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Master Thesis
submitted within the UNIGIS MSc programme at the Department of Geoinformatics - Z_GIS
University of Salzburg
Data-Management Practices in the Komati River Basin Project
By
Mfundi Easter Mathunjwa
103160
A thesis submitted in partial fulfilment of the requirements of the degree of
Master of Science (Geographical Information Science & Systems) – MSc (GISc) Advisor:
Ann Olivier
Pigg’s Peak, Swaziland – 17 September 2016
- 2 - Acknowledgement
It is customary that we recognise and be grateful to all those who provide significant help in the accomplishment of something. My greatest gratitude is also due to the very many fellows that have contributed to the Geographical Information Systems and Science field.
I am particularly humbled by the support given – and I would express my indebtedness to my supervisor, Ms Ann Olivier – for the implicit contributions, astute comments, guidance and support in my Master’s programme and the thesis.
I also owe appreciation to my former supervisor at my workplace, Dr J.D. Dlamini, since without his inspiration and encouragement, it would have been difficult to carry out this research project.
I also give special recognition to Ms Thobekile Zikhali, who provided invaluable information and referrals, where necessary. A big word of appreciation goes to Komati Basin Water Authority (KOBWA); since without their support, this research would not have been completed. I would also like to mention the Chief Executive Officer, Mr Collin Zwane.
To all those who directly and indirectly have contributed to the success of this study, I maintain that it has been an incredible journey.
Thank you – all you good people.
God bless you all.
- 3 - Science Pledge
By my signature below, I certify that my thesis is entirely the result of my own work. I have cited all the sources I have used in my thesis; and I have consistently indicated their origin.
_______________________________________________________________
(Place, Date) (Signature)
- 4 - Abstract
The Komati River Basin is an international drainage basin, the water resources of which are shared between South Africa, Swaziland and Mozambique. With the approval of the Government of Mozambique, which was experiencing civil strife at the time, the Governments of South Africa and Swaziland entered into an agreement; and in 1992, they signed a Treaty on the development and utilisation of the water resources of the Komati River Basin.
Also in 1992, they signed a Treaty establishing a Joint Water Commission (JWC), the mandate of which, among others, was to provide technical support to the two countries on all matters pertaining to water resources, planning, development, utilisation and management. The Komati Basin Water Authority (KOBWA) is the JWC’s implementing agency – with the authority to operate across both countries – the aim of which was to reduce water shortages and to eliminate the vulnerability to droughts.
The water and environmental management activities of KOBWA involve collation and the generation of hydrological and geo-hydrological data in the Komati Basin.
However, in carrying out its mandate, KOBWA faces a lot of challenges with data and information management being two of the key, yet very crucial components, when sharing common pool resources. The government of Swaziland and that of South Africa conducted geo-hydrological assessment and mapping studies in their respective parts of the basin.
The Komati Basin Water Authority (KOBWA) and the riparian states conducted separate groundwater monitoring programmes in the same basin. More data and information are produced on a daily basis; as KOBWA performs its functions.
However, most of the data and information, especially that which is in electronic format, are collected from different sources, in different formats, and are scattered in different workstations at the different centres of KOBWA. Some of the available data allegedly lack cohesion and completeness.
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Therefore, this study aims to understand what data-management practices exist in the Komati River Basin, and to investigate the extent of their effectiveness. The results of the study will benefit all the relevant stakeholders in South Africa and Swaziland.
The indirect benefits would go the communities dependent on the river basin for their living, i.e. the effective management of the data could result in assurance of water flows to both countries.
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Acknowledgements 2
Science Pledge 3
Abstract 4
Table of Contents
1. Introduction 10
1.1 Motivation 11
1.2 Problem Description 11
1.3 Research Objectives and Question 13
1.3.1 Research Objectives 13
1.3.2 Research Question 13
1.3.3 Hypotheses 14
1.4 Limitations 14
1.5 Significance of Research 14
1.6 Framework of the Thesis 14
1.7 Conclusion 15
2. Study Area (Komati River Basin) 16
2.1 Introduction 16
2.2 Location 17
2.3 Legal and Institutional Set-up 18
2.4 Hydrological and Geo-hydrological issues 22
2.5 Conclusion 23
3. Literature Review 24
3.1 Introduction 24
3.2 Definition of data/information-management practices 26
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3.3 International data-management practices 28 3.4 Benefits of good data-management practices 29
3.5 Data management in geo-hydrology 29
3.6 Water-resource management information systems 30 3.7 Implementation of data-management practices using GIS 31
3.8 Data-management practices 32
3.9 Conclusion 35
4. Methodology 36
4.1 Introduction 36
4.2 Study area 36
4.3 Research approach 38
4.3.1 Qualitative data 40
4.4 Research method 41
4.5 Research design 41
4.6 Sampling methods 42
4.7 Data-collection techniques 43
4.8 Data Analysis 44
4.9 Research Instruments 44
4.10 Selecting the participants 44
4.11 Interviews 45
4.11.1 Questionnaires 46
4.12 Data requirements – KOBWA 46
4.13 Importance of data 47
4.14 Data-collection procedures – KOBWA 47 4.15 Limitations in methods, data collection and analysis 48
4.16 Conclusion 49
5. Results and Discussion 50
5.1 Introduction 50
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5.2 Results and discussions 51
5.2.1 Field-work analysis 51
5.3 Interpretation of the main findings 53
5.4 Status of results 54
5.5 Gaps and problems 56
5.6 Other distinct practices 56
5.7 Relevance to the literature 57
5.8 Discussion 58
5.9 Conclusion 60
6. Conclusion and Recommendations 61
6.1 Conclusion 61
6.2 Author’s note 63
6.3 Recommendations 63
6.3.1 Recommendations (other) 64
List of Figures
Figure: 1.1 Defined Map of Komati River Basin
Figure: 2.1 Map showing Study Area Operated by KOBWA
Figure: 2.2 Institutional Framework for managing the Komati River Basin Figure: 3.1 Data Model – Showing how data management spans the practices Figure: 4.1 Schematic layout of study area
Figure: 4.2 Focus of the Study Area
List of Tables
Table: 2.1 Historical agreements, which influenced the water management in the catchment area.
Table: 2 .2 Major Dams in the Komati-River Basin Table: 5.1 Participants Interviewed
Table: 5.2 Current data practices found to be in place or used.
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References 65
List of Acronyms 68
Appendices 69
- 10 - CHAPTER 1 – INTRODUCTION
Chapter 1 Introduction – introduces the background of the study/research focusing on the Komati-River Basin.
1. Introduction
I understand that a good information management provides the essential data necessary, in order to be able to make informed and transparent decisions. As described, information is generated, managed and used by the related stakeholders in the water-resource environment.
The Komati-River Basin (KRB) is an international drainage basin, the water resources of which are shared between South Africa, Swaziland and Mozambique. With the approval of the Government of Mozambique, which was experiencing civil strife at the time, the Governments of South Africa and Swaziland entered into an agreement, and in 1992, they signed a treaty on the development and utilisation of the water resources of the Komati-River Basin (KRB).
Also signed in 1992 was a treaty establishing a Joint Water Commission (JWC), the mandate of which was to provide technical support to the two countries on all matters pertaining to water resources, planning, development, utilisation and management of the water resources.
The Komati-Basin Water Authority (KOBWA) is the Joint Water Commission (JWC) implementing agency, with the authority to operate across both countries.
The aim was to reduce water shortages and to eliminate the vulnerability to droughts.
- 11 - 1.1 Motivation
The water and environmental management activities of Komati Basin Water Authority (KOBWA) involve the collation and generation of hydrological and geo- hydrological data in the Komati-River Basin (KRB). However, in carrying out its mandate, KOBWA faces a lot of challenges with data and information management being two of the key, yet very crucial components, when sharing the common resources.
The two governments – that of Swaziland (SD) and that of the Republic of South Africa (RSA) – conducted geo-hydrological assessment and mapping studies in their respective parts of the basin. The Komati Basin Water Authority (KOBWA) and the riparian states conducted separate groundwater monitoring programmes in the same basin.
More data and information are produced on a daily basis; as KOBWA performs its functions. However, most of the data and information, especially those in electronic format, are collected from different sources, in different formats, and are scattered in different workstations that are at different sites of KOBWA. Some of the available data allegedly lack cohesion and completeness.
1.2 Problem Description
The Komati-River Basin (KRB), despite being small compared to other international basins, is of strategic importance in the region; as it provides services for substantial agricultural practices, which in turn contribute to the economic growth, but also to maintaining the entire basin.
KOBWA needs sufficient and up-to-date data and information on water quality and quantity and the spatial and temporal trends, in order to operate and manage the system effectively and efficiently. The data are required to support decision- making on systems’ operation (water supply and demand management), managing risk and uncertainty, dam safety, as well as environmental management.
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The Komati-Basin Water Authority (KOBWA) conducted studies in the river basin, which aimed at reducing the gap by identifying the potential availability of the hydrological and geo-hydrological data throughout the Komati-River Basin; but unfortunately, it was discovered that the data allegedly lacks a lot of cohesion and completeness.
As the geo-hydrological and hydrological data have become essential tools for water-resource managers, most integrated management-information systems have a least three functional components, namely:
- Data acquisition;
- Data storage and management;
- Information generation and dissemination.
It has also been recognised that there is a fourth component: the complex knowledge products (CKPs) that present the reports, documents, decisions and recommendations that are used in conducting the business of water resource management (DWAF, 2000, Harris et al., 2001). It is perceived to be a common experience that the focus in the development of data and information systems management has been on establishing the first three components, with much less attention being given to the other components.
The author observed that most organisations dealing with the data and the spatial information needed to consider the following issues:
Data storage, quality assurance (metadata) and quality control (data checks);
Spatial-data management;
Information products for decision support;
Information dissemination;
Data integrity (centralised data/elimination of duplication);
Data security;
Ways to improve data-management practices.
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Therefore, this study aims to understand what data-management practices exist in the Komati-River Basin, and also to investigate the extent of their effectiveness.
The results of the study will benefit all the relevant stakeholders in South Africa and Swaziland.
1.3 Research Objectives and Questions
The study’s overall aim is to interrogate the data-management practices at Komati Basin Water Authority (KOBWA) and to ascertain the practices and the use of international best practices and standards that can improve the data practices at KOBWA.
1.3.1 Research Objectives
The main objective of this research work is to understand what data-management practices exist in the Komati-River Basin and to investigate their effectiveness.
To achieve this general objective, the following specific objectives have been formulated.
1. What data-management practices exist within the Komati-River Basin Project?
1.3.2 Research Question
On the basis of the above-defined specific objectives, the following research questions have been proposed.
1. What constitutes sound data practices?
2. To what extent are the Komati-River Basin data-management practices effective?
3. If not effective, what can be done to improve the effectiveness of the data management practices?
- 14 - 1.3.3 Hypothesis
The premise of this research is that there are data practices that have not been developed, or are not being employed. Once these are employed, best-data management practices can be improved at the Komati-Basin Water Authority.
1.4 Limitations
The limitation of this research is mainly resources. Other limitations are related to the choice of research methods, the data practices applied, and the small sample group. The case under this study would have gained the fullest understanding – if both quantitative and qualitative methods had been employed.
Furthermore, additional data sources covering documents from previous studies conducted would be very helpful in achieving optimal and detailed evidence of inquiry. These, and other potential limitations, are further discussed in Chapter Five (Results and Discussion).
1.5 Significance of Research
The results of this research should inform the wider stakeholders found in the Komati River Basin/Catchment. They should also bring indirect benefits to the communities in the catchment – for their living – and for the effective management of the data. This could result in the assurance of flows to both countries (Swaziland and South Africa).
1.6 Framework of the Thesis
The outputs from this study will be presented as follows:
Chapter 1
Introduction – This chapter introduces the background of the study for data- management practices in the Komati River-Basin Project.
- 15 - Chapter 2
Study Area – This chapter presents the general features of the study area;
comprising the hydrological and geo-hydrological features in the Komati-river basin.
Chapter 3
Literature Review – This chapter provides an overview of the data-management practices used in different sectors and in other parts of the region.
Chapter 4
Methodology – This chapter describes the methods of data collection and their analysis to find the answers to the research questions.
Chapter 5
Results and Discussion – This chapter presents the main findings of the analysis of the data, together with a better understanding of the geo- hydrological/hydrological information and data.
Chapter 6
Conclusion and Recommendation – This chapter summarises the findings of the study and provides a proposed set of recommendations to the Komati-River Basin.
1.7 Conclusion
In summary, it would be expected that institutions should employ specific data management protocols. This leads to the fact that the information and the data generated by organizations cannot be directly utilized by any other parties – thereby leading to the allegedly incomplete gaps in the information.
The next chapter, which is Chapter 2, therefore, presents an overall framework, together with the general features of the study area, as well as the hydrological and geo-hydrological features in the Komati-river basin.
- 16 - CHAPTER 2 – THE STUDY AREA
This Chapter 02, the Study Area – will present the general features of the study area: the location, the legal and institutional set-up, the hydrological and geo- hydrological features in the Komati-river basin (KRB).
2.1 Introduction
In the previous chapter, I presented an introductory statement describing the background of the study/research focusing on the Komati-River Basin (KRB). I further presented the problem statement, the research objectives, whereby I needed to understand what data-management practices exist in the Komati- River Basin and to investigate their effectiveness, together with a framework for the thesis. It is crucial that we appreciate data-management practices on a broader scale, in order to understand the benefits thereof.
Having outlined the background for the purpose of this research, I now present the second chapter, which will present the study area in a more detailed manner as the management of water resources in a shared river basin forming the border between two countries. This is a complex and challenging matter – particularly in the area of operation.
The challenges that are experienced in the Komati-Basin Water Authority (KOBWA) area of operation emanate from the previous studies that have been conducted. Thus, KOBWA had to start and develop the components of a data- management and information system, in order to support their operational decision-making.
It is undoubtedly true for the Komati Basin Water Authority (KOBWA) that was established to manage the water resources in the Komati-River Basin.
- 17 - 2.2 Location
The study for the research will focus on the area currently operated by the Komati-Basin Water Authority (KOBWA). The area of operation starts from the two dams, Maguga and Driekoppies moving down to the confluence of the Komati and Crocodile Rivers at Komatipoort. This comprises two major rivers, the Komati and the Lomati Rivers. The length of the Komati and the Lomati River in the area of operation from Maguga to Driekoppies dam is approximately 117 and 192 kilometres (kms) respectively. The Komati River (KR) originates from the Drakensburg Mountains in the Republic of South Africa. It then passes through the northern part of Swaziland before flowing back to the Republic of South Africa and joining the Crocodile River near the border in Mozambique at Ressano Garcia, where it is called the Incomati.
The Komati-Basin Water Authority conducts its extensive business downstream of Maguga dam, which is on the Komati River. It has a tributary, namely the Lomati River, which releases its flow into the Driekoppies dam near the Schoemansdal area in South Africa.
Figure: 2.1 Defined Map of Komati River Basin – Source: (Map generated by author)
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Figure: 2.2 Map showing Study Area Operated by KOBWA - Source: (Map generated by author)
2.3 Legal and Institutional Set-up
Project Scope – KOBWA is a binational company formed in 1993 through the treaty on the development and utilization of the water resources of the Komati River Basin, signed in 1992 between Swaziland and South Africa. The primary purpose of KOBWA is to implement the design, construction, operation and maintenance of the Driekoppies dam in South Africa and the Maguga dam in Swaziland.
The water-resource management in the Komati river basin is based on a legal and institutional framework that is internationally related. The national water legislation in each country since 1998 has emphasized the principles of Integrated Water-Resource Management (IWRM) and information and data management sharing for the better management of the water resources.
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The member states adopted certain trans-boundary agreements that were in line with the establishment of such institutions as the Komati-Basin Water Authority (KOBWA); so that, it could play a crucial role in effectively managing the water resources. In light of the need for such legal settings, a number of institutions at the national and trans-boundary level have been created to address water- sharing issues and environmental integrity.
The roles and responsibilities of these institutions, and how they interact with each other in the management of the Komati-River Basin are fully described in Figure 2.3 below.
Figure: 2.3 Institutional Framework for managing the Komati-River Basin (Source: acwr, 2006)
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JWC is a Joint Water Commission that has responsibility for the overall water governance in the Komati-River Basin.
TPTC is the Tripartite Permanent Technical Committee, which involves the interest of Mozambique on the issues of water governance and policy.
KOBWA is the Komati-Basin Water Authority, which has a responsibility and project authority for the management and operational issues that fall within the scope of the Komati-River Basin Development Project Phase.
ISOTG is the Incomati Systems Operations task Group that assists in developing operating rules for the Incomati basin, with the main focus on the Komati catchment, to make sure that KOBWA could successfully operate certain projects, such as Maguga and Driekoppies (InWEnt &
KOBWA, 2009).
KJOF is the Komati Joint Operations Forum, which facilitates communication and discussions between KOBWA and the stakeholders on the system’s operations.
Most international and regional river basins consist of member states that are driven by the need to preserve their independence in the trans-boundary interactions. They are also concerned with the fairness of the negotiations in their respective countries; and whether they have adequate capacity to ensure fair outcomes. South Africa is listed as a fundamental state – due to the high level of economic developments, which make it more dependent on the shared river;
while Swaziland and Mozambique are considered to be under-impacted states (i.e.) highly depended on water, but less able to negotiate fair deals (Jacobs, 2010).
Apart from the whole framework for managing the Komati water, as shown in Figure 2.3, the national water legislation in each country since 1998 has emphasized the principles of Integrated Water-Resource Management (IWRM)
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and information sharing for the better management of shared resources.
Historical trans-boundary agreements have also played a crucial role and even allowed for the establishment of new institutions that are responsible for effectively managing and monitoring the way water is used. These are briefly mentioned by using information provided by (InWEnt & KOBWA, 2009) as follows.
Table 2.1: Historical agreements, which influenced the water management in the catchment area
Year Agreement
1983 Agreement between the Government of South Africa and Mozambique relative to the Establishment of a Tripartite Permanent Technical Committee (TPTC)
1991 Pigg’s Peak agreement between Swaziland, South Africa and Mozambique for the implementation of the Komati-River Basin Development Project.
1992 Treaty between Swaziland and South Africa in the establishment and functioning of the Joint Water Commission (JWC) as a technical adviser to the parties on issues related to the utilization of shared water resources.
1992 Treaty on the development and utilization of the water resources of the Komati-River Basin signed between South Africa and Swaziland, which led to the establishment of KOBWA.
2002 Tripartite Interim Agreement between Mozambique and South Africa and Swaziland for co-operation on the Protection and Sustainable
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Utilization of the water resources of the Incomati and Maputo watercourses (IncoMaputo agreement)
2.4 Hydrology and Geo-hydrology
The study area, as shown above in Figure 2, is situated in the summer rainfall region; and the basin receives its highest rainfall between December and February. The rainfall ranges from 600 mm/a to 1, 200 mm; and the evaporation varies from 1400mm to 1600mm from the western Highveld to the Eastern Lowveld. The virgin mean annual run-off (MAR) of the basin is about 1420 mm per annum (Enoch M. Dlamini et al., 2007).
The hydrology of the catchment is impacted by the infrastructures that regulate the water to be allocated amongst different water users. The dams along the river routes mainly have the biggest influence. The largest dam is Maguga dam located in Swaziland on the Komati River, which is approximately 22 kilometres away from Pigg’s Peak town. The second largest is Driekoppies dam on the Lomati River, located in the Republic of South Africa approximately 13 kilometres away from the Jeppes Reef border post in the Mpumalanga region.
Table 2.2: Major Dams in the Komati River Basin
Name of Dam Natural MAR (mm) Dam Capacity (mm)
Full Supply Area (km2)
Maguga dam 794.4 332 10.4
Driekoppies dam 241.7 251 18.7
The geo-hydrology of the study areas is characterized by different types of aquifers due to the complex and changing geological environment of the Komati river basin. The basin displays aquifers of the secondary or fractured rock types, as well as the primary or inter-granular type. There are shallow weathered aquifers throughout the basin. These aquifers display unconfined conditions; and they have a regional water table that mimics the topography.
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It is the author’s view that the study area selected in the Komati River Basin will assist in focusing on the data and the information-management practices that have become essential tools for the management of the water resources The structures presented in the previous chapters show that organisations like KOBWA are bound to generate volumes of data and information during their planning and during the construction stages of the various water-related development projects in the Komati Basin.
Having explained the focus of the study area for this thesis, the results that will be obtained in the area (KOBWA’s area of operation) are defined in Figure 2.2.
These should benefit all the relevant stakeholders in South Africa and Swaziland.
Indirect benefits will also be realised; and they would go to the communities dependent on the river basin for their living.
2.5 Conclusion
The next chapter will describe and provide an overview of the data-management practices used in different sectors, and in other parts of the region. This will be achieved through a literature review for a better understanding of the geo- hydrological information and the data in the Komati-river basin.
- 24 - CHAPTER 3 – THE LITERATURE REVIEW
This chapter provides an overview of the data-management practices used in different sectors in other parts of the region.
3.1 Introduction
According to Leedy (1980:64), the literature review serves different purposes to the researcher, And, “among others, it reveals methods of dealing with similar circumstances that might, in turn, reveal information, which may not have existed”. The literature review helps the researcher to delineate and streamline the problem, and to place it in its rightful context.
The purpose of the literature review is to provide the reader with a general overview of the data and information-management practices. In this context, the literature to be reviewed will incorporate data-management practices in a trans- boundary water governance system.
Considering the interdisciplinary nature of the water issues, water-resource management in a trans-boundary basin requires organizing the way data and information are produced and shared to meet the stakeholders’ expectations for numerous activities. Managers of trans-boundary basins must be able to obtain reliable, up-to-date and relevant information when they need it – and in a form that suits the data requirements.
In the previous chapter of the thesis, the author discussed the study area, with its general features being mainly the location, legal and Institutional set-up, as well as the hydrological and geo-hydrological features in the Komati river basin (KRB).
Chapter Two of the research provided a good platform for the reader to locate the associated geographical characteristics of the study area, given that the national water legislations of each country have emphasized the principles of integrated water-resource management and the sharing of data management for better management.
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It is the author’s experience that a good information-management plan provides the essential data necessary to be able to take informed and transparent decisions. As described above, information is generated, managed and used by the water-related stakeholders. Most of the basic institutional roles in integrated river-basin management (IRBM) belong to the public domain; while the services are often provided by private institutions.
Therefore, in order to obtain the theoretical foundations, methods and techniques, the author will have to go through different source of literature on geohydrology for the Komati River Basin (KRB), collating all the existing geo- hydrological monitoring and assessment manuals and guidelines for South Africa and Swaziland, together with information that has been obtained from previous studies conducted in the Komati River Basin over the past years, since the inception of the water-resource projects.
In line with the National Water Act for 1998, South Africa proposed the implementation of the Komati Basin Water Authority (KOBWA) for managing the Komati River Basin, which excludes Mozambique, “as if the river ends at the Ressano Garcia border; whereas the Incomati flows 280 kilometers further through Southern Mozambique before ending in the Maputo Bay” (Leestemaker, n.d).
Article 4(i) of the Inco-Maputo Agreement (2000:6) stipulates the responsibility of the riparian states to exchange information on the quality of the water resources, the quantity, and the use of the water.
Exchanging information amongst riparian states is still a challenge. Similarly, the SADC Revised Protocol (2000:4) encourages states to exchange available information and data on the hydrological, hydro-geological, water quality, meteorological and the environmental condition of the shared watercourses.
Kistin (2007) argues that information-sharing is very challenging because of the issues of data availability, compatibility and occasional reluctance on the part of the riparian states. She further argues that although, there is a SADC’s
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Hydrological Cycle observing system (SADC-HYCOS), access is restricted by passwords, which limit water-resource managers to access data generated in their own country. There are also allegations of the Incomati states withholding data from each other.
3.2 Definition of data and Information-management practices
Researchers have not yet agreed on a common definition of data management.
There is a lack of conceptual clarity with regard to such terms as maintenance, practices and stewardship, which underpin the management of research data;
and no clear distinction exists between these terms. Nevertheless, in this study, the term data management was employed, bearing in mind its limitations.
In one of the reports on data curation in the UK, Lord and Macdonald used the terms data curation and stewardship interchangeably (2003). Whilst they distinguished between curation, archiving and the preservation of data, and offered working definitions of these terms, they employed curation to describe the creation, management and long-term care of research data (2003, p. 5), thereby using curation as an overarching term (2003, p. 12).
Reflecting this broad approach, their current refined definition states concisely:
“Digital curation involves maintaining, preserving and adding value to digital research data throughout their lifecycle” (Digital Curation Centre, 2012).
The motto of the DCC states: “Because good research needs good data”.
Likewise, Geller (2010), in her discussion of intellectual property on the issue of data management, defined data management as part of a regular, good research practice:
Although some researchers may be resistant to instituting and maintaining good data-management practices in their laboratories, such data management, which requires accurate and contemporaneous recording of data, is nothing more than good scientific practice (Geller, 2010).
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The Merriam-Webster Dictionary (2005) defines data as “factual information (as measurements or statistics) used as a basis for reasoning, discussion or calculation.”
The CCSDS (2002/2012) p20) defines “Data” as re-interpretable representation of information in a formalised manner suitable for communication, interpretation or processing.
Struwig and Stead (2010) define data as information, such as pictures, words, and numbers that are gathered, according to certain scientifically acceptable procedures.
Data management refers to an organisation and data for secure and structured access and storage. Data management encompasses a variety of different techniques that facilitate and ensure control and flow from creation to processing, utilisation and deletion.
The NFS (2011); explains “Data Management” as the planning of policies for the management of data types, formats, metadata, standards, integrity, privacy, protection, confidentiality, security, intellectual property rights, dissemination, distribution archives and access.
Data management is implemented through a cohesive infrastructure of technological resources and a governing framework that defines the administrative processes used throughout the lifecycle of the data. Using best practices through all stages of working with data would ensure the accessibility and longevity of the data.
According to various university libraries, developing a data-management plan (DMP) at the beginning of a new project would inform good practice throughout the data cycle. The following practices are fundamental to effective data management and can be applied to all disciplines:
Data-management plan – there should be a complete data-management plan; so that it would not be side-lined, when collecting the data.
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Data sharing – to prevent the data and information from being lost because of poor management.
Data documentation – use metadata to record the details of a study.
Ethical issues – sensitive information in data should be redacted before depositing into a public archive or repository.
Sharing data – datasets should include metadata and all the details pertinent to a study.
Wilson et al. (2010) described data management as a series of activities along the research lifecycle, which “involve all the processes that information from research inputs undergoes, as it is manipulated and analysed en route to becoming a study output” (Wilson et al., 2010). They were defined from the perspective of two communities involved in research – those involved in data protection, and in repositories and researchers who organize data in databases.
Data management has been on the agenda during the last two decades (ARL/NSF Workshop, 2006). However, managing data is not a new aspect of the research setting. The first data archives were established in the 1960s to archive survey data from the social sciences; and these were also the first archives of electronic material (Doorn & Tjalsma, 2007).
From the beginning, the research archives were supposed to serve three specific aims: data verification, reuse and historical value (2007). Furthermore, early examples of data services in libraries were in Geographical Information Systems (GIS), bioinformatics (Gold, 2007b) and the social sciences (Gold, 2007b;
Ogburn, 2010).
3.3 International Data-Management Practices
A wider literature confirms that data-management practices link and include four major data-lifecycle management processes that:
Fulfil departmental, institutional organizational policies and data- management requirements.
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Provide data creations (primary, secondary, tertiary data) data publication, minimal data descriptions.
Facilitate added value (metadata) management and the storage of archived data over the lifecycle of the data.
Integrate a series of technical and strategic actions and consultations to ensure ongoing data authenticity.
3.4 Benefits of good data-management practices
Data-management practices are particularly important in any organisation, especially when such data and information need to be shared. The benefits of data-management practices are:
- More efficient data management (including updates and security);
- Increased data sharing;
- Higher quality data;
- Improved data consistency;
- Increased data integration;
- Better understanding of data; and
- Improved documentation of information resources.
3.5 Data management in Geo-Hydrology
The area of geohydrology processes is one of the primary areas of study in the literature reviewed for this research; thus, it would include the existing groundwater monitoring data in the Komati River Basin; since this is being explored to bring new insights and results on the better understanding of the geo- hydrological information and data in the basin.
The author reviewed literature on the data-management practices in trans- boundary water governance. In the literature reviewed, I noticed that a huge gap exists on the specific data-management practices. Most of the literature pointed to Geographic Information Systems (GIS) and looked at the practices in a more general way, rather than in a critical manner. I will fill this gap by directing the
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study to the Komati River Basin, which is to a large extent viewed as a good measure of bilateral water sharing – nevertheless, it still struggles with the various data-management systems.
Volumes of data and information have been generated during the study, planning and construction stages of various water-related development projects in the Komati Basin.
More data and information are produced on a daily basis; as the Komati Basin Water Authority (KOBWA) performs its functions. However, most of the data and information, especially that in electronic format, can be collected from different sources, in different formats and are scattered in different workstations at the different centres of KOBWA.
Therefore, KOBWA has embarked on an initiative to develop a system for centrally storing and managing the data and information. KOBWA prefers a GIS- based system; because the majority of the data are of a spatial nature or time series with spatial attributes.
In 2001, the Komati Basin Water Authority (KOBWA) undertook to develop the components of a management-information system (MIS) to support the operational decision-making. The development of the (MIS) was modelled on a functional model of the flow of water-resource information (DWAF, 2000, Harris et al., 2001), namely: data acquisition, data storage and management, information generation and dissemination, in addition to complex knowledge products.
3.6 Water Resource-Management Information Systems
Water resource management information systems (WRMIS) have become the most essential tools for water-resource managers. Most of the integrated WRMIS have at least three functional components, namely:
Data acquisition;
Data storage;
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Management, information generation, and dissemination.
It has also been recognized that there is a fourth component, namely: Complex Knowledge products that represent the reporting, documentation and decision- making. These are used when conducting the business of water-resource management (DWAF, 2000, Harris et al., 2001).
It is the author’s experience that the focus in the development of water-resource information systems has been on establishing the first three components with much less attention to being given to the other components of the Laudon and Laudon Model (management, organization etc.).
Most of the new generation of water-resource support systems aimed at integrating database-management systems (DBMS), Geographical Information Systems (GIS), and a range of simulation models, decision models and easy-to- understand user interfaces. These can provide a wide range of data and information products to different stakeholders. Most developments have been integrated with GIS, which provides a tool for storing and displaying spatial data, and the internet that provides an infrastructure for linking to distributed data sources.
3.7 Implementation of data-management practices through GIS
The implementation of Geographic Information Systems (GIS) would use the definition of Campbell and Masser (1995). They believed that the best method to implement GIS is in a corporate environment; because it would yield the strategic benefits and efficiency embedded in GIS technology. The underlying rationale for the corporate approach to GIS implementation is that it would increase the level of data sharing within the river basin, thereby reducing the duplication of data, as well as providing more informed decision-making.
Geographic Information Systems (GIS) appear to be viewed as a significant and potential tool when it comes to managing the planning and maintenance of data in various platforms. This testifies to the hopeful belief in the capability of the new
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technology systems. Geographical Information Systems (GIS) appear to be viewed as a significant and potential tool, when it comes to assisting in managing spatial information and the data in various organizations.
In what way does GIS offer management systems for central storing and handling data and information? It is alleged that most organizations rely largely on data and information to make critical decisions. Consequently, in recent years, the volume of spatial data has grown exponentially.
That alone has created a huge demand for critical data use. In order to fairly provide for the ever-increasing demand for data, it is perceived that data policy and administration should be acknowledged; as they play a crucial role in data- management practices. A sound data policy defines strategic long-term goals for data management in all aspects of a project, agency and organizations (Burley and Peine 2007).
3.8 Data-Management Practices
Reflecting on data practice from the point of view of Information Science, these studies revealed another common theme, namely, the need for timely training and advice (Delserone, 2008; Henty et al., 2008; Thomas, 2011; Wilson et al., 2010). This is supported by the findings from other studies (HATII & University of Glasgow, 2009; Peters & Dryden, 2011) that found that researchers need assistance and support to adopt best practices throughout the data’s lifecycle and to address data-management plans. In addition, there were common features when developing the infrastructure. “The need for data documentation (metadata), training and support, secure storage, and linking data to publications are common across disciplines” (HATII & University of Glasgow, 2009).
There is a shared understanding that the management of research data is essential for the advancement of science (ARL/NSF Workshop, 2006). This is required because of the underlying technology, social factors and organizational risk (Beagrie, 2006).
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Data management is about organizations, and their presence in information technology, data-management practices, and standard applications. In order to meet data-management goals and standards, all those involved in a project must understand their associated roles and responsibilities (National Park Service 2008).
According to Burley and Peine (2007), data should be made available to those who need them or those who are given permission to access them. There are issues that should be addressed regarding access to data and database systems:
Data policies and data-possession issues regarding access and the use of data;
Requirements to gain access to the data;
Differentiated levels of access needed, when considered appropriate;
The cost of providing data versus the cost of providing access to data;
System design considerations;
Issues of the private and the public domain in the context of the data being collected.
All data should be treated as a strategic asset that can be used as a trusted source of information throughout the enterprise. The data need to be managed throughout the entire lifespan. This involves an all-inclusive package, rather than just an assignment to build a single-data warehouse.
The practice of data management was implemented, in order to guarantee that data handlers might have assurance in the data assets that they utilize to make business decisions. It seeks to create a comprehensive program for the management of enterprise data, as opposed to just building a data warehouse.
The management of data comprises various categories. Below is a model that shows how data management extends the practice of data quality, data architecture, metadata management, and data stewardship. Other models may differ; but the basic concept remains the same.
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Figure 3.1 Data Model – Showing how data management spans the practices
Source: (Data Management Practices; Robert E. Story Jr.)
The key point is that Data Management is the predominant practice for these various components, which a larger stakeholder and organizations should review, in order to produce sound practices on data-management issues.
Data control;
Data stewardship;
Data quality;
Data design;
Data principles; and
Data security.
Information and data management sharing are most important parts of the successful water governance in trans-boundary basins (GWP 2000: Grossmann 2005; Sadoff et al., 2008; Raadgever et al., 2008). Therefore, developing information and data-management systems for the operational levels of water- resource management would help to pave the way for establishing viable conditions for integrated water-resource management (IWRM) development for
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riparian states on small trans-boundary basins (Abdullaev & Rakhmatullaev 2012).
3.9 Conclusion
Data management is gradually being recognized as a significant element of active data use in a water-resource environment. Best practices and principles for the managing of data/information have been developed by various agencies in the past, in order to facilitate electronic data access and use.
These principles and best practices range from defining the procedures, roles and responsibilities for data management, organizing, documenting and validating data to enhance their quality; managing data by providing suitable access, while maintaining the security of the data. Best-data management practices and standards are becoming more widely used in trans-boundary water governance.
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This chapter primarily discusses the data collection and the analytical methods;
and it also provides an overview of the research, as well as the restrictions, sampling techniques and procedures.
4.1 Introduction
In the previous chapter of the thesis, the author discussed the literature review in which data management practices in a trans-boundary water governance were presented. Considering the interdisciplinary nature of the water issues, water- resource management in a trans-boundary basin requires organizing the way that data and information are produced and shared, in order to respond to stakeholders’ expectations for numerous activities.
All research is based on some underlying rational expectations and on what constitutes a 'valid' research; and which research methods are applicable for the improvement of knowledge in a specified study. In order to conduct and evaluate any research, therefore, it is imperative to recognise what these agreements are.
This chapter discusses the data collection and the analytical methods.
4.2 The Study Area
The study area selected for this research work is the entire area downstream of Driekoppies and Maguga dams up to the confluence with the Crocodile River within the Komati catchment consisting of the catchment of the Komati River and the Lomati River.
This area lies in the jurisdiction of the Komati Basin Water Authority (KOBWA), which is responsible for the operation and management of the two dams, and to allocate water to the downstream users (Figure 4.1).
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Figure 4.1: Schematic layout of study area - (Source: Mukororira, 2012)
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Figure 4.2: Focus of the Study Area – (Source: Map generated by Author)
4.3 The research approach
The methodological approach is based on the empathetic interaction between the parties involved and the context, which plays once again a fundamental factor.
“Context is something you swim in like a fish” (Dervin 1997, 32) (as cited in Pakard, 2007, p.12).
These implications are fundamental when understanding appropriately the conceptualization of this study; as it is concerned with developing knowledge about information and data. Accordingly, the qualitative approach was chosen for this research (Gorman et al., 2005). Additionally, the research question, interview techniques provided a solid ground for the detailed investigation of the data- management practices.
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Most researchers hesitate to agree on a definition of qualitative investigation. It is argued that it can be determined from its attributes, as outlined in the literature.
The following seemed the key aim in developing a deep understanding, providing a descriptive picture and background of information (Trochim, 2006): the lack of detailed procedures at the outset of research (Denscombe, 2009), and drawing the data from the context (Gorman et al., 2005),
With the statements acknowledged above, the key assumption in the qualitative approach is that the understanding of a problem under investigation can be expanded only from its own perspective. According to Gorman et al. (2005), “the meaning of events, occurrences and interactions can be understood only through the eyes of [the] actual participants in specific situations” (2005, p.3). Essentially, in this methodological approach the existing data serve as a source of valuable meaning.
Discussing the choice of research methods, Gillham (2005) rightly noted that “all raw data require interpretation” (Gillham, 2005, p.8). This further highlights the importance of the reciprocal influence of those taking part in the research and its role in qualitative study.
The aspect of the approach is its developing design, which allows for a certain degree of flexibility, and to adjust appropriate techniques along with the research process. The finding and conclusions will depend on the quality of the research design, the data collection, the data management and the data analysis. The methodology will be committed to the methods and procedures used to obtain the data; how they are to be analyzed; and their interpretation and conclusion.
The research design had an influence on the phases of the research. The qualitative research collection was an important part to obtain background information, which subsequently made it possible to construct the framework.
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In summary, the research will cover the research design, the research method, the sampling method, the data-collection techniques and the research instruments, as presented below.
4.3.1 The Qualitative Data
The study began with an extensive review of the literature related to the field of interest, as well as the best practices and standards in data management. The author felt the need to review and describe the data-management practices at the organisation, Komati Basin Water Authority (KOBWA). The review aimed to include the most recent and complementary literature, in order to get a holistic understanding of the practices.
The material that was reviewed in the fields of Water-Resource Management (Hydrology and Geohydrology) in addition to the documents used was the reports obtained from previous studies that the Komati Basin Water Authority (KOBWA) had conducted.
Gall and Borg (1996) noted that a case study is a method of conducting qualitative research, which involves a distinct approach to scientific inquiry. Case studies strive to portray what it is like to be in a particular situation, to catch the close-up reality, and to give a description of how the participant is living, his experiences and thoughts about the situation. In addition, the study was qualitative; since it used open-ended questionnaires and the sampling technique was purposive.
Qualitative research, which provided a broad overview of the data, was adopted for analysing the primary data collected at Willowfontein. Basically, qualitative research involves the analysis of data, such as words (Mouton 2006: 107).
Interviews helped to gather reliable information relating to the problem being investigated (Hofstee 2006:109).
4.4 The Research Method
In this research, the author seeks to use the descriptive method of research, in order to obtain information on the existing situation of the data and any relevant
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information. The purpose of employing this method is to describe the nature of the situation – as it exists at the time of the study. The author opted to use this kind of approach because of the need to obtain first-hand data.
For this research, the author will use the qualitative approach. The qualitative method documents a flexible and iterative approach. The significance of qualitative research can be understood by examining its characteristics. The main advantage of a qualitative approach is its openness to the adjusting and the refining of the research ideas.
The definition of qualitative research and case-study research has no common definition; and the difficulty in reaching a shared understanding was outlined in the literature (Gillham, 2005); Packard (2007, p.85).
This study has focused on data-management practices, which are currently on the agenda in most organizations; it analyzes and discusses a single case in a defined background – in this case, the Komati Basin-Water Authority (KOBWA), and in other river-basin organizations that deal with data and information for their daily operations.
To guarantee an adequate depth of investigation and where applicable to derive knowledge from the case under inquiry (Gorman et al., 2005 chapter 04), this study provided an essential and rich description of the bounded system (Denscombe, 2003, p.271).
4.5 The Research Design
According to Polit and Hungler (1999), research design is a proposal for guiding the study in a way that maximizes the control over the factors that could affect the validity of the research results. The research design works as a systematic plan: Outlining the study; the researcher’s methods of compilation; the details of how the study will arrive at its conclusions; and finally, the limitations of the research (Kenneth & Wills, 2010). Research design can be used as a sound
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structure that confirms all the collected data. It also helps to eliminate bias, when evaluating theories and arriving at a conclusion.
The study used qualitative research and descriptive-design methods. Descriptive research seeks to depict what already exists in the organization; and it strives to answer the question: “What is happening?” The purpose of descriptive research is to observe, describe and keep documents. Questionnaires and observation (personal engagement) were used during the data-collection process.
4.6 Sampling Methods
The main purpose of sampling is to get a well-composed, descriptive representation of the problem that is being investigated (Gillham, 2005). A research that deals with human subjects builds a relationship with the study participants, as highlighted by Pickard (2007).
Saunders et al. (1997) defined sampling as a process of selecting a representative subset for observations from a population, in order to determine the characteristics of the variable under study.
Strydom, Fouche and Delport (2005) maintain that non-probability sampling represents a valuable group of sampling techniques for use in research that follows a qualitative, a mixed-method approach, and even a quantitative research design.
Collecting and analyzing the primary data, irrespective of the method chosen, can prove to be a very challenging task for researchers to achieve, primarily because of their lack of previous experience. It can be a difficult task to discover a gap in the research area of your interest, or to identify a practical problem to address in an organization of one’s choice. Selecting the most suitable method of primary- data collection, collecting the primary data, and analyzing the data to find answers to your research questions, or to test hypotheses, are not straightforward tasks for many business students.
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The author applied a two-stage sampling method in this study, in order to make the researched data more manageable. The research employed the method to gather the data and establish any data-management problems and also to assist to explain some phenomena and to meet the objectives of the study. The guiding principle was to collect data, which are relevant, reliable, valid and up-to-date.
The method used was also based on applicability, and time considerations (Mouton, 2001).
According to Entwhistle and Nesbert (1975), there is no single correct procedure for sampling. The method chosen depends on the purpose of the inquiry, or the type of analysis to be made, and on certain restrictions, such as time and the facilities that have to be accepted as external constraints.
4.7 Data-Collection Techniques
There are two sources of data; primary-data collections use direct observations;
while secondary data collections may be conducted by collecting information from a diverse source of documents, or from electronically shared information.
After having identified the source of the data in hardcopies (the existing data) obtained from previous studies conducted in the Komati River Basin, I also identified the System Analyst at Komati Basin Water Authority (KOBWA). He was also invited to contribute to the study. The interviews were also extended to the River Operations and the Data-Management Manager. They consequently capture geo-hydrological data and other sources of information.
4.8 Data Analysis
A qualitative data analysis was used – with the major source of data being interviews; and other data sources being documents and the literature. Therefore, qualitative analysis was regarded as appropriate.
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The data analysis took place along with the data collection, in order to allow categories to emerge from the data (Pickard, 2007, pp.155-163). All completed questionnaires were captured and coded by using the rating scale of one to five.
A computer was used for capturing and coding all the completed questions.
Furthermore, to ascertain the highest quality of the analysis, the author applied four rules utilised by Yin (1994), as cited in Tellis. They indicate to:
Demonstrate that the analysis relied on all the relevant evidence;
Embrace all the major interpretations in the analysis;
Address any significant aspect of the case study;
Use the researcher’s expert knowledge to further the analysis (Tellis, 1997).
4.9 The Research Instrument
The author will design a self-administered questionnaire for the data collection process, in order to get qualitative data. The main aim of the interviews is to determine and overcome the challenges observed by the Komati-Basin Water Authority regarding the extent of data-management practices and their effectiveness in the Komati-River Basin/catchment.
4.10 Selecting the participants
Creswell (2007) argues on the importance of selecting suitable applicants for interviews. He affirms that the researcher should employ one of the various types of sampling approaches, such as criterion-based sampling, or critical-case sampling (among many others), in order to obtain qualified candidates that would provide the most credible information to the study. Creswell also suggests the importance of acquiring participants who would be willing to openly and honestly share information or “their story” (p. 133). It might be easier to conduct the interviews with participants in a comfortable environment, where the participants do not feel restricted or uncomfortable to share their information.
- 45 - 4.11 Interviews
The interviews will be used to achieve the main objective of the study. This will comprise an interview with in-house personnel at the Komati-Basin Water Authority (KOBWA), and especially the Systems Analyst. Other catchment management agencies, Government departments, water users, and stakeholders benefiting from the water resource were consulted and interviewed because of their work experience in the water-resource management in the river basin.
The interviews were considered useful to fill existing gaps in the literature on the specific data-management practices. Most literature pointed to Geographical Information Systems (GIS), to collect additional information and data. The interviews allowed, including the personal experience of the experts in the analysis, to gain information on their personal ideas about the situation in a river- basin establishment.
It also helped to fill the gaps by directing the study to the Komati River Basin, which is to a large extent viewed as a good measure of bilateral water sharing.
Yet, it still struggles with the data-management systems. The interviews were conducted by personal contacts. The information and the data from the interview partners contributed to the qualitative analysis of this study. The interviews helped to hear their views on the improvements or gaps that needed to be filled in the context of KOBWA’s operation.
The interviews were conducted as formal conversation interviews (Patton, 2002) to gather information and data on the existence of data-management practices in the Komati River Basin Project, commonly known as the Komati Basin Water Authority (KOBWA).
- 46 - 4.11.1 Questionnaires
The questionnaire was used to gather information beyond the physical reach in responding to the open-ended questions that were used (qualitative data). The questionnaires provided both advantages and disadvantages, as outlined below:
Advantages – There are a number of advantages in using questionnaires;
amongst others, massive amounts of data may be collected, and the respondents can answer at their convenience. It also allows respondents to refer to documents and to provide accurate information.
Disadvantages – The questionnaire is not suitable for an illiterate populace. It is also possible to provide replicated data, amongst others.
4.12 Data Requirement – KOBWA
The Komati Basin Water Authority (KOBWA) needs sufficient and up-to-date data and information about water quality and quantity, and their spatial and temporal trends, in order to operate and manage the system effectively and efficiently. The data are required to support decision-making on systems’ operation (water supply and demand management), managing risk and uncertainty, dam safety, as well as environmental management.
From the above, the listed data used for KOBWA’s operation ranges and incorporates the following:
- Environmental data (water quality);
- Hydrological/Geo-Hydrological data (surface-water gauging stations data);
and
- Meteorological data.
