| Note copyright and disclaimer restrictions. | © Wm James 1999-2002  |   Questions?  |  Updated 02/01/28 |
| Cite: "James, Wm. (2000). 05-661,05-662 Web site. U. of Guelph, Sch. of Eng'rg. www.eos.uoguelph.ca/ webfiles/james"  | 

05-662 Water pollution control planning (for UCT students, CIV530Z  is a programme of individual study on a specialized topic - examination by report/s and possibly an oral) is a graduate engineering course, comprising the six even-numbered modules below: 2. philosophy underlying public water pollution; 4. methods of developing area-wide pollution control plans and sustainable use plans in Ontario and elsewhere; 6. introduction to BMPs and the SLAMM model; 8.  introduction to the WASP model; 10. Urban litter in drainage systems;  12. examination of quantitative and non-quantitative information in the context of planning. No field trips are planned for Jan-Apr 2000. More info is provided in module 0.   

Current modules in this website are for January to April 2002.   

The following is the previous year's (2000) version of this module. It will be deleted later.

module 8

WASP EUTRO5-submodel - structure and optional sensitivity analysis

(adapted by WJ from an original module by Manfred Ostrowski)

contents

WASP

Introduction
How to access WASP
Chapter 1 of manual A 
Chapter 1 of manual B
Further reading
Test file EUTEST.INP
Assignment A8

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Introduction

Pedagogic note: Learning objectives for this module include exploring the basic uncertainty in WASP simulation. In module 8 you will learn about WASP5 and ooptionally how to apply the Submodel EUTRO only, using a single test data file, named EUTEST.INP. This test data file is a modified version of the test file RIVER.INP distributed with the downloaded package. In this module WJ has reused a problem supplied by Manfred Ostrowski, and for this web page, cut and paste material originally written by Ambrose, Wool and Martin for the WASP documentation. You are required to report on the structure and optionally the sensitivity of WASP. Sensitivity, calibration and error analysis (SCEA) is an important part of modelling. SCEA is not covered in detail on this page. Click here to link to an unfinished, preliminary, draft booklet on SCEA for SWMM modelling. You are required to summarize the main points of your potential interest in this topic, and tie your discussion to potential applications to problems in your area.

Source: THE WATER QUALITY ANALYSIS SIMULATION PROGRAM, WASP5.Version 5.00, September 20, 1993,  by Robert B. Ambrose, Jr., Tim A. Wool, James L. Martin, Environmental Research Laboratory, Athens, Georgia 30605. PART A: MODEL DOCUMENTATION; PART B: THE WASP5 INPUT DATASET.  

Introduction continues: 

Summarising the introductory documentation, WASP5/DYNHYD5 is a US EPA generalized modeling framework that simulates contaminant fate in surface waters. Based on the flexible compartment modeling approach, WASP can be applied in one, two, or three dimensions. WASP5 is designed to permit easy substitution of user-written routines into the program structure. Problems that have been studied include biochemical oxygen demand, dissolved oxygen dynamics, nutrients, bacterial contamination and toxic chemical movement. The DYNHYD5 model is a simple hydrodynamic model that simulates variable tidal cycles, wind, and unsteady inflows. WASP produces an output file that can be linked to supply the flows and volumes to the water quality model. WASP includes the source code, executable version, user's guide, and technical support. The WASP package consists of three submodels (DYNHYD, TOXI5 and EUTRO5). WASP is designed to permit easy substitution of user-written routines into the program structure. Problems that have been studied using the WASP framework include biochemical oxygen demand and dissolved oxygen dynamics, nutrients and eutrophication, bacterial contamination, and organic chemical and heavy metal contamination.

Two WASP models are provided: the toxics WASP model, TOXI, combines a kinetic structure adapted from EXAMS2 (Burns and Cline, 1985) with the WASP transport structure and simple sediment balance algorithms to predict dissolved and sorbed chemical concentrations in the bed and overlying waters. The dissolved oxygen/ eutrophication WASP model EUTRO combines a kinetic structure adapted from the Potomac Eutrophication Model (Thomann and Fitzpatrick, 1982) with the WASP transport structure to predict DO and phytoplankton dynamics affected by nutrients and organic material.

WASP input and output linkages also have been provided to other stand-alone models. Flows and volumes predicted by the link-node hydrodynamic model DYNHYD can be read and used by WASP. Loading files from PRZM and HSPF can be reformatted and read by WASP. Toxicant concentrations predicted by TOXI can be read and used by both the WASP Food Chain Model and the fish bioaccumulation model FGETS.

A body of water is represented in WASP as a series of computational elements or segments. Environmental properties and chemical concentrations are modelled as spatially constant within segments. Segment volumes and type (surface water, subsurface water, surface benthic, subsurface benthic) must be specified, along with hydraulic coefficients for riverine networks.

Structurally, the WASP program includes six mechanisms for describing transport. These 'transport fields' consist of advection and dispersion in the water column; advection and dispersion in the pore water; settling, re-suspension, and sedimentation of up to three classes of solids; and evaporation or precipitation. To describe advection within WASP, each inflow or circulation pattern requires specification of the fraction routed through relevant water column segments and the time history of the corresponding flow. Dispersion requires specification of cross-sectional areas between model segments, characteristic mixing lengths, and the time history of the corresponding dispersion coefficient. For each state variable (termed 'system' In WASP), the user must specify loads, boundary concentrations, and initial concentrations. The dissolved fractions of each variable also must be specified for each segment. Only dissolved concentrations are transported by pore water and only particulate concentrations are transported by solids.

Each variable is advected and dispersed among water segments, and exchanged with surficial benthic segments by diffusive mixing. Sorbed or particulate fractions may settle through water column segments and deposit to or erode from surficial benthic segments. Within the bed, dissolved variables may migrate downward or upward through percolation and pore water diffusion. Sorbed variables may migrate downward or upward through net sedimentation or erosion.

To access USEPA's WASP programs and manuals, click here.

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----start of chap 1 in manual A

INTRODUCTION TO THE WASP5 MODEL

The Water Quality Analysis Simulation Program--5 (WASP5), an enhancement of the original WASP (Di Toro et al., 1983; Connolly and Winfield, 1984; Ambrose, R.B. et al., 1988). This model helps users interpret and predict water quality responses to natural phenomena and man-made pollution for various pollution management decisions. WASP5 is a dynamic compartment modeling program for aquatic systems, including both the water column and the underlying benthos. The time-varying processes of advection, dispersion, point and diffuse mass loading, and boundary exchange are represented in the basic program.

Water quality processes are represented in special kinetic subroutines that are either chosen from a library or written by the user. WASP is structured to permit easy substitution of kinetic subroutines into the overall package to form problem-specific models. WASP5 comes with two such models -- TOXI5 for toxicants and EUTRO5 for conventional water quality. Earlier versions of WASP have been used to examine eutrophication and PCB pollution of the Great Lakes (Thomann, 1975; Thomann et al., 1976; Thomann et al, 1979; Di Toro and Connolly, 1980), eutrophication of the Potomac Estuary (Thomann and Fitzpatrick, 1982), kepone pollution of the James River Estuary (O'Connor et al., 1983), volatile organic pollution of the Delaware Estuary (Ambrose, 1987), and heavy metal pollution of the Deep River, North Carolina (JRB, 1984). In addition to these, numerous applications are listed in Di Toro et al., 1983.

The flexibility afforded by WASP is unique. WASP5 permits the modeler to structure one, two, and three dimensional models; allows the specification of time-variable exchange coefficients, advective flows, waste loads and water quality boundary conditions; and permits tailored structuring of the kinetic processes, all within the larger modeling framework without having to write or rewrite large sections of computer code. The two operational WASP5 models, TOXI5 and EUTRO5, are reasonably general. In addition, users may develop new kinetic or reactive structures. This, however requires an additional measure of judgment, insight, and programming experience on the part of the modeler. The kinetic subroutine in WASP (denoted "WASPB"), is kept as a separate section of code, with its own subroutines if desired.

1.1 OVERVIEW OF THE WASP5 MODELING SYSTEM

 

 

 

 

 

 

 

 

 

 

 

The WASP5 system consists of two stand-alone computer programs, DYNHYD5 and WASP5, that can be run in conjunction or separately (1). The hydrodynamics program, DYNHYD5, simulates the movement of water while the water quality program, WASP5, simulates the movement and interaction of pollutants within the water. While DYNHYD5 is delivered with WASP5, other hydrodynamic programs have also been linked with WASP. RIVMOD handles unsteady flow in one-dimensional rivers, while SED3D handles unsteady, three-dimensional flow in lakes and estuaries (contact CEAM for availability).

WASP5 is supplied with two kinetic sub-models to simulate two of the major classes of water quality problems: conventional pollution (involving dissolved oxygen, biochemical oxygen demand, nutrients and eutrophication) and toxic pollution (involving organic chemicals, metals, and sediment). The linkage of either sub-model with the WASP5 program gives the models EUTRO5 and TOXI5, respectively. This is illustrated in 1 with blocks to be substituted into the incomplete WASP5 model. The tracer block can be a dummy sub-model for substances with no kinetic interactions. In most instances, TOXI5 is used for tracers by specifying no decay.

The basic principle of both the hydrodynamics and water-quality program is the conservation of mass. The water volume and water-quality constituent masses being studied are tracked and accounted for over time and space using a series of mass balancing equations. The hydrodynamics program also conserves momentum, or energy, throughout time and space.

1.2 THE BASIC WATER QUALITY MODEL

WASP5 is a dynamic compartment model that can be used to analyze a variety of water quality problems in such diverse water bodies as ponds, streams, lakes, reservoirs, rivers, estuaries, and coastal waters. This section presents an overview of the basic water quality model. Subsequent chapters detail the transport and transformation processes in WASP5 for various water quality constituents.

The equations solved by WASP5 are based on the key principle of the conservation of mass. This principle requires that the mass of each water quality constituent being investigated must be accounted for in one way or another. WASP5 traces each water quality constituent from the point of spatial and temporal input to its final point of export, conserving mass in space and time. To perform these mass balance computations, the user must supply WASP5 with input data defining seven important characteristics:

• simulation and output control
• model segmentation
• advective and dispersive transport
• boundary concentrations
• point and diffuse source waste loads
• kinetic parameters, constants, and time functions
• initial concentrations

These input data, together with the general WASP5 mass balance equations and the specific chemical kinetics equations, uniquely define a special set of water quality equations. These are numerically integrated by WASP5 as the simulation proceeds in time. At user-specified print intervals, WASP5 saves the values of all display variables for subsequent retrieval by the post-processor programs W4DSPLY and W4PLOT. These programs allow the user to interactively produce graphs and tables of variables of all display variables.

1.3 THE GENERAL MASS BALANCE EQUATION

 

 

 

 

 

 

A mass balance equation for dissolved constituents in a body of water must account for all the material entering and leaving through direct and diffuse loading; advective and dispersive transport; and physical, chemical, and biological transformation. Consider the coordinate system shown in 2, where the x- and y-coordinates are in the horizontal plane, and the z-coordinate is in the vertical plane. The mass balance equation around an infinitesimally small fluid volume is:

 

 

 

 

where:

• C = concentration of the water quality constituent, mg/L or g/m³
• t = time, days
• U_x,U_y,U_z = longitudinal, lateral, and vertical advective velocities, m/day
• E_x,E_y,E_z = longitudinal, lateral, and vertical diffusion coefficients, m²/day
• S_L = direct and diffuse loading rate, g/m³-day
• S_B = boundary loading rate (including upstream, downstream, benthic, and atmospheric), g/m³-day
• S_K = total kinetic transformation rate; positive is source, negative is sink, g/m³-day

By expanding the infinitesimally small control volumes into larger adjoining "segments," and by specifying proper transport, loading, and transformation parameters, WASP implements a finite-difference form of equation 1. For brevity and clarity, however, the derivation of the finite-difference form of the mass balance equation will be for a one-dimensional reach. Assuming vertical and lateral homogeneity, we can integrate equation 1 over y and z to obtain

 

where:

A = cross-sectional area, m²

This equation represents the three major classes of water quality processes -- transport (term 1), loading (term 2), and transformation (term 3). The finite-difference form is derived in Appendix E. The model network and the major processes are discussed in the following sections.

1.4 THE MODEL NETWORK

 

 

 

 

 

 

 

 

 

 

The model network is a set of expanded control volumes, or "segments," that together represent the physical configuration of the water body. As 3 illustrates, the network may subdivide the water body laterally and vertically as well as longitudinally. Benthic segments can be included along with water column segments. If the water quality model is being linked to the hydrodynamic model, then water column segments must correspond to the hydrodynamic junctions. Concentrations of water quality constituents are calculated within each segment. Transport rates of water quality constituents are calculated across the interface of adjoining segments.

Segments in WASP may be one of four types, as specified by the input variable ITYPE. A value of 1 indicates the epilimnion (surface water), 2 indicates hypolimnion layers (subsurface), 3 indicates an upper benthic layer, and 4 indicates lower benthic layers. The segment type plays an important role in bed sedimentation and in certain transformation processes. The user should be careful to align segments properly. The segment immediately below each segment is specified by the input variable IBOTSG. This alignment is important when light needs to be passed from one segment to the next in the water column, or when material is buried or eroded in the bed.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Segment volumes and the simulation time step are directly related. As one increases or decreases, the other must do the same to insure stability and numerical accuracy. Segment size can vary dramatically, as illustrated in 4. Characteristic sizes are dictated more by the spatial and temporal scale of the problem being analyzed than by the characteristics of the water body or the pollutant per se. For example, analyzing a problem involving the upstream tidal migration of a pollutant into a water supply might require a time step of minutes to an hour. By contrast, analyzing a problem involving the total residence time of that pollutant in the same water body could allow a time step of hours to a day. In 4, the first network was used to study the general eutrophic status of Lake Ontario. The second network was used to investigate the lake-wide spatial and seasonal variations in eutrophication. The third network was used to predict changes in near-shore eutrophication of Rochester Embayment resulting from specific pollution control plans.

 

 

 

 

 

 

As part of the problem definition, the user must determine how much of the water quality frequency distribution must be predicted. For example, a daily-average dissolved oxygen concentration of 5 mg/L would not sufficiently protect fish if fluctuations result in concentrations less than 2 mg/L for 10% of the time. Predicting extreme concentration values is generally more difficult than predicting average values. 5 illustrates typical frequency distributions predicted by three model time scales and a typical distribution observed by rather thorough sampling as they would be plotted on probability paper. The straight lines imply normal distributions. Reducing the model time step (and consequently segment size) allows better simulation of the frequency distribution. This increase in predictive ability, however, also entails an increase in the resolution of the input data.

Once the nature of the problem has been determined, then the temporal variability of the water body and input loadings must be considered. Generally, the model time step must be somewhat less than the period of variation of the important driving variables. In some cases, this restriction can be relaxed by averaging the input over its period of variation. For example, phytoplankton growth is driven by sunlight, which varies diurnally. Most eutrophication models, however, average the light input over a day, allowing time steps on the order of a day.

Care must be taken so that important non-linear interactions do not get averaged out. When two or more important driving variables have a similar period of variation, then averaging may not be possible. One example is the seasonal variability of light, temperature, nutrient input, and transport in lakes subject to eutrophication. Another example involves discontinuous batch discharges. Such an input into a large lake might safely be averaged over a day or week, because large scale transport variations are relatively infrequent. The same batch input into a tidal estuary cannot safely be averaged, however, because of the semi-diurnal or diurnal tidal variations. A third example is salinity intrusion in estuaries. Tidal variations in flow, volume, and dispersion can interact so that accurate long-term predictions require explicit simulation at time steps on the order of hours.

Once the temporal variability has been determined, then the spatial variability of the water body must be considered. Generally, the important spatial characteristics must be homogeneous within a segment. In some cases, this restriction can be relaxed by judicious averaging over width, depth, and/or length. For example, depth governs the impact of reaeration and sediment oxygen demand in a column of water. Nevertheless, averaging the depth across a river would generally be acceptable in a conventional waste load allocation, whereas averaging the depth across a lake would not generally be acceptable. Other important spatial characteristics to consider (depending upon the problem being analyzed) include temperature, light penetration, velocity, pH, benthic characteristics or fluxes, and sediment concentrations.

The expected spatial variability of the water quality concentrations also affects the segment sizes. The user must determine how much averaging of the concentration gradients is acceptable. Because water quality conditions change rapidly near a loading point and stabilize downstream, studying the effects on a beach a quarter-mile downstream of a discharge requires smaller segments than studying the effects on a beach several miles away.

A final, general guideline may be helpful in obtaining accurate simulations: water column volumes should be roughly the same. If flows vary significantly downstream, then segment volumes should increase proportionately. The user should first choose the proper segment volume and time step in the critical reaches of the water body (V_c, ?t_c), then scale upstream and downstream segments accordingly:

Of course, actual volumes specified must be adjusted to best represent the actual spatial variability, as discussed above. This guideline will allow larger time steps and result in greater numerical accuracy over the entire model network, as explained in the section on "Simulation Parameters" in Chapter 2.

1.5 THE MODEL TRANSPORT SCHEME

Transport includes advection and dispersion of water quality constituents. Advection and dispersion in WASP are each divided into six distinct types, or "fields." The first transport field involves advective flow and dispersive mixing in the water column. Advective flow carries water quality constituents "downstream" with the water and accounts for instream dilution. Dispersion causes further mixing and dilution between regions of high concentrations and regions of low concentrations.

The second transport field specifies the movement of pore water in the sediment bed. Dissolved water quality constituents are carried through the bed by pore water flow and are exchanged between the bed and the water column by pore water diffusion.

The third, fourth, and fifth transport fields specify the transport of particulate pollutants by the settling, resuspension, and sedimentation of solids. Water quality constituents sorbed onto solid particles are transported between the water column and the sediment bed. The three solids fields can be defined by the user as size fractions, such as sand, silt, and clay, or as inorganic, phytoplankton, and organic solids.

The sixth transport field represents evaporation or precipitation from or to surface water segments.

Most transport data, such as flows or settling velocities, must be specified by the user in a WASP input dataset. For water column flow, however, the user may "link" WASP with a hydrodynamics model. If this option is specified, during the simulation WASP will read the contents of a hydrodynamic file for unsteady flows, volumes, depths, and velocities.

 1.6 APPLICATION OF THE MODEL

The first step in applying the model is analyzing the problem to be solved. What questions are being asked? How can a simulation model be used to address these questions? A water quality model can do three basic tasks-- describe present water quality conditions, provide generic predictions, and provide site-specific predictions. The first, descriptive task is to extend in some way a limited site-specific data base. Because monitoring is expensive, data seldom give the spatial and temporal resolution needed to fully characterize a water body. A simulation model can be used to interpolate between observed data, locating, for example, the dissolved oxygen sag point in a river or the maximum salinity intrusion in an estuary. Of course such a model can be used to guide future monitoring efforts. Descriptive models also can be used to infer the important processes controlling present water quality. This information can be used to guide not only monitoring efforts, but also model development efforts.

Providing generic predictions is a second type of modeling task. Site-specific data may not be needed if the goal is to predict the types of water bodies at risk from a new chemical. A crude set of data may be adequate to screen a list of chemicals for potential risk to a particular water body. Generic predictions may sufficiently address the management problem to be solved, or they may be a preliminary step in detailed site-specific analyses.

Providing site-specific predictions is the most stringent modeling task. Calibration to a good set of monitoring data is definitely needed to provide credible predictions. Because predictions often attempt to extrapolate beyond the present data base, however, the model also must have sufficient process integrity. Examples of this type of application include waste load allocation to protect water quality standards and feasibility analysis for remedial actions, such as tertiary treatment, phosphate bans, or agricultural best-management practices.

Analysis of the problem should dictate the spatial and temporal scales for the modeling analysis. Division of the water body into appropriately sized segments was discussed in Section "Model Network." The user must try to extend the network upstream and downstream beyond the influence of the waste loads being studied. If this is not possible, the user should extend the network far enough so that errors in specifying future boundary concentrations do not propogate into the reaches being studied.

The user also should consider aligning the network so that sampling stations and points of interest (such as water withdrawals) fall near the center of a segment. Point source waste loads in streams and rivers with unidirectional flow should be located near the upper end of a segment. In estuaries and other water bodies with oscillating flow, waste loads are best centered within segments. If flows are to be input from DYNHYD5, then a WASP4 segment must coincide with each hydrodynamic junction. Benthic segments, which are not present in the hydrodynamic network, may nevertheless be included in the WASP5 network. WASP5 segment numbering does not have to be the same as DYNHYD5 junction numbering. Segments stacked vertically do not have to be numbered consecutively from surface water segments down.

Once the network is set up, the model study will proceed through four general steps involving, in some manner, hydrodynamics, mass transport, water quality transformations, and environmental toxicology. The first step addresses the question of where the water goes. This can be answered by a combination of gaging, special studies, and hydrodynamic modeling. Flow data can be interpolated or extrapolated using the principle of continuity. Very simple flow routing models can be used; very complicated multi-dimensional hydrodynamic models can also be used with proper averaging over time and space. At present, the most compatible hydrodynamic model is DYNHYD5.

The second step answers the question of where the material in the water is transported. This can be answered by a combination of tracer studies and model calibration. Dye and salinity are often used as tracers.

The third step answers the question of how the material in the water and sediment is transformed and what its fate is. This is the main focus of many studies. Answers depend on a combination of laboratory studies, field monitoring, parameter estimation, calibration, and testing. The net result is sometimes called model validation or verification, which are elusive concepts. The success of this step depends on the skill of the user, who must combine specialized knowledge with common sense and skepticism into a methodical process.

The final step answers the question of how this material is likely to affect anything of interest, such as people, fish, or the ecological balance. Often, predicted concentrations are simply compared with water quality criteria adopted to protect the general aquatic community. Care must be taken to insure that the temporal and spatial scales assumed in developing the criteria are compatible with those predicted by the model. Sometimes principles of physical chemistry or pharmacokinetics are used to predict chemical body burdens and resulting biological effects. The biaccumulation model FGETS (Barber, et al., 1991) and the WASTOX food chain model (Connolly and Thomann, 1985) are good examples of this.

----end of chap 1 in manual A

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---- Chapter 1 of manual B starts 

INTRODUCTION

 1.1 GENERAL CONSIDERATIONS

This section describes the input required to run the WASP5 water quality program. The user should be cautioned about potential changes to the dataset or manual that may accompany version updates of the software. The printed manual may become dated as enhancements are made or errors are identified and corrected. Please download the latest manual accompanying the current version of WASP5.

To arrange the input into a logical format, WASP5 data are divided into 10 groups, A through J:

A - Model Identification and Simulation Control
B - Exchange Coefficients
C - Volumes
D - Flows
E - Boundary Concentrations
F - Waste Loads
G - Environmental Parameters
H - Chemical Constants
I - Time Functions
J - Initial Conditions

The following is a brief explanation of each data group:

DATA GROUP A provides for descriptive model identification and contains simulation control options. The user must specify the number of segments and the number of systems. The user must also specify calculational time steps and print intervals here.

DATA GROUP B contains dispersive exchange information. Dispersion occurs between segments and along a characteristic length. Dispersion coefficients vary with time in a piecewise linear time function.

DATA GROUP C supplies initial segment volume information, and information on the segment type and underlying segment numbers. Hydraulic geometry information can be given to derive segment average depth and velocity as a function of flow. These values are used in reaeration and volatilization calculations only (not in the basic transport calculations.)

DATA GROUP D supplies flow and sediment transport information between segments. Flows may be contained in the WASP input dataset, or may be imported from an external hydrodynamic file. Flows in the WASP5 input dataset vary with time following a piecewise linear time function.

DATA GROUP E supplies concentrations for each system at the boundaries. All system concentrations must be supplied for each boundary. Boundary concentrations vary with time in a piecewise linear time function.

DATA GROUP F defines the waste loads and segments that receive the waste loads for both point and diffuse sources. Point source loads vary with time in a piecewise linear time fuction. Nonpoint source loads vary with time in a daily step function.

DATA GROUP G contains appropriate environmental characteristics of the water body. These parameters are spatially variable, varying with each model segment.

DATA GROUP H contains appropriate chemical characteristics or constants. Constants in WASP remain constant in both time and space.

DATA GROUP I contains appropriate environmental or kinetic time functions.

DATA GROUP J contains initial concentrations for each segment and each system, along with dissolved fractions and the density of solids systems.

The input dataset is a formatted ASCII file. The user must carefully place input data in the appropriate fields, and be sure to right justify integers.

1.2 THE EUTROPHICATION MODEL

EUTRO4 requires the same input format as the basic WASP5 model. This format is explained in detail in the chapters below. This section summarizes the variables needed specifically for EUTRO4.

As described in detail in Chapter 5, the 8 systems for eutrophication modeling are ammonia nitrogen, nitrate nitrogen, inorganic phosphorus, phytoplankton carbon, carbonaceous BOD, dissolved oxygen, organic nitrogen, and organic phosphorus. Table 1 summarizes these systems and their use in six discrete levels of complexity.

The user should note that these discrete levels of complexity are suggestive only. The user may choose to simulate any combination of these variables using any combination of the parameter functions and values described below. In fact, during calibration, the user may choose to simulate only one variable, such as CBOD, while bypassing (and thus holding constant) all other variables.

1.3 THE TOXIC CHEMICAL MODEL

TOXI4 requires the same input format as the basic WASP5 model. This format is explained in detail in the chapters below. This section summarizes the variables needed specifically for TOXI4.

As described in Chapter 7, the 6 systems for toxicant modeling are chemical 1, solids fraction 1, solids fraction 2, solids fraction 3, chemical 2, and chemical 3. Table 2 summarizes these systems and their use in several discrete levels of complexity. These levels of complexity describe possible approaches to simulating solids, equilibrium reactions, and kinetic reactions. They are suggestive only. The user may choose to simulate any combination of these variables using any combination of the parameter functions and values described below.

----end of chap 1 in manual B

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Further reading from the model documentation:

THE WATER QUALITY ANALYSIS SIMULATION PROGRAM, WASP5. Version 5.00, September 20, 1993,  by Robert B. Ambrose, Jr., Tim A. Wool, James L. Martin, Environmental Research Laboratory,Athens, Georgia 30605.

Assigned reading: please read the following:

1.  Chapter 1 in PART B: THE WASP5 INPUT DATASET and 

2.  Chapters 4 and 5 in PART A: MODEL DOCUMENTATION . 

To read the WASP5 manual A (model documentation - 4.78MB) 

• Chaps 0 -3 (front matter, intro, chemical tracer and sediment transport - 658KB): click here. 
• Chap 4 (dissolved oxygen - 252KB): click here.
• Chap 5 (eutrophication - 547KB): click here.
• Chap 6 (simple toxicants - 146KB): click here.
• Chap 7 to end (organic chemicals and all references - 813KB): click here.

To read the rest of WASP5 manual B (input data set - 189KB) 

• Chaps 0 to 8 (front matter, intro and groups A to G - 117KB): click here.
• Chaps 9 to end (H to J and output - 399KB): click here.

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test file EUTEST.INP

MODULE 7 COURSE 611 - EUTRO EXAMPLE - FILE: RIVTEST.INP
BASIC FILE FOR EUTRO SNESITIVITY ANALYSIS START WITH STEADY FLOWS & OPTION 1
NSEG NSYS ICRD MFLG IDMP NSLN INTY ADFC   DD HHMM        A:MODEL OPTIONS
    6    8    0    1     0    0    1  0.0    0 0000    0.00
    1    2    3    4     5    6
    1
       1.0       24.
    2
      1.00        0.       1.00       50.
    1    1    1    1     0    0    1    1
    0    0    +    *     +    *    +    *     +    *    +    *     B:EXCHANGES
    2    0       1.0     +    *    +    *     +    *    +    *     C:VOLUMES
   1.00E05   1.0000
         1          0          1      5.00        0.1      0.43        2.       0.10
         2          0          1      5.00        0.1      0.43        2.       0.10
         3          0          1      5.00        0.1      0.43        2.       0.10
         4          0          1      5.00        0.1      0.43        2.       0.10
         5          0          1      5.00        0.1      0.43        2.       0.10
         6          0          1      5.00        0.1      0.43        2.       0.10
    1    1    +    *     +    *    +    *     +    *    +    *     D: FLOWS
    1       1.0     1.000                    (water column field)
    7
       1.0    0    1        1.0    1    2        1.0    2    3       1.0     3    4
       1.0    4    5        1.0    5    6        1.0    6    0
   26
      5.00        0.       5.00        1.       5.00        2.       5.00        3.
      5.00        4.       5.00        5.       5.00        6.       5.00        7.
      5.00        8.       5.00        9.       5.00       10.       5.00       11.
      5.00       12.       5.00       13.       5.00       14.       5.00       15.
      5.00       16.       5.00       17.       5.00       18.       5.00       19.
      5.00       20.       5.00       21.       5.00       22.       5.00       23.
      5.00       24.       5.00       25.

         2    +    *     +    *    +    *     +    *    +    *     E: BOUNDARIES
      0.00      0.00                                      NH3
    1    2
     10.00        0.      10.00      365.
    6    2
      0.00        0.       0.00      365.
         2
      1.00      1.00                                      NO3
    1    2
      0.00        0.       0.00      365.
    6    2
      0.00        0.       0.00      365.
         2
      1.00      1.00                                      OPO4
    1    2
      0.00        0.       0.00      365.
    6    2
      0.00        0.       0.00      365.
         2
      1.00      1.00                                      CHL a
    1    2
      0.00        0.       0.00      365.
    6    2
      0.00        0.       0.00      365.
         2
      1.00      1.00                                      CBOD
    1    2
      6.00        0.       6.00      365.
    6    2
      4.00        0.       4.00      365.
         2
      1.00      1.00                                      DO
    1    2
      7.00        0.       7.00      365.
    6    2
      7.00        0.       7.00      365.
         2
      1.00      1.00                                      ON
    1    2
      0.00        0.       0.00      365.
    6    2
      0.00        0.       0.00      365.
         2
      1.00      1.00                                      OP
    1    2
      0.00        0.       0.00      365.
    6    2
      0.00        0.       0.00      365.
         0          *    +    *     +    *    (NH3)  *     +    *    F: LOADS
         0                                   (NO3)
         0                                   (PO4)
         0                                   (PHYT)
         1                                   (CBOD)
       1.0       1.0
    1    2
      20.0       0.0       20.0     156.0
         0                                   (DO)
         0                                   (ON)
         0                                   (OP)
         0                                               (NPS LOADS)
         2    +    *     +    *    +    *     +    *    +    *     G: PARAMETERS
TMPSG    3       1.0TMPFN    4        1.0
         1
TMPSG    3       1.0TMPFN    4        1.0
         2
TMPSG    3       1.0TMPFN    4        1.0
         3
TMPSG    3       1.0TMPFN    4        1.0
         4
TMPSG    3       1.0TMPFN    4        1.0
         5
TMPSG    3       1.0TMPFN    4        1.0
         6
TMPSG    3       1.0TMPFN    4        1.0
    +    *    +    *     +    *    +    *     +    *    +    *     H: CONSTANTS
   GLOBALS         0          *          *          *          *
       NH3         0          *          *          *          *
       NO3         0          *          *          *          *
       PO4         0          *          *          *          *
      PHYT         0          *          *          *          *
       BOD         1          *          *          *          *
deoxygent         1
        KD        71       0.20
        DO          1
   oxygent         1
        K2        82       0.00
        ON          0
        OP          0
         1    +    *     +    *    +    *     +    *    +    *     I:TIME FUNCTIONS
TEMP1   26    2
       20.        0.        20.        1.        20.        2.        20.        3.
       20.        4.        20.        5.        20.        6.        20.        7.
       20.        8.        20.        9.        20.       10.        20.       11.
       20.       12.        20.       13.        20.       14.        20.       15.
       20.       16.        20.       17.        20.       18.        20.       19.
       20.       20.        20.       21.        20.       22.        20.       23.
       20.       24.        20.       25.
NH3                                          3   0.0     1.E10
   1:   0.0000        1.0    2:   0.00000       1.0  3:     0.00000  1.0
   4:   0.0000        1.0    5:   0.00000       1.0  6:     0.00000  1.0
NO3                                          3   0.0     1.E10
   1:   0.0000        1.0    2:   0.00000       1.0  3:     0.00000  1.0
   4:   0.0000        1.0    5:   0.00000       1.0  6:     0.00000  1.0
OPO4                                         3   0.0     1.E10
   1:   0.0000        1.0    2:   0.00000       1.0  3:     0.00000  1.0
   4:   0.0000        1.0    5:   0.00000       1.0  6:     0.00000  1.0
CHLA                                         4   0.0     1.E10
   1:   0.0000        1.0    2:   0.00000       1.0  3:     0.00000  1.0
   4:   0.0000        1.0    5:   0.00000       1.0  6:     0.00000  1.0
CBOD                                         3   0.0     1.E10
   1:   0.0000        1.0    2:   0.00000       1.0  3:     0.00000  1.0
   4:   0.0000        1.0    5:   0.00000       1.0  6:     0.00000  1.0
DO                                           3   0.0     1.E10
   1:   0.0000        1.0    2:   0.00000       1.0  3:     0.00000  1.0
   4:   0.0000        1.0    5:   0.00000       1.0  6:     0.00000  1.0
ON                                           3   0.0     1.E10
   1:   0.0000        1.0    2:   0.00000       1.0  3:     0.00000  1.0
   4:   0.0000        1.0    5:   0.00000       1.0  6:     0.00000  1.0
OP                                           3   0.0     1.E10
   1:   0.0000        1.0    2:   0.00000       1.0  3:     0.00000  1.0
   4:   0.0000        1.0    5:   0.00000       1.0  6:     0.00000  1.0

end of test file

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Assignment A8:

1. Carry out the reading assigned in this module. Check through the input datafile to ensure that you understand the processes.  Briefly describe the main points of the model.

2. Describe the system modeled with the package by a graphical schematic.

3. What is the complexity level according to table 1 on page 3 in Manual B?

4. Which parameters are necessary to model that complexity level? (Read Manual A, chapters 4&5)

5. Is it steady state or hydrodynamic simulation?

6. What are the boundary, and initial conditions?

7. What is the simulation period?

Optionally, perform the following analysis

8. Apply EUTEST.INP to the EUTRO5 and confirm that the package is working.Apply the EUTRO5 for complexity levels 1, 2 & 3. Name the parameters to be estimated for each complexity level and indicate plausibility limits for given hydrologic conditions.

9. Then for complexity level 2 only apply a plausible temperature variation during 24 hours (nightly minimum ~8, daily maximum ~28)

10. Propagate a flood wave of your choice (base flow 2 m3/s, peak flow ~ 40 m3/s

11. Apply variable short duration point source load at segment 2 (similar to stormwater overflow event)

12. Develop a 3 dimensional diagram for BOD = f(KD =Parameter 71) and BOD = f(K2= Parameter 82)x-axis horizontal: distance or time, y-axis horizontal: parameter, z-axis vertical: (BOD)

Remember: Sensitivity is the first order derivative of the functions obtained.

13. Do the same for COD.

14. Interpret the results.

Remark: All students should do steps 1 to 7, however, steps 8 - 14 are optional.