Survey
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
4 Water Resources 4.1 Introduction In order for Umgeni Water to fulfil its function as a regional bulk water service provider, it requires a secure and sustainable supply of raw water. The reconciliation between water resource availability and water demands is therefore of primary importance to the organisation and forms an integral part of its infrastructure planning process. Understanding what water resources are available to the organisation both currently and in the future, and what impacts affect the level of assurance from these resources, is key to achieving the balance between supply and demand and in maintaining the assured level of supply required by the customers. The natural climate is the principal determinant of surface water runoff and groundwater. This section describes the climate as experienced within Umgeni Water’s operational area, as well as the possible impacts of climate change on surface water runoff in the Mgeni System. This section also describes the status quo of the water resources, both surface and groundwater, within Umgeni Water’s operational area, and mentions future development plans that are significant to the organisation. The water resources are grouped in logical regions as shown in Figure 4.1. Finally, a progress note is provided on Umgeni Water’s investigation into the less conventional supply options of wastewater reclamation (re-use) and seawater desalination. 67 68 Figure 4.1 Water resource regions in Umgeni Water’s operational area. 4.2 Climate There are three distinct climatic zones within Umgeni Water’s operational area (Figure 4.2), namely: • The Köppen classification Cwb which is the alpine-type climate found in and along the Drakensberg Mountains. • The Köppen classification Cfb which is the more temperate summer rain climate of the Midlands region. • The Köppen classification Cfa which is the subtropical perennial rainfall characterising the areas along the coast. The mean annual precipitation (MAP) within the Umgeni Water operational area varies between 700 and 1000 mm (Figure 4.3) with most rains falling in summer (October to March), although there are occasional winter showers. The national average MAP is about 450 mm per year. The peak rainfall months are December to February in the inland areas and November to March along the coast. The prevailing weather patterns are predominantly orographic, where warm moist air moves in over the continent from the Indian Ocean, rises up the escarpment, cools down and creates rainfall. Rain shadows occur in the interior valley basins of the major rivers where the annual rainfall can drop to below 700 mm. The spatial distribution of evaporation is shown in Figure 4.4. This distribution has a similar pattern to rainfall where a relative high humidity is experienced in summer. There is a daily mean peak in February, ranging from 68% in the inland areas to greater than 72% for the coast and a daily mean low in July, ranging from 60% in the inland areas to greater than 68% at the coast. Potential mean annual gross evaporation (as measured by ‘A’ pan) ranges from between 1 600 mm and 1 800 mm in the west to between 1 400 mm and 1 600 mm in the coastal areas (Figure 4.4). Temperature distribution is shown in Figure 4.5. The mean annual temperature ranges between 12°C and 14°C in the west to between 20°C and 22°C at the coast. Maximum temperatures are experienced in the summer months of December to February and minimum temperatures in the winter months of June and July. Snowfalls on the Drakensberg Mountain between April and September have an influence on the climate. Frost occurs over the same period in the inland areas. 69 70 Figure 4.2 Climatic Zones (Köppen Classification). Figure 4.3 Mean annual precipitation (mm). 71 72 Figure 4.4 Mean annual evaporation (mm). Figure 4.5 Mean annual temperature (0C). 73 74 Figure 4.6 Mean annual runoff (mm). The average number of heavy frost days per annum range from 31 to 60 days for inland areas to nil for the eastern coastal area. The mean annual runoff is illustrated in Figure 4.6. 4.3 Climate Change Introduction Clear evidence exists that the climate is changing globally and that this will have an amplified impact on water resources and therefore on water security and supply. In South Africa, the Department of Environment Affairs (DEA) is designated to lead the country’s climate change agenda, guided by their recently adopted Long Term Mitigation Strategy on Climate Change. Climate change features as one of several strategic national objectives in DEA’s Strategic Plan (2010/11 – 2012/13) namely, to respond and adapt to climate change impacts, which would otherwise threaten South Africa’s ability to realise the Millennium Development Goals. Furthermore, the Department of Science and Technology has identified Global Change as one of the five “Grand Challenges” to be addressed in the ten year plan for research focus in South Africa. Climate change is a component of Global Change, and water quality and quantity are key elements which will be addressed in this “Grand Challenge”, with one of the intended outcomes being to develop the skills base required to deal with the consequences of climate change. It is thus imperative that water service providers consider the possible impacts in their water planning in order to sustain water supply at acceptable assurance levels. Umgeni Water is aware of this potential risk which has featured prominently in the organisations Strategies, Business Plans, Scorecards and Risk Frameworks since 2006. Whilst the significance of this risk is understood, Umgeni Water recognised as early as 2006, that not enough was known about the magnitude of the potential impacts, especially at the operating level of its key water resource, the Mgeni River. It was identified that an investigation was necessary in order to establish a better understanding of the potential impacts at this local scale such that appropriate adaptation controls could be developed and implemented if necessary to bring the residual risk to a level that the organisation was willing to accept. The Mgeni catchment was chosen for this assessment due to its importance in supplying one of South Africa’s most important economic hubs, viz. the Greater Durban-Pietermaritzburg area, at a high level of assurance. The catchment is therefore critical to the utility’s operations. 75 A Framework to Quantify the Impacts of Climate Change Umgeni Water developed a framework (see Figure 4.7) to guide its efforts towards quantifying the possible impacts of a changing climate on its business. At the core of the framework is a hydrological model wherein rainfall and temperature are altered to represent possible scenarios of the impact of future climates on runoff in rivers. These runoff scenarios are then used in water allocation models that contain the physical constraints of a supply system (e.g. the dam and the future demand for water on the dam), using a risk based approach to determine the security of future water supplies. Runoff can also be used in hydraulic and open channel flow models to determine possible impacts on dam safety and flooding respectively. The results of these scientific assessments are included in various short and long term plans, including the Infrastructure Master Plan. The framework is generic in nature, and to date has been applied to the Umgeni catchment as a case study to improve the methodologies, but also since this is Umgeni Water’s most important and complex catchment. The ensuing sections expand on some of the key aspects of the framework, as pertaining to the Umgeni catchment. Figure 4.7 Modelling framework to determine the impacts of a changing climate on water resources. 76 Hydrological Modelling The daily ACRU agro-hydrological model (Schulze, 1995 and updates) from the University of KwaZulu-Natal (UKZN) and their quinery catchment based hydrological modelling has been used for this assessment of the Umgeni catchment (see Figure 4.8). The strengths of this model lie in its ability to model the actual physical processes that occur in the hydrological cycle, and although the model has initially been applied to climate change in this project, it will be invaluable for other applications. Consequently, considerable effort was expended in ensuring accurate input data describing rainfall patterns, land cover and its water use patterns, irrigation, reservoir abstractions, wetlands, soils, and evaporation which were configured as a base scenario in the hydrological model. Figure 4.8 The Mgeni Catchment, KwaZulu-Natal. Climate Modelling The possible impact of increasing greenhouse gas emissions (see Figure 4.9) on global climates has been researched by scientists for some time. Four broad greenhouse gas emission scenarios have been developed by the Intergovernmental Panel on Climate Change and were published in their Special Report on Emissions Scenarios (IPCC, 2007). These emission scenarios have been incorporated into more than 20 Global Circulation Models (GCMs) that have been developed for the purpose of, inter alia, providing possible scenarios of global climate over the next 50 to 100 years. 77 Furthermore, these GCMs have been downscaled to local catchments using either dynamic or statistical techniques that incorporate local climates. Umgeni Water has through its partners including the school of Bioresources Engineering and Environmental Hydrology at the UKZN, the Climate Systems Analysis Group (CSAG) at the University of Cape Town (UCT), the Swedish Meteorological and Hydrological Institute in Sweden, and the Council for Scientific and Industrial Research (CSIR) obtained 35 runoff scenarios that incorporate different GCMs, downscaling techniques and emission scenarios (see Table 4.1). Figure 4.9 CO2 emissions (left panel) and CO2 concentrations (right panel). Table 4.1 Summary of available Global Circulation Models. Source # of Scenarios Downscale method GCMs CSAG UCT (vers 1) 4 Statistical CCC, CRM, ECH and IPS SMHI 5 Dynamic EC4_B2, EC4_A2, EC5_A1B, CCSM3_A1B, CCSM3_B2 CSIR 6 Dynamic CSIRO, GFDL20, GFDL21, MIROC, MPI, UKMO Statistical MR2, MR1, IP2, IP1, Gi2, Gi1, G22, G21, G12, G11, E22, E21, E12, E11, CS2, CS1, CN2, CN1, CC2, CC1 CSAG UCT (vers 2) 20 A Changing Climate and Water Supply – Results To date, the potential impacts on hydrology of the Mgeni catchment and water security (yield) at the 4 main dams has been modeled using 9 GCMs (from CSAG UCT version 1 and SMHI). Unfortunately these results (typified in Figure 4.10, Figure 4.11, Figure 4.12 and Figure 4.13) are far from conclusive with for example the potential impact on water yield ranging between -15 and +40%, with the SMHI and UCT models seeming to be relatively dry and wet respectively. There are a 78 number of possible reasons for this including that the models have been downscaled using different techniques by different institutions and that the UCT models are now dated, around 5 years. Furthermore, there is no scientific (or any other) basis to support the credibility of any 1 model or scenario over another. Put another way, any one of the 9 modelled has an equal possibility of representing the climate of the future. Figure 4.10 Possible changes in runoff for a particularly wet GCM (GFDL). Figure 4.11 Possible changes in runoff for a particularly dry GCM (ECHAM5). 79 Figure 4.12 Possible average monthly runoff (as % of annual total). Figure 4.13 Possible future water yields (as % of present). Way Forward The most up-to-date science has been used in this assessment. However, the discipline of performing impact studies, such as water resources, based on scenarios of future climates is relatively new. There are also numerous complexities that are associated with modelling the natural climate – water processes, resulting in increased uncertainty. The confidence levels in the results of such studies are therefore less than ideal. There are, however, several improvements that can be made to the modelling process. At the heart of these improvements is the inclusion of new scientific developments especially with regards to modelling of future climates such as new improved models and using bias correction techniques to ensure that predicted rainfall and potential evaporation are 80 more adequately represented. These improvements should greatly reduce uncertainty and enhance the credibility of the water planning process at Umgeni Water. In this regard, a further 26 scenarios recently became available viz. from the CSIR and more recent GCMs from the UCT. These scenarios are to be analysed during the first quarter of 2012, using the same methodology as the first 9 scenarios. It is hoped that this further analysis will provide a convergence of results, at the very least agree on the direction of change. Failing this, at least the spread of results, which could be summarised using a probabilistic approach, should be more meaningful. Regardless of the results, which are fundamentally based on uncertainty, it will be important for Umgeni Water to develop flexible adaptive strategies to cope with these potential impacts. It is undesirable for the utility to be faced with issues such as unachievable deadlines for water resource development, or loss of supply potential, hence the results from the process described above will be used to develop sustainable solutions. Water resource development plans, system operating rules and disaster risk management plans will contain the means of implementing these strategies. 81