Long-Term Dynamic Modeling Approach to Quantifying Attached Algal Growth and Associated Impacts on Dissolved Oxygen in the Lower Truckee River, Nevada

Nutrient loads enter the lower Truckee River of western Nevada, affecting the growth of attached algae (periphyton) which causes depressed nighttime dissolved oxygen (DO) levels. The lower Truckee River is home to the endangered cui-ui and threatened Lahontan cut-throat trout, with DO standards being established to in part protect these species. Hydrodynamics, nutrient concentrations, periphyton biomass, and DO data spanning August 2000–December 2001 were used to calibrate and verify a modified version of the Water Quality Analysis Simulation Program Version 5 (WASP5). Under typical loading conditions the periphyton community is nitrogen limited, however nitrogen loading from an upstream wastewater treatment facility increased greatly during the analysis period due to approved site construction activities (discharge permit excursion) causing the periphyton community to temporarily become phosphorus limited. The developed modeling approach, with limited calibration, was able to accurately track dynamic system responses. Removing the impact of the noted discharge permit excursion resulted in a minimum computed DO value of 4.13?mg/L, occurring at the downstream end of the modeling domain on August 8, 2001. Additionally removing the impact of all nutrient loads from area agriculture resulted in a predicted minimum DO value of 4.54?mg/L, while also shifting its location significantly upstream and its timing to April 26, 2001. Meeting all prescribed DO standards required establishing a minimum in-stream flow value of 1.81?m3/s (64.0?ft3/s) downstream of Derby Dam.     

Modeling Approach to Periphyton and Nutrient Interaction in a Stream

We propose a model of the development of a periphyton community in a stream under the influence of nutrients and light. Coupling the model with a nutrient transport model clarified the longitudinal distribution of both periphyton community and nutrients. The thickness of the periphyton mat, an important factor regulating nutrient exchange between the mat and overflowing water, was determined from water velocity and the periphyton biomass. We compared the results of this study with three observational data sets to overall validate our proposal: (1) a comparison of electrical conductance in two channels with different periphyton biomasses validated the model in the mass exchange between stationary and flowing water zones; (2) a comparison of the temporal variation in periphyton biomass and nutrient concentration in a once-through and a re-circulated water channel, validated the relationships among the periphyton biomass, the nutrient uptake rate, and the nutrient concentrations in the stationary water zone; and (3) a longitudinal distribution of the algal species composition of Stigeoclonium and Chamaesiphon, and the nutrient concentrations of a 140 m reach was reproduced and compared with measured data. The light intensity indirectly controlled the nutrient gradients along the stream by the periphyton biomass in the third application.     

Distributed Sensitivity Analysis of Flood Inundation Model Calibration

Uncertainties in hydrodynamic model calibration and boundary conditions can have a significant influence on flood inundation predictions. Uncertainty analysis involves quantification of these uncertainties and their propagation through to inundation predictions. In this paper the inverse problem of sensitivity analysis is tackled, in order to diagnose the influence that model input variables, together and in combination, have on the uncertainty in the inundation model prediction. Variance-based global sensitivity analysis is applied to simulation of a flood on a reach of the River Thames (United Kingdom) for which a synthetic aperture radar image of the extent of flooding was available for model validation. The sensitivity analysis using the method of Sobol’ quantifies the significant influence of variance in the Manning channel roughness coefficient in raster-based flood inundation model predictions of flood outline and flood depth. The spatial influence of the Manning channel roughness coefficient is analyzed by dividing the channel into subreaches and calculating variance-based sensitivity indices for each subreach. Replicated Latin hypercube sampling is used for sensitivity analysis with correlated input variables. The methodology identifies subreaches of channel that have the most influence on variance in the model predictions, demonstrating how far boundary effects propagate into the model and indicating where further data acquisition and nested higher-resolution model studies should be targeted.     

Integrated Hydrodynamic and Water Quality Modeling System to Support Nutrient Total Maximum Daily Load Development for Wissahickon Creek, Pennsylvania

This paper presents a hydrodynamic and water quality modeling system for Wissahickon Creek, Pa. Past data show that high nutrient levels in Wissahickon Creek were linked to large diurnal fluctuations in oxygen concentration, which combining with the deoxygenation effect of carbonaceous biological oxygen demand (CBOD) causes violations of dissolved oxygen (DO) standards. To obtain quantitative knowledge about the cause of the DO impairment, an integrated modeling system was developed based on a linked environmental fluid dynamics code (EFDC) and water quality simulation program for eutrophication (WASP/EUTRO5) modeling framework. The EFDC was used to simulate hydrodynamic and temperature in the stream, and the resulting flow information were incorporated into the WASP/EUTRO5 to simulate the fate and transport of nutrients, CBOD, algae, and DO. The standard WASP/EUTRO5 model was enhanced to include a periphyton dynamics module and a diurnal DO simulation module to better represent the prototype. The integrated modeling framework was applied to simulate the creek for a low flow period when monitoring data are available, and the results indicate that the model is a reasonable numerical representation of the prototype.     

Optimal Wasteload Allocation Procedure for Achieving Dissolved Oxygen Water Quality Objectives. I: Sensitivity Analysis

A method is presented to compute sensitivities of in-stream dissolved oxygen (DO) with respect to perturbations in the load vector and the reaction coefficients that make up the eutrophication cycle. It is shown that the direct sensitivity method, i.e., the repetitive solution of the direct problem, produces the desired information, however at a large computational cost. The utilization of the adjoint sensitivity method proves to be a much more efficient way to compute these sensitivities as large subsets of the sensitivity information domain can be easily extracted with just a few runs. It is found that for the given problem setup, in-stream DO is most sensitive to ammonia, effluent DO, algae, and carbonaceous biochemical oxygen demand (CBOD) loads. Additionally, the computed sensitivities vary considerably in their general trend over the simulation time. Sensitivities also are computed with respect to the reaction coefficients (26 total) that govern the interdependency of all constituents. Sediment oxygen demand proves to be the coefficient with the highest influence that is three orders of magnitude higher than the next set of coefficients comprised of reaeration, CBOD degradation, nitrification, and denitrification. All other coefficients have a negligible influence on DO concentrations. Computations are carried out using a two-dimensional model formulation applied to a long rectangular channel with varying width and slope and periodic but unsteady flow conditions.     

High-Frequency Diel Dissolved Oxygen Stream Data Modeled for Variable Temperature and Scale

Diel dissolved oxygen (DO) concentrations and temperature were sensed at high-frequency and modeled in an eastern Iowan stream, Clear Creek, in an agricultural setting. The magnitude of the diel changes in DO and temperature were largest at the upstream (headwater) station. Inclusion of temperature change factors increased the accuracy of modeling results and yielded estimates of the reaeration rate constant, primary production rate, and respiration rate. The DO modeling of the high-frequency measurements (15-min intervals) revealed a temperature-driven nonlinear reaeration process that led to increases in nighttime DO concentrations. The DO modeling results from three sensing stations in the watershed revealed decreasing trends in primary productivity, respiration, and the reaeration rate constant with increasing drainage area. Light extinction from suspended solids was the main factor limiting net primary production. As a result, the P/R ratio also decreased with increasing drainage area. High-frequency sensor data and DO modeling revealed the effects of temperature and watershed scale on the primary factors that dictate diel DO dynamics in a stream setting.     

Uncertainty of Weekly Nitrate-Nitrogen Forecasts Using Artificial Neural Networks

Nonpoint source pollution affects the quality of numerous watersheds in the Midwestern United States. The Illinois State Water Survey conducted this study to (1) assess the potential of artificial neural networks (ANNs) in forecasting weekly nitrate-nitrogen (nitrate-N) concentration; and (2) evaluate the uncertainty associated with those forecasts. Three ANN models were applied to predict weekly nitrate-N concentrations in the Sangamon River near Decatur, Illinois, based on past weekly precipitation, air temperature, discharge, and past nitrate-N concentrations. Those ANN models were more accurate than the linear regression models having the same inputs and output. Uncertainty of the ANN models was further expressed through the entropy principle, as defined in the information theory. Using several inputs in an ANN-based forecasting model reduced the uncertainty expressed through the marginal entropy of weekly nitrate-N concentrations. The uncertainty of predictions was expressed as conditional entropy of future nitrate concentrations for given past precipitation, temperature, discharge, and nitrate-N concentration. In general, the uncertainty of predictions decreased with model complexity. Including additional input variables produced more accurate predictions. However, using the previous weekly data (week t?1) did not reduce the uncertainty in the predictions of future nitrate concentrations (week t+1) based on current weekly data (week t).     

Jackson River Modeling: 50‐Year Perspective

The development of water quality models, and also the nature of water quality impairment, is uniquely presented in the point source dissolved oxygen (DO) modeling completed in the Jackson River (Virginia) over the past 50?years. Various water quality modeling studies have been completed in the Jackson River over the years starting with the earliest of modeling frameworks, the Streeter–Phelps equation (1950s and 1960s); progressing to a biochemical oxygen demand–DO model (1970s and 1990s) including diurnal photosynthetic effects (DIURNAL); a Monte Carlo DO analysis using the DIURNAL model (1990s); to the most recent modeling that is currently developing a periphyton model to assess the impact of nutrient loadings on the periphyton community and ultimately DO levels (2000). These early modeling studies were completed by such modeling forefathers as Clarence J. Velz and Donald J. O'Connor, both completing their work at academic institutions (Manhattan College and the University of Michigan) and private consulting firms (Hydroscience and HydroQual, Inc.). Interesting to note is that Earle B. Phelps taught Clarence J. Velz, Donald J. O’Connor’s eventual professor at Manhattan College. Other work completed on the river by early environmental engineers included reaeration studies by Ernest C. Tsivoglou (1966) and the first activated sludge wastewater treatment design for a pulp and paper mill by Wesley Eckenfelder (1950s). The studies investigated: how to improve existing DO conditions in the river; the effects of color reductions on diurnal DO swings; proposed upstream flow regulation effects on water quality and river temperature; and the impact of instream oxygen addition.     

Parameter Sensitivity and Predictive Uncertainty in a New Water Quality Model, Q2

A new dynamic model of water quality, Q2, has recently been developed, capable of simulating large branched river systems. This paper describes the application of a generalized sensitivity analysis (GSA) to Q2 for single reaches of the River Thames in southern England. Focusing on the simulation of dissolved oxygen (DO) (since this may be regarded as a proxy for the overall health of a river); the GSA is used to identify key parameters controlling model behavior and provide a probabilistic procedure for model calibration. It is shown that, in the River Thames at least, it is more important to obtain high quality forcing functions than to obtain improved parameter estimates once approximate values have been estimated. Furthermore, there is a need to ensure reasonable simulation of a range of water quality determinands, since a focus only on DO increases predictive uncertainty in the DO simulations. The Q2 model has been applied here to the River Thames, but it has a broad utility for evaluating other systems in Europe and around the world.     

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.     

Optimal Wasteload Allocation Procedure for Achieving Dissolved Oxygen Water Quality Objectives. II: Optimal Load Control

This paper presents the development of an efficient strategy for achieving in-stream dissolved oxygen (DO) water quality standards (WQSs) via optimized point-load control strategies using the adjoint method. To this end, a least-squares-type objective function is formulated that measures the difference between desired (WQSs) and current DO concentrations at strategically selected monitoring points in the domain. The goal is to minimize the difference between actual DO concentration and the WQS, hence allowing time-variant loadings to utilize the assimilative capacity of the receiving water body at an optimal level. Time-variant discharge rates for a number of discharge locations are considered as control parameters, while different zone-specific critical DO levels are imposed as constraints. The selection of the control is kept flexible and a number of different scenarios are tested. First, only carbonaceous biochemical oxygen demand is used, which allows for a reduction of the number of equations that need to be solved. In the other tests, all constituents are switched on and different variables at each load node are selected as a control by first varying the concentrations individually, and then linking them through control of the volumetric flow rate. Optimization is achieved using a conjugate gradient search method, for which the gradients are computed through the solution of both the direct and adjoint problems. It is shown that the large amount of gradient information (parameter space has a dimension of several thousands) can be computed very efficiently using the adjoint, and that optimized results are achieved after only a few iterations irrespective of the initial guess. Computations are carried out using both two-dimensional model formulation applied to a long rectangular channel with varying width and slope and a model for the upper Potomac River estuary.     

Spillway and Metal Toxicity Influenced Stream Reaeration

In this study, effects of initial dissolved oxygen (DO) deficit values on the formation of DO deficit curves under the influence of inorganic metal compounds (HgCl2, ZnSO4.7H2O) are investigated. DO deficit curves and critical DO deficit values are significantly effected. Smooth and stepped spillways cause increased DO concentrations at the downstream part of the channel. DO concentrations change depending on the flow types, discharge rates, traveling times and channel slope.     

Comparison of the Monod and Droop Methods for Dynamic Water Quality Simulations

The Monod method is widely used to model nutrient limitation and primary productivity in water bodies. It offers a straightforward approach to simulate the main processes governing eutrophication and it allows the proper representation of many aquatic systems. The Monod method is not able to represent the nutrient luxury uptake by algae, which consists of the excess nutrient uptake during times of high nutrient availability in the water column. The Droop method, which is also used to model nutrient limitation and primary productivity, takes into account the luxury uptake of nutrients. Because of the relative complexity of the Droop method, it has not been systematically adopted for the simulation of large stream networks. The Water Quality Analysis Simulation Program (WASP) version 7.1 was updated to include nutrient luxury uptake for periphyton growth. The objective of this paper is to present the new nutrient limitation processes simulated by WASP 7.1 and to compare the performance of the Droop and the Monod methods for a complex stream network where periphyton is the main organism responsible for primary productivity. Two applications of WASP 7.1 with the Droop and Monod methods were developed for the Raritan River Basin in New Jersey. Water quality parameters affecting the transport and fate of nutrients were calibrated based on observed data collected for the Raritan River total maximum daily load. The dissolved oxygen and nutrients simulated with WASP 7.1, obtained with the Droop and Monod methods, were compared at selected monitoring stations under different flows and nutrient availability conditions. The comparison of the WASP 7.1 applications showed the importance of using the Droop method when periphyton was the main organism responsible for primary productivity. The data simulated with the Droop method resulted in good agreement with the observed data for dissolved oxygen, ammonia-nitrogen, nitrate-nitrogen, and dissolved orthophosphate at the selected stations. The Monod method was not able to capture the diel dissolved oxygen variation when nutrients were scarce, and it resulted in unrealistic diel variations of nutrients at times of strong primary productivity at some locations.     

Confidence, uncertainty, and the use of information.

When a person makes predictions about an unknown quantity, a distinction can be made between beliefs about possible values for the quantity and the belief that a given prediction is correct. We use the term uncertainty to refer to the former, and confidence to refer to the latter. Four experiments demonstrated that confidence and uncertainty are affected in different ways by the available information. Confidence increased as the amount of information increased, especially if this variable was manipulated within subjects. Confidence was reduced by increasing the apparent difficulty of the task if manipulated within subjects, but not between subjects. Uncertainty increased with the amount of information (i.e., certainty was reduced), a result that is inconsistent with statistical theory. We proposed that uncertainty is determined by the number of different predictions that can be generated, whereas confidence is influenced by salient factors that people believe affect the accuracy of their predictions. Information is used to suggest possible outcomes in the former case, and to evaluate hypotheses in the latter case. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Density Intrusion and Variation in Dissolved Oxygen Concentrations in a Bay with a Sill at Its Mouth

This paper describes the influence of water outside a bay on water quality within the bay for a typical enclosed bay with a sill at its mouth. The influence of water outside Ohfunato Bay, Japan was expressed in a one-dimensional vertical dissolved oxygen (DO) model as the rate of seawater exchange caused by tides and the density difference between water inside and outside the bay. A nonhydrostatic, three-dimensional model was used to confirm the occurrence of density intrusions. A one-dimensional vertical DO model was used to examine long-term changes in DO concentrations in the bottom layer of the bay. Results indicated that seawater exchange caused by density differences had a significant effect on the formation and disappearance of anoxic water in the bay’s bottom layer.     

Diffusional Mass Transfer at Sediment–Water Interface of Cylindrical Sediment Oxygen Demand Chamber

Diffusional mass transfer of dissolved substances across the sediment–water interface in coastal waters is an important factor for realistic determination of sediment oxygen demand (SOD) and nutrient recycle. The benthic diffusive boundary layer inside a cylindrical chamber commonly deployed for in situ measurements of sediment oxygen demand is studied. In a series of laboratory experiments, the SOD is measured with the chamber operated in both continuous flow and batch modes, and a microelectrode is employed to measure the near bed dissolved oxygen (DO) profile for different chamber flows and sediment types. The dependence of the diffusive boundary layer thickness and the sediment–water mass transfer coefficient on the hydraulic parameters are quantified. Using the derived mass transfer coefficient, it is shown that for a given sediment type, the SOD is a function of the bulk DO concentration and chamber flowrate. The theoretical predictions are validated by both laboratory and field SOD data.     

Calibration and Validation of an Empirical Dissolved Oxygen Model

A common difficulty in stream health assessments is the scarcity of real-time dissolved oxygen (DO) data. Discrete DO measurements, collected at times often imposed by sampling constraints, are difficult to use in assessments because of diurnal variations. An empirical model is developed here to adjust these discrete measurements to a common time-reference value using an extended stochastic harmonic analysis (ESHA) algorithm, which was originally formulated with a fraction of DO saturation model by the authors. The model was calibrated and validated for different stream sites across Minnesota, incorporating effects of different ecoregions and variable drainage areas. Data were normalized to increase the general applicability of the fitted parameters. Model calibration for five long record stations accurately represented observed diurnal variations in DO. The root-mean-square error (RMSE) for predicting hourly DO ranged from 0.53?to?0.80?mg/L and for predicting DO at a standard time ranged from 0.44?to?0.91?mg/L. Estimated model parameters were robust in terms of both spatial and temporal variations. Analytical as well as numerical analyses of parameter uncertainties were performed using sensitivity coefficients. Model validation with independent data for eight different Minnesota streams was performed using three different approaches for estimating parameters. The best approach considered both ecoregional location and watershed size to select representative model parameters. The RMSE for predicting hourly DO and standard DO respectively ranged from 0.53?to?1.65?mg/L and 0.00?to?1.83?mg/L. The developed model is a useful tool for total maximum daily load assessment of aquatic ecosystem health across a range of temporal and spatial scales. It is more elegant and simpler than the application of the ESHA algorithm for the fraction of DO saturation model.     

Modeling a Combined Anaerobic/Anoxic Oxide and Rotating Biological Contactors Process under Dissolved Oxygen Variation by Using an Activated Sludge-Biofilm Hybrid Model

A hybrid model which incorporated a biofilm model into the general dynamic model was developed to predict the effluent quality of a combined activated sludge and biofilm process—Taiwan National Central University Process 1. The system was performed under three different dissolved oxygen (DO) conditions in the oxic tank, including 2.0, 1.0, and 0.5 mg/L. When the DO increased from 0.5 to 2.0 mg/L, the soluble biodegradable substrate (SS) and soluble phosphate (PO4) in the effluent were not significantly influenced. Their removal efficiencies were above 92 and 94%. Ammonia–nitrogen (NH3) removal efficiency increased from 36 to 83% and nitrate–nitrogen (NO3) increased from 1.7 to 2.9 mg/L. In biofilm, when the DO was 2.0 mg/L, the active autotrophic biomass (ZA) fraction was 15.7% (surface) to 12.9% (substratum). But when the DO was 0.5 mg/L, the ZA fraction became lower and the fraction was 6.2% (surface) to 3.5% (substratum). The fraction of active nonpoly-P heterotrophic biomass (ZH) in the biofilm did not vary significantly, the values were about 28–35%. ZI decreased as the DO increased. SS in the biofilm did not vary significantly and was maintained at about 2.0 mg/L. When DO increased, NO3 also increased, NH3 decreased from 13.1 to 1.8 mg/L in biofilm.     

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.     

Uncertainty Assessment of a Water-Quality Model for Ephemeral Rivers Using GLUE Analysis

Every model is, by definition, a simplification of the system under investigation. Although it would be desirable to reduce the gap between the simulated and the observed behaviors of the system to zero, this reduction is generally impossible owing to the unavoidable uncertainties inherent in any modeling procedure. Uncertainty analyses can provide useful insights into the best model approach to be used for obtaining results with a high level of significance and reliability. The evaluation of parameter uncertainties is necessary for calibration and for estimating the impact of these uncertainties on model performance. In this context, the uncertainty of a river water-quality model developed in previous studies is presented. The main goal is to gain insights into the modeling approaches concerning small rivers. Previous works generally focused on modeling the large river while neglecting the small one. Following a model calibration, the model uncertainty has been assessed by means of the generalized likelihood uncertainty estimation (GLUE). The results showed that the biological process related to the biological oxygen demand (BOD) removal influenced mainly by the parameters characterizing deoxygenation and nitrogen removal. On the other hand, the biological processes related to nitrogen removal were influenced not only by the parameters related to the nitrogen removal but also to oxygen concentration. The application of the GLUE methodology shows that the river quality model considered is suitable for simulating the important processes involved. Uncertainty bounds showed different amplitudes with respect to the pollutant species considered. In particular, the oxygen uncertainty bounds were narrower with respect to the other model components suggesting much attention must be paid to both model algorithms and quality data to be gathered. The study confirmed the suitability of the GLUE methodology as a powerful tool as a simplified screening methodology to assess uncertainty.