IDENTIFICATION OF AN OPTIMAL SAMPLING STRATEGY FOR A CONSTRUCTED WETLAND1

ABSTRACT: The objective of this investigation was to determine the effect of sampling frequency and sampling type on estimates of monthly nutrient loads and flow‐weighted nutrient concentrations in a constructed wetland. Phosphorus and nitrogen loads and concentrations entering and leaving a subtropical wetland (the Everglades Nutrient Removal Project, ENRP) were calculated on the basis of three sampling frequencies. The first frequency included weekly composite samples (three daily samples composited for one week) and grab samples from August 1994 to July 1997, representing a base‐line condition for comparison with results using reduced sampling frequencies. The second and third sampling frequency included three and two composite samples per month, respectively, drawn from the weekly samples. Total phosphorus and nitrogen loads calculated using two and three samples per month were almost identical to results based on four samples per month (least‐squares regression coefficients ranged from 0.96 to 0.98). Results of monthly mean flow‐weighted nutrient concentrations, obtained using reduced sampling frequencies, also were strongly correlated to concentrations calculated using the base‐line sampling frequency (r²ranged from 0.82 to 0.93). Grab samples did not always provide good estimates of loads or concentrations, particularly at the inflow when data were highly variable. From the results of this study, we can recommend that bi‐weekly composite sampling be used to monitor nutrient concentrations and loads discharged from larger‐scale Everglades Stormwater Treatment Areas (STAs) now under construction. Because there are high costs associated with water sample collection and processing, studies to identify optimal sampling frequencies should be a key feature in the design of any comprehensive wetland‐monitoring program.     

IDENTIFICATION OF CHANGES IN STREAMFLOW CHARACTERISTICS1

ABSTRACT: A set of procedures for identifying changes in selected streamflow characteristics at sites having long‐term continuous streamflow records is illustrated by using streamflow data from the Waccamaw River at Freeland, North Carolina for the 55‐year period of 1940–1994. Data were evaluated and compared to streamflow in the adjacent Lumber River Basin to determine if changes in streamflow characteristics in the Waccamaw River were localized and possibly the result of some human activity, or consistent with regional variations. Following 1963, droughts in the Waccamaw Basin seem to have been less severe than in the Lumber Basin, and the annual one‐, seven‐, and 30‐day low flows exhibited a slightly increasing trend in the Waccamaw River. Mean daily flows in the Waccamaw River at the 90 percent exceedance level (low flows) during 1985–194, a relatively dry period, were very nearly equal to flows at the same exceedance level for 1970–1979, which represents the 10‐year period between 1940 and 1994 with the highest flows. Prior to the 1980s, flows per unit drainage area in the Waccamaw Basin were generally less than those in the Lumber Basin, but after 1980, the opposite was true. The ratio of base flow to runoff in the Waccamaw River may have changed relative to that in the Lumber River in the late 1970s. There was greater variability in Waccamaw River streamflow than in Lumber River flow, and flow variability in the Waccamaw River may have increased slightly during 1985–1994.     

MASS BALANCE MODEL ESTIMATION OF PHOSPHORUS CONCENTRATIONS IN RESERVOIRS1

ABSTRACT: Mass balance models have been common tools in lake quality management for some years. However, verification for use on reservoirs, especially in the Western United States, has been seriously lacking, In this study, such a verification is attempted using data from the U.S EPA National Eutrophication Survey. Several models from the literature are compared for accuracy in application to the western reservoir data. Model standard error and correlation between estimated and observed reservoir phosphorus concentrations are the Criteria used for comparison. Standard errors am further used to calculate uncertainty of trophic state classification based on estimated phosphorus concentration. The model proposed by Dillon and Rigler (1974) proved most accurate, with a correlation coefficient of 0.86 and standard error of 0.2, based on logarithmic transformed values. Deficiencies in the other models appear to & from coefficients fit to lake data and from inappropriate model formulation.     

A COMPARATIVE STUDY OF LINEAR AND NONLINEAR TIME SERIES MODELS FOR WATER QUALITY1

ABSTRACT: Surface water quality data are routinely collected in river basins by state or federal agencies. The observed quality of river water generally reflects the overall quality of the ecosystem of the river basin. Advanced statistical methods are often needed to extract valuable information from the vast amount of data for developing management strategies. Among the measured water quality constituents, total phosphorus is most often the limiting nutrient in freshwater aquatic systems. Relatively low concentrations of phosphorus in surface waters may create eutrophication problems. Phosphorus is a non-conservative constituent. Its time series generally exhibits nonlinear behavior. Linear models are shown to be inadequate. This paper presents a nonlinear state-dependent model for the phosphorous data collected at DeSoto, Kansas. The nonlinear model gives significant reductions in error variance and forecasting error as compared to the best linear autoregressive model identified.     

ESTIMATING THE MEAN AND VARIANCE OF CENSORED PHOSPHORUS CONCENTRATIONS IN FLORIDA RAINFALL1

ABSTRACT: The total phosphorous (TP) concentrations in the South Florida rainfall have been recorded in weekly intervals with a detection limit (D_L) of 3.5 μg/L. As a large amount of the data is reported as below the D_L, appropriate statistical methods are needed for data analysis. Thus, an attempt was made to identify an appropriate method to estimate the mean and variance of the data. In particular, a method to separate the statistics for the below D_L portion from the estimated population statistics is proposed. The estimated statistics of the censored data are compared with the statistics of the uncensored data available from the recent years’ laboratory records. It was found that the one-step restricted maximum likelihood method is the most accurate for the wet TP data, and that the proposed method to combine the estimated statistics for TP < D_L portion and the sample statistics for TP ≥ D_L portion improves estimates compared to the conventional maximum likelihood estimates.     

A MULTICOMPONENT MODEL OF PHOSPHORUS DYNAMICS IN RESERVOIRS1

The models available for simulating phosphorus dynamics and trophic state in impoundments vary widely. The simpler empirically derived phosphorus models tend to be appropriate for long-term, steady or near steady state analyses. The more complex ecosystem models, because of computational expense and the importance of input parameter uncertainty, are impractical for very long-term simulation and most applicable for time-variable water quality simulations generally of short to intermediate time frames. An improved model for time variable, long-term simulation of trophic state in reservoirs with fluctuating inflow and outflow rates and volume is needed. Such a model is developed in this paper representing the phosphorus cycle in two-layer (i.e., epilimnion and hypolimnion) reservoirs. The model is designed to simulate seasonally varying reservoir water quality and eutrophication potential by using the phosphorus state variable as the water quality indicator. Long-term simulations with fluctuating volumes and variable influent and effluent flow rates are feasible and practical. The model utility is demonstrated through application to a pumped storage reservoir characteristic of these conditions.     

WATER QUALITY TRENDS AT INFLOWS TO EVERGLADES NATIONAL PARK1

ABSTRACT: Water quality data collected at inflows to Everglades National Park (ENP) are analyzed for trends using the seasonal Kendall test (Hirsch et al., 1982; Hirsch and Slack, 1984). The period of record is 1977–1989 for inflows to Shark River Slough and 1983–1989 for inflows to Taylor Slough and ENP's Coastal Basin. The analysis considers 20 water quality components, including nutrients, field measurements, inorganic species, and optical properties. Significant (p<0.10) increasing trends in total phosphorus concentration are indicated at eight out of nine stations examined. When the data are adjusted to account for variations in antecedent rainfall and water surface elevation, increasing trends are indicated at seven out of nine stations. Phosphorus trend magnitudes range from 4 percent/year to 21 percent/year Decreasing trends in the Total N/P ratio are detected at seven out of nine stations. N/P trend magnitudes range from -7 percent/year to -15 percent/year. Trends in water quality components other than nutrients are observed less frequently and are of less importance from a water-quality-management perspective. The apparent nutrient trends are not explained by variations in marsh water elevation, antecedent rainfall, flow, or season.     

A FRAMEWORK FOR PHOSPHORUS TRANSPORT MODELING IN THE LAKE OKEECHOBEE WATERSHED1

ABSTRACT: A modeling framework was developed to determine phosphorus loadings to Lake Okeechobee from watersheds located north of the lake. This framework consists of the land-based model CREAMS-WT, the in-stream transport model QUAL2E, and an interface procedure to format the land-based model output for use by the in-stream model. QUAL2E hydraulics and water quality routines were modified to account for flow routing and phosphorus retention in both wetlands and stream channels. Phosphorus loadings obtained from previous applications of CREAMS-WT were used by QUAL2E, and calibration and verification showed that QUAL2E accurately simulated seasonal and annual phosphorus loadings from a watershed. Sensitivity and uncertainty analyses indicated that the accuracy of monthly loadings can be improved by using better estimates of in-stream phosphorus decay rates, ground water phosphorus concentrations, and runoff phosphorus concentrations as input to QUAL2E.     

DESIGN BASIS FOR EVERGLADES STORMWATER TREATMENT AREAS1

ABSTRACT: The State of Florida (1994) has adopted a plan for addressing Everglades eutrophication problems by reducing anthropogenic phosphorus loads. The plan involves implementation of Best Management Practices in agricultural watersheds and construction of regional treatment marshes (Stormwater Treatment Areas or STA's). This paper describes the development, testing, and application of a mass-balance model for sizing STA's to achieve treatment objectives. The model is calibrated and tested against peat and water-column data collected in Water Conservation Area-2A (WCA-2A), where phosphorus dynamics and eutrophication impacts have been intensively studied. The 26-year-average rate of phosphorus accretion in peat is shown to be proportional to average water-column phosphorus concentration, with a proportionality constant of 10.2 m/yr (90 percent Confidence Interval = 8.9 to 11.6 m/yr). Spatial and temporal variations in marsh water-column data suggest that drought-induced recycling of phosphorus was important during periods of low stage in WCA-2A. Maintaining wet conditions will be important to promote phosphorus removal in STA's. Sensitivity analysis of STA performance is conducted over the range of uncertainty in model parameter estimates to assess the adequacy of the model as a basis for STA design.     

THE USE OF A SIMPLE MODEL AND UNCERTAINTY ANALYSIS IN LAKE MANAGEMENT1

ABSTRACT: A simple, black-box lake model was developed for phosphorus, using nonlinear regression analysis on a data base of north temperate lakes. The uncertainty associated with the model was then combined with the parameter uncertainty and the independent variable uncertainty to provide an estimate of the confidence limits associated with a predicted value. The prediction uncertainty is often neglected, yet it is an important measure of the usefulness of a model. Prediction uncertainty reflects the modeler's confidence in the model, and it should be used by a decision maker as a weight indicating the value of the model prediction. A procedure is outlined that combined lake modeling and uncertainty analysis for use in lake quality assessment and lake management. An example is provided illustrating the use of this procedure in nutrient budget sampling design, data analysis, and the evaluation of lake management strategies for a 208 program in New Hampshire.     

AN EVALUATION OF EIGHT WASTELOAD ALLOCATION METHODS1

Evidence suggests that there is no superior wasteload allocation method. Eight allocation strategies have been evaluated based on: total cost of implementation, equity in distributing costs and loads among dischargers, effectiveness in use of available waste assimilative capacity, and sensitivity to changes in water-quality-related variables. One method, which allocated equal percentages of the maximum allowable dissolved oxygen deficit, was eliminated as a feasible strategy because it led to excessive costs and overly conservative load estimates. The other seven methods remained viable alternatives. Two methods proved to be insensitive to changes in the water-quality-related variables tested, which may be advantageous in certain applications. This report presents seven workable alternatives that may be used in wasteload allocation and demonstrates a procedure to determine the practicability of other methods.     

A PRACTICAL MODEL INTEGRATING QUALITY ASSURANCE INTO ENVIRONMENTAL MONITORING1

ABSTRACT: A model of comprehensive environmental monitoring process with integral quality assurance is presented. This model views the monitoring process as iterative cycles of a series of elements: design, plan, protocols, preparation, field liaison, sample collection, sample handling, laboratory analysis, data transmission, data validation, data approval, data provision, statistical analysis, and reporting. Quality assurance is linked to each element, not just to laboratory analysis. The program of quality assurance ensures that environmental monitoring data are compatible with the project goals, are comparable between various sampling agencies, and maintain a high degree of scientific credibility. The key characteristics of the overall quality assurance process are detailed documentation, timely resolution of problems, regular reporting, and routine independent audits.     

USE OF A HYDROLOGIC MODEL IN A BASIN-WIDE WATER ALLOCATION PROCEEDING1

ABSTRACT: The Montana Department of Natural Resources and Conservation developed a hydrologic model to help analyze the effects of allocating water for consumptive and instream uses in the upper Missouri River basin of Montana. The model, a PC-based FORTRAN program, uses a mass-balance approach to compute monthly streamflows, reservoir operations, hydropower production, and irrigation and municipal water uses throughout the 54,000 square mile basin for a 59-year base period. Simulation results are presented as monthly mean and percentile-exceedence values. The model was run for baseline conditions and six hypothetical water-allocation alternatives. Results were used by staff resource area specialists to assess potential impacts to water quantity and distribution, water rights, water quality, stream channel form, fisheries, wildlife, recreation, hydropower production, and economics. These analyses were presented to the public and the decision-making board in an environmental impact statement (EIS). Though, in many instances, the model did not allow for detailed, site-specific analyses, the model was an important tool and its simulation results formed the hydrologic basis for the EIS.     

NPS MODEL PARAMETER UNCERTAINTY ANALYSIS FOR AN OFF-STREAM RESERVOIR1

ABSTRACT: Parameter uncertainties exert a significant effect on nonpoint source pollution (NPS) modeling results. A decision made on the basis of such results may thereby be inappropriate. In this work, the parameter uncertainty is analyzed to explore an improved modeling procedure. Drainage patterns generated from digital elevation data and rainfall are the major parameters examined. A case study for the watershed of the Posan off-stream reservoir is implemented. A significant spatial variation of NPS distribution simulated with a drainage pattern generated from varied methods is observed. The effects of rainfall randomness on the spatial loading distribution are assessed and computed based on a Monte Carlo simulation. The proposed procedure is capable of improving the quality of modeling results and the decision for an appropriate control strategy.     

ECONOMIC AND WATER QUALITY EFFECTS OF VARIABLE AND UNIFORM APPLICATION OF NITROGEN1

ABSTRACT: Nitrogen (N) fertilizer rates for achieving optimum crop yields often vary within a field due to spatial variability in soil moisture and nitrogen content and other crop growth factors. When there is substantial within-field variability in these factors, uniform application of N (UAN) may not be economically efficient in terms of maximizing net return because N is likely to be over-applied in some areas and under-applied in other areas of the field. In addition, over-application can adversely affect water quality. A sample of fields in a Midwestern agricultural watershed is used to test for statistically significant differences in N application rates, crop yields, surface and ground water quality and net returns between UAN and variable application of N (VAN) for four cropping systems. Profitability and water quality benefits of VAN are sensitive to the distribution of soil types within a field. Water quality effects and profitability of UAN and VAN vary with cropping systems. VAN is not uniformly superior to UAN in terms of increasing net returns and improving water quality for the farming systems and watershed evaluated in this study.     

QUANTIFYING MODEL OUTPUT UNCERTAINTY DUE TO SPATIAL VARIABILITY OF RAINFALL1

Traditionally in the application of hydrologic/water quality (H/WQ) models, rainfall is assumed to be spatially homogeneous and is considered not to contribute to output uncertainty. The objective of this study was to assess the uncertainty induced in model outputs solely due to rainfall spatial variability. The study was conducted using the AGNPS model and the rainfall pattern captured by a network of 17 rain gauges. For each rainfall event, the model was run using the rainfall captured by each rain gauge, one at a time, under the assumption of rainfall spatial homogeneity. A large uncertainty in the modeled outputs resulted from the rainfall spatial variability. The uncertainty in the modeled outputs exceeded the input rainfall uncertainty. Results of this study indicate that spatial variability of rainfall should be captured and used in H/WQ models in order to accurately assess the release and transport of pollutants. A large uncertainty in the model outputs can be expected if this rainfall property is not taken into account.     

MODEL ACCURACY IN SNOWMELT-RUNOFF FORECASTS EXTENDING FROM 1 TO 20 DAYS1

ABSTRACT: This paper examines the performance of snowmelt-runoff models in conditions approximating real-time forecast situations. These tests are one part of an intercomparison of models recently conducted by the World Meteorological Organization (WMO). Daily runoff from the Canadian snowmelt basin Illecille. waet (1155 km², 509–3150 m a.s.l.) was forecast for 1 to 20 days ahead. The performance of models was better than in a previous WMO project, which dealt with runoff simulations from historical data, for the following reasons: (1) conditions for models were more favorable than a real-time forecast situation because measured input data and not meteorological forecast inputs were distributed to the modelers; (2) the selected test basin was relatively easy to handle and familiar from the previous WMO project; and (3) all kinds of updating were allowed so that some models even improved their accuracy towards longer forecast times. Based on this experience, a more realistic follow-up project can be imagined which would include temperature forecasts and quantitative precipitation forecasts instead of measured data.     

USE OF FIRST-ORDER UNCERTAINTY ANALYSIS TO OPTIMIZE SUCCESSFUL STREAM WATER QUALITY SIMULATION1

ABSTRACT: A first-order uncertainty technique is developed to quantify the relationship between field data collection and a modeling exercise involving both calibration and subsequent verification. A simple statistic (LTOTAL) is used to quantify the total likelihood (probability) of successfully calibrating and verifying the model. Results from the first-order technique are compared with those from a traditional Monte Carlo simulation approach using a simple Streeter-Phelps dissolved oxygen model. The largest single difference is caused by the filtering or removal of unrealistic outcomes within the Monte Carlo framework. The amount of bias inherent in the first-order approach is also a function of the magnitude of input variability and sampling location. The minimum bias of the first-order technique is approximately 20 percent for a case involving relatively large uncertainties. However the bias is well behaved (consistent) so as to allow for correct decision making regarding the relative efficacy of various sampling strategies. The utility of the first-order technique is demonstrated by linking data collection costs with modeling performance. For a simple and inexpensive project, a wise and informed selection resulted in an LTOTAL value of 86 percent, while an uninformed selection could result in an LTOTAL value of only 55 percent.     

AN ANALYSIS OF SEASONAL FECAL COLIFORM LEVELS IN THE TCHEFUNCTE RWER1

ABSTRACT: A model for estimating seasonal fecal coliform concentrations in the Tchefuncte River as a function of river discharge was developed. Data on fecal coliform concentration were obtained from the Louisiana Department of Health and Hospitals and were available for a period of 15 years (1975 through 1992) from three locations. Stream flow data were obtained from a gaging station of the U. S. Geological Survey at Folsom, Louisiana. These data were available for 49 years (1943 through 1991). The climate of the area is characterized by different precipitation/runoff mechanisms for the summer and winter seasons. The division for seasons used in this analysis was May through October (summer season), and November through April (winter season). Because of the combined effects of climatic mechanisms causing precipitation and the seasonal variation of evapotranspiration, runoff is greater in the winter season resulting in higher fecal coliform counts in the Tchefuncte River. Statistical analysis revealed a statistically significant relationship between fecal coliform concentration and discharge for each season, at each of three sites on the Tchefuncte River.