nearly all existing water resource planning methods assume that historical streamflows will remain unchanged in the future. In the few instances when trends in extreme events have been considered, most recent work has focused on the influence of climate change, alone. This study takes a different approach by exploring trends in floods in watersheds which are subject to a very broad range of anthropogenic influences, not limited to climate change. A simple statistical model is developed which can both mimic observed flood trends as well as the frequency of floods in a nonstationary world. This model is used to explore a range of flood planning issues in a nonstationary world. A decadal flood magnification factor is defined as the ratio of the T‐year flood in a decade to the T‐year flood today. Using historical flood data across the United States we obtain flood magnification factors in excess of 2‐5 for many regions of the United States, particularly those regions with higher population densities. Similarly, we compute recurrence reduction factors which indicate that what is now considered the 100‐year flood, may become much more common in many watersheds. Nonstationarity in floods can result from a variety of anthropogenic processes including changes in land use, climate, and water use, with likely interactions among those processes making it very difficult to attribute trends to a particular cause.     

A Framework to Develop Nationwide Flooding Extents Using Climate Models and Assess Forecast Potential for Flood Resilience

The methods used to simulate flood inundation extents can be significantly improved by high‐resolution spatial data captured over a large area. This paper presents a hydraulic analysis methodology and framework to estimate national‐level floodplain changes likely to be generated by climate change. The hydraulic analysis was performed using existing published Federal Emergency Management Agency 100‐year floodplains and estimated 100‐ and 10‐year return period peak flow discharges. The discharges were estimated using climate variables from global climate models for two future growth scenarios: Representative Concentration Pathways 2.6 and 8.5. River channel dimensions were developed based on existing regional United States Geological Survey publications relating bankfull discharges with channel characteristics. Mathematic relationships for channel bankfull topwidth, depth, and side slope to contributing drainage area measured at model cross sections were developed. The proposed framework can be utilized at a national level to identify critical areas for flood risk assessment. Existing hydraulic models at these “hot spots” could be repurposed for near–real‐time flood forecasting operations. Revitalizing these models for use in simulating flood scenarios in near–real time through the use of meteorological forecasts could provide useful information for first responders of flood emergencies.     

Coastal Flood Inundation Monitoring with Satellite C‐band and L‐band Synthetic Aperture Radar Data

Satellite Synthetic Aperture Radar (SAR) was evaluated as a method to operationally monitor the occurrence and distribution of storm‐ and tidal‐related flooding of spatially extensive coastal marshes within the north‐central Gulf of Mexico. Maps representing the occurrence of marsh surface inundation were created from available Advanced Land Observation Satellite (ALOS) Phased Array type L‐Band SAR (PALSAR) (L‐band) (21 scenes with HH polarizations in Wide Beam [100 m]) data and Environmental Satellite (ENVISAT) Advanced SAR (ASAR) (C‐band) data (24 scenes with VV and HH polarizations in Wide Swath [150 m]) during 2006‐2009 covering 500 km of the Louisiana coastal zone. Mapping was primarily based on a decrease in backscatter between reference and target scenes, and as an extension of previous studies, the flood inundation mapping performance was assessed by the degree of correspondence between inundation mapping and inland water levels. Both PALSAR‐ and ASAR‐based mapping at times were based on suboptimal reference scenes; however, ASAR performance seemed more sensitive to reference‐scene quality and other types of scene variability. Related to water depth, PALSAR and ASAR mapping accuracies tended to be lower when water depths were shallow and increased as water levels decreased below or increased above the ground surface, but this pattern was more pronounced with ASAR. Overall, PALSAR‐based inundation accuracies averaged 84% (n = 160), while ASAR‐based mapping accuracies averaged 62% (n = 245).     

Using OpenMI and a Model MAP to Integrate WaterML2 and NetCDF Data Sources into Flood Modeling of Genoa,Italy

Extreme hydrometeorological events such as flash floods have caused considerable loss of life and damage to infrastructure over recent years. Flood events in the Mediterranean region between 1990 and 2006 caused over 4,500 fatalities and cost over €29 billion in damage, with Italy one of the worst affected countries. The Distributed Computing Infrastructure for Hydro‐Meteorology (DRIHM) project is a European initiative aiming at providing an open, fully integrated eScience environment for predicting, managing, and mitigating the risks related to such extreme weather phenomena. Incorporating both modeled and observational data sources, it enables seamless access to a set of computing resources with the objective of providing a collection of services for performing experiments with numerical models in meteorology, hydrology, and hydraulics. The purpose of this article is to demonstrate how this flexible modeling architecture has been constructed using a set of standards including the NetCDF and WaterML2 file formats, in‐memory coupling with OpenMI, controlled vocabularies such as CF Standard Names, ISO19139 metadata, and a Model MAP (Metadata, Adaptors, Portability) gateway concept for preparing numerical models for standardized use. Hydraulic results, including the impact to buildings and hazards to people, are given for the use cases of the severe and fatal flash floods, which occurred in Genoa, Italy in November 2011 and October 2014.     

Streamflow Response to Climate as Influenced by Geology and Elevation1

Mayer, Timothy D. and Seth W. Naman, 2011. Streamflow Response to Climate as Influenced by Geology and Elevation. Journal of the American Water Resources Association (JAWRA) 47(4):724‐738. DOI: 10.1111/j.1752‐1688.2011.00537.x Abstract: This study examines the regional streamflow response in 25 predominately unregulated basins to warmer winter temperatures and snowpack reductions over the last half century in the Klamath Basin of California and Oregon. Geologic controls of streamflow in the region result in two general stream types: surface‐dominated and groundwater‐dominated basins. Surface‐dominated basins were further differentiated into rain basins and snowmelt basins on the basis of elevation and timing of winter runoff. Streamflow characteristics and response to climate vary with stream type, as discussed in the study. Warmer winter temperatures and snowpack reductions have caused significantly earlier runoff peaks in both snowmelt and groundwater basins in the region. In the groundwater basins, the streamflow response to changes in snowpack is smoothed and delayed and the effects are extended longer in the summer. Our results indicate that absolute decreases in July‐September base flows are significantly greater, by an order of magnitude, in groundwater basins compared to surface‐dominated basins. The declines are important because groundwater basins sustain Upper Klamath Lake inflows and mainstem river flows during the typically dry summers of the area. Upper Klamath Lake April‐September net inflows have decreased an estimated 16% or 84 thousand acre‐feet (103.6 Mm³) since 1961, with the summer months showing proportionately more decline. These changes will exacerbate water supply problems for agriculture and natural resources in the region.     

A Multi‐Agency Nutrient Dataset Used to Estimate Loads,Improve Monitoring Design,and Calibrate Regional Nutrient SPARROW Models1

Saad, David A., Gregory E. Schwarz, Dale M. Robertson, and Nathaniel L. Booth, 2011. A Multi‐Agency Nutrient Dataset Used to Estimate Loads, Improve Monitoring Design, and Calibrate Regional Nutrient SPARROW Models. Journal of the American Water Resources Association (JAWRA) 47(5):933‐949. DOI: 10.1111/j.1752‐1688. 2011.00575.x Abstract: Stream‐loading information was compiled from federal, state, and local agencies, and selected universities as part of an effort to develop regional SPAtially Referenced Regressions On Watershed attributes (SPARROW) models to help describe the distribution, sources, and transport of nutrients in streams throughout much of the United States. After screening, 2,739 sites, sampled by 73 agencies, were identified as having suitable data for calculating long‐term mean annual nutrient loads required for SPARROW model calibration. These sites had a wide range in nutrient concentrations, loads, and yields, and environmental characteristics in their basins. An analysis of the accuracy in load estimates relative to site attributes indicated that accuracy in loads improve with increases in the number of observations, the proportion of uncensored data, and the variability in flow on observation days, whereas accuracy declines with increases in the root mean square error of the water‐quality model, the flow‐bias ratio, the number of days between samples, the variability in daily streamflow for the prediction period, and if the load estimate has been detrended. Based on compiled data, all areas of the country had recent declines in the number of sites with sufficient water‐quality data to compute accurate annual loads and support regional modeling analyses. These declines were caused by decreases in the number of sites being sampled and data not being entered in readily accessible databases.     

A Faster and Economical Approach to Floodplain Mapping Using Soil Information

Flood inundation maps play a key role in assessment and mitigation of potential flood hazards. However, owing to high costs associated with the conventional flood mapping methods, many communities in the United States lack flood inundation maps. The objective of this study is to develop and examine an economical alternative approach to floodplain mapping using widely available soil survey geographic (SSURGO) database. In this study, floodplain maps are developed for the entire state of Indiana, and some counties in Minnesota, Wisconsin, and Washington states by identifying flood‐prone soil map units based on their attributes. For validation, the flood extents obtained from SSURGO database are compared with the extents from other floodplain maps such as the Federal Emergency Management Agency issued flood insurance rate maps (FIRMs), flood extents observed during past floods, and flood maps derived using digital elevation models. In general, SSURGO‐based floodplain maps (SFMs) are largely in agreement with other flood inundation maps. Specifically, the floodplain extents from SFMs cover 78‐95% area compared to FIRMs and observed flood extents. Thus, albeit with a slight loss in accuracy, the SSURGO approach offers an economical and fast alternative for floodplain mapping. In particular, it has potentially high utility in areas where no detailed flood studies have been conducted.     

Improvement in HSPF's Low‐Flow Predictions by Implementation of a Power Law Groundwater Storage‐Discharge Relationship

We have enhanced the ability of a widely used watershed model, Hydrologic Simulation Program — FORTRAN (HSPF), to predict low flows by reconfiguring the algorithm that simulates groundwater discharge. During dry weather periods, flow in most streams consists primarily of base flow, that is, groundwater discharged from underlying aquifers. In this study, HSPF's groundwater storage‐discharge relationship is changed from a linear to a more general nonlinear relationship which takes the form of a power law. The nonlinear algorithm is capable of simulating streamflow recession curves that have been found in some studies to better match observed dry weather hydrographs. The altered version of HSPF is implemented in the Chesapeake Bay Program's Phase 5 Model, an HSPF‐based model that simulates nutrient and sediment loads to the Chesapeake Bay, and is tested in the upper Potomac River basin, a 29,950 km² drainage area that is part of the Bay watershed. The nonlinear relationship improved median Nash‐Sutcliffe efficiencies for log daily flows at the model's 45 calibration points. Mean absolute percent error on low‐flow days dropped in five major Potomac River tributaries by up to 12 percentage points, and in the Potomac River itself by four percentage points, where low‐flow days were defined as days when observed flows were in the lowest 5th percentile range. Percent bias on low‐flow days improved by eight percentage points in the Potomac River, from ?11 to ?3%.     

Sources of Suspended-Sediment Flux in Streams of the Chesapeake Bay Watershed: A Regional Application of the SPARROW Model1

Brakebill, John W., Scott W. Ator, and Gregory E. Schwarz, 2010. Sources of Suspended-Sediment Flux in Streams of the Chesapeake Bay Watershed: A Regional Application of the SPARROW Model. Journal of the American Water Resources Association (JAWRA) 46(4): 757-776. DOI: 10.1111/j.1752-1688.2010.00450.x Abstract: We describe the sources and transport of fluvial suspended sediment in nontidal streams of the Chesapeake Bay watershed and vicinity. We applied SPAtially Referenced Regressions on Watershed attributes, which spatially correlates estimated mean annual flux of suspended sediment in nontidal streams with sources of suspended sediment and transport factors. According to our model, urban development generates on average the greatest amount of suspended sediment per unit area (3,928 Mg/km²/year), although agriculture is much more widespread and is the greatest overall source of suspended sediment (57 Mg/km²/year). Factors affecting sediment transport from uplands to streams include mean basin slope, reservoirs, physiography, and soil permeability. On average, 59% of upland suspended sediment generated is temporarily stored along large rivers draining the Coastal Plain or in reservoirs throughout the watershed. Applying erosion and sediment controls from agriculture and urban development in areas of the northern Piedmont close to the upper Bay, where the combined effects of watershed characteristics on sediment transport have the greatest influence may be most helpful in mitigating sedimentation in the bay and its tributaries. Stream restoration efforts addressing floodplain and bank stabilization and incision may be more effective in smaller, headwater streams outside of the Coastal Plain.     

Hydrologic Connectivity and the Contribution of Stream Headwaters to Ecological Integrity at Regional Scales1

Abstract: Cumulatively, headwater streams contribute to maintaining hydrologic connectivity and ecosystem integrity at regional scales. Hydrologic connectivity is the water‐mediated transport of matter, energy and organisms within or between elements of the hydrologic cycle. Headwater streams compose over two‐thirds of total stream length in a typical river drainage and directly connect the upland and riparian landscape to the rest of the stream ecosystem. Altering headwater streams, e.g., by channelization, diversion through pipes, impoundment and burial, modifies fluxes between uplands and downstream river segments and eliminates distinctive habitats. The large‐scale ecological effects of altering headwaters are amplified by land uses that alter runoff and nutrient loads to streams, and by widespread dam construction on larger rivers (which frequently leaves free‐flowing upstream portions of river systems essential to sustaining aquatic biodiversity). We discuss three examples of large‐scale consequences of cumulative headwater alteration. Downstream eutrophication and coastal hypoxia result, in part, from agricultural practices that alter headwaters and wetlands while increasing nutrient runoff. Extensive headwater alteration is also expected to lower secondary productivity of river systems by reducing stream‐system length and trophic subsidies to downstream river segments, affecting aquatic communities and terrestrial wildlife that utilize aquatic resources. Reduced viability of freshwater biota may occur with cumulative headwater alteration, including for species that occupy a range of stream sizes but for which headwater streams diversify the network of interconnected populations or enhance survival for particular life stages. Developing a more predictive understanding of ecological patterns that may emerge on regional scales as a result of headwater alterations will require studies focused on components and pathways that connect headwaters to river, coastal and terrestrial ecosystems. Linkages between headwaters and downstream ecosystems cannot be discounted when addressing large‐scale issues such as hypoxia in the Gulf of Mexico and global losses of biodiversity.     

The Controversy Over Natural Channel Design: Substantive Explanations and Potential Avenues for Resolution1

Lave, Rebecca, 2009. The Controversy Over Natural Channel Design: Substantive Explanations and Potential Avenues for Resolution. Journal of the American Water Resources Association (JAWRA) 45(6):1519‐1532. Abstract: The controversy over Natural Channel Design (NCD) has perplexed, and sometimes paralyzed, the stream restoration community in the United States for more than a decade. Despite the high level of energy expended by participants on both sides, the content of the discussion has not advanced significantly. The two sides seem to be talking past each other, rather than engaging in constructive conversation. This paper attempts to start that conversation. Based on five years of primarily social science research, this paper explains the key components of the NCD approach, evaluates a number of the most common objections raised by its critics, offers a brief explanation for the widespread use of NCD, and concludes with suggestions about how to bring the controversy to a close.     

Assessing the Impacts of E. coli Laden Streambed Sediment on E. coli Loads over a Range of Flows and Sediment Characteristics

Understanding sediment Escherichia coli levels (i.e., pathogen indicators) and their contribution to the water column during resuspension is critical for predicting in‐stream E. coli levels and the potential risk to human health. The U.S. Environmental Protection Agency's current water quality testing strategies, however, rely on water borne E. coli concentrations to assess stream E. coli levels and identify impaired waters. In this work, we conducted a scenario analysis using a range of flows, sediment/water bacteria fractions, and particle sizes to which E. coli attach to assess the impact of E. coli in streambed sediments on water column E. coli levels. We used simple sediment transport theory to calculate the potential total E. coli concentrations in a stream with and without the resuspension process. Results clearly indicate that inclusion of resuspending sediment attached E. coli is necessary for watershed assessments and data on sediment attached E. coli concentrations is much needed. When neglecting the streambed sediment E. coli concentrations, the model predicted average E. coli loads of 10⁷ Colony Forming Units (CFU)/s; however, when streambed sediment E. coli concentrations were included in the model, the predictions ranged from 10¹⁰ to 10¹⁴ CFU/s. To evaluate the predictions, E. coli data in the streambed sediment and the water column were monitored in Squaw Creek, Iowa. Comparisons between measured and predicted E. coli loads yielded an R²‐value of 0.85.