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.     

Simulation of Metals Total Maximum Daily Loads and Remediation in a Mining-Impacted Stream

Simulation of metals transport was performed to help develop metals total maximum daily loads (TMDLs) and evaluate remediation alternatives in a mountain stream in Montana impacted by hundreds of abandoned hardrock metal mines. These types of watersheds are widespread in Montana and many other areas of the western United States. Impacts from abandoned hardrock or metal mines include loadings of sediment, metals, and other pollutants causing impairment of multiple beneficial uses and exceedances of water quality standards. The United States Environmental Protection Agency (EPA) Water Quality Analysis Simulation Program (WASP) was used to model and evaluate TMDLs for several heavy metals in Tenmile Creek, a mountain stream supplying drinking water to the City of Helena, Mont. The model was calibrated for baseflow conditions and validated using data collected by the EPA and the United States Geological Survey, and used to assess existing metals loadings and losses, including interactions between metals in water and bed sediment, uncertainty, water quality standard exceedances, TMDLs, potential source areas, and required reductions in loadings. During baseflow conditions, adits and point sources contribute significant metals loadings to Tenmile Creek. Exceedances of standards are widespread throughout the stream under both baseflow and higher flow conditions. Adsorption and precipitation onto bed sediments play a primary role in losses from the water column in some areas. Modeling results indicate that some uncertainty exists in the metal partition coefficients associated with sediment, significance of precipitation reactions, and in locations of unidentified sources and losses of metals. TMDLs and loading reductions were calculated based on variations in flow, concentrations, loadings, and standards (which vary with hardness) along the mainstem. In most cases, considerable reductions in loadings are required to achieve TMDLs and water quality standards. Reductions in loadings from point sources, mine waste near watercourses, and streambed sediment can help improve water quality, but alteration of the water supply scheme and increasing baseflow will also be needed.     

Retrospective Comparison of Watershed Analysis Risk Management Framework and Hydrologic Simulation Program Fortran Applications to Mica Creek Watershed

As part of an ongoing watershed model comparison program for forested watersheds, Watershed Analysis Risk Management Framework (WARMF V5.18) and Hydrologic Simulation Program Fortran (HSPF V10) were independently applied to the Mica Creek Watershed in Idaho. A comprehensive model comparison was made in terms of watershed delineation, hydrologic formulations, model parameterization, meteorological data, hydrologic calibration, and hydrologic verification. Comparison was not made for water quality, which was not simulated in the HSPF application. It was concluded that WARMF is a mechanistic model structured to simulate the hydrologic processes, whereas HSPF is an empirical water budget model. The WARMF is suitable for application to forested watersheds. It successfully predicted stream flows comparable to measured values. The HSPF results were also good, if one ignores an unrealistic amount of water loss to inactive groundwater and an empirical treatment of rain-on-snow events.     

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.     

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.     

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.     

Approach Using Active Groundwater Storage for Hydrologic Model Calibration in West-Central Florida

Hydrologic model calibration is always a challenging and tedious process especially for the calibration of complex models, which includes continuous hydrograph models, requires sophisticated calibration methods. The Hydrologic Simulation Program-FORTRAN (HSPF) is one of the popular and powerful time variable hydrologic models. However, in order to improve the assessment of hydrologic activities in shallow ground water settings, the model needs to be reliably calibrated for ground water contribution. Little guidance is provided in the literature concerning the manner of this contribution. In fact, the most common calibration of HSPF uses subjective parameter fitting and focuses on the attainment of statistical goodness of fit of runoff fluxes and water levels, ignoring ground water components. The goal of this research is using a different approach to calibrate HSPF with observed water table records. In this study, HSPF is applied on a small area in west-central Florida and calibrated by comparing active ground water storage to well elevation records in range land and forested land covers. The Nash-Sutcliffe efficiency and correlation coefficient computed using observed and simulated daily flows are 0.91 and 0.96 at Peace River, respectively, also with good fair results for other stations in the model domain. The study shows that improved calibration of the model can be achieved if active ground water storage and well records are compared for timing and magnitude of fluctuations.     

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.     

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.     

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%.     

Modeling Escherichia Coli and Its Sources in an Urban Bayou with Hydrologic Simulation Program—FORTRAN

Bacterial levels in Buffalo Bayou in Houston commonly exceed contact recreation standards. Potential sources of bacteria include wastewater treatment plants, sanitary sewer overflows, septic systems, wet and dry nonpoint-source discharges via direct runoff and pipes, direct deposition, and sediment. A water-quality model in the Hydrologic Simulation Program—FORTRAN (HSPF) was calibrated and validated for hydrology, sediment, and Escherichia coli and subsequently used to evaluate the impacts of the bacterial sources in the watershed. In addition, simple estimates of bacterial loads were calculated along with source evaluations from load duration curves. Load reductions based upon the simple estimates indicated that water-quality standards were met by reducing dry-weather indicator bacterial loads by 69% and wet-weather loads by 98%. When these load reductions were implemented in the HSPF model, however, standards were not met under dry-weather conditions. Residual nonpoint-source loading was found to cause the discrepancy between simple load estimate calculations and the developed water-quality model. This paper demonstrates that runoff can play a significant role in maintaining high levels of bacteria under all flow conditions and that understanding the temporal variations in bacterial source loading is critical to ensure that load reductions will achieve water-quality standards.     

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.     

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.     

Decision Support System for Stakeholder Involvement

Stakeholder involvement is essential to the development of a total maximum daily load (TMDL) and its implementation plan. A tool, beyond a simulation model, is needed to support the decision making process that requires negotiation and compromise among stakeholders. The decision support system (DSS) described herein has a TMDL module to calculate various combinations of point and nonpoint loads that can meet the water quality criteria. Its Consensus module allows stakeholders to formulate, evaluate, modify, and vote for alternatives. The DSS displays bar charts for pollution loads from various subwatersheds and attributes the nonpoint loads to land uses. The water quality consequence of the pollution loads is output in maps, which shows sections meeting criteria in green and those not in red. The DSS requires a front end effort of site specific adaptation and model calibration. An Internet-based stakeholder process was developed to allow more concerned citizens to participate in management decisions.     

Event and Continuous Hydrologic Modeling with HEC-HMS

Event hydrologic modeling reveals how a basin responds to an individual rainfall event (e.g., quantity of surface runoff, peak, timing of the peak, detention). In contrast, continuous hydrologic modeling synthesizes hydrologic processes and phenomena (i.e., synthetic responses of the basin to a number of rain events and their cumulative effects) over a longer time period that includes both wet and dry conditions. Thus, fine-scale event hydrologic modeling is particularly useful for understanding detailed hydrologic processes and identifying the relevant parameters that can be further used for coarse-scale continuous modeling, especially when long-term intensive monitoring data are not available or the data are incomplete. Joint event and continuous hydrologic modeling with the Hydrologic Engineering Center’s Hydrologic Modeling System (HEC-HMS) is discussed in this technical note and an application to the Mona Lake watershed in west Michigan is presented. Specifically, four rainfall events were selected for calibrating/verifying the event model and identifying model parameters. The calibrated parameters were then used in the continuous hydrologic model. The Soil Conservation Service curve number and soil moisture accounting methods in HEC-HMS were used for simulating surface runoff in the event and continuous models, respectively, and the relationship between the two rainfall-runoff models was analyzed. The simulations provided hydrologic details about quantity, variability, and sources of runoff in the watershed. The model output suggests that the fine-scale (5?min time step) event hydrologic modeling, supported by intensive field data, is useful for improving the coarse-scale (hourly time step) continuous modeling by providing more accurate and well-calibrated parameters.     

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.     

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.     

Integrated Hydrologic Modeling and GIS in Water Resources Management

The integration of a physically-based distributed model with a geographic information system (GIS) in watershed-based water resources management is presented, and an example watershed is chosen to demonstrate the spatial database and modeling system developed in this study. The spatial data is first processed by GIS. The model is then used to simulate runoff hydrographs. It operates at a daily time step on 1 × 1 km grid squares and simulates important hydrologic processes including evapotranspiration, snowmelt, infiltration, aquifer recharge, ground-water flow, and overland and channel runoff. Finally, the model result is displayed by using GIS. This study demonstrates that the integration of a physically based distributed model and GIS may successfully and efficiently implement the watershed-based water resources management. Not only does this process facilitate examination of a wider range of alternatives that would be impossible by using conventional methods, but it also provides a living management that could be modified and updated by water managers once the watershed condition is changed.     

Utility of LANDSAT-Derived Land Use Data for Estimating Storm-Water Pollutant Loads in an Urbanizing Area

In many watersheds located in southern California, efforts are being focused on urban runoff because of its adverse impact on receiving water quality. The Sweetwater River watershed is a good example, where the drainage area is rapidly urbanizing and deteriorating reservoir water quality. Contaminated storm water is captured and diverted but as urbanization increases, additional runoff will be generated which will overload the existing infrastructure. To better manage the diversion systems and minimize future construction, storm-water volumes and pollutant loadings need to be estimated. Due to the lack of real-time storm-water runoff monitoring data, pollutant loadings must be estimated from land use information. We used satellite imagery to estimate selected storm-water pollutant loads and compared the results to predictions using land use information from public records. Satellite imagery was useful in estimating storm-water pollutant loads and identifying high loading areas. Satellite imagery with appropriate classification is a promising tool for watershed management and for prioritizing best management practices.     

Eutrophication Model for the Patuxent Estuary: Advances in Predictive Capabilities

A robust eutrophication and sediment diagenesis model has been developed for the Patuxent Estuary to study the impact of different nutrient loadings on phytoplankton biomass and dissolved oxygen (DO) levels. The modeling approach was to begin with an existing water quality model (CE-QUAL-W2) for the Patuxent Estuary (hereafter referred to as the Estuary). First, formulations for the water column kinetics were completely replaced with routines based on the WASP/EUTRO5 water quality model. Then, a sediment diagenesis component was added to simulate the accumulation and mineralization of organic matter in the sediment, the generation of sediment oxygen demand, and the flux of phosphate and ammonia from the sediment. Loadings from the tributaries for nutrients and flow were based on a combination of watershed modeling and sampling by scientists at the Smithsonian Environmental Research Center. The new model was able to reproduce the ambient water quality data from 1997 to 1999 by adequately simulating the high concentrations of phytoplankton and low DO levels in the Estuary. The model was then used to evaluate the response to various hypothetical nutrient loading scenarios. Model results show that phytoplankton growth in the upper Estuary is much more sensitive to nutrient loading from tributaries than in the lower estuary. Further, model results indicate that DO concentrations in the lower Estuary are largely influenced by levels of nutrients and organic carbon at the mouth of the Estuary.