Figure 4.10 Results of a river network application
Figure 4.11 The Altamaha River system
In order to model the river network, a simplified, conceptual version of the network is depicted in Figure 4.12 below. This version illustrates the differences in the real versus linear length between the upstream and the downstream of the channels, with real distances in blue and linear distances in black. These values are used to calculate the sinuosity factors of the rivers, which help modify the model for the meandering nature of rivers. The three channels in the Altamaha River network are called Altamaha River Main 1, Altamaha River Main 2, and the Ohopee River, which acts as a tributary entering the main stream divided by this junction. The channels are divided into small reaches at 394 cross-sections. The required data at these nodes are obtained by using measurements taken at three gaging stations by USGS, and the topographic maps of the region. Each node corresponds to a USGS gage, so geometric information as well as the flow and water elevation at the start of the model is known. The geometric information, which is actually the depth versus width information at each node, is known from the gages and
application of this model, each cross-section if described with 10 sets of elevation-top width pairs.
Figure 4.12 Conceptual drawing of the Altamaha River network
From previous modeling studies in the same area, Manning’s roughness coefficients have been selected and have values between 0.020 to 0.030 within the main channel and 0.030 to 0.070 along the floodplain (Gunduz and Aral 2004).
Altamaha River Main 1
Altamaha River Main 2 24909.7m
32056.2 m
41397.9 m 51609.1 m
22841.7m 31998.3 m Ohopee River
Three boundary conditions are specified for the application of Altamaha River system for the river flow model. The upstream boundary conditions at both the Altamaha River as well as Ohoopee River is taken to be discharge-time series obtained from Baxley and Reidsville river stream gages operated by U.S. Geological Survey. The most downstream boundary condition is a rating curve obtained from the Doctortown gauging station, developed by the U.S. Geological Survey staff for use in their modeling studies.
The initial discharge and stage conditions in the river network are based on previous studies in the same domain (Gunduz and Aral 2004).
Figure 4.13 Cross section view of a node.
The results of the Altamaha River applications will be used directly and indirectly as input for the contaminant transport model, which will be explained in detail in the next chapter. The results of this application include a velocity distribution in the river network
Whole width of the river
width of the main river
Width is used to calculate the surface area of each element together with the distance between nodes. Depth will then be used to calculate the volume of water in each element using the previously calculated surface area information. Velocities at each node will be used in the advection portion of the contaminant transport equation as well as in the calculation of a longitudinal dispersion coefficient for each element, using an empirical formula. All these results will be prepared as an array input in a small program developed to handle output and then to use the output of the hydrodynamic portion and convert it into input files to be used by the contaminant transport model.
As these results are intermediate steps in the solution of totally dynamic fugacity-based water quality model, they are not shown here. Just as an example, the velocity distribution in the Altamaha River network is given below:
Velocity Change in Time in Upper Altamaha River
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8
0 50 100 150 200 250 300 350 400 450 500
Tim e (days)
Velocity (m/s)
Figure 4.14 Velocity time series at location 5 km from upstream in the Altamaha River system
The velocity distribution follows the rise and fall of water levels due to rain events, water intake, and other activities performed in a channel, so it does not follow a smooth curve.
The real USGS stream gage readings are input into the solution of the model as initial and boundary conditions, and the results reflect changes in the river elevations and flow rate fluctuations due to natural and artificial reasons. The velocity time series is illustrated in Figure 4.14 and the width and depth distribution at each cross-section are used as input information into the contaminant transport model developed in Chapter 5.
CHAPTER 5
CONTAMINANT TRANSPORT MODELING IN RIVERS
One of the most studied aspects of the general mass transport process in the environment has been contaminant transport in rivers. Since most cities have arisen along rivers and streams carrying fresh water, contaminants and the fate and transport of contaminants are very important to humans. Thus, many models that simulate the migration of contaminants along a river have been developed. However, because of their predictive capabilities as well as cost-effectiveness, only mathematical models can be used to predict the response of rivers to an external pollution load.
Rivers are usually faced with two major water quality issues: eutrophication (algal bloom due to nutrient enrichment) and contamination by hazardous substances. So far, the purpose of most river water quality models is to assess eutrophication. Eutrophication models follow the fate of algae (phytoplankton) and green plants and their effect on the dissolved oxygen and nutrient concentration of a river.
In this thesis, interest is not in the modeling of eutrophication but in the fate and transport of hazardous substances in a river. Contamination by hazardous substances in rivers is
usually examined under the heading of contaminant fate models that describe the fate and transport of contaminants in the environment.