<?xml version="1.0" encoding="ISO-8859-1"?><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
<front>
<journal-meta>
<journal-id>1816-7950</journal-id>
<journal-title><![CDATA[Water SA]]></journal-title>
<abbrev-journal-title><![CDATA[Water SA]]></abbrev-journal-title>
<issn>1816-7950</issn>
<publisher>
<publisher-name><![CDATA[Water Research Commission (WRC)]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S1816-79502012000300008</article-id>
<title-group>
<article-title xml:lang="en"><![CDATA[Climate change vulnerability index for South African aquifers]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Dennis]]></surname>
<given-names><![CDATA[Ingrid]]></given-names>
</name>
<xref ref-type="aff" rid="A01"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Dennis]]></surname>
<given-names><![CDATA[Rainier]]></given-names>
</name>
<xref ref-type="aff" rid="A01"/>
</contrib>
</contrib-group>
<aff id="A01">
<institution><![CDATA[,North-West University Unit for Environmental Sciences and Management ]]></institution>
<addr-line><![CDATA[Potchefstroom ]]></addr-line>
<country>South Africa</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>00</month>
<year>2012</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>00</month>
<year>2012</year>
</pub-date>
<volume>38</volume>
<numero>3</numero>
<fpage>417</fpage>
<lpage>426</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.za/scielo.php?script=sci_arttext&amp;pid=S1816-79502012000300008&amp;lng=en&amp;nrm=iso&amp;tlng=en"></self-uri><self-uri xlink:href="http://www.scielo.org.za/scielo.php?script=sci_abstract&amp;pid=S1816-79502012000300008&amp;lng=en&amp;nrm=iso&amp;tlng=en"></self-uri><self-uri xlink:href="http://www.scielo.org.za/scielo.php?script=sci_pdf&amp;pid=S1816-79502012000300008&amp;lng=en&amp;nrm=iso&amp;tlng=en"></self-uri><abstract abstract-type="short" xml:lang="en"><p><![CDATA[South Africa is viewed as a water-stressed country with an average annual rainfall of 500 mm and any climatic change could have adverse impacts on water resources of the country. The potential impacts of climate change on water resources and surface hydrology for Africa and Southern Africa have received considerable attention from hydrologists during the past decade. Very little research has been conducted on the future impact of climate change on groundwater resources in South Africa. Climate change can affect groundwater levels, recharge and groundwater contribution to baseflow. To assess these impacts a climate change vulnerability index was developed. This vulnerability-index method is known as the DART index. The parameters considered in the DART method are as follows: depth to water-level change, aquifer type (storativity), recharge and transmissivity. The DART index is used as a regional screening tool to identify areas that could experience possible changes in their groundwater resources as a result of climate change. The current DART index does not account for adaptation and migration occurrences.]]></p></abstract>
<kwd-group>
<kwd lng="en"><![CDATA[groundwater]]></kwd>
<kwd lng="en"><![CDATA[climate change]]></kwd>
<kwd lng="en"><![CDATA[vulnerability index]]></kwd>
<kwd lng="en"><![CDATA[South Africa]]></kwd>
<kwd lng="en"><![CDATA[DART]]></kwd>
</kwd-group>
</article-meta>
</front><body><![CDATA[ <p><font face="Verdana, Arial, Helvetica, sans-serif" size="4"><b><a name="top"></a>Climate    change vulnerability index for South African aquifers</b></font></p>     <p>&nbsp;</p>     <p>&nbsp;</p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2"><b>Ingrid Dennis;    Rainier Dennis<a href="#back"><sup>*</sup></a></b></font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">Unit for Environmental    Sciences and Management, North-West University, Private Bag X6001, Potchefstroom    2520, South Africa</font></p>     <p>&nbsp;</p>     <p>&nbsp;</p> <hr size="1" noshade>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2"><b>ABSTRACT</b></font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">South Africa is    viewed as a water-stressed country with an average annual rainfall of 500 mm    and any climatic change could have adverse impacts on water resources of the    country. The potential impacts of climate change on water resources and surface    hydrology for Africa and Southern Africa have received considerable attention    from hydrologists during the past decade. Very little research has been conducted    on the future impact of climate change on groundwater resources in South Africa.    Climate change can affect groundwater levels, recharge and groundwater contribution    to baseflow. To assess these impacts a climate change vulnerability index was    developed. This vulnerability-index method is known as the DART index. The parameters    considered in the DART method are as follows: depth to water-level change, aquifer    type (storativity), recharge and transmissivity. The DART index is used as a    regional screening tool to identify areas that could experience possible changes    in their groundwater resources as a result of climate change. The current DART    index does not account for adaptation and migration occurrences.</font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2"><b>Keywords:</b>    groundwater, climate change, vulnerability index, South Africa, DART</font></p> <hr size="1" noshade>     ]]></body>
<body><![CDATA[<p>&nbsp;</p>     <p>&nbsp;</p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="3"><b>Introduction</b></font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">Climate change    is driven by changes in the atmospheric concentrations of greenhouse gases and    aerosols. These gases affect the absorption, scattering and emission of radiation    within the atmosphere and the earth's surface, thus resulting in changes in    the energy balance (IPCC, 2007). Since the mid-19<sup>th</sup> century, our    globe has been moving towards a warm period (Oliver-Smith, 2009). As the planet    warms, rainfall patterns become erratic and extreme events such as droughts    and floods become more frequent.</font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">South Africa is    viewed as a water-stressed country with an average annual rainfall of 500 mm    (the world average annual rainfall is 860 mm) with decreasing precipitation    from east to west. Total groundwater use is estimated at 15% over 65% of the    surface area of South Africa.</font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">Any climatic change    could have adverse impacts on the water resources of a water-stressed country    like South Africa. The potential impacts of climate change on water resources    and surface hydrology for Africa and Southern Africa have received considerable    attention from hydrologists during the past decade (e.g. Lumsden et al., 2009;    IPCC, 2008), but very little research has been conducted on the future impact    of climate change on groundwater resources in South Africa. Climate change can    affect groundwater levels, recharge and groundwater contribution to baseflow.    The question of the likely impact of climate change on renewable groundwater    resources is highly relevant, but under-researched (Kundzewicz et al., 2008).    This paper serves as a first step in assessing the impact of climate change    on South Africa's aquifers on a regional scale.</font></p>     <p>&nbsp;</p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="3"><b>What is climate    change?</b></font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">The earth's climate    system is governed by the energy that it continuously receives from the sun.    About 70% of all solar energy is absorbed by the earth through the oceans, continents    and the atmosphere whereas the remaining 30% is reflected back to space. The    absorbed heat is later re-emitted in the form of infrared radiation or transferred    by heat fluxes. However, certain gases in the troposphere and stratosphere absorb    most of the outgoing infrared radiation before it can escape into space, thereby    warming the atmosphere before the heat is once again re-emitted. These are referred    to as greenhouse gases (IPCC, 2007).</font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">This greenhouse    effect results in the earth being warmer than it would be. Without it, life    on earth would not be able to exist. However, of current concern to scientists    is the increased concentration of greenhouse gases (for example, due to the    burning of fossil fuels and deforestation) within the earth's atmosphere, which    results in the warming of the lower atmosphere and appears to be changing present    climate patterns. A shift in the earth's climatic regimes and changes in the    nature of weather events are commonly referred to as climate change.</font></p>     ]]></body>
<body><![CDATA[<p>&nbsp;</p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="3"><b>Climate change    in South Africa</b></font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">Africa is seen    as one of the most vulnerable continents to climate change and variability due    to multiple stresses and low adaptive capacity. The livelihoods of people in    Africa, including South Africa, are often directly linked to the climate of    the area (CSIR, 2010).</font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">South Africa is    a water-limited country with a changing water-management structure and priorities.    It is situated in a region with increasing levels of water scarcity and water-quality    problems, compounded by population growth and issues of social and economic    development. The introduction of additional stresses on water resources arising    from potential climate change can intensify these problems over much of the    country.</font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">Predicted climatic    changes for South Africa include a general warming across the country of higher    average temperatures in sub-humid areas. Mukheibir (2008) suggests that the    temperature is expected to increase by approximately 1.5&deg;C along the coast    and 2&deg;C to 3&deg;C inland of the coastal mountains by 2050. Cav&eacute;    et al. (2003) stated that the Western Cape is likely to experience an extended    summer.</font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">Decreases in rainfall    for the Western and Northern Cape Provinces and disrupted rainfall patterns    for other areas can be expected. Eastern and Southern Africa, on the other hand,    can expect higher average annual rainfall patterns. Hewitson et al. (2005) indicate    a wetter escarpment in the east, a shorter winter season in the south-west,    a slight increase in intensity of precipitation, and drying in the far west.</font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">Schulze (2000)    has demonstrated clear runoff reductions in the already dry western part of    Southern Africa. Turpie et al. (2002) suggest that the country's main rivers    are likely to have reduced runoff or become less predictable. Arnell (1999)    too predicts a substantial reduction in runoff in the Limpopo (-30%) and Orange    (-5%) catchments as well as decreases in the volumes of low flows in these 2    rivers.</font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">An increase in    the occurrence of extreme events (floods and droughts), depending on the region    and the time of year, may occur due to the projected increases in rainfall and    rainfall intensity that cause flooding. According to predictions, a rise in    sea levels in coastal zones as well as seasonal changes (i.e. shifts in the    annual timing of rainfall and temperature) can be expected.</font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">It is clear from    this discussion that climate change is a reality and is therefore an important    consideration in the field of geohydrology. Despite its relatively small contribution    to bulk water supply, more than 60% of South Africa's population is dependent    on groundwater (Braune and Xu, 2008).</font></p>     <p>&nbsp;</p>     ]]></body>
<body><![CDATA[<p><font face="Verdana, Arial, Helvetica, sans-serif" size="3"><b>Quantifying    climate-change impacts</b> </font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2"><b>Preamble</b></font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">Global General    Circulation Models (GCMs) have become the primary tools for the projection of    climate change. Bates et al. (2008) describes a GCM as a numerical representation    of the climate system, based on the physical, chemical and biological properties    of its components, their interactions and feedback processes. GCMs depict the    climate using a 3D grid over the globe. The horizontal resolution of these grids    can vary between 250 km and 600 km which is considered coarse when compared    to the scale at which typical geohydrological are carried out. Projections of    future climate change through GCMs may provide insight into potential broad-scale    changes in the atmosphere and ocean. These changes include shifts in the major    circulation zones and the degree of sea-level rise.</font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">It is evident from    GCMs that rising concentrations of greenhouse gases may have a significant impact    on the global climate. It is not clear, however, to what extent local-scale    meteorological processes will be affected. The gap between what climate modellers    are able to provide and what impact assessors require, is bridged by means of    so-called 'downscaling' techniques (Wilby and Wigley, 1997). The term 'downscaling'    refers to the development of regional-scale projections based on global models.    This introduces an uncertainty that limits confidence in the magnitude of the    projected change, although the pattern of change can be interpreted with greater    certainty (Mukheibir and Ziervogel, 2006).</font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2"><b>Aspects to consider    when evaluating climate-change impacts</b></font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">The main reason    for studying the interactions between aquifers and the atmosphere is to determine    how groundwater resources are affected by climate variability and climate change.    Cav&eacute; et al. (2003) propose that rainfall-recharge relationships may be    used in a first attempt to assess the impacts of climatic change on groundwater    resources. Data from various studies were compiled, and recharge rates were    compared to annual rainfall for Southern Africa. Large differences in recharge    values were identified for areas with an annual rainfall of less than 500 mm.    The observed rainfall-recharge relationship can be used as a tool to examine    possible groundwater trends if the projected changes in mean annual precipitation    occur as a response to human-induced climate change.</font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">Aquifer recharge    and groundwater levels interact, and depend on climate and groundwater use.    Each aquifer has different properties and requires detailed characterisation    and eventually quantification (e.g. numerical modelling) of these processes    and linking of the recharge model to an appropriate climate model (York et al.,    2002). In practice, any aquifer that has an existing and verified conceptual    model, together with a calibrated numerical model, can be assessed for climate-change    impacts through scenario simulations. The accuracy of predictions depends largely    on scale of the project and availability of geohydrological and climatic datasets.</font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">Another method    proposed by Van Tonder (2010) is to utilise recession curves on projected streamflow    to obtain the change in groundwater contribution to baseflow. He proposes the    method developed by Moore (1997) where the recession curve is the specific part    of the flood hydrograph after the crest (and the rainfall event) where streamflow    diminishes. The slope of the recession curve flattens over time from its initial    steepness as the quickflow component passes and baseflow becomes dominant. A    recession period lasts until streamflow begins to increase again due to subsequent    rainfall. Hence, recession curves are the sections of the hydrograph that are    dominated by the release of water from natural storages, typically assumed to    be groundwater discharge.</font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2"><b>Quantifying    climate-change impacts on groundwater</b></font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">In analogy with    the DRASTIC vulnerability index (Lynch et al., 1994), the DART methodology was    developed. The parameters considered in the DART methodology are as follows:</font></p>     ]]></body>
<body><![CDATA[<blockquote>        <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2"><b>D</b> - Depth      to water level change</font></p>       <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2"><b>A</b> - Aquifer      type (storativity)</font></p>       <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2"><b>R</b> - Recharge</font></p>       <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2"><b>T</b> - Transmissivity</font></p> </blockquote>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">The DRASTIC vulnerability    index was developed to express aquifer vulnerability with reference to the threat    of pollution. The DART methodology focuses more on typical parameters used in    sustainability studies, but also indirectly accommodates the issue of quality    due to the fact that the water quality is likely to deteriorate with a drop    in water level over time as the salt load will concentrate. The availability    of regional data to support the DART index was a major consideration in the    selection of parameters.</font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">Two scenarios are    considered in the calculation of the DART index; current and future. The current    scenario is representative of the current precipitation patterns and represents    the time period between 1961 and 2000. The future scenario is a prediction based    on the selected GCM scenario and represents the time period between 2046 and    2065.</font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">The most probable    future scenario, in terms of atmospheric carbon dioxide concentration, is currently    uncertain. What is known, however, is that even if emissions were to be cut    today, the earth is still committed to a certain degree of climatic change (Davis,    2010). For the purpose of this article the Meteorological Research Institute    Coupled General Circulation Model was chosen with a future A2 SRES (Special    Report on <i>Emissions Scenarios)</i> emissions scenario.</font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">The A2 storyline    and scenario describes a very heterogeneous world, assuming a moderate to high    growth in greenhouse-gas concentration. The observed CO<sub>2</sub> emissions    compared to the A2 story line are shown in <a href="#f1">Fig. 1</a>. The downscaled    datasets were made available by the Climate System Analysis Group at the University    of Cape Town.</font></p>     <p><a name="f1"></a></p>     ]]></body>
<body><![CDATA[<p>&nbsp;</p>     <p align="center"><img src="/img/revistas/wsa/v38n3/08f01.jpg"></p>     <p>&nbsp;</p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2"><b>Aquifer type</b></font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">The aquifer type    was derived using the geohydrological maps of South Africa in conjunction with    the classification of aquifer type given in <a href="#t1">Table 1</a>. The resultant    map of aquifer types is shown in <a href="#f2">Fig. 2</a>. The aquifer type    is considered a static variable in the DART index and will only change with    updates to the geohydrological maps of South Africa.</font></p>     <p><a name="f2"></a></p>     <p>&nbsp;</p>     <p align="center"><img src="/img/revistas/wsa/v38n3/08f02.jpg"></p>     <p>&nbsp;</p>     <p><a name="t1"></a></p>     ]]></body>
<body><![CDATA[<p>&nbsp;</p>     <p align="center"><img src="/img/revistas/wsa/v38n3/08t01.jpg"></p>     <p>&nbsp;</p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2"><b>Recharge</b></font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">Recharge is a function    of both precipitation and slope and an attempt was made to formulate a recharge    function based on the aforementioned parameters to accommodate monthly recharge    figures based on monthly precipitation.</font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">The slope of the    area influences recharge in the sense that the higher the slope the more runoff    will occur leading to reduced recharge in these areas. A maximum slope of 28%    is detected over the whole extent of South Africa if a topographical grid of    1 km x 1 km is used as shown in <a href="#f3">Fig. 3</a>. A maximum slope of    30% was chosen as an absolute maximum and the following exponential scaling    relationship was assumed for the recharge:</font></p>     <p><a name="f3"></a></p>     <p>&nbsp;</p>     <p align="center"><img src="/img/revistas/wsa/v38n3/08f03.jpg"></p>     <p>&nbsp;</p>     ]]></body>
<body><![CDATA[<p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">The second parameter    defining the recharge function is the precipitation. The current precipitation    scenario for South Africa is shown in <a href="#f4">Fig. 4</a>. The grid structure    of <a href="#f4">Fig. 4</a> is the grid on which the climate-change scenarios    used are presented, hence the results of the DART index will also be based on    the extent of this particular grid.</font></p>     <p><a name="f4"></a></p>     <p>&nbsp;</p>     <p align="center"><img src="/img/revistas/wsa/v38n3/08f04.jpg"></p>     <p>&nbsp;</p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">Cav&eacute; et    al. (2003) established a rainfall-recharge relationship based on multiple observations    as shown in <a href="#f5">Fig. 5</a>. This relationship was proposed as a tool    to examine possible groundwater trends in response to human-induced climate    change:</font></p>     <p><a name="f5"></a></p>     <p>&nbsp;</p>     <p align="center"><img src="/img/revistas/wsa/v38n3/08f05.jpg"></p>     <p>&nbsp;</p>     ]]></body>
<body><![CDATA[<blockquote>        <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2"><i>Recharge</i>      (rara)=148*ln <i>(Precipitation)</i> - 880</font></p> </blockquote>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">In the above recharge    relationship, recharge becomes negligible for rainfall lower than 400 mm/a (Cav&eacute;    et al., 2003).</font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">The recharge function    formulated for the purpose of this study is a combination of the recharge-rainfall    relationship defined by Cav&eacute; et al. (2003) and the slope dependency assumed    for the recharge. The formulated recharge function is presented below and the    graphical representation is shown in <a href="#f6">Fig. 6</a>.</font></p>     <p><a name="f6"></a></p>     <p>&nbsp;</p>     <p align="center"><img src="/img/revistas/wsa/v38n3/08f06.jpg"></p>     <p>&nbsp;</p>     <p align="center"><img src="/img/revistas/wsa/v38n3/08s02.jpg"></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">The resultant recharge    formulation allowed for recharge to be calculated as a function of the precipitation    and slope over the area. National recharge datasets, e.g. GRA2 (Groundwater    Resources Assessment Phase2) reports recharge percentages on quaternary catchment    level which would not be suited for the GIS procedure utilised in this study    as quaternary boundaries would appear to create artefacts.</font></p>     ]]></body>
<body><![CDATA[<p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">The purpose of    the aforementioned recharge function is to determine a smooth recharge cover    over the whole of South Africa. Research on groundwater recharge is an ongoing    field of study. Governing mechanisms like episodic recharge are not yet fully    understood and cannot be modelled. The DART methodology should be updated accordingly    as new recharge models become available.</font></p>     <p>&nbsp;</p>     <p align="center"><img src="/img/revistas/wsa/v38n3/08f07.jpg"></p>     <p>&nbsp;</p>     <p>&nbsp;</p>     <p align="center"><img src="/img/revistas/wsa/v38n3/08f08.jpg"></p>     <p>&nbsp;</p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="3"><b>Depth to water    level change</b></font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">The depth to water    level was determined by using the average water level for each borehole on the    NGA (National Groundwater Archive) and then performing Bayesian interpolation    to exploit the correlation between water level and topography. A total of 244    733 boreholes were used and the borehole distribution is shown in <a href="#f9">Fig.    9</a>. A map of the resultant water levels in metres below ground level (m bgl)    is shown in <a href="#f10">Fig. 10</a>. These water levels are used as the reference    level for the current climate scenario.</font></p>     <p><a name="f9"></a></p>     ]]></body>
<body><![CDATA[<p>&nbsp;</p>     <p align="center"><img src="/img/revistas/wsa/v38n3/08f09.jpg"></p>     <p>&nbsp;</p>     <p><a name="f10"></a></p>     <p>&nbsp;</p>     <p align="center"><img src="/img/revistas/wsa/v38n3/08f10.jpg"></p>     <p>&nbsp;</p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">parameter. The    following set of maps presented in <a href="#f11">Fig. 11</a> show the monthly    water-level change between the current and future scenario.</font></p>     <p><a name="f11"></a></p>     <p>&nbsp;</p>     ]]></body>
<body><![CDATA[<p align="center"><img src="/img/revistas/wsa/v38n3/08f11.jpg"></p>     <p>&nbsp;</p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2"><b>Transmissivity</b></font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">The transmissivity    map was also produced through using the geohydrological maps of South Africa    and translating the yield values to transmissivity values using a factor of    5. Traditionally a factor 10 was used for this purpose as a rule of thumb, but    has been revised to a factor 5 as more information became available over time    (Van Tonder, 2010).</font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">The resultant transmissivities    lie in the range of 0.25 m<sup>2</sup>/d to 25 m<sup>2</sup>/d. The transmissivity    map is shown in <a href="#f12">Fig. 12</a>. Note that higher transmissivities    can occur due to the fractured nature of formations.</font></p>     <p><a name="f12"></a></p>     <p>&nbsp;</p>     <p align="center"><img src="/img/revistas/wsa/v38n3/08f12.jpg"></p>     <p>&nbsp;</p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">The change in water    level per month for both the current and future scenarios was determined using    the following relationship between water level, recharge and storage coefficient:</font></p>     ]]></body>
<body><![CDATA[<p align="center"><img src="/img/revistas/wsa/v38n3/08s01.jpg"></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">It is clear from    the relationship that the recharge is the driving force of the water level since    the storage coefficient is a static</font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2"><b>DART index calculation</b></font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">With datasets produced    for each parameter used in the DART index the calculation is done according    to the ranges, classification and associated weights presented in <a href="/img/revistas/wsa/v38n3/08t02.jpg">Table    2</a>. The DART index has a maximum score of 10 where higher values represent    more resilience to the climate-change impacts driven by the change in rainfall.</font></p>     <p>&nbsp;</p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="3"><b>Results of assessment</b></font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">The results of    the DART index are presented in <a href="/img/revistas/wsa/v38n3/html/08f13a16.htm">Figs 13 to    16</a>, which represent the monthly results for a complete hydrological year.    The results are presented as the current DART index and the effective change    the future scenario will have for each of the months. A negative value in the    change of the DART index indicates deterioration in the index compared to the    current scenario. It is important to keep in mind that the DART index is a regional    index and that it should be used to identify areas that will be negatively impacted    by climate change with respect to groundwater.</font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">The average change    in the DART index over a hydrological year is shown in <a href="#f17">Fig. 17</a>.    Note that for the majority of the country the DART index remains unchanged.    Areas that will experience an average degradation in their current DART index    are mainly situated in the Western Cape. These areas are characterised mainly    by a high slope percentage and low transmissivity values.</font></p>     <p><a name="f17"></a></p>     <p>&nbsp;</p>     ]]></body>
<body><![CDATA[<p align="center"><img src="/img/revistas/wsa/v38n3/08f17.jpg"></p>     <p>&nbsp;</p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="3"><b>Conclusions    and recommendations</b></font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">The DART index    is used as a regional screening tool to identify areas that could experience    possible changes in their groundwater resources as a result of climate change.</font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">The monthly DART    index calculations indicate a strong spatial and temporal dependency of the    index with a maximum negative index change of 6 and a maximum positive index    change of 2 over the simulated hydrological year. A negative index change represents    areas which will experience more stress on their groundwater resources with    respect to their current groundwater conditions.</font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">The temporal nature    of the DART index is also scale-dependent. This is evident from the average    change in the DART index. On average, the majority of the country will maintain    its current DART index. Note that, due to the selected recharge model, large    portions of western South Africa do not experience a change in recharge, which    in turn implies no change in water level. These low-precipitation areas are    prone to episodic recharge events.</font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">Areas subject to    average degradation of their current DART index are mainly situated in the Western    Cape and are characterised mainly by a high slope percentage and low transmissivity    values.</font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">Two scenarios manifest    themselves in areas which are subject to the same negative change in the DART    index: </font></p> <ul>       <li><font face="Verdana, Arial, Helvetica, sans-serif" size="2">Areas not experiencing      stress in their current ground- water resources might experience possible      stress in their future groundwater resources for certain months of the year.</font></li>       <li><font face="Verdana, Arial, Helvetica, sans-serif" size="2">Areas currently      experiencing stress in their groundwater resources might experience failure      of their groundwater resources in future for certain months of the year.</font></li>     ]]></body>
<body><![CDATA[</ul>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">The question is    how effectively these possible changes can be managed and will people be able    to adapt? Detailed local-scale studies should be conducted to quantify the actual    impacts in areas highlighted by the DART index. The current DART methodology    does not account for the effect of adaptation and migration.</font></p>     <p>&nbsp;</p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="3"><b>Acknowledgements</b></font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">The project team    gratefully acknowledges the contributions made by the following people and institutes:</font></p> <ul>       <li><font face="Verdana, Arial, Helvetica, sans-serif" size="2">The Water Research      Commission for funding this work. In particular, the support and guidance      of Chris Moseki is noted.</font></li>       <li><font face="Verdana, Arial, Helvetica, sans-serif" size="2">The Institute      for Groundwater Studies at the University of the Free State is acknowledged      for their support during the study of the impacts of climate change on Karoo      aquifers.</font></li>     </ul>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">The project team    values the inputs made by Prof. Gerrit van Tonder.</font></p>     <p>&nbsp;</p>     ]]></body>
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