WATER QUALITY MODELING FOR THE SOUTHERN PART OF ASWAN HIGH DAM RESERVOIR, LAKE NUBIA M. Elshemy 1, T.T. H. Le 1, G. Meon 1, and M. Heikal 1 Leichtweiss-Institute for Hydraulics and Water Resources, University of Braunschweig, Germany. Nile Research Institute, National Water Research Center, Egypt. ABSTRACT Water quality of reservoirs is of particular concern. With increasing environmental degradation and multiple uses of reservoirs, water quality has become an issue of great concern. Egypt is extremely dependent on the River Nile; the country hardly has any other fresh water resources. Full control of the Nile water was achieved in the 197s after the construction of the Aswan High Dam (AHD). In this paper, the southern part of the AHD reservoir, Lake Nubia, was modeled to investigate the hydrodynamics and water quality of the reservoir water body. For this, a two-dimensional hydrodynamic and water quality modeling system CE-QUAL-W was applied. The model was calibrated with data from the year and verified with data from the year 7 by applying the same set of parameters and constants which were used in the calibration process. The presented model simulates the hydrodynamic characteristics (water surface level and water temperature) profiles with excellent agreement. The simulated concentrations of key water quality constituents such as dissolved oxygen, nutrients, and algal biomass closely match the measured values. In the following, the calibrated model is going to be used to simulate the impact of changed inflow characteristics related to pollution and water quantities and of different reservoir operation strategies on the water quality. INTRODUCTION Egypt is extremely dependent on the River Nile, the country hardly has any other fresh water resources (MWRI 5). Full control of the Nile water discharge was achieved in 197s after the construction of the AHD, and as a result; the AHD reservoir was formed. It is considered as one of the largest man-made lakes in the world; its volume is about 1 (Avakyan and lakovleva 199) billion cubic meters at a water level of 1 meter. It is located at the border between Egypt and Sudan between the latitudes 3 5' and 7'N, and the longitudes 3 35' and 33 15'E, as seen in Figure 1. The current length of the submerged area is about 5 km, of which 35 km are within the Egyptian territory and is known as Lake Nasser, while the 15 km stretch which lies in the northern part of Sudan is known as Lake Nubia. Lake Nubia is the study area for this work. The industrial and agricultural activities, due to the increase in population of Egypt, has resulted in a rapid deterioration of the quality of the water resources (MWRI 5). Egypt realized the importance of protecting the AHD reservoir from pollution, as it is almost the sole source of fresh water to the country (MWRI ). Figure 1. Location map of Lake Nubia (MWRI 5), and its sampling stations.
Within the framework of this study, a two-dimensional, laterally averaged, finite difference hydrodynamic and water quality code, CE-QUAL-W, was applied to build up a hydrodynamic and water quality model for Lake Nubia. In this study, the proposed model was calibrated and verified by the existing available observational data of Lake Nubia. STUDY AREA The River Nile is the main and sole inflow source of Lake Nubia. Lake Nubia can be divided into two sections: the riverine section and the semi-riverine section (Abdel-Latif 19). The riverine section, with all-year riverine characteristics, is comprising the southern part of the lake, from the southern end to Daweishat (St. 5), as shown in Figure 1. While the semi-riverine section, with riverine characteristics during the flood season (from the second half of July to November) and lacustrine characteristics during the rest of the year, comprises the northern part of the lake extending from Daweishat. The study area is a true desert climate. The rainfall of this area is not only scanty, but also extremely irregular and variable. Figure shows the Lake Nubia inflow during the study period. Inflow (billion cubic meters) 35 3 5 Lake Nubia inflow (5 7) 15 1 5 May 5 Jul 5 Sep 5 Oct 5 Dec 5 Feb Mar May Jul Aug Oct Nov Jan 7 Mar 7 Apr 7 Jun 7 Aug 7 Month / Year Figure. Lake Nubia inflow during the study period. CE-QUAL-W CODE DESCRIPTION CE-QUAL-W is a two-dimensional, longitudinal/vertical, hydrodynamic and water quality code. This code has been applied to rivers, lakes, reservoirs, estuaries, and combinations thereof (Cole and Wells ). It contains one module, which models both hydrodynamics and water quality. CE-QUAL-W is based on an earlier reservoir code that has been enhanced by using the water quality processes of QUAL, this has made this code a very powerful prediction modeling system for reservoirs and reservoir flow management (Palmer 1). It has been widely used for reservoirs in the United States and around the world, and is considered the preferred model of choice for reservoir water quality simulation (Fang et al. 7). This code computes water surface elevation, horizontal and vertical velocities, water temperature and up to twenty-eight other water quality parameters such as dissolved oxygen and nutrients. A full documentation of the code is given by Cole and Wells (). MODEL PERFORMANCE The basic input data for CE-QUAL-W include: reservoir topography (bathymetry), stream flow, temperature and water quality records as well as meteorological information. The bathymetry of Lake Nubia was modeled by establishing a finite difference grid consisting of three main branches with segments along a longitudinal axis and 7 vertical layers of m depth, as seen in Figure. A specific width was assigned to each cell of the model grid. The inflow data are supplied from one gauging station at the upstream end of the reservoir, St. 1, as shown in Figure 1. All inflows and reservoir surface elevations were specified as daily average values. The meteorological data were obtained for the nearby local meteorological station from the internet (website of Weather Underground ). The recorded data were given for every six hours. The measured data include hydrodynamic and water quality records. The measured hydrodynamic data consist of water surface level and water temperature. The measured water quality data consist of dissolved oxygen, chlorophyll-a, orthophosphate, nitrate-nitrite, ammonium, total dissolved solids, total suspended solids and ph. In-reservoir temperature and constituent concentration profiles were measured at 1 stations (St. 1-1) positioned along the longitudinal axis of Lake Nubia, as seen in Figure 1. The water samples were collected from the surface and at 5, 5, 5 and % depth, except for chlorophyll-a samples, which were collected two times. The field data in (during the period from 7th to 19th January), and in 7 (during the period from nd to 1th February) were used to calibrate and verify the model, respectively. The in-reservoir water quality condition at the first station, (St. 1), as seen in Figure 1, was used as the initial conditions.
Figure 3. The finite difference representation for the model of Lake Nubia. MODEL CALIBRATION The proposed model was calibrated using coefficients determined for the calibration period (January ). For the other model coefficients not measured in this study, default values provided by the code software were used as recommended by Cole and Wells (). Some model coefficients are displayed in Table 1. Table 1. Some of model coefficients of CE-QUAL-W used in this study. Coefficient Variable Value Horizontal eddy viscosity AX 1. m /s Horizontal eddy diffusivity DX 1. m /s Chezy bottom friction factor CHEZY 7 m ½ /s Wind-sheltering coefficient WSC 1. ASSESSMENT OF MODEL PERFORMANCE Two statistics were used to compare simulated and measured in-reservoir observations, the absolute mean error (AME) and the root mean square error (RMS) (Cole and Tillman 1). The AME indicates how far, on the average, simulated values are from measured values, while the RMS indicates the spread of how far the computed values deviate from the observed data. AME and RMS are computed according to the following equations: (1) () RESULTS AND DISCUSSION Hydrodynamic results Figure shows the longitudinal profile of water surface levels in Lake Nubia during the studied calibration period, a close match between the simulated and measured water surface levels can be noticed. The AME is. m, and the corresponding RMS is.1 m. For the verification process, AME is.13 m and RMS is.15 m. The AME and RMS values, of the calibration and verification processes, show good agreement of the simulated water surface levels with the observed water surface levels. Vertical profiles of the simulated and the measured temperature at different stations for the calibration and verification processes are shown in Figures 5 and, respectively. The simulation results match closely the measured vertical temperature profiles. The average AME of the calibration period for the eight stations (St. -9) is.55 C, while the corresponding average RMS is.73 C. For the verification period, the average AME is.3 C, and the corresponding average RMS is.397 C. These vertical profiles are closely matching the typical thermal distribution for warm monomictic lakes in winter (Thomas et al. 199).
Water surface level (m) 17 175 17 173 17 Water Level Measured Water Level Simulated AME=. RMS=.1 1. Jan 1. Jan 13. Jan Sampling 11. Jan 9. Jan 9. Jan. Jan Date St. 9 St. 7 St. Sampling Station S t. 5 St. St. 3 St. 3 3 3 3 3 Distance upstream AHD (Km) Figure. Longitudinal profile of water surface levels in Lake Nubia at different stations and dates, January. Water Temperature ( C) AME=.3 RMS=.3 AME=.1 RMS=.17 Tmeas Tsim AME=.5 RMS=. AME=. RMS=.5 AME=.1 RMS=.5 St., Jan., St. 3, Jan. 9, St. 5, Jan. 11, St. 7, Jan. 1, St., Jan. 1, Figure 5. Model calibration: vertical profiles of water temperature in Lake Nubia at different stations and dates, January. Water Temperature ( C) 1 AME=.1 RMS=.15 Figure. Model verification: vertical profiles of water temperature in Lake Nubia at different stations and dates, February 7. Water quality results AME=. RMS=.1 The water quality model results and field measurements of the calibration process for the second station (St. ), as an example, are presented in vertical profiles, as shown in Figure 7. The AME values of the calibration period, are:. g/m 3,. g/m 3,.5 g/m 3,.51 g/m 3,.15 g/m 3,.77 g/m 3, 3.79 g/m 3, and. for dissolved oxygen, chlorophyll-a, ortho-phosphate, nitrate-nitrite, ammonium, total dissolved solids, total suspended solids, and ph, respectively. The corresponding RMS values are:.5 g/m 3,. g/m 3,.5 g/m 3,.51 g/m 3,.1 g/m 3,.77 g/m 3,.51 g/m 3, and., respectively. Tmeas Tsim AME=.15 RMS=.11 AME=.3 RMS=.5 AME=.3 RMS=.3 St., Feb. 3, 7 St. 3, Feb., 7 St. 5, Feb. 5, 7 St. 7, Feb. 9, 7 St., Feb. 11, 7
1 1 1..1..3..5.1.15..5..... 1. DO g/m 3 AME=. RMS=.5 Chl-a g/m 3 AME=. RMS=. PO g/m 3 AME=.5 RMS=.5 NO3 -NO g/m 3 AME=.51 RMS=.51..5.1.15. 1 1 1 1 5 1 15 5 7 9 11 NH g/m 3 AME=.15 RMS=.1 TDS g/m 3 AME=.77 RMS=.77 TSS g/m 3 AME=3.79 RMS=.51 ph AME=. RMS=. Figure 7. Model calibration: vertical profiles of measured (x) and simulated ( ) key water quality parameters in Lake Nubia at Station No. on. January. For the verification process, Figure shows the the water quality model results and field measurements at St., as an example. AME are:.19 g/m 3,. g/m 3,.1 g/m 3,.19 g/m 3,.3 g/m 3, 5. g/m 3, and.5 for dissolved oxygen, chlorophyll-a, ortho-phosphate, nitrate-nitrite, total dissolved solids, total suspended solids, and ph, respectively. The corresponding RMS are:.35 g/m 3,. g/m 3,.1 g/m 3,.33 g/m 3,.51 g/m 3,.99 g/m 3, and.31, respectively. 1 1 1..1..3..5.1.15..5..... 1. DO g/m 3 AME=.19 RMS=.35 Chl-a g/m 3 AME=. RMS=. PO g/m 3 AME=.1 RMS=.1 NO3 -NO g/m 3 AME=.19 RMS=.33..5.1.15. 1 1 1 1 5 1 15 5 7 9 11 NH g/m 3 NH meas<.1 g/m 3 TDS g/m 3 AME=.3 RMS=.51 TSS g/m 3 AME=5. RMS=.99 ph AME=.5 RMS=.31 Figure. Model verification: vertical profiles of measured and simulated key water quality parameters in Lake Nubia at Station No. on 11. February 7. The vertical profiles of dissolved oxygen closely match the typical winter stratification of dissolved oxygen for oligotrophic lakes (Wetzel 1), where the dissolved oxygen concentration is relatively constant with the water depth as it is in the water temperature profile. Figure shows a decrease of chlorophyll-a and dissolved oxygen concentrations, at the bottom layer, and an increase of ortho-phosphate, nitrate-nitrite, and total suspended solids as the phytoplankton growth is subjected to light limitation. Figures 7- show that the simulation results and the field measurements are in reasonable concordances.
CONCLUSIONS The present hydrodynamic and water quality characteristics of Lake Nubia were investigated using the laterally averaged, two-dimensional hydrodynamic and water quality modeling system (code), CE-QUAL-W. The model was calibrated and verified with data from January and February 7, respectively. The hydrodynamic model simulation shows good agreement with the observed water surface levels and the measured water temperature profiles at various locations and dates. The water quality model reproduces spatial and temporal concentration distributions of key water quality constituents such as: dissolved oxygen, chlorophyll-a, ortho-phosphate, nitrate-nitrite, ammonium, total dissolved solids, total suspended solids, and ph. The model results closely mimic the measured vertical profiles of the water quality constituents. The current modeling system can be further developed as a management tool for the evaluation of different management strategies of controlling the reservoir hydrodynamic and water quality characteristics. The effect of future climate conditions on the reservoir hydrodynamic and water quality characteristics are being examined. ACKNOWLEDGMENT This paper originated as part of a PhD thesis funded by the Egyptian government. Providing the field data for this modeling study by Nile Research Institute (NRI) and Water Resource Research Institute (WRRI), Egypt, was greatly appreciated. REFERENCES Abdel-Latif, A.-F. (19). Lake Nasser, in: Status of African reservoir fisheries. J. M. Kapetsky and T. Petr, FAO CIFA Technical Paper 1. Avakyan, A. B. and V. B. lakovleva (199). Status of global reservoirs: The position in the late twentieth century. Lakes & Reservoirs: Research and Management 3: 5-5. Cole, T. M. and D. H. Tillman (1). Water Quality Modeling of Allatoona and West Point Reservoirs Using CE- QUAL-W. ERDC/EL SR-1-3, U.S. Army Engineer Research and Development Center, Vicksburg, MS. Cole, T. M. and S. A. Wells (). CE-QUAL-W: A two-dimensional, laterally averaged, Hydrodynamic and Water Quality Model, Version 3.. Department of Civil and Environmental Engineering, Portland State University, Portland, OR. Fang, X., R. Shrestha, Alan W. Groeger, Che-Jen Lin, and Mien Jao (7). Simulation of Impacts of Stream flow and Climate Conditions on Amistad Reservoir. Journal of Contemporary Water Research and Education (137): 1-. Ministry of Water Resources and Irrigation of Egypt, MWRI (). Adopted measures to face major challenges in the Egyptian Water Sector. Ministry of Water Resources and Irrigation of Egypt, MWRI (5). Water for the Future, National Water Resources Plan for Egypt - 17. Palmer, M. D. (1). Water quality modeling : a guide to effective practice. Washington, D.C., World Bank. Thomas, R., M. Meybeck, and A. Beim (199). Lakes, in: Water quality assessments: a guide to the use of biota, sediments and water in environmental monitoring. D. V. Chapman. London [u.a.], Spon. Weather Underground, http://www.wunderground.com/. Wetzel, R. G. (1). Limnology: lake and river ecosystems. San Diego, Academic Press.