DEVELOPMENT OF HYDRODYNAMIC, WATER QUALITY AND EUTROPHICATION MODELS - Integrating GIS, Remote Sensing, and Mathematical Modelling for Surface Water Quality Management - page 145

In Delft3D-WAQ each computational cell has a unique number ranging from 1 to N, where N is the
total number of computational cells. Also, each surface area that is shared with another computational
cell is identified by a unique number, ranging from 1 to Q, where Q is the total number of shared
surface areas. Mass can be exchanged between the computational cells over these shared surface areas.
Therefore, the shared surface areas are also referred to as exchanges . Delft3D-WAQ defines an
exchange by the numbers of the two computational cells that share the surface area. For each cell, the
volume, dimensions, surface area, and neighbouring computational cells (i.e. exchanges) are known.
Thus, the water system is described by the individual computational cells, and through the exchanges
it is known how the individual computational cells are interconnected. The basis for water quality
modelling is the flow of water between the computational cells which is derived from the Delft3D-
FLOW hydrodynamic model. Substances and water quality processes can be added to generate the
water quality model.
7.5.1. Development of Main Water Quality Indicators Model
As explained in chapter 6 , lake Edko, like most of the coastal lakes connected to drainage watersheds,
is mainly used as a drainage sink to get rid of the continuous flow of drainage water coming from the
catchment. This is in addition to other important uses of the lake, which include fishing inside the lake,
preserving aquatic life, and sustaining fisheries around the lake area. For better understanding of the
effect of different sources of pollution on the lake water quality and to assess the water quality, a water
quality model is coupled with the developed hydrodynamic model to simulate the transport of different
pollutants discharging to the water body of the lake through the two main drains.
The main pollutants reaching the lake are largely agricultural drainage water polluted with fertilizers
and pesticides, untreated domestic wastewater, and waste loads from the fish ponds surrounding the
water body and also from industrial wastes discharged to the upstream sub-catchments connected to
the Edko main drain. The model aims at providing a better understanding of the fate of pollutants that
enter the lake, and the spatial and temporal variations in the concentrations of these pollutants. The
main objective of the model is to assess the seasonal variations of these pollutants in order to define
the most critical indicators.
In discussing the practice of surface water resources engineering and water quality modeling,
Rafailidis (1994) reports that the following determinants are of importance: Carbonaceous
Biochemical Oxygen Demand (BOD), Dissolved Oxygen (DO), Ammoniac compounds and coliform
Bacteria. BOD indicates the overall organic pollution of the water, and (DO) shows whether the
aquatic life may be sustained there. The nutrient concentration (indicated by forms of nitrogen) gives
the potential for eutrophication. Coliform counts indicate the danger of disease for humans using the
water. The temperature, salinity and total suspended matter are also considered of importance in the
modelling.
The parameters selected for the water quality model were based on the main water use of the lake,
namely, the aquatic life and the fisheries. Also the existing pollution problems in the lake area
indicated that the main problem there is eutrophication in addition to organic pollution from the
untreated human waste and fisheries waste dumped into the lake through the two main drains.
Therefore, the selected parameters are divided into three groups for the study of these problems. The
first group consists of general variables including: Temperature, Salinity, dissolved oxygen and total
suspended matter. The second group includes the nutrient variables: nitrogen compounds (ammonia
NH4 and nitrates NO3) and phosphorous compounds (orthophosphate PO4). The third group is formed
from the organic compounds variables and it includes: the biological oxygen demand BOD and the
chemical oxygen demand COD.