REGULATED RIVERS: RESEARCH & MANAGEMENT, VOL. 4, 235-247 (1989)

MODELLING WATER QUALITY OF A REREGULATED STREAM BELOW A PEAKING HYDROPOWER DAM

MARC J. ZIMMERMAN AND MARK S. DORTCH Water Quality Modelling Group, Ecosystem Research and Simulation Division, Environmental Laboratory,

U.S. Army Engineer Waterways Experiment Station, P.O. Box 631, Vichburg, M S 39180, U.S.A.

ABSTRACT

This paper describes CE-QUAL-RIV1 , a dynamic, one-dimensional, stream water quality model capable of simulating branched riverine systems with multiple hydraulic control structures, such as weirs, reregulation dams, and navigation locks and dams. We provide examples of potential water quality impacts associated with operations alternatives for a reregulation dam proposed for construction downstream from Buford Dam on the Chattahoochee River near Atlanta, Georgia, in the southeastern United States. Model calibration, confirmation, and application are examined. The model is calibrated for stage, transport, temperature, dissolved oxygen, carbonaceous biochemical oxygen demand, ammonium-N, and nitrate-N. Results indicate that release operations which maintain cool temperatures in summer may cause undesirable decreases in dissolved oxygen and increases in dissolved iron in autumn. Flexibility in release scheduling is recommended to avoid unnecessary problems.

KEY WORDS Water quality modelling Chattahoochee River Reregulation dam

INTRODUCTION

A variety of analytical and numerical models have been applied to analysis of stream water quality. One-dimensional (1-D) numerical models which assume complete lateral and vertical mixing (Brown and Barnwell, 1987; Hydrologic Engineering Center, 1984) are used in cases not amenable to analytical solution. In order to simplify hydraulic simulations required for constituent transport, most 1-D stream models assume constant or slowly varying flow throughout the study reach. Such assumptions may not be justified when dealing with rapidly varying flows, such as the riverine reach below a peaking hydropower plant. The reservoir withdrawal zone expands and contracts under peaking and base flow release operations, respectively, and, if the pool is stratified, release water quality will vary. Thus, unsteady flow conditions call for use of a dynamic (unsteady flow and water quality) stream model.

This study was conducted with a dynamic stream water quality model to determine effects on water quality of a proposed reregulation dam to be sited about 10 km downstream from Buford Dam, a peaking hydropower project. Reregulation structures effectively smooth unsteady flows by storing high inflows while providing a steady, continuous discharge. The Chattahoochee River reregulation structure would provide a steady, continuous flow greater than the present base flow. The primary reason for considering construction of a reregulation dam was to provide an adequate water supply for future needs of the Atlanta metropolitan region.

We make the assumption that the proposed reregulation dam will be built. Then, using two proposed operations scenarios for the three dams in the study reach, we proceed to compare impacts on water quality in a critical reach near intakes to a fish hatchery.

088&9375/89/030235-13$06.50 0 1989 by John Wiley & Sons, Ltd.

Received 18 July 1988 Revised 14 December 1988

236 M . J . Z I M M E K M A N AND M . S. DOKTCtl

MODEL DESCRIPTION

We utilized CE-QUAL-RIVl, a 1-D, numerical, hydrodynamic, and water quality model, developed by Bedford et al. (1983). The model consists of two codes: RIVIH, a stand-alone hydraulic routing code that simulates river flows, water surface elevations (stage), depths, cross-sectional areas, and top widths, and RIVlQ, a water quality code using output from RlVlH to drive transport algorithms.

RIVIH, patterned after the National Weather Service Dambreak Model (Fread, 1978) uses the four point, implicit, finite difference method to solve the continuity and momentum equations. The model permits unequal space and time steps and allows simulation of dynamically coupled, branched river systems. Cross-sectional area and discharge are the dependent variables in the hydrodynamic equations.

RlVl H requires river geometry and boundary conditions to perform the hydraulic calculations. Geometric data include locations of control structures, stream bed elevations, river cross-sections, and distances between nodes. Manning’s coefficients are used to describe channel roughness. Boundary conditions include initial flow rates and stages, lateral inflows or withdrawals, and boundary conditions defined by discharge, stage, or a stage-discharge rating curve.

After computing hydraulic conditions with RlVl H, RIVlQ can calculate dynamic changes in temperature and concentrations of water quality variables. RlVlQ uses an explicit, finite difference method to solve the constituent advective transport and reaction equations. A two point, fourth order scheme (Holley and Preissmann, 1978) minimizes numerical dispersion of the advective transport term. The dispersion term of the transport equation is solved implicitly.

RlVlQ requires initial in-stream and inflow boundary water quality concentrations, meteorological data for temperature computations, and rate coefficients. Accurate initial concentrations in the stream may not be crucial if the simulation period is sufficiently long to ‘flush’ the initial conditions through the system.

The model includes ten water quality state variables: temperature, dissolved oxygen (DO), carbonaceous biochemical oxygen demand (CBOD), organic nitrogen, ammonia nitrogen, nitrate nitrogen, orthophosphate phosphorus, dissolved iron, dissolved manganese, and coliform bacteria. Effects of phytoplankton and macrophyte growth and respiration are incorporated through their impacts on nutrient balances and DO.

Temperature computations use a direct energy balance (Brown and Barnwell, 1987) and include effects of net short wave and long wave radiation, back radiation, evaporative cooling, conduction, and thermal loadings from inflow boundaries and lateral inputs. Computed temperatures control reaction rates for other water quality constituents.

Computing D O concentration is a primary focus of the model. Reaeration and photosynthesis serve as sources of oxygen, while CBOD decay, nitrification, plant respiration, and iron and manganese oxidation serve as sinks. A variety of stream reaeration formulae are offered; reaeration through control structures conforms to an empirical relationship developed by Wilhelms and Smith (1981); and wind dominated reaeration in pooled reaches (such as reregulation pools) is determined by the O’Connor formulation (O’Connor, 1983). Hydropower releases are not reaerated.

MOD EL CA LIB RAT1 ON

Study area This study examines a reach of the Chattahoochee River, Georgia, between Buford Dam (River

km 560.5) and Peachtree Creek (river km 484.4) (Figure 1). Buford Dam is a Corps of Engineers peaking hydropower dam with discharges varying from 16 to 240 m3 s-’ within a day. Morgan Falls Dam, a small, shallow, run-of-the-river hydropower project owned and operated by Georgia Power Company, lies approximately 58 river km below Buford Dam. Although Morgan Falls Dam is not specifically a reregulation project, it does damp Buford Dam release flow fluctuations.

For modeiling purposes, the Chattahoochee River was divided into two subreaches for existing conditions (without the proposed reregulation dam). The upper subreach extended from Buford Dam to

MODELLING WATER QUALITY 237

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(KM 532 31 MORGAN FALLS DAM

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SOUTH ATLANTA CAROLINA ATLANTA GAGE (KM 487.61

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Figure I . Thc Chattahoochcc River study rcach in the vicinity of Atlanta, Gcorgia

Morgan Falls Dam. The lower subreach extended from Morgan Falls Dam to the confluence with Peachtree Creek, located at the end of the study reach. Time varying flow rates were specified for Buford Dam releases (the upstream boundary) and Morgan Falls releases. A rating curve defined the lower subreach downstream boundary condition at Peachtree Creek. To model conditions with the proposed reregulation dam, the upper subreach was divided at the site of the proposed reregulation dam. Flow rate boundary conditions were also specified at the reregulation dam.

Each subreach consists of a series of nodes (points at which the model makes predictions about hydraulic and water quality conditions). At any given node, lateral inflows (e.g. small streams and creeks) and withdrawals (e.g. water supply diversions) can be defined. The Buford Dam to Morgan Falls Dam subreach contained 35 nodes; the subreach from Morgan Falls Dam to Peachtree Creek had 15 nodes; the subreach of the reregulation pool had 11 nodes. Thus, simulations without reregulation had 50 nodes, while, with the reregulation dam, 51 nodes (one extra node being needed at the reregulation dam) were used.

Hydraulic calibration First steps in model application involved calibrating RIVlH for flow and stage. Initial calibrations were

conducted for a steady-state, low flow release from Buford Dam of 16m3 s-'. Values for river stage during the steady, low flow conditions of 17 July 1976 (Jobson and Keefer, 1979) were compared with model predictions. As stage increased, Manning's n coefficients were lowered, diminishing frictional drag and bringing modelled stage data into agreement with observed values (Figure 2). Bed elevations and

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Figure 2. Profilc of calibrated and observed stages for steady low flow event of 17 July 1976

TER

node locations are also shown in the figure. Observations for most of the downstream reach were non-existent except for stage readings at two downstream nodes, the Atlanta Water Works (river km 484.4) and the Atlanta Gage (river km 487.6). Manning’s n values for nodes without observed stages were adjusted to resemble values used for similar upstream reaches (i.e. high values for riffles and low values for pools).

After completing the steady, low flow calibration, unsteady flow simulations tested the adequacy of Manning’s n values and model geometry for a range of flow conditions. Data available from studies conducted during 21-23 March 1976 (Faye and Cherry, 1980) provided the basis for unsteady flow comparisons. Significant ungauged lateral inflows during this period were estimated using a weighted average based on known gauged flows and drainage basin area.

Unsteady flow comparisons revealed that several nodes (primarily in riffle areas) required Manning’s n values that varied from a high value at low stage to a low value at high stage. Therefore, linear interpolations for calibrated low and high flow n values were developed and used for several nodes in riffle areas. The n values were similar to values obtained by Jobson and Keefer (1979) during their flow simulations of the same events (17 July 1976 and 21-23 March 1976). Steady and unsteady flow calibrations enabled development of a rating curve for the boundary condition at the last node (Peachtree Creek). Results of unsteady flow calibrations at five stations for 21-23 March 1976 (Figure 3) indicated close agreement between simulated and observed stages.

Muss trunsport confirmation Prior to attempting water quality simulations, transport of a conservative substance (dye) was modelled

and results were compared with observed steady and unsteady dye tracer studies. For the first test, a

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Figure 3 . Calibrated and observed stagc historics for unsteady flow event of 21-23 March 1976

simulated dye slug was introduced into the steady, low flow, and the predicted travel time of the dye peak was determined from output. These results compared favourably with travel times reported for steady, low flow tracer studies (Figure 4).

Unsteady flow field studies of 21-23 March 1976 included dye tracer and temperature measurements (Jobson and Keefer, 1979) in addition to stage recordings previously cited. Dye was continuously released at a constant rate just below Buford Dam, and dye concentrations were recorded at two downstream stations throughout the unsteady flow event. The dye tracer was modelled by introducing a constant source of a conservative constituent at the Buford Dam node. Close correspondence between computed and observed dye concentration histories at both downstream stations (Figure 5) further confirmed the model’s ability to simulate mass transport.

240 M . J . Z I M M E K M A N A N D M . S . DOKTCII

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Figurc 4. Computcd and ohscrvcd travcl times of thc dyc pcak for thc steady low flow cvcnt

L I T T L E S F E R R Y BRIDGE RIVER KM 547.0

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Figurc 5 . Computed and ohscrvcd dyc concentrations for thc unstcady flow cvcnt of 21-23 March 1976

Thermal calibration The unsteady flow event of 21-23 March 1976 (Jobson and Keefer, 1979; Faye and Cherry, 1980)

provided the basis for calibrating water temperature simulations. Lateral inflow temperatures were approximated using the mean monthly averaged equilibrium temperatures during March for the period of record.

Meteorological data for simulating temperature, obtained from the National Oceanographic and

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Figure 6. Computed and observed stream temperature for the unsteady flow event of 21-23 March 1976

Atmospheric Administration (NOAA), represent measurements made at the Atlanta airport weather station (approximately 45 km distant) during the time period studied. Meteorological data included dew point and dry bulb temperatures, atmospheric pressure, wind speed, and cloud cover. Results of this simulation compared favourably with observations (Figure 6), and no further adjustments or calibrations were deemed necessary.

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Figure 7. Computed and observed stagcs for model conrirmation, 12-19 July 1976

Model confirmation Comparing flow and temperature simulations for 12-19 July 1976 with stage and temperature

recordings at the Atlanta Gage (river km 487.6) substantiated the calibrated model’s validity (Figures 7 and 8); stage and temperature data were unavailable elsewhere between Buford Dam and the Atlanta Gage. Unsteady flows for weekday peaking hydropower and steady low flows on the weekend occurred during this period. Contemporaneous meteorological data were obtained from NOAA. Mean monthly (July) averaged equilibrium temperature, modified for shading, served as lateral inflow temperature.

Most rate coefficients affecting water quality variables were obtained from previous Chattahoochee River modelling studies and other relevant works (Miller and Jennings, 1979; Bedford et al. , 1983; Brown and Barnwell, 1987). Iron oxidation rates were determined by examining iron concentrations measured at

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Figure 8. Computed and observed temperatures for model confirmation, 12-19 July 1976

MODELLING WATER QUALITY 243

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MEAN, MAXIMUM, AND MINIMUM VALUE OBSERVED DURING AUTUMN (1973-1981)

t SIMULATED AUTUMN WATER QUALITY CONDITIONS AVERAGED OVER ONE WEEK

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r 1 I 560 550 540 530 520 510 500 490 480

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Figure 9. Comparison of computed average water quality conditions (DO, CBOD, NH4-N, N03-N) versus observed autumnal ranges in Chattahoochee River study reach

several stations below Buford Dam. Rates of change in concentration over known distances made it possible to estimate travel times and, thence, oxidation rates in the river.

Field data were insufficient to calibrate or confirm the model for other water quality variables during the specific flow period, 12-19 July 1976. However, model results for autumn conditions were reasonably consistent with autumn values obtained from monthly water quality samples collected by the Georgia Department of Natural Resources (Figure 9).

CASE STUDY Simulation conditions

Following calibration and confirmation, the model was used to examine effects on water quality of a reregulation dam proposed for a site 10 km downstream from Buford Dam. Particular concerns regarding

244 M. J . ZIMMERMAN AND M. S. DORTCH

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Figure 10. Hydrographs depicting flows at three dams for two operations alternatives examined hcre. Principal significant differences are the minimum flow releases of 0 vs. 17m3 s - l at Buford Dam

effects on water quality included potential increases in water temperature and dissolved metals concentrations and decreases in DO concentrations. In order to examine these concerns, midsummer and fall conditions were simulated. In summer, meteorological conditions cause stream water temperatures to reach their highest values; in autumn, waters released from the stratified Lake Lanier pool above Buford Dam contain their lowest concentrations of DO and highest concentrations of dissolved iron and manganese.

We selected an eight day simulation period to allow a full weekly cycle of peaking hydropower generation including a typical weekend with low flow. Furthermore, the eight day simulations used stressful meteorologic conditions, likely to drive stream temperatures to levels approaching extreme

MODELLING WATER QUALITY 245

Table I . Upstream water quality boundary conditions (Buford Dam Releases)

Constituent Units Season Summer Autumn

Temperature "C low flow* 8.6 10.6

Ultimate CBOD mg I - ' 2.0 2.0 Organic nitrogen mgI-' low flow 0.2 0.18

high flowt 11.1 14.2

high flow 0-2 0-24 Ammonia nitrogen mgl-' low flow 0.13 0.32

Nitrate nitrogen mg I - ' 0-30 0.10 high flow 0.13 0.16

Phosphate phosphorus mg I - ' 0.01 0.01 DO mgI-' low flow 5-0 1 *0

high flow 6.0 3.5 Dissolved manganese mgl-' low flow 0- 1 0.8

high flow 0.1 0.3

high flow 0.2 0.6 Dissolved iron mgl-' low flow 0.2 1.5

*Minimum flow (17m's I ) .

'Peaking powcr flow (240m' s I ) .

historical records. We defined stressful meteorologic conditions as those associated with air temperatures exceeded only once every ten years. Approximately forty years of meteorological data were examined to determine when such conditions occurred, and data were selected from summer (July) and autumn (September-October) time periods.

Simulations presented here depict impacts on water quality of two different operations scenarios for a proposed reregulation dam with a 2.5 day water supply capacity. Attention focuses on summer water temperature and autumn DO and dissolved iron concentrations, not the entire array of model variables for both times of year.

Hydropower generation schedules are similar under both scenarios with maximum daily peaking hydropower releases from Buford Dam of 240m3 s-' (Figure 10) and steady flow releases from the reregulation dam of 42 m3 s-I. More significantly, one option calls for a minimum release of 17 m3 s-' from Buford Dam while the other eliminates flows from Buford during off-peak periods (except for several hours on Mondays to adjust the reregulation pool). Morgan Falls Dam operations are the same for both scenarios, reflecting weekday peaking releases.

When a reservoir is stratified, reservoir release water quality varies depending on release rate, degree of stratification, and depth of the intake. Low flows from Buford Dam tend to release cooler waters containing lower concentrations of DO and higher concentrations of dissolved, reduced materials such as ammonium, iron, and manganese. During summer and fall, the larger peaking hydropower releases expand the zone from which water is withdrawn from Lake Lanier. Peaking flows draw water from higher elevations in the reservoir pool, and these waters tend to be warmer, contain higher oxygen concentrations and lower dissolved metal concentrations. Field data were used to establish release water quality condtions (Table I) at Buford Dam for low flow and peaking discharges.

RESULTS AND DISCUSSION

We present results for one critical site in the reregulation dam pool near water intakes for a trout hatchery, an environmentally sensitive location, 2.4 km downstream from Buford Dam. Summer water temperature and autumn DO and dissolved metals concentrations at this site constitute major concerns in

246 M . J . ZIMMERMAN A N D M . S. DORTCII

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COMPUTED WATER QUALITY AT TROUT HATCHERY, JULY CONDITIONS

Figurc 11. Effect of diffcrcnt rclcasc rcgimcs on summer (July) watcr temperatures at trout hatchery water intakes

this study. As expected, slightly higher stream temperatures occur with the 0 m3 s-' minimum flow option (Figure 11); only peaking hydropower releases occur, and these have temperatures of 1 l.l"C, whereas, with 17 m3 s-' minimum flows, minimum release temperatures are 8.6"C. Under neither flow scenario d o temperatures exceed the maximum legal limit of 18.3"C.

In autumn, DO concentrations are higher and dissolved iron concentrations generally lower for the Om3 s-' option (Figure 12). Minimum low flows of 17m3 s-' constantly draw hypolimnetic waters with 1.0mg I - ' DO and 1.5 mg I - ' dissolved iron and rarely reach the same DO and iron concentrations as the Om3 s-' minimum flow option. Both options violate regulations for water quality (minimum DO

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Figure 12. Effect of diffcrcnt rclcasc rcgimcs on autumn (Octobcr) DO and dissolved Fe concentrations at trout hatchery

MODELLING WATER QUALITY 247

concentration 5.0 mg I-’, maximum dissolved iron concentration 1 .0 mg I - ’ ) at the intakes and would require either additional treatment (perhaps turbine venting) or different release operations.

CONCLUSIONS

A dynamic stream model, such as CE-QUAL-RIV1, should be used to focus on transient water quality conditions resulting from unsteady flows on regulated streams. The degree of resolution obtainable with a dynamic stream model can prove invaluable for environmentally sensitive studies of projects with transient flow conditions.

The results of this study clearly show the difficulties which may arise from using a single operations plan throughout the year. A zero-flow minimum release may keep downstream DO relatively high and dissolved iron concentrations low when the upstream impoundment is strongly stratified. But, the same release pattern, during the warmest part of the summer can cause downstream temperature increases, relative to a low-flow release. Thus, potentially deleterious effects of the operations scenarios presented here can be ameliorated using a flexible seasonal release plan based on knowledge of in-pool water quality and likely meteorological conditions. Of course, financial considerations associated with different operations may render some ecologically attractive alternatives economically infeasible.

ACKNOWLEDGEMENTS

The authors thank Tom Cole and Ross Hall for their thoughtful reviews of this manuscript prior to its submission for publication. The tests described and the resulting data presented herein, unless otherwise noted, were obtained from a study conducted by the U.S. Army Engineers Waterways Experiment Station for the U.S. Army Engineer District, Savannah. Permission was granted by the Chief of Engineers to publish this information.

REFERENCES

Bedford, K. W., Sykes, R. M., and Libicki, C. 1983. ‘Dynamic advective water quality model for rivers’, Journal of the

Brown, L. C. and Barnwell, T. 0. Jr. 1987. The Enhanced Stream Water Quality Models QUALSE and QUALZE-UNCAS:

Faye, R. E. and Cherry, R. N. 1980. ‘Channel and dynamic flow characteristics of the Chattahoochee River, Buford Dam to

Fread, D. L. 1978. DAMBRK: The NWS Dam-Break Flood Forecasting Model, Office of Hydrology, National Weather Service,

Holley, R. M. and Preissmann, A. 1978. ‘Accurate calculation of transport in two dimensions’, Journaf ofthe Hydraulics Division,

Hydrologic Engineering Center 1984. HEC-SQ: Simulation of Flood Control and Conservation Systems (Including Water Quality

Jobson, H. E. and Keefer, T. N. 1979. ‘Modeling highly transient flow, mass, and heat transport in the Chattahoochee River near

Miller, J. E. and Jennings, M. E. 1979. ‘Modeling nitrogen, oxygen, Chattahoochee River, Ga.’, Journal of the Environmental

O’Connor, D. J . 1983. ‘Wind effects on gas-liquid transfer coefficients’, Journal ofthe Environmental Engineering Division, ASCE,

Wilhelms, S. C. and Smith, D. R. 1981. ‘Reaeration Through Gated-Conduit. Outlet Works’, Technical Report E-81-5, U.S. Army

Environmental Engineering Division, ASCE, 109, 535-554.

Documentation and User Manual, EPA/600/>87/007, U S . Environmental Protection Agency, Athens, Georgia.

Georgia Highway 141’, U.S. Geological Survey Water-Supply Paper, 2463.

Silver Spring, Maryland.

ASCE, 103, HYl1, 1259-1277.

Analysis), U.S. Army Engineers Hydrologic Engineering Center, Davis, California.

Atlanta, Georgia’, U. S. Geological Survey Professional Paper, 1136.

Engineering Division, ASCE, 105, 641-653.

109, 731-752.

Engineer Waterways Experiment Station, Vicksburg, Mississippi.