The key institutional changes which occurred in 2010 are shown in Table 2.1. Table 2.1 Key institutional changes during 2010.

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1 2. S I T U AT I O N A L I T U AT I O N A L A N A L Y S I S This section lists how the different trends in Umgeni Water s working environment have changed using a version of the STEEPLE 1 analysis. This section differs from the other sections of the IMP in that it refers to the previous versions of the IMP. This is done to avoid repetition of explanations of sources of information that have become standard in planning practice. Reference is made to the previous IMPs in case the reader requires further explanation on the relevant piece of information I N S T I T U T I O N A L The key water sector institutions viz. the WSAs and the Water Management Areas (WMAs) occurring within Umgeni Water s working area are shown in Figure 2.1. The key institutional changes which occurred in 2010 are shown in Table 2.1. Table 2.1 Key institutional changes during Year Institutional Change Impact 2010 The wards for the 2011 local elections were published on 2 nd September The South African Geographical Naming Committee published the changes to the official spelling of the toponyms listed in Table 2.3 in October These changes include Mgeni River now being spelt as umngeni River, Mloti River as umdloti River, Mkomazi River as emkhomazi River, Mlazi River as umlaza River and Tongati River as uthongathi River The District Management Areas (DMAs) will cease to exist after the 2011 local elections (UW 2009). The number of wards in the WSAs for which Umgeni Water is the bulk water service provider has increased by 26 to 400. The change in the number of wards per local municipality is shown in Table 2.2 below. The change in the spatial distribution of the wards is illustrated in Figure 2.2. The 2011 ward boundaries are shown in red whilst the 2006 ward boundaries are illustrated in black. It is noted that one of the reasons for the number of wards increasing in a municipality is that the population density in that particular area has increased. Therefore for those areas in which the number of wards has increased (shown in green in Figure 2.3), it could indicate areas in which there has been an increase in population density. Until the new spellings become commonly used, users of the toponyms should know that the new spellings refer to the same places as that of the old spellings. The changes in the municipal boundaries are shown in Figure 2.4. The DMAs are illustrated with the green hatching, the 2011 municipal boundaries are delineated in red and the 2009 municipal boundaries are in black (IMP 2009). 1 An extended form of the PEST (Political, Economical, Sociological and Technological) analysis. STEEPLE is an acronym for Social/Demographic, Technological, Economic, Environmental (Natural), Political, Legal and Ethical. 6

2 Figure 2.1 Institutional boundaries. 7

3 Table 2.2 Changes in the number of wards. WSA Local Municipality No. of Wards Elections No. of Wards Elections Change ethekwini ethekwini Ugu Vulamehlo Ugu Umdoni Ugu Umzumbe Ugu umuziwabantu Ugu Ezingoleni Ugu Hibiscus Coast Umgungundlovu umshwathi Umgungundlovu umngeni Umgungundlovu Mpofana Umgungundlovu Impendle The Msunduzi The Msunduzi Umgungundlovu Mkhambathini Umgungundlovu Richmond Ilembe Mandeni Ilembe KwaDukuza Ilembe Ndwedwe Ilembe Maphumulo Sisonke Ingwe Sisonke Kwa Sani Sisonke Greater Kokstad Sisonke ubuhlebezwe Sisonke Umzimkhulu Total

4 Figure 2.2 Changes in ward boundaries (MDB 2010). 9

5 Figure 2.3 Municipalities with a change in the number of wards. 10

6 Table 2.3 Changes in official spelling of selected toponyms (SAGNC 2010). Official Spelling Feature Description Previous Name as per SAGNC List Previous Name as per 1 : Topographic Maps amanzimtoti River Amanzimtoti Manzimtoti emanzimtoti Town Amanzimtoti Amanzimtoti emdloti Town Umdloti Umdloti umdloti River Umdloti Mdloti umkhomazi Village Umkomaas Umkomaas emkhomazi River Umkomaas Mkomazi umngeni River Umgeni Mgeni emlaza Township Umlaas Umlazi umlaza River Umlaas Mlazi ezimbokodweni Village Umbongintwini Umbogintwini KwaKhangela Town Congella Congella KwaMakhutha Township kwamakhutha KwaMakhutha othongathi Town Tongaat Tongaat uthongathi River Tongaat Tongati umhlanga Suburb Umhlanga Rocks Umhlanga Rocks Figure 2.4 Changes in municipal boundaries (MDB 2010). 11

7 The new boundaries for the WSAs and their constituent local municipalities are shown in Figure 2.5. The municipal categorisation as derived from the State of Local Government report (2009; IMP 2010) continues to provide the foundation for all planning work undertaken by government. The categorisation, which builds on the categorisation as defined in the Constitution (1996), refers to the size of municipalities in terms of population, percentage of urban population and size of municipal budgets. These characteristics are relatively fixed over time and assist with understanding of municipal profiles (CoGTA 2009b: 8). The categories are as follows: A Metros. Large urban complexes with populations over 1 million and accounting for 56% of all municipal expenditure in the country. B1 Local Municipalities with large budgets and containing secondary cities. B2 Local Municipalities with a large town as a core. B3 Local Municipalities with small towns, with relatively small population and significant proportion of urban population but with no large town as a core. B4 Local Municipalities which are mainly rural with communal tenure and with, at most, one or two small towns in their area. C1 District Municipalities which are not water service authorities. C2 District Municipalities which are water service authorities. (CoGTA 2009a: 9) This categorisation as applied to Umgeni Water s area is shown in Figure 2.6. Urban areas as identified by the Department of Rural Development and Land Reform s (DRDLR) 2009 Urban Edges study (2009b) and rural settlements as identified by the DRDLR s 2009 Rural Settlements Update Project in KZN study (2009a) in relation to the CoGTA s A C2 categorisation are shown in Figure 2.7. The results of these two studies are discussed further in Section 2.4. CoGTA (2009b: 76) has also developed a spatial classification system for local municipalities based on the indicators of functionality, socio-economic profile and backlog status. The four municipal classifications are: Class 1 Most vulnerable. Class 2 Second most vulnerable. Class 3 Second highest performing. Class 4 Highest performing. (CoGTA 2009a: 76) This classification is illustrated in Figure 2.8. Both classifications, as applicable to Umgeni Water s area are summarised in Table 2.4. It is shown in Figures that at present, Umgeni Water s infrastructure is predominantly in those areas that are urban and which are high-performing. 12

8 Figure 2.5 WSAs and their constituent local municipalities. 13

9 Figure 2.6 CoGTA s A C2 Categorisation. 14

10 Figure 2.7 Urban areas, rural settlements and CoGTAs A C2 Categorisation. 15

11 Figure 2.8 CoGTA s Spatial Classification. 16

12 Table 2.4 CoGTA s A C2 categorisation and spatial classification system. District Municipal ID District Municipality Local Municipal ID Local Municipality CoGTA A C2 Categorisation CoGTA Spatial Classification ETH ethekwini ETH ethekwini A Not Applicable DC21 Ugu KZN211 Vulamehlo B4 Class 1: Most Vulnerable DC21 Ugu KZN212 Umdoni B2 Class 3: Second Highest Performing DC21 Ugu KZN213 Umzumbe B4 Class 1: Most Vulnerable DC21 Ugu KZN214 umuziwabantu B3 Class 1: Most Vulnerable DC21 Ugu KZN215 Ezingoleni B4 Class 1: Most Vulnerable DC21 Ugu KZN216 Hibiscus Coast B2 Class 3: Second Highest Performing DC22 Umgungungdlovu KZN221 umshwathi B4 Class 2: Second Most Vulnerable DC22 Umgungungdlovu KZN222 umngeni B2 Class 4: Highest Performing DC22 Umgungundlovu KZN223 Mpofana B3 Class 3: Second Highest Performing DC22 Umgungundlovu KZN224 Impendle B4 Class 1: Most Vulnerable DC22 Umgungundlovu KZN225 The Msunduzi B1 Class 4: Highest Performing DC22 Umgungundlovu KZN226 Mkhambathini B3 Class 2: Second Most Vulnerable DC22 Umgungundlovu KZN227 Richmond B4 Class 2: Second Most Vulnerable DC29 Ilembe KZN291 Mandeni B4 Class 2: Second Most Vulnerable DC29 Ilembe KZN292 KwaDukuza B2 Class 4: Highest Performing DC29 Ilembe KZN293 Ndwedwe B4 Class 1: Most Vulnerable DC29 Ilembe KZN294 Maphumulo B4 Class 1: Most Vulnerable DC43 Sisonke KZN431 Ingwe B4 Class 1: Most Vulnerable DC43 Sisonke KZN432 KwaSani B3 Class 2: Second Most Vulnerable DC43 Sisonke KZN433 Greater Kokstad B2 Class 3: Second Highest Performing DC43 Sisonke KZN434 Ubuhlebezwe B4 Class 2: Second Most Vulnerable DC43 Sisonke KZN435 Umzimkhulu B4 Class 1: Most Vulnerable The cadastral dataset for the province is currently being cleaned by the Surveyor-General. One of the steps being undertaken by the Surveyor-General is the removal of duplicate records. This is illustrated in Table 2.5 which shows the reduction in duplicate records. Table 2.5 Reduction of duplicate records in the KZN cadastral dataset by the Surveyor-General. KwaZulu-Natal October 2009 January 2010 July 2010 November 2010 January 2011 Number of Erven 921, , , , ,778 Number of Farm Portions 67,200 67,269 67,496 67,454 67,335 Table 2.5 shows that prior to November 2010, the number of cadastrals in the province was increasing. This is a result of the number of sub-division applications that is received and approved. The number of sub-division applications as received by KZN CoGTA for approval 17

13 under the Town Planning Ordinance and for comment under the Planning and Development Act are shown in Figure 2.9 and the spatial distribution of these applications in Figure Figure 2.9 Number of sub-division applications submitted to CoGTA for the period for the WSAs for whom Umgeni Water is BWSP (AFS: 2010). Rushton (2008) reported that where properties were sub-divided into sizes of 5ha or less, a trend of the surrounding properties becoming sub-divided into smaller properties occurred, thereby resulting in increasing densities. The areas highlighted in Figure 2.10 may therefore experience increases in water consumption and should be monitored for growth. 18

14 Figure 2.10 Location of sub-division applications (AFS: 2010). 19

15 The proposed land use for the majority of the sub-division applications is residential (Figure 2.11) and most of the sub-division applications are located along the T-Junction i.e. along the N3 and the N2 (Figure 2.10). An increase in sub-divisions for residential land use suggests that an increase in water consumption may result. It is also shown in Figure 2.10 that the areas of New Hanover, Richmond, Himeville and Ixopo have also been receiving a number of sub-division applications. These areas should therefore also be monitored in terms of increasing water consumption. Figure 2.11 Land use type per sub-division application (AFS 2010). Cadastrals and Ingoyama Land Trust land are shown in Figure The status of the gazetted restitution claims are illustrated in Figure It is shown in this figure that a number claims have been settled in the Camperdown area and the area in the vicinity of the town of KwaDukuza. A number of settlement type redistribution projects are being undertaken in the KwaDukuza town area (Figure 2.14) but there are also a number of settlement projects occurring in the north-eastern boundary of Mpofana Municipality. This figure shows that these two areas should be monitored in terms of increasing water consumption. An analysis of the political environment is not included. It is, however, noted that local government elections will be held in

16 Figure 2.12 Land ownership. 21

17 Figure 2.13 Status of gazetted restitution claims (Oct 10). 22

18 Figure 2.14 Types of redistribution projects (Oct 10). 23