Räumliche und zeitliche Konsolidierung in der Abwasser-Qualitätsüberwachung [Elektronische Ressource] : eine Fallstudie aus dem El-Salam Kanal-Projekt in Ägypten / vorgelegt von Mohamed Shaban Mohamed Abu-Salama

Mohamed Aboulola

Sujets

• Social work

Informations

• Publié par: leuphana_universitat_luneburg
• Publié le: 01 janvier 2007
• Nombre de lectures: 46
• Langue: Deutsch
• Poids de l'ouvrage: 8 Mo

Extrait

UNIVERSITÄT LÜNEBURG
Fakultät III
Umwelt und Technik





RÄUMLICHE UND ZEITLICHE KONSOLIDIERUNG IN DER
ABWASSER-QUALITÄTSÜBERWACHUNG:
EINE FALLSTUDIE AUS DEM EL-SALAM KANAL-PROJEKT IN ÄGYPTEN





Dissertation


zur Erlangung des akademischen Grades eines
Doktors der Naturwissenschaften
(Dr. rer. nat.)



vorgelegt von

Mohamed Shaban Mohamed Abu-Salama

aus Kairo, Ägypten
2007


1. Gutachter : Prof. Dr. Wolfgang Ruck
2. Gutachter : Prof. Dr. Brigitte Urban
3. Gutachter : Prof. Dr. Holger Wildhagen



UNIVERSITÄT LÜNEBURG
Fakultät III
Umwelt und Technik





SPATIAL AND TEMPORAL CONSOLIDATION OF DRAINAGE WATER QUALITY
MONITORING NETWORKS:
A CASE STUDY FROM THE EL-SALAM CANAL PROJECT IN EGYPT






Dissertation

A Thesis Submitted for the Fulfillment of the Requirements for
The Degree of Doctorate in Natural Sciences
(Dr. rer. nat.)




Submitted by

Mohamed Shaban Mohamed Abu-Salama
From Cairo, Egypt
2007



1. Refree : Prof. Dr. Wolfgang Ruck
2. Refree : Prof. Dr. Brigitte Urban
3. Refree : Prof. Dr. Holger Wildhagen


VERSICHERUNG
Ich versichere, dass ich die eingereichte Dissertation Spatial and Temporal
Consolidation of Drainage Water Quality Monitoring Networks: A Case Study from
the El-Salam Canal Project in Egypt selbst ndig und ohne unerlaubte Hilfsmittel
verfasst habe. Anderer als der von mir angegebenen Hilfsmittel und Schriften habe
ich mich nicht bedient. Alle wrtlich oder sinngem den Schriften anderer
Autorinnen oder Autoren entnommenen Stellen habe ich kenntlich gemacht.

Name: Mohamed Shaban Mohamed Abu-Salama

Datum: 13 July 2007

Unterschrift:

?
?
?I
ACKNOWLEDGMENT
I would like to express my sincere gratitude and appreciation to Prof. Dr. Wolfgang Ruck,
Prof. Dr. Brigitte Urban and Prof. Dr. Holger Wildhagen for their continuous encouragement,
support, advice and skillful guidance to make the completion of this study possible.
Particular mention must be made to Dr. Rolf Hübener, whose sincere efforts extended to
more than a scientific guidance, his endless support and encouragement, have continued
since the author came to Germany.
Grateful thanks and appreciation are due to Prof. Dr. Shaden Abdel-Gawad, the chairperson
of the National Water Research Center, Ministry of Water Resources and Irrigation in Egypt,
for her continuous valuable guidance throughout my professional career.
Also, I would like to extend my appreciation to the staff of my home institution (Drainage
Research Institute) for their encouragement and support.
Last but not the least; I am very grateful to Nescha Maria Hofer for her co-operation and
being by my side all the time in my study.


Mohamed Shaban Mohamed Abu-Salama














II
SPATIAL AND TEMPORAL CONSOLIDATION OF DRAINAGE WATER QUALITY
MONITORING NETWORKS:
A CASE STUDY FROM THE EL-SALAM CANAL PROJECT IN EGYPT
ABSTRACT
The El-Salam Canal Project aims at increasing the Egyptian agricultural productivity through
agricultural and stock development by irrigating about 263,500 ha gross of new lands.
In order to stretch the limited water supply to cover these new reclaimed areas, fresh River Nile
water is augmented with agriculture drainage water from Hadus and Lower Serw drains, which
receive almost all kinds of wastes. The overall objective of this research is to introduce a
rationalization technique for the drainage water quality-monitoring network for Hadus drain as a
main feeder of El-Salam Canal Project. Later on, this technique may be applied for other parts in
the National Water Quality Monitoring Program in Egypt.
The rationalization process started firstly with assessing and reformulating the current objectives
of the network. Then, the monitoring locations were identified using integrated logical and
statistical approaches. Finally, a sampling frequency regime was recommended to facilitate
proper and integrated information management.
As a result, the monitoring network was divided into three priority levels (Layers I, II and III) as
following:
• Layer I: highest priority level and includes eight monitoring locations
• Layer II: second priority level and includes three locations
• Layer III: lowest priority level and includes five locations
These results were validated using three integrated statistical methods. The validation results
ensure that excluding the monitoring locations in layer III does not significantly affect the
information produced by the monitoring network.
Based on the evaluation of sampling frequencies, it is recommended to have 6 (instead of 12)
samples per year for 18 (out of 36 examined) parameters (COD, TSS, TVS, N-NO , Pb, Ca, Na, 3
Cl, Visib, BOD, Cu, Fe, Mn, pH, TDS, K, SO and DO). The measured parameter SO will 4_m 4_m
automatically replace the SO (calculated). SAR and Adj. SAR also can be calculated from the 4
other parameters. For the other fifteen parameters (Mg, EC, Br, Ni, Sal, Cd, TN, TP, Temp,
Fecal, Coli and N-NH , Zn, P and Turb), it is recommended to continue with 12 samples/year. 4
These recommendations may ensure significant reduction in the total cost of the monitoring
network. This facilitates a fiscal resource, which is a key prerequisite in developing a successful
program. The rescued budget can be redirected to achieve better performance in terms of
improving the current resources. In addition, a frame of stakeholders-participation mechanism
was proposed to ensure better water quality management in the project area.
III
TABLE OF CONTENTS

ACKNOWLEDGMENT I
ABSTRACTI
LIST OF FIGURES VIII
LIST OF TABLES XI
ABBREVIATIONS XIII
CHAPTER 1
1. ENVIRONMENTAL ASPECTS OF IRRIGATED AGRICULTURE IN EGYPT 1
1.1 INTRODUCTION 1
1.2 WATER DELIVERY SYSTEM 2
1.3 IRRIGATION PRACTICES 3
1.4 SPECIFIC SOIL WATER ISSUES 5
1.5 AGRICULTURAL DRAINAGE 6
1.6 DRAINAGE WATER REUSE 9
1.7 DRAINAGE WATER QUALITY MONITORING 11
1.8 PROBLEM DEFINITION 14
1.9 OBJECTIVES 16
CHAPTER 2
2. EL-SALAM CANAL WATER QUALITY MONITORING OBJECTIVES 18
2.1 WATER QUALITY MONITORING OBJECTIVES 18
2.1.1 Purposes of Monitoring 19
2.1.2 Complexity Regarding Definition of Monitoring Objectives 24
2.2 EL-SALAM CANAL MONITORING OBJECTIVES 25
2.2.1 Compiling the Available Information 25
2.2.2 Developing Brief Description of the System 26
2.2.3 Stakeholder Analysis 27
2.2.3.1 Stakeholder Groups 27
2.2.3.2 Stakeholder Participations 37
2.2.3.3 Stakeholders/Objectives Matrix (SOM) 37
2.2.3.4 Stakeholders/Objectives Matrix Analysis 39
2.3 MONITORING OBJECTIVES RESULTS AND DISCUSSIONS 39
IV
CHAPTER 3
3. NETWORK DESIGN FUNDAMENTALS AND STATISTICAL EVALUATION 47
3.1 SAMPLING SITES 47
3.2 METHODS FOR LOCATING SAMPLING SITES 48
3.2.1 Early Practices 48
3.2.2 Site Selection to Comply with Monitoring Objectives 49
3.2.3 Systematic Approaches 50
3.3 SAMPLING FREQUENCY 53
3.4 METHODS FOR DETERMINIG SAMPLING FREQUENCY 54
3.4.1 Sampling Frequency to Comply with Monitoring Objectives 54
3.4.2 Statistical Methods 55
3.4.2.1 Checking Compliance with Standards 55
3.4.2.2 Determination of the True Mean Values of Water Quality Variables 56
3.4.2.3 Detecting Trends 57
3.5 PRINCIPELES IN STATISTICAL EVALUATION 60
3.5.1 Parametric and Nonparametric Approaches 60
3.5.2 Wilcoxon Signed Rank Test 63
3.5.3 Factor Analysis (FA) 64
3.5.3.1 Principle Component Analysis (PCA) 64
3.5.4 Cluster Analysis (CA) 65
3.5.5 Multivariate Analysis of Variance (MANOVA) 66
3.5.6 Discriminant Function Analysis (DFA) 67
3.6 MULTIVARIATE ANALYSES AND ENVIRONMENTAL MONITORING 68
CHAPTER 4
4. SAMPLING SITES FOR HADUS DRAIN MONITORING NETWORK 74
4.1 PRELIMINARY ANALYSES 74
4.1.1 Spatial Analysis 74
4.1.2 Data Screening and Detecting Outliers 78
4.1.3 Descriptive Statistics, Check Normality and Dependency 79
4.2 PRELIMINARY RESULTS 80
4.2.1 Data Inspection 80
4.2.2 Check Normality 80
4.2.3 Check Dependency 82
4.3 SIMILARITY ANALYSIS 84
4.3.1 Means 84
V
4.3.1.1 Factor Analysis and Principle Components 84
4.3.1.2 Hierarchical Cluster Analysis (HCA) 87
4.3.1.3 Discriminant Function Analysis (DFA) 87
4.3.2 Yearly Averages 91
4.3.2.1 Results and Interpretation for Site Group 1 91
4.3.2.1.1 Multivariate Analysis of Variance (MANOVA) 91
4.3.2.1.2 Discriminant Function Analysis (DFA) 96
4.3.2.2 Summary Results for All Site Groups 100
4.3.3 Monthly Data 107
4.3.3.1 Results and Interpretation 107
4.3.3.1.1 Nonparametric Comparisons 107
4.3.3.1.2 Correlation and Regression Analyses 111