Decision Support System for Total Maximum Daily Load

A decision support system (DSS) was developed to calculate total maximum daily loads (TMDLs) of various pollutants for water quality limited sections (WQLS) within a river basin. The DSS includes a watershed simulation model, a database, a consensus building module, and a TMDL module that provides a worksheet for the calculations. The system can generate multiple combinations of waste load allocation and non-point-load allocation to meet the water quality criteria for the intended uses of the WQLS. Considering various possible solutions, the regulatory agency and local stakeholders can negotiate an option most agreeable to all parties. The methodology is demonstrated with an example application in the Catawba River Basin, which extends from North Carolina to South Carolina.     

Viewing Total Maximum Daily Loads as a Process, Not a Singular Value: Adaptive Watershed Management

This paper describes adaptive watershed management, which combines concepts for adaptive management and watershed management to address the various uncertain elements in a total maximum daily load (TMDL). The paper discusses how adaptive watershed management allows initial progress to be made while additional information is collected and incorporated in the TMDL. Adaptive watershed management differs from the conventional TMDL approach as a result of feedback loops, which allow managers to proceed with implementation of controls in a progressive manner, avoiding unproductive and irresolvable debate over uncertainty in the numeric value of the TMDL or the efficacy of the controls. Over time, improvements in monitoring, modeling, TMDL analysis, water quality targets, and control actions contribute to the improved effectiveness of the TMDL. The adaptive watershed management approach can be applied in situations dominated by nonpoint sources or having significant uncertainty in any number of issues. The paper includes examples of previous uses of adaptive approaches, a discussion of additional elements that need to be considered, and identification of regulatory and other obstacles.     

Applying the First-Order Error Analysis in Determining the Margin of Safety for Total Maximum Daily Load Computations

There are significant uncertainties associated with certain aspects of the total maximum daily load (TMDL) estimation. Selection of the “margin of safety (MOS)” term is typically made by subjectively assigning to it a small percentage (5–10%) of the TMDL load. To introduce some objectivity into the MOS estimation, the first-order error analysis (FOEA) was utilized to quantify the MOS term in the TMDL formulation. A case study, which was based on a previous study entitled “Nitrate TMDL Development for Muddy Creek/Dry River, Virginia,” is presented in this paper. Besides computational efficiency, one of the major advantages of FOEA is its capability of determining the relative importance of the various parameters that contribute to the overall variance of the model output. Precipitation was found by far to be the most dominant source of uncertainty. Furthermore, a relationship was established to link the pollutant loads with the FOEA output concentrations. The results from testing different TMDL allocation scenarios demonstrate that with the increase of relative percentage of nonpoint sources load reduction in the total load reduction, the portion needed to be reserved for MOS increases as well. The MOS term can be related to the variability in rainfall and therefore would be different for different locations in the country. In summary, as a practical, less subjective and reliable approach to TMDL uncertainty analysis, the use of the FOEA is considered as a viable alternative to the current simple explicit and implicit methods in estimating the MOS term for TMDL calculations.     

Models Quantify the Total Maximum Daily Load Process

Mathematical models have been used for many years to assist in the management of water quality. The total maximum daily load (TMDL) process is no exception; models represent the means by which the assimilative capacity of a water body can be quantified and a waste load allocation can be determined such that the assimilative capacity is not exceeded. Unfortunately, in many TMDLs, the use of models has not always adhered to the best modeling practices that have been developed over the past half-century. This paper presents what are felt to be the most important principles of good modeling practice relative to all of the steps in developing and applying a model for computing a TMDL. These steps include: Problem definition and setting management objectives; data synthesis for use in modeling; model selection; model calibration and, if possible confirmation; model application; iterative modeling; and model postaudit. Since mathematical modeling of aquatic systems is not an exact science, it is essential that these steps be fully transparent to all TMDL stakeholders through comprehensive documentation of the entire process, including specification of all inputs and assumptions. The overriding consideration is that data richness and quality govern the level of model complexity that can be applied to a given system. The model should never be more complex than the data allow. Also, in applying a model, one should always attempt to quantify the uncertainty in predictions. In general, quantifying uncertainty is easier with simple models, which is another reason to begin with a simple framework.     

Estimating Nonpoint Source Pollution in the Upper Yangtze River Using the Export Coefficient Model, Remote Sensing, and Geographical Information System

Recently, increasing nutrient (i.e., nitrogen and phosphorus) concentrations have been observed in the surface water of many countries and this nonpoint source (NPS) pollution has become an important factor in the deterioration of water quality in the upper reach of the Yangtze River Basin. In this paper, the NPS pollution loads in the upper reach of Yangtze River Basin in the year 2000 were estimated using export coefficient model and remote sensing techniques. The spatial distributions of the NPS loads within the watershed were then displayed using geographical information system. Results indicated that the total nitrogen load was 1.947×106?t and the total phosphorus load was 8.364×104?t. Important source areas for the nutrients were croplands in the Jinsha R. and Jialing R. watershed, as well as the Chongqing municipality.     

Simplified Databased Total Maximum Daily Loads, or the World is Log-Normal

The total maximum daily load (TMDL) approaches that have relied mostly on deterministic modeling have inherent problems with considerations of a margin of safety and estimating probabilities of excursions of water quality standards expressed in terms of magnitude, duration, and frequency. A tiered probabilistic TMDL approach is proposed in this paper. A simple databased Tier I TMDL that uses statistical principles has been proposed for watersheds that have adequate water quality databases enabling statistical evaluations. Studies have shown that for many pollutants, event mean concentrations in runoff, wastewater loads, and concentrations in the receiving waters follow the log-normal probability distribution. Other probability distributions are also applicable. Tier II Monte Carlo simulation, using a simpler deterministic or black box water quality model as a transfer function, can then be used to generate time series of data, which fills the data gaps and allows estimation of probabilities of excursions of chronic standards that are averaged over periods of 4 or 30 days. Statistical approaches, including Monte Carlo, allow replacement of an arbitrary margin of safety by a quantitative estimation of uncertainty and enable linking the model results to the standards defined in terms of magnitude, frequency, and duration.     

Bacteria Load Estimator Spreadsheet Tool for Modeling Spatial Escherichia coli Loads to an Urban Bayou

The model developed in this paper, the bacteria loading estimator spreadsheet tool (BLEST), was designed as an easy to use indicator bacteria model that can overcome the shortcomings of many of the simpler total maximum daily load (TMDL) modeling approaches by integrating spatial variation into load estimates. BLEST was applied to the Buffalo Bayou watershed in Houston, Texas and incorporated loading from point and nonpoint sources, such as wastewater treatment plants, sanitary sewer overflows, septic systems, storm sewer leaks, runoff, bed sediment resuspension, and direct deposition. The dry weather Escherichia coli load in Buffalo Bayou was estimated using BLEST to be 244 billion MPN/day and would require an overall 48% reduction to meet the contact recreation standard, while wet weather loads would need to be reduced by 99.7%. Dry weather loads were primarily caused by animal direct deposition, septic systems and discharges from storm sewers under dry weather conditions, while wet weather loads were mostly attributable to runoff and resuspension from sediment. Unlike most simple TMDL load allocation strategies, BLEST can be used to evaluate spatially variable load reduction strategies. For example, septic system load reductions implemented in less than 10% of the subwatersheds resulted in a decrease in bayou loading of more than 20%.     

Estimating Nutrient Outflow from Argicultural Watersheds to the River Kali in India

In India, fertilizers and chemicals are applied to different crops, which in turn, cause nonpoint source pollution of surface water and groundwater of the region. In the present work, extensive water quality surveys were done to estimate the nutrient outflow from three small agricultural watershed of the Kali Basin, Uttar Pradesh, India. A total of 576 field data sets have been collected during March 1999–February 2000 from four sampling stations. During the monsoon period the nutrient outflow from these agricultural watersheds were found to be orders of magnitude higher than during the nonmonsoon period. The percentage of nutrients outflow from each watershed was estimated on a monthly basis by obtaining periodical cropping patterns and the amounts of fertilizer applied for each watershed. A maximum of 85% of total nitrate and 70% of total orthophosphate applied in the field was found to be lost during the month of July from the third agricultural watershed having maximum slope and minimum watershed area. Using the data sets generated during field surveys, commonly used modeling approaches based on mass balance differential loading and decay fraction were tested for their applicability to estimate nonpoint source (NPS) pollution in the River Kali. The NPS concentration and load values computed from these approaches were compared with the NPS values measured in the field and the performances of different equations have been evaluated using error estimations such as standard error, normal mean error, mean multiplicative error, and correlation statistics. Further, a refined model based on reaction kinetics and mass balance differential loading has been proposed for the River Kali that minimizes error estimates and improves correlation between observed and computed nonpoint source loads.     

History of Innovative Best Management Practice Development and its Role in Addressing Water Quality Limited Waterbodies

Best management practices (BMPs) are practical control measures (including technological, economic, and institutional considerations) that have been demonstrated to effectively minimize water quality impacts. The use of BMPs is widely accepted as the most appropriate method of controlling nonpoint sources of pollution because BMPs prevent or minimize pollution rather than retrospectively respond to it. Still, there is a stigma that BMPs do not afford quite the same degree of protection or assurance of pollution control that effluent treatment and process controls do for point sources. Here we provide a brief history of BMPs and their emergence as a practical water pollution control tool for nonpoint source activities, with a focus on the history of forestry BMPs. This history demonstrates the variety of BMPs used to avoid or minimize the generation of nonpoint source pollutants or reduce delivery of these materials to streams. It also demonstrates the extensive testing of BMP effectiveness that has been conducted throughout the United States. Those who must select or design BMPs face difficult issues about balancing desirable and undesirable inputs of watershed materials and energy to streams. We show that BMPs and nonpoint source control programs are not a “weak sister” of effluent treatment and point source control efforts, and are effectively addressing extremely complex and variable watershed conditions. Best management practices continue to evolve as research identifies new environmental concerns and control options and, as the primary tool for controlling nonpoint source pollution, play a key role in addressing water quality limited waterbodies.     

Biological Assessment and Criteria Improve Total Maximum Daily Load Decision Making

Mandated total maximum daily load (TMDL) analyses present an excellent opportunity to restore the nation’s degraded waters. The current norm for TMDL practice is, however, unlikely to achieve this goal without improved water quality standards plus systematic monitoring and assessment using biological criteria. Better than chemical and physical criteria alone, biological criteria link human actions, their impacts on water bodies, and societal goals, which are expressed as designated uses. To be adequate, monitoring should improve understanding of the connections among stressor, exposure, and response gradients. Water quality standards, monitoring, and assessment can improve water resources because they track water body condition, not the number of TMDLs completed. Federal and state leadership must set policy goals, as required by the Clean Water Act, and provide adequate fiscal and professional resources. States with high-quality programs should serve as models. Administrators should use the advances made in 2 decades of water resource science to improve their water management programs. Without such improvements, those involved in the TMDL process will continue to be frustrated, and the nation’s waters will continue to decline.     

Bacteria Loads from Point and Nonpoint Sources in an Urban Watershed

A pathogen impaired watershed in Houston, Tex., was studied to assess the spatial and temporal nature of point and nonpoint bacterial load contributions. End-of-pipe sampling at wastewater treatment plant effluent and storm sewers discharging under dry weather conditions was undertaken. Relatively low concentrations of E. coli were found in wastewater treatment effluent, with a geometric mean of 5 MPN/dL, while dry weather storm sewer discharges exhibited a geometric mean concentration of 212 MPN/dL. Loads from both point and nonpoint sources of E. coli were calculated and compared to in-stream bacteria loads. Nonpoint loads were estimated using an event mean concentration approach on an annual basis. Nonpoint source (NPS) loads were the primary source of bacteria loading to the bayou. Wastewater treatment plant and dry weather storm sewer loads, however, dominated in dry weather conditions. While NPS loads remained relatively constant from headwaters to the mouth of the bayou, point source loads exhibited greater spatial variability depending on the distribution of the discharging pipes. The study points to the need for spatial and temporal considerations in managing bacterial pollution in streams.     

Hydrologic and Water Quality Integration Tool: HydroWAMIT

A spatially distributed and continuous hydrologic model focusing on total maximum daily load (TMDL) projects was developed. Hydrologic models frequently used for TMDLs such as the hydrologic simulation program—FORTRAN (HSPF), soil and water assessment tool (SWAT), and generalized watershed loading function (GWLF) differ considerably in terms of spatial resolution, simulated processes, and linkage flexibility to external water quality models. The requirement of using an external water quality model for simulating specific processes is not uncommon. In addition, the scale of the watershed and water quality modeling, and the need for a robust and cost-effective modeling framework justify the development of alternative watershed modeling tools for TMDLs. The hydrologic and water quality integration tool (HydroWAMIT) is a spatially distributed and continuous time model that incorporates some of the features of GWLF and HSPF to provide a robust modeling structure for TMDL projects. HydroWAMIT operates within the WAMIT structure, developed by Omni Environmental LLC for the Passaic River TMDL in N. J. HydroWAMIT is divided into some basic components: the hydrologic component, responsible for the simulation of surface flow and baseflow from subwatersheds; the nonpoint-source (NPS) component, responsible for the calculation of the subwatershed NPS loads; and the linkage component, responsible for linking the flows and loads from HydroWAMIT to the water quality analysis simulation program (WASP). HydroWAMIT operates with the diffusion analogy flow model for flow routing. HydroWAMIT provides surface runoff, baseflow and associated loads as outputs for a daily timestep, and is relatively easy to calibrate compared to hydrologic models like HSPF. HydroWAMIT assumes that the soil profile is divided into saturated and unsaturated layers. The water available in the unsaturated layer directly affects the surface runoff from pervious areas. Surface runoff from impervious areas is calculated separately according to precipitation and the impervious fractions of the watershed. Baseflow is given by a linear function of the available water in the saturated zone. The utility of HydroWAMIT is illustrated for the North Branch and South Branch Raritan River Watershed (NSBRW) in New Jersey. The model was calibrated, validated, and linked to the WASP. The NPS component was tested for total dissolved solids. Available weather data and point-source discharges were used to prepare the meteorological and flow inputs for the model. Digital land use, soil type datasets, and digital elevation models were used for determining input data parameters and model segmentation. HydroWAMIT was successfully calibrated and validated for monthly and daily flows for the NSBRW outlet. The model statistics obtained using HydroWAMIT are comparable with statistics of HSPF and SWAT applications for medium and large drainage areas. The results show that HydroWAMIT is a feasible alternative to HSPF and SWAT, especially for large-scale TMDLs that require particular processes for water quality simulation and minor hydrologic model calibration effort.     

Development of Refined BOD and DO Models for Highly Polluted Kali River in India

Most commonly used river water quality models for biochemical oxygen demand (BOD) and dissolved oxygen (DO) simulations are mainly based on advection, decay, settling, and loading functions. Using these concepts, refined river water quality models for BOD and DO simulations are developed in the present work considering a large number of physically based parameters and input variables. The refined models developed can be transformed to some of the commonly used river water quality models, if physically based parameters and input variables are omitted or removed. To test the applicability of the refined models developed and commonly used models, a total of 732 water quality and flow data sets are collected during March 1999–February 2000 from 22 sampling stations of the River Kali in India. River Kali is a highly polluted river in India and receives continuous inflow of untreated point source pollution from municipal and industrial wastes and nonpoint source pollution from agricultural areas. Newton–Raphson technique is used to optimize the model parameters during calibration and the performance of different models are evaluated using error estimation, viz. standard error and mean multiplicative error, and correlation statistics (r2). The results indicate that the BOD–DO models proposed by Camp in 1963 provide better results in comparison to other commonly used models. Moreover, the refined models developed for BOD and DO simulations minimize error estimates and improve correlation between observed and computed BOD and DO values of River Kali.     

Improving Total Maximum Daily Loads with Lessons Learned from Long-Term Detailed Monitoring

Many thousands of impaired water segments in the United States will be the subject of total maximum daily load (TMDL) determinations in the next decade. Many of these load allocations will be established with access to only minimal local data. Long-term and detailed datasets from other locations can facilitate this process by offering general insights into the processes that interact to produce the chemistry observed in a particular waterbody over time. These insights can lead to more enlightened interpretation of sparse but locally relevant water quality data. They can also inform the design of implementation monitoring to evaluate success of TMDLs. Finally, study of such datasets reveals biases that may result from inappropriate sampling design or data interpretation algorithms, and may lead to erroneous conclusions about the success or failure of a TMDL program in a specific watershed.     

Dissolved Oxygen and pH Modeling of a Periphyton Dominated, Nutrient Enriched River

Nutrient enrichment of the South Umpqua River, Oregon was linked to periphyton growth and large diel fluctuations in dissolved oxygen and hydrogen ion (pH) concentrations using the water quality model QUAL2Kw. The available data provide a good case study for the relatively new water quality model. QUAL2Kw simulates a dynamic diel heat budget and water quality kinetics for a one-dimensional, steady-flow system and is part of a family of models meant to serve as an update to the widely used QUAL2E. The model was used to quantify nonpoint source loading, determine the pollutant of concern, estimate natural conditions, and calculate a phosphorus total maximum daily load during summer, low-flow conditions. Control of both nonpoint and point sources is required to achieve the low instream phosphorus concentrations necessary to meet water quality criteria. To our knowledge, this is the first paper that reports on the application of a model for computing the maximum allowable load necessary to manage the diel variation in pH.     

Development of a Simple Phosphorus Model for a Large Urban Watershed: A Case Study

Often, the initiation of a total maximum daily load (TMDL) program is delayed until intensive monitoring data can be collected—even in watersheds where large historical data sets exist. This paper provides a case study of a modeling effort that utilizes available historical data to fulfill an intermediate goal of a TMDL program for the Passaic River Basin. The subject model is developed to simulate total phosphorus concentrations (and loads) within the basin’s effluent-dominated streams. The model is based on the assumption that the primary process controlling in-stream total phosphorus concentrations is the dilution of the cumulative upstream effluent load—which was computed on a continuous (daily) basis. Model comparisons indicate a generally good fit to long-term river-monitoring data at several key sites. Model results, and data analyses, suggest that secondary processes have a relatively minor impact on total phosphorus (TP) concentrations in this relatively large, urbanized system. This finding is consistent with a previous QUAL2E model study of the system, and consistent with the relatively conservative behavior of TP reported in many medium-to-large river systems throughout the United States. Model results are used to facilitate TMDL planning efforts for a major water supply reservoir in the basin.     

Confounding Effect of Flow on Estuarine Response to Nitrogen Loading

The total maximum daily load (TMDL) concept provides the basis for regulating pollution load from riverine sources to impaired water bodies. However, load is comprised of two components: flow and concentration. These two components may have confounding, or even conflicting, effects on waterbody attributes of concern. This is particularly the case for dynamic, advective systems, such as estuaries. Resolving these components is critical for properly predicting the response of impaired systems to watershed management actions. The Neuse River Estuary in North Carolina is an example of such an impaired system. Nitrogen has been identified as the pollutant of concern, and the process of developing a TMDL for nitrogen is underway. We, therefore, analyze the extensive data that have been collected for the Neuse River and estuary to investigate spatiotemporal relationships between river flow, riverine total nitrogen (TN) inputs, water temperature, dissolved inorganic nitrogen concentration, algal density, and primary productivity. Results support the belief that phytoplankton in the estuary are under substantial riverine control. However, the riverine TN concentration alone has only a minor role in determining estuarine chlorophyll concentration. River flow has a stronger influence, likely through its effects on down-estuary nitrogen delivery, residence time, salinity, and turbidity. These results imply that using riverine nitrogen load as the metric to evaluate watershed nutrient management may not be appropriate. While nitrogen controls should reduce loads in the long term, in the short term, river flow is the dominant component of load and has the opposite effect of nitrogen on algae at the up-estuary locations.     

Modeling Nonpoint Source Pollutant Losses from a Small Watershed Using HSPF Model

Hydrologic models play an important role in the assessment of nonpoint source (NPS) pollution, which is essential for the environmental management of water resources. The present study has been undertaken to evaluate the applicability of a physically based continuous time scale, hydrological, and water quality computer model—Hydrologic Simulation Program-Fortran (HSPF)—in simulating runoff and sediment associated NPS pollutant losses from a small mixed type (land under agriculture, shrubs and forest, rocks, grasses) watershed of the Damodar Valley Corporation, Hazaribagh, India. Water soluble NO3–N, NH4–N, and P were considered as pollutants and their concentrations in the runoff were measured at the outlet of the watershed, randomly for 15 dates during the monsoon season (June–October) of 2000 and 2001. The model calibration and validation results reveal that the seasonal trend of HSPF simulated runoff, sediment yield, and NPS pollutants compared reasonably with their measured counterparts. Although the concentrations of pollutants were generally overpredicted for NO3–N and underpredicted for NH4–N and water-soluble P in the month of June when fertilizers releasing NH4–N and P are applied in rice fields, the differences in the mean concentration were not significantly different at a 95% level of confidence. Variation in the simulated losses of water soluble N and P species between the years occurred largely due to differences in the amount and distribution of rainfall. These results indicate that the HSPF model can be used as a tool for simulating runoff and sediment associated NPS pollution losses from the study area.     

Including Source-Specific Phosphorus Mobility in a Nonpoint Source Pollution Model for Agricultural Watersheds

Most widely used nonpoint source models associate pollutant loads almost exclusively with land use via pollutant export coefficients and some kind of runoff coefficient. Not surprisingly, the range of management options suggested by such models’ simulations are largely linked to changes in land use. This problem is addressed by developing models of dissolved phosphorus (DP) mobility for specific agricultural sources: manure, fertilizers, soil/plant complexes, and impervious surfaces and those associated with baseflow P loads. These models are coupled with a spatially distributed hydrologic model, the variable source loading function model. The model was applied to a small (164?ha), upstate New York watershed and tested against 1996–2000 stream flow and DP data. The source-specific model required no direct calibration of parameters compared to eight parameters needed in a similar export coefficient type model. Both models predicted stream DP loads well but the source-specific model provided additional insights into, for example, how much DP in the stream was derived from accumulated soil P as opposed to direct leaching from manure. This type of information is necessary to develop and assess a full range of options for best management practices, especially those that involve nonstatic activities such as manure spreading.     

Role of Effluent Permit Trading in Total Maximum Daily Load Programs: Overview and Uncertainty and Reliability Implications

Many jurisdictions in the United States are currently preparing total maximum daily load (TMDL) programs for stream segments that come under Section 303(d) of the Clean Water Act. Among the options being considered by many state pollution control agencies is that of permit trading, otherwise known as permit transfers, transferable permits, emissions trading, bubbles, pollution rights, marketable effluent permits, and transferable discharge permits. Under such programs, a permit to discharge into a watercourse, issued as part of a wasteload allocation program, is treated as a marketable commodity. This paper presents a qualitative discussion of the strengths and weaknesses of permit trading in the context of a TMDL program, and discusses the circumstances that favor it. The paper also presents hypothetical quantitative findings to illustrate the circumstances under which a regional administrator might wish to adopt a program of permit trading, and if so, what type of permits would suit it best.