DSM2 Qual



Water Quality

The distribution of water quality variables in space and time is computed by solving the one-dimensional advection-dispersion equation in which non-conservative constituent relationships are considered to be governed, in general, by first order rates (see equations on page 3-5). The processes of chemical and biochemical transformations, including interaction among various parameters as represented in the model are shown in Figure 3.1 at the end of this chapter. These constituents include dissolved oxygen, carbonaceous BOD, phytoplankton, organic nitrogen, ammonia nitrogen, nitrite nitrogen, nitrate nitrogen, organic phosphorus, dissolved phosphorus, TDS, and temperature. The conceptual and functional descriptions of the constituent reactions are based generally on QUAL2E (Brown and Barnwell 1987); although in certain instances they were updated based on the work of Bowie et al., (1985). Mass balance equations are written for all quality constituents in each parcel of water (see equations on page 3-5). The reader is referred to Jobson and Scoellhamer (1987) for a description of the Lagrangian formulation which provides the basic framework for DSM2-Qual.

In applying the water quality model, changes in concentration due to advection and dispersion, including changes due to tributaries or agricultural drainage are first computed. Next, concentrations of each constituent in each parcel of water are updated, accounting for decay, growth, and biochemical transformations. New subroutines developed for modeling non-conservative constituents are structured in modular form to facilitate extension for simulation of additional constituents (in the case that such needs arise in the future). Subroutine KINETICS updates constituent concentrations at each time step. A single or any combination of the eleven water quality variables can be modeled to suit the needs of the user. KINETICS is called by the parcel tracking subroutine of DSM2-QUAL for every parcel at each time step. The model has also been extended to simulate kinetic interactions in reservoirs (extended open water bodies encountered in the Delta).

Subroutine CALSCSK builds a source/sink matrix within KINETICS for each non-conservative constituent simulated. For simulation of temperature, a subroutine that computes net transfer of energy at the air-water interface has been adapted from the QUAL2E model with some modification. Required meteorology data (obtained preferably at hourly intervals) include dry bulb and wet bulb atmospheric temperatures, wind speed, atmospheric pressure, and cloudiness.

Physical, chemical, and biological rate coefficients required for KINETICS are read as input. Some of these coefficients are constant throughout the system; some vary by location; and most are temperature-dependent. A list of these coefficients and sample values is provided in chapter 5.

The numerical scheme for updating kinetic interactions was developed considering properties of Lagrangian box models that are most accurate when time steps are small enough to define the dominant temporal variations in flow and concentration. A relatively simple scheme that takes advantage of small time steps­­the Modified Euler method­­is used to update concentrations. Concentration updating is done at least once in every time step, and more often if the parcel in question has passed a grid point before the current time step is fully accounted for. In the latter case, the reaction time step will be the increment of time remaining to be accounted for­­less than the simulation time step (typically 15 minutes). Consequently, reaction time steps remain small, so the Modified Euler scheme for concentration updating is appropriate. Since changes in concentration of any constituent affect the other constituents, tests are included in DSM2-Qual to check whether corrections to constituent concentrations are necessary.

The ability of the model to simulate the dissolved oxygen sag on a reach of the San Joaquin River near Stockton was recently demonstrated. DSM2-Qual was capable of capturing diurnal variations of important constituents such as dissolved oxygen, phytoplankton, temperature, and nutrients under the unsteady conditions of the estuary. Variations were realistic, although lack of a large temporal variation in observed data was somewhat of an impediment to testing the model's full capacity to predict field conditions. Tests of the model's capability to distinguish between alternatives in terms of incremental changes in water quality were encouraging (Rajbhandari 1995). The model has great potential for use as a practical tool for analysis of the impacts of water management alternatives.

To enhance the predictive capability of the model, sensitivity analysis should be performed to determine the relative influence of rate coefficients on model response. Calibrated values of the rate coefficients which are most sensitive should be refined. Also, subject to a consistent expansion of the database, future extensions in the model to add additional variables (such as zooplankton) are likely to result in improvement in model performance. Extension of model to represent sediment transport capability should also be investigated such that a dynamic interaction of sediments with simulated constituents is possible. Other uses of the model would be in providing the spatial and temporal distributions of water quality variables for the Particle Tracking Model, so that aquatic species can be more accurately modeled.



Bowie, G. L., Mills, W. B., Porcella, D. B., Campbell, C. L., Pagenkopt, J. R., Rupp, G. L., Johnson, K. M., Chan, P. W. H., and Gherini, S. A. (1985). Rates, Constants and Kinetics Formulations in Surface Water Quality Modeling. 2nd Ed., US EPA, Athens, Georgia, EPA 600/3-85/040.

Brown, L. C., and Barnwell, T. O. (1987). The Enhanced Stream Water Quality Models QUAL2E and QUAL2E-UNCAS: Documentation and Users Manual. US EPA, Athens, Georgia, EPA 600/3-87/007.

Jobson, H. E., and Schoellhamer, D. H. (1987). Users Manual for a Branched Lagrangian Transport Model. U.S. Geological Survey, Water Resources Investigation Report 87-4163.

O'Connor, D. J. and Dobbins, W. E. (1956). Mechanism of Reaeration in Natural Streams.
J. Sanitary Engrg. Div., ASCE, 82(6), 1-30.

Orlob, G. T. and N. Marjanovic (1989) Heat Exchange. Ch. 5 in Mathematical Submodels in Water Quality Systems, ed. S.E. Jorgensen and M.J. Gromiec, Elsevier Pub.

Rajbhandari, H. L. (1995). Dynamic Simulation of Water Quality in Surface Water Systems Utilizing a Lagrangian Reference Frame. PhD Dissertation, Univ. of California, Davis, Calif.

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