Total Maximum Daily Load Allocation Research Articles

Influence of Reservoir Infill on Coastal Deep Water Hypoxia

Ecological restoration of the Chesapeake through the Chesapeake Bay total maximum daily load (TMDL) requires the reduction of nitrogen, phosphorus, and sediment loads in the Chesapeake watershed because of the tidal water quality impairments and damage to living resources they cause. Within the Chesapeake watershed, the Conowingo Reservoir has been filling in with sediment for almost a century and is now in a state of near-full capacity called . The development of the Chesapeake TMDL in 2010 was with the assumption that the Conowingo Reservoir was still effectively trapping sediment and nutrients. This is now known not to be the case. In a TMDL, pollutant loads beyond the TMDL allocation, which are brought about by growth or other conditions, must be offset. Using the analysis tools of the Chesapeake TMDL for assessing the degree of water quality standard attainment, the estimated nutrient and sediment loads from a simulated dynamic equilibrium infill condition of the Conowingo Reservoir were determined. The influence on Chesapeake water quality by a large storm and scour event of January 1996 on the Susquehanna River was estimated, and the same storm and scour events were also evaluated in the more critical living resource period of June. An analysis was also made on the estimated influence of more moderate high flow events. The infill of the Conowingo reservoir had estimated impairments of water quality, primarily on deep-water and deep-channel dissolved oxygen, because of increased discharge and transport of organic and particulate inorganic nutrients from the Conowingo Reservoir.

An Indirect Simulation-Optimization Model for Determining Optimal TMDL Allocation under Uncertainty

An indirect simulation-optimization model framework with enhanced computational efficiency and risk-based decision-making capability was developed to determine optimal total maximum daily load (TMDL) allocation under uncertainty. To convert the traditional direct simulation-optimization model into our indirect equivalent model framework, we proposed a two-step strategy: (1) application of interval regression equations derived by a Bayesian recursive regression tree (BRRT v2) algorithm, which approximates the original hydrodynamic and water-quality simulation models and accurately quantifies the inherent nonlinear relationship between nutrient load reductions and the credible interval of algal biomass with a given confidence interval; and (2) incorporation of the calibrated interval regression equations into an uncertain optimization framework, which is further converted to our indirect equivalent framework by the enhanced-interval linear programming (EILP) method and provides approximate-optimal solutions at various risk levels. The proposed strategy was applied to the Swift Creek Reservoir’s nutrient TMDL allocation (Chesterfield County, VA) to identify the minimum nutrient load allocations required from eight sub-watersheds to ensure compliance with user-specified chlorophyll criteria. Our results indicated that the BRRT-EILP model could identify critical sub-watersheds faster than the traditional one and requires lower reduction of nutrient loadings compared to traditional stochastic simulation and trial-and-error (TAE) approaches. This suggests that our proposed framework performs better in optimal TMDL development compared to the traditional simulation-optimization models and provides extreme and non-extreme tradeoff analysis under uncertainty for risk-based decision making.

Arguments for inclusion of economic criteria in the total maximum daily load (TMDL) allocation phase

The idea of including economic analysis in pollution control studies is not new. There is a long tradition of research modeling least cost load allocation for water pollution control that has led to a substantial awareness that failure to take costs into account in load allocations can greatly increase the costs of water pollution control. Despite this understanding, the current load allocation approach adopted under United States Environmental Protection Agency total maximum daily load (TMDL) program allocates pollutant loads among different polluters in the absence of economic criteria. Many water quality professionals question the appropriateness of including economic criteria into an already complex and cumbersome TMDL allocation process. The question is not why we do not include economics into waste load allocations, rather the question is why we should? This paper attempts to identify and present the benefits associated with the incorporation of economic criteria into the traditional TMDL allocation process. The TMDL process is considered to be a holistic watershed approach and as such should not overlook the economic consequences of pollutant allocation alternatives. This paper attempts to focus less on the mechanism of optimizing the costs and more on the benefits derived as a by-product of doing so. The advantages of incorporating economic criteria for a bacteria load allocation in the Roses Creek watershed in the Commonwealth of Virginia are presented in this paper.

TMDL development for the Taihu Lake’s influent rivers, China using variable daily load expressions

Influent river carrying nutrient pollutants from watershed loads makes a great contribution to the eutrophication in river-fed lake. It is scientific standard to make policies on river pollution control based on loading capacity of the river of interest. To control eutrophication in Taihu Lake has been the focal point of “The Twelfth Five-Year Guideline” proposed by Chinese government. The Taigeyunhe, Caoqiaohe and Yincungang Rivers which were the most polluted influent rivers in Taihu Lake Basin were scheduled for nutrient total maximum daily load (TMDL). A variety of mechanistic and empirical models are applied worldwide for TMDL development. However, model selection depends on management objectives, site-specific characteristics and availability of data resource. In this study, based on watershed characteristics and limited data, a nutrient TMDL is developed using flow and temporally variable daily load expressions. The simple and effective approaches specify allowable daily maximum loads for controlling on instantaneous high load and allowable daily median loads for achieving long-term TMDL allocation. For the entire river system, loading capacities are much lower during low flows. The maximum percent load reductions for biochemical oxygen demand, ammonia nitrogen, total nitrogen in spring and total phosphorus in winter can be obtained when pollution source inputs seasonally vary. This study provides local authority with two different alternatives in decision-making for pollution control on influent rivers and then to reduce external loads to the lake.

Economic total maximum daily load for watershed-based pollutant trading

Water quality trading (WQT) is supported by the US Environmental Protection Agency (USEPA) under the framework of its total maximum daily load (TMDL) program. An innovative approach is presented in this paper that proposes post-TMDL trade by calculating pollutant rights for each pollutant source within a watershed. Several water quality trading programs are currently operating in the USA with an objective to achieve overall pollutant reduction impacts that are equivalent or better than TMDL scenarios. These programs use trading ratios for establishing water quality equivalence among pollutant reductions. The inbuilt uncertainty in modeling the effects of pollutants in a watershed from both the point and nonpoint sources on receiving waterbodies makes WQT very difficult. A higher trading ratio carries with it increased mitigation costs, but cannot ensure the attainment of the required water quality with certainty. The selection of an applicable trading ratio, therefore, is not a simple process. The proposed approach uses an Economic TMDL optimization model that determines an economic pollutant reduction scenario that can be compared with actual TMDL allocations to calculate selling/purchasing rights for each contributing source. The methodology is presented using the established TMDLs for the bacteria (fecal coliform) impaired Muddy Creek subwatershed WAR1 in Rockingham County, Virginia, USA. Case study results show that an environmentally and economically superior trading scenario can be realized by using Economic TMDL model or any similar model that considers the cost of TMDL allocations.

Microbial source tracking markers for detection of fecal contamination in environmental waters: relationships between pathogens and human health outcomes

Microbial source tracking (MST) describes a suite of methods and an investigative strategy for determination of fecal pollution sources in environmental waters that rely on the association of certain fecal microorganisms with a particular host. MST is used to assess recreational water quality and associated human health risk, and total maximum daily load allocations. Many methods rely on signature molecules (markers) such as DNA sequences of host-associated microorganisms. Human sewage pollution is among the greatest concerns for human health due to (1) the known risk of exposure to human waste and (2) the public and regulatory will to reduce sewage pollution; however, methods to identify animal sources are receiving increasing attention as our understanding of zoonotic disease potential improves. Here, we review the performance of MST methods in initial reports and field studies, with particular emphasis on quantitative PCR (qPCR). Relationships among human-associated MST markers, fecal indicator bacteria, pathogens, and human health outcomes are presented along with recommendations for future research. An integrated understanding of the advantages and drawbacks of the many MST methods targeting human sources advanced over the past several decades will benefit managers, regulators, researchers, and other users of this rapidly growing area of environmental microbiology.

Development of the Chesapeake Bay Watershed Total Maximum Daily Load Allocation

AbstractNutrient load allocations and subsequent reductions in total nitrogen and phosphorus have been applied in the Chesapeake watershed since 1992 to reduce hypoxia and to restore living resources. In 2010, sediment allocations were established to augment nutrient allocations supporting the submerged aquatic vegetation resource. From the initial introduction of nutrient allocations in 1992 to the present, the allocations have become more completely applied to all areas and loads in the watershed and have also become more rigorously assessed and tracked. The latest 2010 application of nutrient and sediment allocations were made as part of the Chesapeake Bay total maximum daily load and covered all six states of the Chesapeake watershed. A quantitative allocation process was developed that applied principles of equity and efficiency in the watershed, while achieving all tidal water quality standards through an assessment of equitable levels of effort in reducing nutrients and sediments. The level of effort was determined through application of two key watershed scenarios: one where no action was taken in nutrient control and one where maximum nutrient control efforts were applied. Once the level of effort was determined for different jurisdictions, the overall load reduction was set watershed‐wide to achieve dissolved oxygen water quality standards. Further adjustments were made to the allocation to achieve the James River chlorophyll‐a standard.

Building a Stormwater Utility Organization to Meet the Challenges of Stormwater Management Requirements Now and In The Future

Building a Stormwater Utility Organization to Meet the Challenges of Stormwater Management Requirements Now and In The FutureIn many cases, stormwater utility organizations are relatively new in their formation and evolution, as compared to utilities providing drinking and wastewater services. Currently, stormwater utilities are evolving rapidly to address impending challenges such as new and stricter Municipal Separate Storm Sewer System (MS4) permit requirements and Total Maximum Daily Load allocations. Many...Author(s)Linda BlankenshipFernando PasquelAllison WestlundSourceProceedings of the Water Environment FederationDocument typeConference PaperPublisherWater Environment FederationPrint publication date Oct, 2013ISSN1938-6478DOI10.2175/193864713813692045Volume / Issue2013 / 11Content sourceWEFTECCopyright2013Word count169

Simple Optimization Method to Determine Best Management Practices to Reduce Phosphorus Loading in Echo Reservoir, Utah

This study develops and applies a simple linear optimization program to identify cost-effective best management practices (BMPs) to reduce phosphorus loading in Echo Reservoir, Utah. The optimization program tests the feasibility of proposed total maximum daily load (TMDL) allocations based on potential BMP options and provides information regarding the spatial redistribution of loads among sub-watersheds. The current version of the TMDL for Echo Reservoir allocates phosphorus loads to existing non-point phosphorus sources in different sub-watersheds to meet a specified total load. Optimization results show that it is feasible to implement BMPs for non-point sources in each sub-watershed to meet reduction targets at a cost of $1.0 million. However, relaxing these targets can achieve the overall target at lower cost. The optimization program and results provide a simple tool to test the feasibility of proposed TMDL allocations based on potential BMP options and can also recommend spatial redistributions of loads among sub-watersheds to lower costs.

Incorporating uncertainty and objective load reduction allocation into the Total Maximum Daily Load process in Korea

This paper presents advancements to the approach for Total Maximum Daily Load (TMDL) development in Korea. The current Korean TMDL process does not directly consider uncertainty and it does not include an objective approach to allocate pollutant load reductions. This paper develops a methodology to address uncertainty by incorporating a margin of safety (MOS) based on three approaches: judgment, standard error of loading characteristics, and uncertainty and variability of loading characteristics. In addition, three pollutant load reduction allocation approaches are compared to assess their impact: equal load, equal percent, and equity standard reductions. These two proposed additions to the TMDL process in Korea are demonstrated for a BOD TMDL development in the Anyangcheon Watershed. The results confirm the importance of incorporating uncertainty into the TMDL process and clearly illustrate the significant differences in TMDL and load allocation produced when using different approaches to estimate the MOS. Further, the comparison of the three load allocation strategies highlights the potential limitations of equal load and equal percent reduction approaches. The use of technical expert and decision maker ranking of factors create an equitable and sustainable load allocation among the sub-watersheds. It can be concluded that incorporating uncertainty and providing an objective load allocation strategy are essential elements needed for future TMDL development in Korea.

A Stochastic Method to Characterize Model Uncertainty for a Nutrient TMDL

The U.S. EPA's Total Maximum Daily Load (TMDL) program has encountered hindrances in its implementation partly because of its strong dependence on mathematical models to set limitations on the release of impairing substances. The uncertainty associated with predictions of such models is often not scientifically quantified and typically assigned as an arbitrary margin of safety (MOS) in the TMDL allocation. The Soil Water Assessment Tool (SWAT) model was evaluated to determine its applicability to identify the impairment status and tabulate a nutrient TMDL for a waterbody located in the Piedmont physiographic region of Maryland. The methodology for tabulating the nutrient TMDL is an enhancement over current methods used in Maryland. The mean-value first-order reliability method (MFORM) was paired with a stochastic approach to tabulate a science-based estimate of model uncertainty and MOS for the TMDL approach. Monthly streamflow estimates were quite good, with Nash-Sutcliffe efficiency (NSE) coefficients of 0.75 and 0.70 for the calibration and validation phases, respectively. Sediment and nutrients were not estimated as well as streamflow on a monthly basis; however, large improvements in model estimation were observed on an annual time scale. MOS was determined based on the desired level of confidence in meeting the water quality standard. The water quality standard was met at 20% nitrate reduction (9.9 kg N d-1) with a 37.5% level of confidence. The water quality goal was met by a 30% reduction in nitrate load (8.6 kg N d-1), in which case there was a 75% chance of meeting the water quality standard. Therefore, the MOS load (the difference between the standard and the goal) was 1.3 kg N d-1 or 10% of the baseline load. These results indicate that SWAT is a suitable model for use in TMDL assessments of impaired water bodies, especially assessments based on long-term simulations. In addition, the stochastic method used to quantify MOS for a nitrate TMDL is an improvement over current methods because it provides a formal, scientifically derived measure of model uncertainty.

Potential cost savings from discharge allowance trading: A case study and implications for water quality trading

Applying a trading ratio system similar to that proposed by Hung and Shaw (2005), we estimate the potential cost savings of a phosphorus emissions trading program that meets overall total maximum daily load allocations among 22 wastewater treatment plants (WWTPs) in the Passaic River watershed (United States) to be a modest 2–3% relative to a no‐trade baseline. These results may be typical of those in relatively small watersheds such as the Passaic, where there are limited numbers of potential traders and relatively homogeneous abatement technologies across WWTPs. More substantial gains from trade may accrue to a concentrated group of WWTPs, suggesting that watershed managers should focus on a targeted set of traders within a watershed. Under certain conditions, additional gains may be achieved by aggregating WWTPs into zones within which there can be one‐to‐one allowance trading.

Linking trading ratio with TMDL (total maximum daily load) allocation matrix and uncertainty analysis

An innovative approach for total maximum daily load (TMDL) allocation and implementation is the watershed-based pollutant trading. Given the inherent scientific uncertainty for the tradeoffs between point and nonpoint sources, setting of trading ratios can be a contentious issue and was already listed as an obstacle by several pollutant trading programs. One of the fundamental reasons that a trading ratio is often set higher (e.g. greater than 2) is to allow for uncertainty in the level of control needed to attain water quality standards, and to provide a buffer in case traded reductions are less effective than expected. However, most of the available studies did not provide an approach to explicitly address the determination of trading ratio. Uncertainty analysis has rarely been linked to determination of trading ratio.This paper presents a practical methodology in estimating "equivalent trading ratio (ETR)" and links uncertainty analysis with trading ratio determination from TMDL allocation process. Determination of ETR can provide a preliminary evaluation of "tradeoffs" between various combination of point and nonpoint source control strategies on ambient water quality improvement. A greater portion of NPS load reduction in overall TMDL load reduction generally correlates with greater uncertainty and thus requires greater trading ratio. The rigorous quantification of trading ratio will enhance the scientific basis and thus public perception for more informed decision in overall watershed-based pollutant trading program.

Comparison of wetland and agriculture drainage as sources of biochemical oxygen demand to the San Joaquin River, California

For many years, the San Joaquin River (SJR) has had low dissolved oxygen conditions intermittently during the late summer and early fall. The low dissolved oxygen conditions are impacting critical fish habitat and the SJR is being regulated under a state of California remediation plan that includes the development of a total maximum daily load (TMDL) allocation for oxygen demanding substances. In support of the development of a scientific TMDL allocation, studies are being conducted to characterize water quality in the many tributaries of the SJR. This study identified the sources of biochemical oxygen demand (BOD) in two western tributaries of the SJR, Mud Slough and Salt Slough, and measured the loads of BOD, algae, and ammonia entering the SJR from wetland and agricultural sources. Mud and Salt Sloughs drain the Grassland Watershed. The watershed contains seasonal wetlands, irrigated farmland, and other agricultural lands. This drainage is under close regulatory scrutiny, because it produces a majority of the selenium and boron entering the SJR. In this study, wetland and irrigated agricultural drainage were sampled separately and a comparison was made to determine differences in water quality. In addition, water entering the study area was compared to water exiting the study area to determine the effect of water use in the region on water quality. This study demonstrated that BOD loads from the Grassland Watershed to the SJR were proportional to flow during June–October, the most critical time for dissolved oxygen deficits in the lower SJR. This indicates that Mud and Salt Sloughs are not producing more BOD than other tributaries in the region that are not under close regulatory scrutiny. The BOD concentration of wetland drainage is higher than that of agricultural drainage, but the higher agricultural drainage flows result in a higher mass loading of BOD. Wetland flooding and irrigation of crops both had a negative impact on water quality. Algal growth was identified as the major source of BOD in agricultural drainage and locations where BOD control could potentially be implemented were identified.

Robust optimization for total maximum daily load allocations

The determination of the pollutant load distribution among different pollutant sources in a watershed is a critical step in total maximum daily load (TMDL) development. Under current TMDL practices, TMDL allocations are typically determined through a trial‐and‐error approach of reducing pollutant loadings until a watershed simulation model predicts that water quality standards will be met given a margin of safety. Unfortunately, many feasible combinations of load reductions and significant uncertainties may exist. Therefore it is difficult and time‐consuming to compare various allocation scenarios using a trial‐and‐error approach. A robust optimization model is developed in this study to incorporate the uncertainty of water quality predictions and to minimize pollutant load reductions given various levels of reliability with respect to the water quality standards. The generalized likelihood uncertainty estimation approach is used to explicitly address the uncertainty of a watershed simulation model, the Hydrological Simulation Program–Fortran. The uncertainty is integrated into TMDL allocations using a robust genetic algorithm model linked with a response matrix approach. The developed robust optimization model is demonstrated using a case study based on the Moore's Creek fecal coliform TMDL study. The trade‐offs between reliability levels and total load reductions of allocation scenarios are evaluated, and the optimized load reduction scenarios are compared with the scenario generated by a trial‐and‐error approach and approved by the U.S. Environmental Protection Agency. The results show that the optimized load reduction scenario requires 30% less load reductions than the scenario approved by the U.S. Environmental Protection Agency at the same reliability level.

Applying SWAT for TMDL programs to a small watershed containing rice paddy fields

The main objective of this study was to apply the soil and water assessment tool (SWAT) to develop total maximum daily load (TMDL) programs for a small watershed containing rice paddy fields in the Republic of Korea. The total maximum daily load system (TOLOS), based on ArcView SWAT (AVSWAT) using geographic information system (GIS) and remote sensing (RS), was incorporated with the SWAT model to simulate water balance and water quality from irrigated paddy fields. Model parameters related to hydrology and water quality were calibrated and validated by comparing model predictions with the field data collected for 4 years. The results indicated that the simulated runoff and water quality values were acceptably close to the observed data. Water quality parameters also appeared to be reasonably comparable to the field data. The applicability of the system for TMDL development was tested in terms of TMDL allocations and the redistribution of load reductions to 23 sub-areas within the watershed. The results demonstrated that the urbanized subwatershed #2, with residences and other community activities, required the largest allocation of road reduction. TOLOS thus appears to be a useful tool for planning TMDL for a small watershed including rice paddies in Korea.

BSLC: A TOOL FOR BACTERIA SOURCE CHARACTERIZATION FOR WATERSHED MANAGEMENT

The Total Maximum Daily Load (TMDL) program is an integrated watershed assessment and management processdesigned to address surface water quality impairments. The presence of pathogen indicator bacteria [fecal coliform andEscherichia coli (E. coli)] is reported to be the most widespread cause of water quality impairment in the United States.Watershed-scale simulation models, when used in a what-if scenario assessment mode, can assist stakeholders andwatershed planners in making informed immediate and long-term land-use-based watershed management decisions designedto control bacterial contamination and improve water quality. However, to use such models, accurate characterization ofbacteria sources present in a watershed is necessary. The objectives of this article are to describe the process developed andused by the Center for TMDL and Watershed Studies at Virginia Tech to characterize bacterial source inputs needed for awatershed-scale simulation model and to introduce a software tool, the Bacteria Source Load Calculator (BSLC), that aidsin the source characterization and TMDL allocation scenario development process. The BSLC uses externally generatedinputs, such as land use distribution and livestock, wildlife, and human population estimates, to calculate monthly bacterialland loadings and hourly bacterial stream loadings. The program was developed using Visual Basic for Applications (VBA)in Microsoft Excel. The BSLC and its underlying methodology have been used in the development of 21 bacterial TMDLs inVirginia. The BSLC software greatly simplifies the creation of required data files needed by watershed-scale simulationmodels and provides consistency in data development and processing.

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 ...

Case Study of Impact of Total Maximum Daily Load Allocations on Nitrate Leaching

An analysis of the impact of total maximum daily load (TMDL) allocations on the potential leaching of nitrates to groundwater in the Muddy Creek/Dry River watershed of Virginia is presented. The Muddy Creek/Dry River watershed has experienced nitrate impairments to both surface water and groundwater. Using the Nitrate Leaching and Economic Analysis Package, this work estimates the change in the potential mass of nitrate leaching into the subsurface, given a range of feasible load allocations developed in the nitrate TMDL of this watershed. Modeling analysis suggests that TMDL allocations would reduce the leaching mass and concentrations by 8.5% on average in the Muddy Creek watershed. Furthermore, while feasible load allocations performed similarly with respect to surface water reductions, the selected TMDL allocation scenario provides only half the leaching reduction of other feasible allocation scenarios. While expanding the scope of this TMDL to also protect the subsurface water resources would have been a reasonable and prudent management approach, the expanded complexity was impossible within the short completion schedule allowed for TMDLs.