Cairo Drinking Water Plants along the Nile River. Ph.D. Seminar. Prepared by. Mohamed Ahmed Reda Hamed. Ain Shams University. Faculty Of Engineering.
Ain Shams University Faculty Of Engineering Irrigation &Hydraulics Department
Water Quality Management Upstream Cairo Drinking Water Plants along the Nile River Ph.D. Seminar Prepared by Mohamed Ahmed Reda Hamed Supervised by Prof. Dr. Abdel Kawi Khalifa Prof. Dr. Mohamed Nour El-Deen Prof. Dr. Mohammed Hassan Abd El-Razik Dr. Hussein El Gammal
Dr. Peter Hany Sobhy Riad May 2016
Contents • • • • • • • • • •
Introduction Problem Statement Research Objective &Methodology Water Quality Index MIKE11 Water Quality Model Management Scenarios Multi Criteria Analysis Water Quality Management Information System Results and Discussion Conclusions
Introduction • Water is a precious resource essential for the well being of all living organisms. However, water is under potential severe threats from all human activities. • The limited amounts of rainfall make the country dependent mainly on water from the Nile River which currently suffer from increasing pollution caused by the discharging of agricultural drainage, untreated or partially treated domestic and industrial wastewater. • Deteriorating water quality is a particular threat in countries with scarce water resources as the case of Egypt .However, the management of river water quality is a major environmental challenge.
Problem Statement • Sustainable development of water resources in Egypt is impeded by a number of challenges, most notably a rapid population growth, water scarcity and water quality deterioration. • Surface water quality deterioration at the intakes of Cairo drinking water plants along River Nile due to increasing level of pollutants concentration above the guidelines paid the attention of public concern and may cause health hazards. • Cairo Drinking Water Plants that take their raw water source from Nile river need a particular attention and better management to prevent health hazards.
•
According to 2010 Census of Population:-
- Urban population = 33.5 million capita - Rural population = 45.5 million capita
•
According to HCWW Master Plan:-
- - In Cairo, Actual per Capita consumption= 650 L/day - In Alex., Actual per Capita consumption= 590 L/day
•
According to Egyptian Code:-
- - In Urban, Actual per Capita consumption= 250 : 280 L/day - In Rural, Actual per Capita consumption= 150 : 200 L/day
•
In Germany:-
•
Average per Capita consumption= 90 L/day
إحت اجات م اه الشرب ط قاً للكود المصر Millar m3/year Consumed Water (Now) 9.0 7.2
2006
10.0
11.0
11.6
12.5
7.9
2010
2020
2030
2037
2040
2050
• At year 2050, Egypt Predicted Population =146 million capita • Average Actual daily consumption ranged from 110 to 650 L/day
• For all Egypt Governorates, Total accumulated DWPs productivity =28 million m3/day. • Cairo DWPs productivity =6 million m3/day
Study Objectives The main objective of the research is managing surface water quality upstream Cairo water drinking plants. This main objective can be divided into the following specific objectives:1-Estimate the surface Water Quality Index (WQI) upstream Cairo drinking water plants along River Nile . 2-Derive the best surface water quality modeling approach for the study area. 3-Develop and evaluate the management scenarios for improving water quality. 4-Develop the Water Quality Management Information System (WQMIS) to facilitate water quality management upstream Cairo drinking water plants.
Methodology The Methodology of work is described as follows:-
Study Area • Cairo, located on the River Nile south of the Mediterranean Sea, just upstream of the point where the river widens into the Delta. Cairo has an area of 353 km2 with an average reach length along the river about 50 km (from Km 900 to km 950 Referenced to Aswan High Dam). • The study area covers Cairo governorate along the River Nile, bounded by El Saff town (Giza Governorate) at Km 877.00 from the South and El Kanater town (Qalubia Governorate) at Km 953.00 from the North.
Study Area Layout
Greater Cairo Drinking Water Plants Drinking water plant Tibeen Kafr Elw North Helwan Maadi Fostat El Roda Rod El Farg Amerea Mostrod El Marg El Obour El Asher Shubra el Khiema Gezeret El Dahab 6 October Giza Embaba El Sheikh Zayed
Plant intake geographic location
Cairo
Cairo
Surface water source
River Nile
Ismailia canal
New Cities Qalubia
Sharkawia canal
River Nile Giza El Rayah El Behery
Raw water (m3/day)
Treated water production (m3/day)
Sludge and washing water (m3/day)
178608 78238 321003 209179 1114381 323216 819695 404226 1281328 650000 860000 600000
155649 70728 283539 161772 1046974 164625 720908 389853 1155899 526232 790000 500000
47000 14000 39000 86000 150000 7000 115000 25000 130000 41000 49000 39000
379146
358091
21582
550000
49000
30000
300000 168000 950000
275000 130000 922000
19000 9500 52000
500000
400000
42000
Pollution Sources Description No.
Pollution Sources Name
1 2
El Massanda Drain Ghamaza Soghra Drain
3
Ghamaza Kobra Drain
4
Khour Sail El Tibeen
Mixed Waste
5
Waste and cooling water
10
Tibeen Power Station Tibeen Drinking Water Plant Kafr El Elw Drinking Water Plant North Helwan Drinking Water Plant Maadi Drinking Water Plant Fostat Drinking Water Plant
11
Gezeret El Dahab Drinking Water Plant
12
15
El Roda Drinking Water Plant Giza Drinking Water Plant Rod El Farag Drinking Water Plant El Nasser Glass
16
Embaba Drinking Water Plant
17
Delta Cotton Kanater
6 7 8 9
13 14
Description Agricultural drainage water mixed with partially treated or untreated domestic wastewater and industrial wastewater
Wastewater from drinking water plants sludge disposal
Industrial effluent Wastewater from drinking water plants sludge disposal Industrial effluent
Sampling Sites • Surface Water samples were collected from various sampling locations of rivers, canal, drains and industrial pollution sources of study area. • The measured data include study reach , drains, industrial pollution sources and waste water from drinking water plants sludge disposal. • The collection and various chemical analysis for water quality parameter is done at Cairo Drinking water Company Central Laboratory.
Water Quality Index Determination • The desired WQI for study area was calculated based on Canadian Council of Ministers of the Environment (CCME, 2005). • In the formulation of WQI, Nine physical, chemical and biological parameters: pH, Dissolved Oxygen (DO), Total Dissolved Salts (TDS), Nitrates ,Ammonia, Iron, Biological Oxygen Demand (BOD), Chemical Oxygen Demand (COD), Fecal Coliform (FC) are selected according to their relative importance from the point of view of suitability for drinking water purposes. • The analyses of water samples were carried out at Cairo drinking water company central laboratory according to the standard methods for the examination of water and wastewater (APHA, 2012) for twelve consequence months during year 2013 to show the effect of the spatial and temporal variation
Study Area Water Quality Modeling • MIKE11 was adopted to simulate the water quality status. • This model was calibrated and validated to simulate different scenarios for improving water quality problems in the study area. • In this study, Three water quality datasets are used (2012,2013,2104) for model calibration, run and validation respectively.
Model Processes The Hydro Dynamic (HD) module is the core of the system and solves either the full hydrodynamic (St. Venant) equations or one of the two simpler versions called diffusive wave and kinematics wave equation.
The St. Venant equation for momentum and how the simpler forms may be derived by dropping terms which are shown as follows (Chow, et al., 1988):
Where:A: is the wetted area (or reach volume per unit length). t: is the time. Q: is the discharge. x: is the distance downstream. q: is the lateral inflow per unit length, g is the acceleration due to gravity. Y: is the depth, a: is a momentum coefficient. S0: is the bed slope Sf: is the friction slope.
MIKE11 Modules
Simulation Editor in MIKE11 Model
Cross-Section Editor of MIKE11 Model
Water Quality Management Scenarios • Water quality management scenarios are simulated using 2013 WQ data set and the pre-calibrated model as a base condition. • The main objective of this simulation is to propose alternative solution to improve the water quality of the study reach. • Six scenarios using Mike11 HD, AD and EcoLab modules are designated as explained in table below.
Management Scenarios Description Scenario Base Condition
Scenario (1)
Description
Pre-Simulated model with 2013water quality dataset. Treatment of four polluted drains (El Massanda, Ghamaza Soghra, Ghamaza Kobra and Khour Sail drains) using wetland technique in order to reduce pollution loads from these drains.
Scenario (2)
Stopping the sludge disposal effluent from the treatment processes of seven DWPs (Tibeen, Kafr El Elw, North Helwan, Maadi, Fostat , El Roda and Rod El Farag) and applying sludge treatment alternative.
Scenario (3)
Twenty percent increase in study reach discharge over the maximum discharge in low demand period in order to dilute the effect of pollution concentrations .
Scenario (4)
Combination of scenario (1), scenario (2) and scenario (3). Treatment of four polluted drains by constructing wastewater treatment
Scenario (5) Scenario (6)
plants to reduce pollution loads from these drains. Combination of scenario (1), scenario (2) and scenario (5).
MCA Framework • MCA identifies multiple criteria against which the study area water quality management scenarios can be evaluated and then compared to each other.
• MCA technique mainly based on ranking for prioritizing the alternatives through technical, economical environmental and socio-cultural criteria.
Applying MCA Technique The following methodological steps were followed to construct MCA:-Choose evaluation criteria. -The criteria are used to measure the performance of decision options. -These values be sourced from expert judgments and other environmental models. -Weight the criteria based on the degree of importance of each adaptation option. -Rank or score the options. -Prioritization of options based on the final weighted scores per option which calculated according to the equation:Where:Value (x) = Final value for alternative x Wi (x) = Weight of criterion i for alternative x Ci(x) = Score of criterion i for alternative x
Water Quality Results Water Quality Parameter
Mean value
Standard Guidelines
pH
7.97±0.24
6.50-8.50
DO (mg/l)
7.89±0.31
≥ 6.00 (mg/l)
TDS (mg/l)
294.04±41.5
≤ 500.00 (mg/l)
Nitrate (mg/l)
0.37±0.08
≤2.00 (mg/l)
Ammonia (mg/l)
0.25±0.05
≤0.50 (mg/l)
Iron (mg/l)
0.32±.10
≤1.00 (mg/l)
BOD (mg/l)
5.33±0.29
≤6.00 (mg/l)
COD (mg/l)
17.92±1.47
≤10.00 (mg/l)
FC (FCU)
1194±89
≤1000 (FCU)
WQI
95.70±0.4
--
WQI Rank
Excellent
--
Model Calibration Results
S im ulated E C (μS /cm ) 2012
364.00
y = 0.5982x + 142.32
362.00
2
R = 0.7613 360.00 358.00 356.00 354.00 352.00 350.00 350
352
354
356
358
360
362
Observed EC(μS/cm)2012
364
366
368
370
Model Run Results
S im u la te d D O (m g /l)
7.45 7.40
y = 0.8453x + 1.1063
7.35
2
R = 0.893
7.30 7.25 7.20 7.15 7.10 7.05 7.05
7.1
7.15
7.2
7.25
7.3
Observed DO (mg/l)
7.35
7.4
7.45
7.5
Model Run Results
Simulated BOD (mg/l)
3.58
y = 0.3507x + 2.2927 3.56
2
R = 0.5827
3.54 3.52 3.50 3.48 3.46 3.4
3.45
3.5
3.55
Observed BOD (mg/l)
3.6
3.65
Model Run Results
18.05
Sim ulated C O D (m g/l)
18.00
y = 0.4936x + 9.0064
17.95
2
R = 0.7201
17.90 17.85 17.80 17.75 17.75
17.8
17.85
17.9
17.95
18
18.05
Observed COD (mg/l)
18.1
18.15
18.2
18.25
Model Run Results
1400.00
Simulated FC (C FU/100mL)
y = 0.5312x + 644.09 2
1380.00
R = 0.7604
1360.00
1340.00
1320.00
1300.00 1350
1355
1360
1365
1370
1375
1380
Observed FC(CFU/100mL)
1385
1390
1395
1400
Model Evaluation Statistics • Various statistical measures e.g. root mean square error (RMSE), relative means absolute error (MAE)rel, percent bias (PBIAS), Sutcliffe Efficiency and coefficient of determination (R2) were used for error estimation and to assess calibration , verification and validation of the model. • The errors between observed and simulated data and the model efficiency were calculated with the help of statistical measures as presented:-
PBIAS NSE
R2
Parameters
(MAE)rel
DO BOD COD FC
0.003 0.008 0.044
0.168 0.03 0.02
0.879 0.59 0.71
0.89 0.66 0.71
0.003
0.20
0.58
0.76
-The relative mean absolute error (MAE)rel value is very small and tend to be equal it's optimal statistics value (Zero) for various simulated results. -The magnitude of PBIAS is very small suggesting a good accuracy of the model calibrated and validated results. -The model accuracy is further confirmed from high values (close to 1) of NSE and R2 at the calibration points. -It is evident that there is an excellent match of observed and modeled results at different sites of the study area.
Management Scenarios Results
Water quality improvement upstream DWPs under various scenarios Scenario
Mean BOD Reduction Percent
Mean COD Reduction Percent
Mean FC Reduction Percent
Scenario (1)
20.0
11.9
13.8
Scenario (2)
12.4
10.9
12.3
Scenario (3)
8.1
9.5
8.0
Scenario (4)
33.3
11.1
18.8
Scenario (5)
37.0
11.8
15.3
Scenario (6)
39.9
13.4
26.2
45
Reduction Percent
40 35 30 25 20 15
Mean BOD
10
Mean COD 5
Mean FC
0
Senario (1)
Senario (2)
Senario (3)
Senario (4)
Scenario
Senario (5)
Senario (6)
MCA for Management Scenarios Evaluation
MCA Total Weight Scores
MC A (T o tal weig h t sco re)
100% 90% 80% 70% 60% 50% 40%
Social & Community
30%
Economical
20%
Environmental
10%
Technical
0% Senario (1) Senario (2) Senario (3) Senario (4) Senario (5) Senario (6) Scenario
It can be noted from MCA that:•
MCA total weight score for various management scenario were found 68.0%, 73.6% , 62.0%, 55.2%, 67.2%, and 62.00% for scenario (1), (2), (3), (4), (5) and (6) respectively.
•
Scenario (1) for treatment of study area drains by using wetland technique has a relatively high technical criteria weight but a relatively low social & community criteria weight due to effect of stakeholders acceptability ,Health and safety risks sub criteria evaluation.
•
Scenario (2) for DWPs sludge treatment has the highest overall weight score, total technical and environmental weight scores. However, this scenario can be represent the most convenient scenario for study area water quality management.
•
Scenarios (2) and (3) have the highest economical criteria total weights.
•
Scenarios based on increasing Nile discharge at low flow month such as scenarios (3), (5) and (6) have a relatively low technical criteria total weight due to their sustainability sub criteria inverse effect on compliance with current water management strategy.
•
Scenario (5) for treatment drain discharge by constructing wastewater treatment plants has a relatively high technical weight but a relatively low economical weight
Cairo Reach Water Quality Management Information System (WQMIS) •
The developed information system includes three types of information for stream, DWPs, and various water quality parameters.
•
Cairo Drinking Water Plants WQMIS includes five modules to deal with study area geographic and hydraulic characteristics, sources of pollution, water quality data, modeling results and reports.
•
WQMIS database was developed through Microsoft Visual C as programming language.
•
The interface of the developed system is constructed using new forms which created with command buttons to perform the needed functions as shown in figure below.
Pollution Sources Module This module shows different sources of pollution for the Cairo reach. It has three sub modules, which include wastewater from drains, DWPs and factories.
Water Quality Data Module •It includes two sub modules. The first part of this module is the evaluation of water quality trend represented in WQI. • The second sub module summarizes some of important water quality parameters for the Cairo reach for several years. •These data were presented in different forms as tables, bar-charts, and graphs.
Modeling Results Module •
This module includes six sub modules. It includes water quality model calibration, simulation, verification, water quality management scenarios results , scenarios comparison and MCA scenarios evaluation.
Reports Module This module is the output of the database. Reports are obtained either in form of tables, graphics or in the technical reports.
Conclusion The results of various water quality parameters proved that the water quality at the study area is impacted by a relatively high concentration of COD and FC due to treated or partially treated domestic wastewater and industrial wastewater mixed with agricultural drainage water discharged to the river. Based on water quality index, the water quality in Cairo reach was ranged from good to excellent. However, the WQI study on this reach shows that the water can be used for different purposes. Water quality management scenarios were simulated by MIKE11 water quality model. The main objective of this simulation is to present alternative solution to improve the water quality of the study reach; however, six scenarios using MIKE11 are presented. These scenarios are mainly based on applying various treatment techniques on pollution sources (drains, factories and wastewater from DWPs) for pollution loads reduction and also applying dilution process to reduce the effect of pollution concentrations.
Conclusion -MCA techniques based on four main criteria alternatives through technical, economical environmental and socio-cultural criteria, was used to identify the most preferred water quality management scenarios to rank them as a short list of a limited number of options for subsequent detailed appraisal to distinguish acceptable from unacceptable possibilities. •
The developed MCA framework show that there is significant value of such framework in providing information and input for different decisionmaking levels.
• MCA results for different scenarios showed that the water quality management scenario focusing on treatment of DWPs sludge is the most convenient scenario
Conclusion •
The developed WQMIS links with Geographical Information System (GIS) platform with water quality assessment module. Thus, the developed WQMIS supports the performance of water quality management operations and allows for designing portable application runs under multiple platforms and open systems.
•
The sub modules are linked through a simple Graphical User Interface (GUI), this developed interface is functional and flexible to facilitate water quality control.
•
Reports of various types are made to support water quality management requirements. They can be graphical charts, geo-referenced maps or tabular reports.
•
The developed system is able to support multi-users for multitasks using a variety of data types simultaneously.
•
Therefore this study might assist the decision makers in the pollution management and improve water quality upstream Cairo drinking water plants..
