Temperature coping strategies across Mopani District.
\r\n\tPrevalence of reading disability among school-age children depends upon the criteria used for definition; however, the prevalence of written expression disorders in estimated to be between 5 and 12 percent, the prevalence of written expression disorders is estimated to be between 7 and 15 percent, while the prevalence of dyscalculia is estimated to be between 3 and 6 percent.
\r\n\r\n\tRisk factors for learning disorders are family history, socio-economic conditions, prematurity, presence of other developmental, mental and health conditions (e.g. behavioral disorders, autism, attention deficit and hyperactivity disorders), prenatal exposition to neurotoxic agents, genetic disorders, particular medical conditions, history of traumatic brain injury or other neurological conditions.
",isbn:"978-1-83968-588-0",printIsbn:"978-1-83968-587-3",pdfIsbn:"978-1-83968-589-7",doi:null,price:0,priceEur:0,priceUsd:0,slug:null,numberOfPages:0,isOpenForSubmission:!0,hash:"0999e5f759c2380ae5a4a2ee0835c98d",bookSignature:" Sandro Misciagna",publishedDate:null,coverURL:"https://cdn.intechopen.com/books/images_new/10910.jpg",keywords:"Learning Disability Definition, Brain Plasticity, Learning Disability Evaluation, Learning Disabilities Resources, Psychoeducation Evaluation, Clinical Features, Dyslexia, Dysgraphia, Dyscalculia, Intellectual Disabilities, Autism Spectrum Disorders, ADHD",numberOfDownloads:null,numberOfWosCitations:0,numberOfCrossrefCitations:null,numberOfDimensionsCitations:null,numberOfTotalCitations:null,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"April 16th 2021",dateEndSecondStepPublish:"May 14th 2021",dateEndThirdStepPublish:"July 13th 2021",dateEndFourthStepPublish:"October 1st 2021",dateEndFifthStepPublish:"November 30th 2021",remainingDaysToSecondStep:"24 days",secondStepPassed:!1,currentStepOfPublishingProcess:2,editedByType:null,kuFlag:!1,biosketch:"Dr. Sandro Misciagna received his degree in medicine at the Catholic University in Rome. As a clinician, he has worked in different neurological departments in Italian hospitals, Alzheimer’s clinics, neuropsychiatric clinics, and neurological rehabilitative departments as the Neurological Department and Stroke Unit of Belcolle Hospital in Viterbo, Italy.",coeditorOneBiosketch:null,coeditorTwoBiosketch:null,coeditorThreeBiosketch:null,coeditorFourBiosketch:null,coeditorFiveBiosketch:null,editors:[{id:"103586",title:null,name:"Sandro",middleName:null,surname:"Misciagna",slug:"sandro-misciagna",fullName:"Sandro Misciagna",profilePictureURL:"https://mts.intechopen.com/storage/users/103586/images/system/103586.jpg",biography:"Dr. Sandro Misciagna was born in Italy in 1969. He received a degree in medicine in 1995 and another in neurology in 1999 from The Catholic University, Rome. From 1993 to 1995, he was involved in research of cerebellar functions. From 1994 to 2003, he attended the Neuropsychological department involved in research in cognitive and behavioural disorders. From 2001 to 2003, he taught neuropsychology, neurology, and cognitive rehabilitation. In 2003, he obtained a Ph.D. in Neuroscience with a thesis on the behavioural and cognitive profile of frontotemporal dementia. Dr. Misciagna has worked in various neurology departments, Alzheimer’s clinics, neuropsychiatric clinics, and neuro-rehabilitative departments. In November 2016, he began working as a neurologist at Belcolle Hospital, Viterbo, where he has run the epilepsy centre since February 2019.",institutionString:"Ospedale di Belcolle",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"4",totalChapterViews:"0",totalEditedBooks:"3",institution:{name:"Ospedale di Belcolle",institutionURL:null,country:{name:"Italy"}}}],coeditorOne:null,coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"21",title:"Psychology",slug:"psychology"}],chapters:null,productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"},personalPublishingAssistant:{id:"280415",firstName:"Josip",lastName:"Knapic",middleName:null,title:"Mr.",imageUrl:"https://mts.intechopen.com/storage/users/280415/images/8050_n.jpg",email:"josip@intechopen.com",biography:"As an Author Service Manager my responsibilities include monitoring and facilitating all publishing activities for authors and editors. From chapter submission and review, to approval and revision, copy-editing and design, until final publication, I work closely with authors and editors to ensure a simple and easy publishing process. I maintain constant and effective communication with authors, editors and reviewers, which allows for a level of personal support that enables contributors to fully commit and concentrate on the chapters they are writing, editing, or reviewing. I assist authors in the preparation of their full chapter submissions and track important deadlines and ensure they are met. I help to coordinate internal processes such as linguistic review, and monitor the technical aspects of the process. As an ASM I am also involved in the acquisition of editors. 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In many cases, this is simply solved by running a CFD model and estimating the ocean surface amplitude at the source [1] from it. This estimate of the amplitudes involves many problems and can be very uncertain, when the measured amplitudes are small, but a better method is still to be found.
\nSometimes it is better to estimate the initial wave itself, and when that is done, the energy transmission from the source to the point of impact can be quite accurately modeled in CFD models [2, 3, 4], if the shallow water wave equations are in the numerically stable domain.
\nStrong earthquakes cause large deformations of the surface of the earth, so tsunamis are more often than not strengthened by landslides triggered by the earthquake. Often the triggering earthquake does not contribute any significant amount of energy to the tsunami wave, and this seems to be the general case in the North Atlantic, where few dangerous tsunamis are reported.
\nThere have also been speculations in the scientific community about the danger of tsunamis in the North Atlantic from gigantic glacial flood waves of volcanic origin, (jökulhlaups), emerging on the south coast of Iceland. In this case, there is a well-defined probability of occurrence [5] and clear geological evidence of the volcanic events [6] but practically no historical evidence of tsunamis. For the landslide tsunamis, we introduce a translatory wave model to estimate the initial disturbance [7]. Block slide models are popular for this purpose [8]; in them the blocks must reach very high velocities to create a serious tsunami. The translatory wave model assumes that sliding blocks break up and become debris flows when the velocity is high enough.
\nWhen the wave crest of the tsunami approaches a beach, instability of the wave fronts, wave breaking, and reflection set in. There may be little reflection on a flat beach but large energy dissipation due to wave breaking.
\nFew authors discuss how this problem is to be handled in practical hazard assessment, and most often this is simply done by making all coasts completely reflecting. This is on the safe side in run-up estimation. But how the correct boundary conditions should be formulated in terms of reflection and energy dissipation in the various models reported is an open question.
\nThe following treatment on tsunamis has the emphasis on the estimation of initial disturbance and energy formation in the tsunami. The underlying theories are formulated in [8, 9] and the case studies in Chapter 7. The theory of CFD modeling of a tsunami and the associated procedures of preparing tsunami warnings are left out, as they can be found in various internet resources of the government institutions that make them.
\nTsunamis are ocean waves that are considerably different from the best known types of ocean waves, storm waves, and ocean tides. There is much less periodicity in tsunamis, and they can run over dry land in a more or less unpredictable way. On dry land, large tsunami waves have a devastating power that resembles flood waves of the type “translatory waves” [6], such waves knock down most everything in their way. Out in the oceans (deep water), it is normally like a long wave and can be modeled using the shallow water wave theory. In this, it resembles the tidal wave.
\nHowever, there are several snags in the numerical modeling of tsunamis. Ordinary storm waves create steep wave crests that break in the shore line, but tsunamis are more like a bore, or a moving hydraulic jump; Figure 1 illustrates this difference. How the final inundation height is affected is unclear. Energy is lost in the jump as the bore moves inland, but with water behind has not, so it keeps moving. Then there is the role of the bathymetry; it has an influence on the dispersion and reflection of the wave fronts that is sometimes significant and sometimes not.
\nDifference between storm waves (a) and tsunamis (b) [
In short, the mathematics and numerical schemes are well developed in tsunami modeling, but there are pitfalls that can be difficult to avoid. Even models that have been through a scrutineer’s process of calibration and validation can fail. Still, the initial conditions in the source area are the biggest uncertainty. It has therefore been concluded that verification and validation are necessary for each case, even for models that have been through this process before [10].
\nThere are several numerical methods available to treat such waves using, for example, the well-known St. Venant’s equations, see [11], to take an example. But the names used here, St. Venant’s equations and translatory waves, are usually not mentioned. Analytical solutions are possible for stationary flows using a wave progressing with constant velocity down an inclined plane, or in a funnel, as the translatory wave in [7]. In there it is also demonstrated that numerical solutions of the St. Venant’s equations can produce exactly this kind of flow without presuming a constant velocity wave.
\nHowever, when a wave runs upwards a mild slope with constant celerity c, as a translatory wave, c will inevitably reach the shallow water wave celerity, c = √gD (g acceleration of gravity and D the water depth) somewhere, and then the surface profile may become unstable, which can result in a breaking wave (bore) or a series of braking waves if the wave is very long. Figure 2 shows a nearshore breakup of this kind. The successive waves, resulting from the breakup, ride upon each other making the ultimate tsunami run-up very difficult to predict, even when the deep-water wave is well known. This difficulty is discussed further in Sections 5 and 7.
\nNearshore breakup of a tsunami wave in Phi Phi Island 2004.
It sounds like a misconception, but in deep waters outside the continental shelfs, tsunamis propagate as shallow water waves. The mathematics of shallow water waves has been investigated by many; the analytical description is well known from [12] and similar works. The equations are a system of partial differential equations of the hyperbolic type, and the solution propagates along the characteristics.
\nTsunamis originate in a source area, unlike the tidal wave that propagates in the same manner in deep water but originates from a gravity potential created by the moon and the sun (astronomical tide). In a point, well away from the source area, a tsunami wave front propagates along the line drawn from the source area through the point with the phase velocity c = √gD, called the wave orthogonal. The actual water velocity is much lower than c. How much lower depends on the wave amplitude H in the point and the usual shallow water formulae for local energy, E = ⅛ρgH2, and transported energy, Etr = E c, applied for a wave train, if there is one.
\nThe full set of the partial differential equation system for tsunami propagation is nonlinear and includes terms for Coriolis forces and shear stress at the bottom and wind stress at the surface of the ocean. However out on deep water, the shear stress terms are not dominating so the equation system is only weakly nonlinear. This means that the nonlinear interaction with the local astronomical tide will be small, so its amplitude and velocity can be added without damaging errors, while the wave stays in deep water. This is not the case in shallow water.
\nThe wave celerity c of a tsunami is the velocity of propagation of both the surface disturbance and the transported energy. This velocity is very high when the water depth is counted in kilometers, comparable to the travel speed of a passenger jet. This has a great impact on the danger of the tsunami. The tsunami attack comes swiftly, few hours after the onset of the wave from the source area.
\nPrediction of tsunamis is very important in disaster prevention, and a large warning system is maintained all over the world, see, for example, https://www.tsunami.gov/. A simulation model that solves the partial differential system numerically is the heart of every warning system. The model usually simulates the real wave quite well in deep water, so the estimate for the arriving time of the attacking wave may be quite accurate even when the amplitude of it is less accurately predicted. Waves that originate from the continental shelf and run over deep water regions to their place of attack are a special problem. They usually start out as displacement waves, i.e., waves without characteristic periodicity, but change to an oscillatory wave train in deep water, and the periodicity of the wave train may be difficult to model.
\nNumerical simulations of tsunami waves are an invaluable part of the tsunami warning system, but the uncertainty about initial wave heights and total wave energy generation is a problem.
\nShortly after the tsunami wave hits the continental shelf, it reaches shallow water where the processes of wave refraction and diffraction take over the propagation. The wave becomes highly nonlinear as these processes, called the shoaling, set in. The wave fronts turn toward the coast, so the angle of attack is different from the deep-water direction. An example of wave fronts curved by shoaling may be seen in Figure 2.
\nWhen the wave hits the shoreline, the shoaling process is finished and is followed by the run-up. Approaching the coast from a reference point, the tsunami wave runs into a new near-field process of breaking and run-up of the tsunami wave and inundation of the land. In the run-up, large tsunami waves travel ashore as spilling breakers; this is a nonlinear process. The methods to predict such processes are extremely complex; depend on the incoming wave height and natural and manmade landscape; and are very difficult to model. The run-up wave height must be estimated for each place individually. Several mathematical solutions exist for the shoaling process, both analytical and numerical from CFD. The analytical methods mostly utilize conservation of momentum or transported energy, but they are for two-dimensional waves only. Run-up heights and attenuation are very difficult to control in numerical calculation, because of difficulties in modeling the breaking of water waves, influence of obstacles on the beach, and the amount of energy dissipated in this process [13].
\nIn finding some expressions for shoaling and run-up of two-dimensional waves, two kinds of waves will be considered: Firstly, a displacement wave, which is translatory in nature. Secondly, an oscillatory wave is considered; it has different properties than the displacement wave. When we have big tsunamis, it will be the displacement wave that hits the nearby coasts but may become an oscillatory wave farther away from the source.
\nA bore, H meters high above still water level, will be formed as the water particles cannot overtake the wave front. A bore that inundates the land travels ashore as a breaking wave. Bore is formed when the water velocity u = c. According to first-order wave theory, this leads to H = D (D is the breaking depth of the wave), but from higher-order theories and practical experience, H = 0.7 D is closer to the true value for long waves breaking on a beach. If the beach slope is only slight (e.g., river estuaries), traditional long wave mild slope equations in [13] are valid. We will have an inundation, or run-up, to a level of R = H above still water level. If the slope is steep, full or partial reflection sets in, but for steep and mild slopes, R will not exceed:
\nThe shoaling process is assumed to be near linear for tsunami waves of a very small steepness. Linear theory for shoaling means keeping the energy flux constant until the point of breaking. Then we find:
\n\n
The amplification factor due to shoaling of the radial wave is denoted as a. Hb(r) is the breaker height of the incoming radial wave. For waves of around 1 m coming in from the deep regions of the ocean, it can become a = 2–5. For waves of a few centimeters, it can become a = 5–10. When Hb(r) is found, the run-up will be the same as in the case of the displacement wave, 1.0–1.35 times the breaking wave height.
\nThis investigation shows that the run-up process depends very heavily on the far field wave height. But if a reference point is selected in water that is deep enough to exclude the effect of breaking on the wave height estimation, then we will have a quasi-linear transfer process from the source area to the reference point. This means that a fixed coefficient, independent of source area wave height, can be used as a wave height transfer coefficient from the source area to the reference point. This method is utilized in Chapter 6.
\nLarge earthquakes usually start a tsunami. The earthquake deforms the bottom landscape and creates a surface disturbance in the source area and the associated transfer of energy to the water mass. This energy is transmitted from the source area by the tsunami wave.
\nAn earthquake of magnitude 7 or larger on the Richter scale usually starts a tsunami. However, this is a rule of thumb only; smaller earthquakes can trigger a tsunami by starting a submarine landslide on bottom slopes. If it does, the magnitude of the tsunami depends on the size of the landslide, so the tsunami can be enormous even though the earthquake is small. Some years ago, it was discovered that huge submarine landslides on the continental shelf of the North Atlantic Ocean have caused large tsunamis. In Table 7.1 in [14], 11 submarine landslides with slide volumes 20–20,000 km3 are listed. Submarine landslides of that magnitude run as translatory waves. The deadliest tsunami attacks in the recent years have struck Indonesia and the Indian Ocean coasts; the most recent one is the Anak Krakatau volcano, where a submarine landslide of type Case 1a (see Section 5.1) caused a tsunami December 22, 2018.
\nIf a landslide is triggered or not, it can be stated that a movement on the sea bottom creates a surface disturbance with a certain potential energy, deduced by the common methods of wave mechanics. Some kinetic energy will also be created in the boundary layer around the moving object; this is mechanical energy and can thus be converted in wave energy in the tsunami wave. But as a rule, the kinetic energy will be converted to turbulent energy that cannot be converted into wave energy and is dissipated. Thus, the total potential energy of a mass that flows from land and into the sea is not converted into wave energy; only the potential energy of the initial disturbance it causes on the sea surface contributes to the tsunami.
\nIn estimating the mechanical wave energy generated in the source area of a tsunami, three types must be considered and separate estimates devised for each one. The different types are landslides down mountain slopes and in the water where V > c (Case 1). Totally submerged submarine landslides where V < c at least in for a part of the slide (Case 2) and bottom landscape features are moving vertically and horizontally (Case 3). The initial tsunami wave height is estimated. The energy transmitted to the water by the movement of the landslide is estimated from the moving mass. The total wave energy is estimated as the potential energy in the water mass the slide displaces from the still water surface, using the assumption that turbulent energy transmitted to the water cannot be regenerated as mechanical energy in the tsunami wave.
\nThe wave energy transmission away from the source area can be translatory or by a solitary group of oscillatory waves. The wave transmission can be estimated in numerical models, and the shoaling also until either the point of breaking or where the numerical stability is lost in the model. In the following we will therefore estimate the wave energy generation in the source area and the corresponding wave amplitudes. In the following, the expressions for the wave energy and amplitude h depend on the variables listed here.
B: The width of the submarine landslide | \nV: Velocity of the front | \n
y0: The frontal height of the landslide | \nLh: The length under water | \n
xv: Distance from the shoreline to c = V | \nxw: Distance to slide front | \n
Cm: Average wave celerity in xw − xv | \nLhb = Ls + (xw − xv)Cm/V | \n
Ls: Effective length of a submerged slide | \nρ: Density of water | \n
For further discussion and estimation of slide dimensions, see Section 7 and [6, 9, 15].
\nIn this case the surface disturbance, or the water wave, cannot run away from the translatory wave, i.e., the submarine landslide that causes it because c < V. The water volume above the still water level will therefore simply be equal to the displacing volume, of the submerged part of the slide. The estimates for the energy of the initial wave are for the two sub-cases: Case 1a, a slide that originates from land, and Case 1b, a slide that originates at the sea bottom.
\nThe displaced water volume will be equal to the total submerged volume of the slide. The slide will hit the water with a great splash and run on the bottom until it stops. The water will be lifted the distance y0 from the bottom, and this will be the resulting height of the water wave when the slide suddenly stops. In that situation, the energy added to the water will be.
\n\n
The wave progresses in the x direction with the shallow water velocity c. In a numerical model, the initial condition for the tsunami wave height h will be zero everywhere, except in the source area where h = y0 in an area of size B Lh.
\nNow the slide will leave a scar, or a hole Ls long, in the seabed of volume LsB y0. An equal part of the slide will be outside the scar and leave a heap at the slide front. The hole and the heap have the same volume. We will find.
\n\n
In a numerical model, the initial condition for the tsunami wave height h will be zero everywhere, except in the source area where h = −y0 in the hole area of size B Ls and h = +y0 in the heap area.
\nIn this case, the slide passes the point where V = c, or the depth D = V2/g, and the water wave will run away from the front of the translatory slide wave. When the slide front stops, the water wave front will be at a distance Lha = xv + (xw − xv)Cm/V away from the shoreline. In estimating the energy, we still have to distinguish between the two schemes (a) and (b) as before.
\nIn a point xv from the shoreline, we have c = V, the velocity of the slide, but the slide stops at the position xw from the shoreline. With Cm denoting the average shallow water wave velocity in xw − xv, we will have Lha = xv + (xw − xv)Cm/V for the distance from the shoreline to the water wave front. Now we have a wave height slightly less than before.
\n\n
The energy of the water wave becomes
\n\n
In a numerical model, the initial condition for the tsunami wave height h will be zero everywhere, except in the source area; we will have h = h2a in a square of size B Lha.
\nAssuming the slide will start where c < V, we now have Lhb = Ls + (xw − xv)Cm/V. The slide will leave a scar in the seabed of size LsB. A part of the slide, κ Ls(κ< 1) long, will be outside the scar and leave a hole in the scar of area of volume κy0LsB. At = 0 there will be a through in the water table approximately corresponding to this volume, but in the front of the slide, we have an initial wave Lhb long and h2b high with the same volume as the through. Then we have.
\n\n
In a numerical model, the initial condition for the tsunami wave height h will be zero everywhere, except in the source area; we will have a through y0 deep and a wave h2b high at time t = 0.
\nIn both Case 1 and Case 2, the slide is very likely to be in shallow water. A sudden increase in depth is therefore possible as soon as the tsunami wave sets out from the source area. A translatory wave with the velocity V, in a place where the wave celerity is c1, will in theory continue to flow until the bottom slope I0 is zero, but in practice it will stop sooner. The water wave will therefore run into deeper water with higher wave velocity c2, and that affects the wave height. When the slope where the slide is running downhill fades out to a flat bottom, there is no problem in the numerical model, but in the rare occasions when there is a sudden increase in the ocean depth just in front of that point, it may provide better results to find the height h2 of the initial wave in the deeper water:
\n\n
Here index 1 refers to the shallower source area and 2 to deeper water. The energy flow Eq. (8) assumes the translatory wave motion to be preserved. The translatory wave may be transformed into a group of oscillatory waves; the details of that wave group are unclear.
\nSimilarly, it is not quite clear what will happen in the case when the slide starts at a depth where c > V. In this case, the distance xv is not defined, but if the run time of the slide can be estimated, the water wave height can easily be found.
\nA movement of the ocean bottom by an earthquake usually happens fast. The movement will leave an uplift of the ocean surface where the bottom is lifted and a sink where the bottom sinks down. Both the lift and the sink contribute to the potential energy of the disturbance.
\nThere are two possibilities to model this: Firstly, to find the Fourier transform of the surface disturbance and, secondly, to use linear wave theory to radiate it away from the source. Analytic models can be used for this if the boundary configuration can be coped with. Otherwise, a numerical model with an initial surface disturbance of the same configuration as the bottom disturbance is the only chance.
\nThe earthquake event and the devastation caused by this tsunami is very well documented; it is the most famous tsunami event of recent years. It took place off the Pacific coast of Tohoku, Japan, on Friday, March 11, 2011 at 05:46 UTC. It was caused by a Mw 9.0 (magnitude moment) undersea megathrust earthquake with the epicenter approximately 70 km east of the Oshika Peninsula of Tohoku with the hypocenter in approximately 30 km deep water (see Figure 3 gray arrow).
\nLocation chart of the tsunami site with the epicenter (red star) and an exploration well, drilled at site C00 19, [
From the data obtained in the exploratory drilling at the site shown in Figure 3, it was concluded in [16] that the tsunami was caused by the mass movement shown in Figure 4.
\nThe 2011 Tohoku earthquake: Coseismic slip distribution model, from [
The details of the bottom deformation are estimated and pictured in Figure 3b in [18]. This picture resembles a 150 km long slide scar with Ls and B about 110 km and y0 about 8 m using the symbols in Chapter 5.2. This would be a Case 2b slide, stopping 25–75 km from the trench, see Figure 4; here the average bottom slope is about 4/50 or 8–9%. It is interesting to note that layers of fine sediments on such a slope can easily liquify, slide down the slope, and cause a bottom deformation like the one pictured in [18] and indicated by black arrows in Figure 4. No evidence has been found in [16] to support this suggested slide event, but the information on the bottom deformation given in [18] is considered reliable, and it is supported by a coseismic slip model in Figure 4 in [17]. The suggested slide would have characteristics that can be calculated using the equations for the Case 2b slide. If the slide is due to liquefaction, the movement will start at the onset of the strong motion and stop when it stops. According to graphs in [18], this time is about 30 seconds; this is an information additional to what we have in Sections 5.2.2 and 5.2.3.
\nV = 2 m/s corresponds to the 9% slope and y0 = 8 m. Together with the time 30 s, this gives a horizontal flow path of 60 m. This corresponds well to Figure 4, giving 56 m as maximum horizontal deformation.
\nThe water depth gives c = 250 m/s so we get Lbh = 250 × 30 = 7500 m = 7.5 km for the initial disturbance. As the flow path is short the κ ∼ 0. Now we get.
\nLbh = Ls + 7.5 = 110 + 7.5 = 117.5 km.
\nThe uplift caused by the coseismic movement means that there will be just a small hole in the scar area. The volume of the heap caused by the slide will be.
\nWT2b = By0Ls = 1 × 110000 × 8 × 110000 = 9.68 × 1010 m3 = 96.8 km3.
\nThe height of the wave with same volume as in Section 5.2:
\nh2b = WT2b/(Lhb B) = 8 × 110/117.5 = 7.5 m.
\nEq. (7) must be modified due to the uplift and the small scar hole; this is done by putting κ ∼ 0 as before, and then we have for the energy in the source area:
\nEW2a = ½h2b2 Lhbρ g B = ½ 7.52 × 117500 × 1025 × 9.81 × 110000 = 3.6 1015 Nm.
\nThis result can be checked against the simulation results published by NOAA [19]; it is on Figure 5 and shows the spread of the tsunami very well. Comparing this with a ring wave spreading in an effective 90° conical channel gives a resulting average wave height 2–3 feet 900 km from the source. According to C = 250 m/s (800 km/h), this should occur after little more than 1 hour. This checks well against Figure 5.
\nSpreading of the Tohoku tsunami in the Pacific Ocean March 11, 2011. (NOAA Center for tsunami research, Pacific marine environmental laboratory; NOAA. 2011. Printed in the N.Y. Times).
The bottom deformations that caused the very strong Tohoku tsunami in the Pacific Ocean, simulated numerically by the Japanese and USA scientists, [17, 19], can be explained by a submarine landslide. This suggests that the coseismic slip of the earthquake triggers a sliding of the surface sediments. In combination they cause the bottom deformation. Finally, it can thus be concluded that the coseismic slip and the landslide are both responsible for the Tohoku tsunami in March 2011, not the coseismic slip alone.
\nThis shows that in assessing the tsunami risk in the Pacific coastal regions of Japan, the landslide risk must be considered. This fact may result in that considerably larger events than the Tohoku tsunami are possible if a larger slide than this 8 m thick slide is released. This landslide is not very high compared to what has happened elsewhere. The assessment of this possibility of larger slides can be difficult; there is considerable uncertainty in estimating the height (y0) of possible landslides.
\nThere are many tsunami sources in the Atlantic Ocean, but in the northern regions, the tsunami risk is less than in many other places, and the source of the main threat may be unknown, both location and magnitude. A good method is presented in [9], to estimate the hazard curves for a reference point in south Iceland. This involves estimating initial wave heights at the source and their frequencies. Then the transfer functions must be applied, and the hazard curves are found by numerical integration.
\nTo assess the risk, we have to estimate event return periods for the various event magnitudes and the correlation structure of the event history. This correlation may be between time length between events and event magnitude and autocorrelation (positive or negative) in the time history.
\nThe very long records necessary for a complete picture of the event statistics are normally not available. Certain assumptions are necessary, but we must estimate the basic statistics such as average time between events, ta, the standard deviation associated to it, ts and the correlation between magnitude and event interval ρ (note the different meaning of ρ in chapter 5). Now the following formula can be derived for the interval between tectonic events, it being earthquakes, submarine slides, or volcanic events:
\n\n
i | \nNumber of event occurring at time t(i) | \n
gk(i) = ((t(i + 1) − t(i) − ta)/ts | \nDimensionless relative time between events | \n
hk(i) = ρ(Hk(i) − Ha)/Hs | \nRelative magnitude, e.g., wave height | \n
ρ = E{gk(i)hk(i)} | \nMagnitude time correlation (E denotes average) | \n
ek(i) | \nRandom function ek(0.1) | \n
k | \nSeries number | \n
The time between the tectonic events i and i + 1 is known when gk(i) is known so series for the occurrence of events in time can be simulated when hk(i) is known. If the simulation period is a limited number of years into the future, it is necessary to simulate sufficiently many series (the number k) so the statistical distribution of H is represented.
\nIf this statistical distribution is not known, some classification that fits available observations of H has to be assumed. Three classes, small, medium, and large events, should be considered as minimum. Then the Monte Carlo method is used to simulate the k series, and they are used to determine the statistics of interest empirically. These are various hazard curves and event probabilities for fixed periods to come, e.g., economical lifetime of structures and so on. It must be noted that the probability of a specified event of a given class happening in the next year is not a constant. This probability will increase with time.
\nThere are several methods to estimate the distribution functions we have to use as building blocks in Eq. (9) recommended in the literature. The log-normal distribution is often usable for gk, especially when ρ is low [5].
\nWhen there is more than one source, the procedure has to be repeated for all significant sources. Then the transfer functions have to be applied and Ha and Hs calculated for the chosen reference point. Hs is much more difficult to estimate from observations than Ha, but sometimes it is possible to estimate the coefficient of variation Cv = Ha/Hs. If not it has to be included as a parameter in order to estimate the accuracy of calculated probabilities and risks.
\nIn [9], all this is done for a reference point south of Iceland. There are eight possible sources for tsunamis in the North Atlantic, six of these are found significant for the reference point chosen. For clarification the reference point is shown and the resulting risk curve.
\nThe only significant Icelandic source contributing to the calculated tsunami height in the reference point on Figure 6 is the Katla volcano [6]. The hazard curves for these points are in Figure 7. Here all the risk curves follow the Gumbel distribution P(H > x) = exp(−exp(−y)) where y = 3.91 + 1.12 x rather closely. Here the probability P does not denote the next event, but the maximum to be expected in the next year (annual maximum); it will be x = (y − 3.91)/1.11 in each point in Figure 7.
\nIcelandic coastal waters, depth scale by deeper blue for each 200 m. Population centers in red [
Hazard curves for the reference point with three different Cv values. The abscissa is the Gumbel variate [
The probability is for the maximum to be expected in the next year (annual maximum). To take an example, the maximum to be expected in the very next year with probability P = 1% or 0.01 has the Gumbel variate 0.4, corresponding to a wave height of x = 0.1 m which is rather insignificant, but for P = 0.1%, the Gumbel variate is 2.8 giving seven times larger wave height.
\nTsunami attack is very difficult to predict, even though the models that simulate the propagation of the tsunami wave over deep water are very good and in most cases reliable. The mathematics of these models is very difficult, but effective, as long as the wave stays in deep water [20]. The difficulty in modeling is to predict the shoaling and the run-up. And then there is the uncertainty about the initial wave height and wave energy formation in the source area.
\nThe importance in such analysis is to identify the sources that cause the largest tsunami threats. The methods devised in Chapter 5 can be used to estimate the initial wave and energy in the source area when the bottom deformation is known. This is demonstrated in the case study of the Tohoku tsunami, in Section 6.1; in [21] is a detailed description of this huge event and its consequences.
\nThe cause of the bottom deformation is directly or indirectly an earthquake. It can start a submarine landslide, or the earthquake wave itself can deform the bottom so much that a large tsunami is produced, especially earthquakes above 7 in magnitude. But this very information tells us that the variability in tsunami properties will be very great in the source area. The magnitude of the average event may be possible to estimate from existing observations and geophysical data, but their standard deviation will always be difficult to estimate; usually there are not enough observations of serious tsunami events to establish a reliable value for this coefficient.
\nIn the example taken in Section 6.2, there are eight identified tsunami sources in the North Atlantic Ocean, six of these contribute significantly to the hazard curve in the danger zone on Figure 7. This is the zone above 2 m, meaning that the tsunami has to be 2 m or higher to pose any significant threat alone, i.e., without being accompanied by a flood of different origin [9] or attacking upon a spring tide flood.
\nThe effect of the coefficient of variation on the hazard curve Figure 7 is quiet surprising. The estimation of its value is very difficult. However, to leave it out corresponds to estimating its value to be zero, and that is totally unsatisfactory. In Figure 7 the effect of three different values, common in geophysical data, is demonstrated, and the difference is quite striking. The difference in frequency of occurrence is of one decade, up or down, from the Cv = 1/2 value.
\nThe translatory wave theory is used to estimate the expressions for energy and wave height in the source area, and it can be used for the initial conditions in wave models.
\nEarthquakes, of too small a magnitude to produce dangerous tsunamis themselves, can do so by triggering submarine landslides.
\nApproximate analytical methods can give good results as a first approximation for the transfer functions that link the wave heights in the source area to wave heights in a reference point selected in the wave propagation path. The best position for such a point is offshore, outside the zone of nonlinear shoaling and wave breaking, but near the places where the attack of the tsunami is expected. Then a hazard assessment may produce a wave height-frequency curve for this point.
\nIt is clearly demonstrated that it is very important to include the Cv factor for the event magnitude in the hazard assessment. Otherwise the tsunami wave heights for a given frequency may be seriously underestimated.
\nFor high Cv values the hazard curves may be expected to follow the Gumbel distribution or possibly another distribution of the extreme value distribution family because the hazard curve is the maximum expected frequency for a given wave height.
\nPart of the theories herein is developed for the Básendaflóð (The Flood at Basendar Iceland in 1799) research directed by Sigurður Sigurðarson, Section Engineer, Icelandic Road and Coastal Administration, and in cooperation with Gísli Viggósson Consulting Engineer, Reykjavík Iceland. This project was supported financially by the Research Fund of the Icelandic Road and Coastal Administration who also sponsored this publication. Their support is greatly acknowledged.
\nThe authors acknowledge Japan Agency for Marine-Earth Science and Technology and the NOAA Center for Tsunami Research, Pacific Marine Environmental Laboratory, for the use of material referred by them.
\nThe author declares that there are no conflict of interests regarding the publication of this chapter.
Adaptation to climate change hazard is attracting growing international attention as confidence in forecasts for climate change is rising [1]. Developing countries have unique adaptation needs because of high vulnerabilities and the tendencies to bear a significant share of global climate change costs [2]. The Intergovernmental Panel on Climate Change\'s (IPCC) Fourth Assessment Report noted that public recognition and concern about the global environmental issue of human-induced climate change has reached unprecedented heights. Research into the drivers, both natural and anthropogenic, the character and magnitude, their impact on human living conditions and ecosystems, and possible approaches to adaptation and mitigation, as well-as understanding of the complex relationships with ecosystems interacting with them, has also increased in recent years [3].
While anthropogenic greenhouse gas emissions, which aggravates climate change are mainly from rich industrialized countries, the consequences of which are projected to be relatively acute and more serious in developing countries particularly in semi-arid region of Africa, where, for instance, rise in temperature and reduction in precipitation are likely to result in high evaporation, with serious health related consequences [4, 5]. South Africa like many developing countries’ national economies and employment heavily rely on climate-fed activities [6], coupled with high poverty levels, limited technological and weak institutional ability to adapt to climate change qualifies for classical case in which urban populations (children, elderly, persons with disabilities and women) are more susceptible to climate change adversities [7].
Nonetheless, climate change adaptation strategies and projects on one hand, still focus mainly on sustainable rural adaptation, without much attention on urban areas, especially small and medium towns, where there is increasing household vulnerability and climate change pressures [8]. Current literature on adaptation to climate change in urban areas are largely coastal and big city biased [9, 10, 11]. On the other hand the early years of international climate change studies’ attention on adaptation as a strategy was compromised by mitigation and impacts [12]. In recent years, several models incorporate mitigation, as an anthropogenic intervention to the changing climate [3] and has rapidly escalated, while models that incorporate adaptation are still in their various stages of development, advancement and yet to reach maturity [13].
Inherently, it has become urgent to focus on approaches and instruments that assist with the reduction and reversal of the prevailing and unescapable climate change hazards, coupled with the need to maximize the immediate manifestation of the net benefits of adaptation [14]. As an essential policy response, local level and individual (including private) households’ adaptation strategies to climate change needs to be apportioned the desired priority in climate change policy agendas at all levels and scales of governance.
This chapter aims through a holistic approach, to provide the highlights of the South African governments at several levels and scales of governance to advance adaption and mitigation urban household practices and interventions. This analysis and discussion is conducted within the global context of existing adaptation framework that incorporate the local level and individual households’ (private) adaptive practices, efforts and initiatives. Furthermore, the chapter also identifies some of the key issues hindering the success of urban adaptation policies and interventions in the region.
In brief, the chapter places in perspective, the basic steps necessary for a more participatory urban management for sustainable households’ adaptation to climate-related hazards in the semi-arid region of Mopani, South Africa.
The new climate is no longer a doubtful global reality, but a phenomenon that we need to learn to live with for years to come [11]. Its disposition to leaving no facet of human endeavor immune from its negative externalities are unpredictable and presents very worrisome realities for the contemporary society and urban communities [15] largely manifesting beyond alterations in temperature and precipitation threatening the existence of humanity, particularly in Africa, and other developing countries [3, 16].
Adaptive ability to climate change hazard is considered a new field of endeavor, serving as a converging point for several experts, ranging from development experts, climate scientists, planners, disaster managers, and a host of other experts and disciplines/fields [17]. This has brought about divergent conceptual models to the study of vulnerability and adaptation, though addressing similar issues and emphasizing similar processes, but rather with different vocabularies [18]. The growth in the body of literature on the conceptual issue has brought about a confusing set of terminologies with unclear relationship [16, 19, 20]. However, notwithstanding the differences, the recognitions and understanding of the need to curtail the adversities of the phenomenon is the most crucial.
The frustrations from the present context of failure to successfully mitigate greenhouse gas emissions and curtail its associate developmental issues has resulted in adaptation becoming not only an inevitable strategy to frustrate vulnerability but also an integral social components for vulnerability assessment [16, 21]. However, this course of action is still in the trial periods of being considered relevant, particularly within science and policy contexts [22, 23].
Adaptation to climate change, is the “adjustment in natural or human systems in response to actual or expected climatic stimuli or their effects, which moderates harm or exploits beneficial opportunities” [24] as cited in [25]. It can take various dimensions from being reactive or anticipatory, private or public, and autonomous or planned [24], it can equally either be active or passive [26], spontaneous or prompted by alteration in conditions [27]. It is however a phenomenon that its success is hinges on the adoption of several co-and interdependent factors, including but not limited to human, technological y and policy matters.
However, many regions of the world, particularly Africa currently have limited access to these technologies, appropriate information and financial resources [28]. The cost-effective use of adaptation strategies will therefore depend upon the availability of financial resources, technology transfer, and cultural, educational, managerial, institutional, legal and regulatory practices, both applicable domestically and internationally [29, 30]. Hence “the need to consider indigenous knowledge system-based support and intervention”, for effective climate change adaptation strategies as one of the under-studied and utilized adaptation and mitigation strategy especially in Africa and developing countries in general [31].
In this chapter we further argue that like all other cultures, in Mopani District people are essentially adaptive, while exposed to environmental variability and risky circumstances in the past. These events called to question the local people’s adaptive capacity in respect to environmental variability and risk within the resources and technologies available options to them [32]. Therefore, to efficiently and adequately confront the prevailing and the potential climate change hazards, indigenous knowledge (IK) must be embraced, but be enhanced particularly beyond peoples’ experienced coping option ranges [33, 34]. The development and adoption of IK notion has necessitated the paradigm shift from organic adaptation approach to scientific adaptation framework models that attempt to respond to gaps ranging from adaptation needs determination, to adaptation assessment and interventions. The ensuing section of this chapter attempts at the identification of some existing adaptation models from a historical lens perspective, to typologies of these models and gaps that characterized them as well-as offering suggestions for improvements.
Adaptation modeling field is wide, varied and is punctuated with largely unclear disciplinary/field boundaries [35]. The definition of what are its constituents is equally open to numerous interpretations, with tagging of several models as adaptation models added another confusing layer to the identity and boundaries controversies [36]. In several contexts of science, models are considered very essential and key in different fields, disciplines and specialties. For instance, Evolutionary models are very important in the biological sciences disciplines while the agent-based models are a dominant feature in the social sciences [37]. Models are painstakingly built, tested, compared and revised in light of practice and feed-back loop for future lessons [36].
On a general note a classification of models on climate change adaptation was further made in line with the existing ones by [36] who identified two distinct typologies or categories of adaptation models, these include:
Adaptation Centered Models (ACMs); and
Impact Centered Models (ICMs);
Over time, advancement in understanding the consequences of climate change and policy interpretations and the associated challenges has occasioned a shift in global priority in climate change policy [37, 38, 39, 40]. At the onset, an undeviating cause–effect style prevailed, then climate situations forms the foundation upon which future climate impacts is estimated, which then outlines the needs for adaptation. With this linear concept, on one hand, adaptation to climate change is divorced from social activities and processes where needs are informed by scientific manipulations [41, 42] on one hand. On the other hand, a more comprehensive approach where the risk assessment is guided by management of past climatic hazards experience, and adaptation recommendation are determined by the option’s probability to reduce the prevailing and future climate risks while synergizing with other policy objectives, and existing management activity [43]. The later concept is currently in vogue and has enjoyed patronage from researchers, academics and policy makers, informed by its openness and comprehensiveness. Upon the determination and assessment of the needs, the choice of the form of adaptation will be made from the following identified three adaptation options:
No-regrets adaptation options;
Proactive anticipatory adaptation; and
Win-win adaptation
These options are not new, but the policies in various forms of decision models about them in Mopani District like other municipalities is currently characterized by limited attention and priorities [44]. Thus, making the success of the municipal adaptation efforts to appear unsuccessful.
However, a probe into the available literature and survey analysis with respect to climate change adaptation and the various adopted models in the study area, revealed some essential issues. These are policy related issues; Climate change issue; and adaptation issues. These issues form the fundamentals upon which the following identified gaps are considered critical in the existing models. These include:
With respect to climate change adaptation and the various adopted models, survey revealed some essential issues related to policy; Climate change issue; and adaptation issues. These issues form the fundamentals upon which the following identified gaps are considered critical in the existing models. These include:
Our findings revealed that many models on climate change adaptation, apart from being highly mathematical in nature, are based on methodological ideas that originate from the advanced economies [45], limiting their applicability in local African communities’ context. This is because the assumptions upon which the models are largely based are alien to the prevailing realities in the region particularly in Semi-arid region of Mopani District in South Africa. In addition, several of these models are largely rural biased [46], or centered on metropolitan, big and coastal cities [47]. Similarly, some are rather infrastructure or sector-specific adaptation framework such as water, transport agriculture and energy sectors [48, 49, 50, 51, 52], while rather than local community based adaptation models, other models have focused on macro level postulations [53]. Hence the need for a flexible household-based conceptual framework model that is participatory and applicable at all levels of policy and decision making.
Several studies have advocated for household-based climate change adaptation strategy to be anchored by municipal planning agency [54, 55, 56]. The study acknowledges that most local municipalities in the district are still relying on macro level climate change adaptation formulated policies from the national government. Despite that the impacts of climate change on both human and environment are well acknowledged in the various municipalities’ planning instruments (Integrated Development Plans, Spatial Development Framework etc.), yet, little evidence exist to indicate the efforts to pragmatically and coherently address the challenges [44].
During data collection, our interactions with the community members, revealed that municipal governments were rather relying on reactive adaptation procedure rather than proactive. The delay in reporting of incidence of hazards have resulted in more costly, more devastating and sometimes unrepairable situations. Due to the devastating consequences often occasioned by late reporting of climate change emergencies, the climate change adaptation challenges are complex, dynamic and contextual, thereby requiring urgent attention by stakeholders.
For adaptation to be beneficial and cost effective, it should not be solely reactionary but rather proactive and anticipatory [57]. Changing climate is no longer in doubt so also is the likelihood of the trend to proceed to the coming century at an unprecedented rate in history, as projected [20, 58] with strong signals to a rising hazards for regions of such countries that are already water-stressed, like Mopani District, Limpopo province [5, 59] and other semi-arid regions of Africa are also projected.
Hence for effective communities adaptation, government at all levels have pivotal roles to play, particularly within the global context of adaptation framework as guided by the current regime. On this basis the chapter highlights the various steps taken by the South African governments (National, Provincial, District and Local Municipalities) with regard to adaptation needs of the citizens, through policies, program and projects interventions.
In order to understand the roles of the various levels of government in South Africa in combatting the menace occasioned by climate change across the country, activities of government (National, Provincial, District as well-as local municipalities) regarding climate change adaptation were reviewed. This was assessed through the policies, strategies and legislations (Acts), and it was equally further done within the global context. The Republic of South Africa, being a signatory to Kyoto Protocol and a part of the United Nations Framework Convention on Climate Change (UNFCCC), has taken several initiatives (past and present) in striving to fulfil the expected obligations as regards the protection of citizens and the regional territory against the aggressiveness of climate change and its associated adversities. Some of these efforts as regards adaptation are highlighted in different eras in this section, and these include the following:
The legal framework for managing disaster in South Africa preceding democratic rule, were largely administered by the Civil Protection Act No. 67 of 1977 [60]. The National Disaster Management Framework (NDMF) was initiated but was characterized by inadequacies following over a hundred lives lost to Lainsburg floods in the year 1981 alone [61]. In reaction to this incidence, out of various legislative and structural reforms that were put together to overhaul the system for proper integration of disaster management was the South Africa Constitution of 1996.
The South Africa Constitution of 1996 marked the beginning of a prominent legislative and structural reforms of disaster management, by specifying the roles of the government at all levels in Part A Schedule 4 [62]. This necessitated the extension of the Civil Protection Act, the pioneer integrated policy on the management of disaster, called “the Green Paper on Disaster Management” [63].
The same era has witnessed active participation in various fora and conventions with respect to dealing with the challenges and opportunities that climate change presents since 1994. Commitment have been shown by the country to sustainable development with both active international participation and institutionalizing national frameworks. The frameworks include out of others: the Kyoto Protocol, the United Nations Framework Convention on Climate Change, the Cancun Agreement, the Convention on International Trade in Endangered Species of Wild Fauna and Flora, the Ramsah Convention on Wetlands of International Importance, the Basel Convention on the Control of Transboundary Movement of Hazardous Wastes and Their Disposal, and the Montreal Protocol for the Protection of the Ozone Layer [64] cit. in [65]. This suggests an involving participation of the country on climate change issues at the global realm.
Similarly, South Africa has at various times successfully instituted some climate change related legal frameworks that are either sector-prone (e.g. waste management, carbon tax, transport, energy efficiency, renewable energy and several others). Other related planning instrument is the Integrated Development Planning (IDP), through which short and medium-terms development objectives, strategies and programs are prepared as strategic plans for municipalities. It is a key instrument for guiding and informing fiscal allocation (budget), administration and decision making for service delivery and development within municipal’s jurisdiction [66]. Subsequently, White Paper on Disaster Management was produced, emphasizing proactive and integrated approach in the management of disaster through public (stakeholders) participation and capacity building [67]. Targeting the creation of National Disaster Management Centre, enhance disaster prevention among the poor and disadvantaged zones, ensure adequate funding system and facilitate access to information (South African Government Gazette).
In 2002 Disaster Management Act 57 of 2002 was institutionalized, highlighting the guiding philosophies for disaster management and defined tasks [68]. The Act provides for the establishment of Intergovernmental Committee on Disaster Management, with powers to the Premier of the concerned Province and Local Government to select members. While at national level, the Minister of Cooperative Governance and Traditional Affairs is empowered to establish a National Disaster Management Advisory Forum with several governmental and non-governmental organizational representatives, traditional institutions and various professional, Sec 5. (1). Section 8. (1) Establishes a National Disaster Management Centre (NDMF) to form part of, at the same time functions within the control of the Minister under a state department of the public service. Provincial disaster management framework is instituted in Section 28. (1) of the Act not only to be established but also implement a disaster management framework aligned to the NDMF objectives and in consistent with the provisions of Act (No. 57,2002) and the NDMF, 33 (I). The local government is empowered under chapter 5 to appoint a disaster officer [62]. This gave birth to the establishment of Mopani District Disaster Management Centre at District Municipal level and the appointment of disaster manager in the five local municipalities in Mopani District as gathered during our field survey, they equally had plans for disaster management framework [69].
In 2011, the parliaments of South Africa adopted the National Climate Change Response Strategy (NCCRS). The policy document is generally anchored on some strategic priorities such as risk reduction and management; mitigation actions (with significant targeted outcomes); sectoral responses; policy and regulatory alignment.
The establishment of the National Climate Change Monitoring and Evaluation System came with the objectives of tracking South Africa’s transition to a climate resilient society, by following-up on the country’s transition to a lower carbon economy and by tracking climate finance. The benefits of the system include out of others, the provision of an evidence-based impacts and the vulnerabilities to climate change, and providing learning for the workability and otherwise of climate change response. This will inform the future responses to climate change as well-as facilitate the assessment of the impact and need for climate finance and institutionalizing national communication and biennial update reports. As promising as these objectives are, the M&E system has till now been struggling to find its rightful place, because of the disconnect between the municipalities and the grassroots where the data (for national communication and biennial reports) ought to be generated. Although the M&S system is substantially mitigation-focused not adaptation oriented, it still remains a viable too and mechanism for managing adaptation if well captured and harnessed.
The specific urban policy and planning that was institutionalized that “seek to influence the distributions and operations of investment and consumption processes in cities for the common good” [70] was the South African Integrated Urban Development Framework (IUDF) as approved in 2016 by Cabinet. Although attempt by various Government’s Departments have in different ways attempted to address the challenges of urban areas since 1994 with significant achievements in areas such as service extension, municipal reform, urban renewal and economic infrastructure development, these efforts are largely viewed as inadequate [71]. Not so much achievements have been recorded in the mainstreaming of climate change to urban planning. The municipalities in Mopani District are still relying on the National Urban Policy without plans (currently) to have theirs that embrace the economic, political, social and environmental peculiarities of their respective areas. However, the adoption of the Paris Agreement as well as the New Urban Agenda, signaled a renewed motivation for action, particularly to mainstreaming climate change in Urban Policy.
The Mopani District Municipality in line with the National Disaster Management Act 2005 acknowledges the current and the potential climate change threats to both human and the environment. It equally recognizes the need for actions to mitigate, as well as prepare for the projected changes (adaptation) in the District. Consequent upon this, the district municipality in 2016 developed Vulnerability Assessment and Climate Change Response Plan to prioritize the development of Climate Change Response strategies. The Plan recognizes several numbers of ways that climate change will impact on human settlements across the district and thus identifies related indicators, sub-projects and actions for inclusion in the service delivery and the plans for budget implementation [72]. Our field survey revealed that the identified projects are held for paucity of funds.
The frustrations from the failure of municipalities to guarantee the protection of households through the implementation of a pragmatic actions have prompted private adaptation initiatives across the selected towns in the district to curtail the impacts of climate change. The section of this chapter succeeding the description of the study area and methods, addresses the various initiatives of households towards coping with climate change in the selected towns.
Located in the semi-arid region, the northern-most province (Limpopo) of South Africa, Mopani District Municipality is a category C municipality (Figure 1).
Mopani District municipality showing the five local Municipalities within the context of Limpopo Province and South Africa Context.
The district consist of five local Municipalities, including: Greater Giyani, (the district administrative seat), Maruleng, Greater Letaba, Ba-Phalaborwa and Greater Tzaneen. The municipality is situated on Longitudes: 29° 52´E to 31° 52´E and Latitudes: 23° 0´S to 24° 38´S, with 31° E as the central meridian. It covers 13,948.418 ha (10.2%) of the surface area of South Africa. It shares boundaries in the east with Mozambique, in the north, with Vhembe District Municipality through Thulamela & Makhado municipalities, while bordered in the south, by Mpumalanga province through Ehlanzeni District Municipality and, by Capricorn District Municipality to the west [72].
Being within the semi-arid region, the district is characterized by temperature that ranges from a high average of 21°C in the Mountainous areas with a very high average of 25°C in the dry low-veld areas of Kruger National Park. In the district Frost rarely occurs, while the monthly distribution of the average daily maximum temperatures indicates that the average midday temperatures for Mopani Rest Camp (Kruger) range from 23.7°C in June to 30°C in January. The region is the coldest during June when the mercury drops to 8°C on average during the night. The District falls within the Letaba Catchment area, which is 13 779 km2 and has a mean annual precipitation of 612mm (Environmental Management Framework for the Olifants and Letaba river catchment areas, Report, 2009).
Mopani Rest Camp (Kruger) receives about 520 mm of rain per year, with most proportion (85%) of precipitation in Mopani District is received in mid-summer, while with the lowest (3 mm) is received in June and the highest (96 mm) in January [72]. The rainfall varies from the mountainous zones in the Drakensberg Mountains (2000 mm/a) and the dry low-veld in the Kruger National Park (400 mm/a). The district is situated within the Letaba Catchments area which has a 612 mm Mean annual precipitation.
Climate is recognized by the municipality to be changing, altering and resulting to rising temperature and reduced and erratic rainfall across the district, which is a reflection of the regional climate [58, 75]. The new climate pattern according to the district Integrated Development Plan has caused reduction of access to potable water, food security threats and increase health effects to poverty stricken communities [72]. Part of the strategies identified in the planning instrument for the mitigation of the emission of global warming causing-gases include: utilizing every space for plants, using alternative forms of energy and strict control against deforestation.
Consequent upon climate change challenges, households in Mopani have consistently adopted several private and individual strategies to adapt with the varying climate change extreme events. In line with this, we examine the individual household coping strategies to climate change related extreme events and hazards in six purposively selected small and medium-sized towns (Tzaneen, Nkowankowa, Hoedspruit, Modjadjiskloof, Phalaborwa and Giyani) in Mopani District. Sample size of 500 were estimated and drawn using multistage random sampling method, with proportional share to each towns. Guided by the focus of this chapter, data collection methods emphasizes direct/personal interviews, questionnaire and visual inspection/ transect walk in order to ensure a high rate of response. Though the study adopts mixed method, open-ended questions were minimized, and well-ordered, where necessary. Review of existing literature was used to complement the current research findings. The investigated variables were isolated because of their being the direct location-specific effects occasioned by climate change. These variables are categorized into three, these include: those strategies related to increased temperature; reduced water level (rainfalls); and incidence of flood. These variables were cross tabulated against the selected towns of respondents and are discussed as follow.
Although efforts are on-going globally, regionally and nationally to reverse the trend in climate variability through research, treaties, collaborations, dialogues and other mechanisms, it is essential to appreciate that adaptation to the new climate change regime remains for now, the only realistic and sustainable option that is available [73, 74]. However, household’s private adaptation strategy is becoming an increasingly important component to the urban setting, since the end to the failure of Municipal governments to effectively deal with adaptation to climate change in urban center is indeterminate.
Occurrence of heat waves as a result of rise in temperature is generally evident in the semi-arid region of South Africa [58] and particularly in Mopani District of Limpopo province [75]. According to [76], households’ and municipal responses to cope with high temperature or heat waves can be undertaken via tree planting and several other strategies. In line with this understanding, household’s individual rising temperature coping strategy in the selected towns in the district were identified. The strategies include tree planting, minimizing bush burning, preservation of water bodies, eco-friendly faming practice, Flower and Grass Planting, the use of Fan and Air conditioner and the creation of Parks and Gardens. Table 1, depicts the responses from households, on the preferred coping strategies for increasing temperature across the selected towns in Mopani, these are subsequently discussed.
Towns | Tree planting | Flower and grass planting | Create parks & garden | Minimize bush burning | preserve water bodies | Eco-friendly farming | Use of fans and air condition |
---|---|---|---|---|---|---|---|
Tzaneen | 66.3 | 45.6 | 0.0 | 100.0 | 0.0 | 0.0 | 100.0 |
Nkowankowa | 56.6 | 18.3 | 0.0 | 100.0 | 0.0 | 0.6 | 100.0 |
Hoedspruit | 88.9 | 100.0 | 0.0 | 100.0 | 83.3 | 11.1 | 100.0 |
Modjadjiskloof | 50.0 | 80.0 | 0.0 | 100.0 | 60.0 | 0.0 | 100.0 |
Phalaborwa | 95.2 | 98.8 | 0.0 | 98.0 | 77.4 | 0.0 | 100.0 |
Giyani | 100.0 | 51.5 | 0.0 | 100.0 | 2.3 | 0.0 | 100.0 |
Temperature coping strategies across Mopani District.
Source: Authors’ Field Data, 2019.
Tree planting is one of the popular coping strategies and was recommended for mitigating the impact of high temperature [77]. This assertion was validated in the selected towns, with the results obtained from our investigation where 63.3% of households in Tzaneen, and 56.6% in Nkowankowa were in agreement with tree planting strategy to cope with heat waves. Hoedspruit accounted for 88.9%, Modjadjiskloof 50% while in Phalaborwa and Giyani 95.2% and 100% of households employed the strategy respectively. The findings suggests wide range of acceptability of tree planting as temperature coping strategy. The general acceptability of the strategy across the towns was adduced to its affordability and effectiveness as a coping strategy for increasing temperature.
An examination of the relevance of reducing bush burning as a strategy for coping with temperature in the selected towns in Mopani District was undertaken and the results of the respondents’ answers to the strategy reveals that in Nkowankowa, Tzaneen, Hoedspruit and Modjadjiskloof, minimizing bush burning was considered by every household, as an appropriate strategy, while in Phalaborwa, 2% of the entire households surveyed declined the choice of the strategy. The employment of bush burning minimization to curtail the impact of heatwaves at municipal level will be an acceptable and effective strategy that will make meaningful impacts across the district.
With respect to the respondents adopting the conservation of water bodies in their communities, Table 1 shows that more than four in every five respondents in Phalaborwa, three in every five in Modjadjiskloof respectively endorsed the strategy to cope with temperature. However, the strategy only enjoyed the acceptability of only 2.3% respondents in Giyani. This strategy was equally unpopular in both Tzaneen and Nkowankowa. The reason for Hoedspruit, Phalaborwa and Modjadjiskloof in favor of this strategy was traced to the awareness of the benefits of the strategy among households, facilitated by NGOs and the respective municipalities. This result reflects that the municipalities of the two towns complied with the water conservation Act No. 36 [78].
In the narratives of current literature reviewed on the adoption of eco-friendly farming practices as temperature coping strategy, it shows that it is a promising strategy as reported by [79]. But the results of the acceptability test of the strategy in the selected towns show otherwise. For example, in Tzaneen, Modjadjiskloof, Phalaborwa and Giyani, no respondent indicated adopting it as a strategy. Only Hoedspruit accounted for 11.1%. The result reflects the economic activities of significant proportion of respondents from non-primary sources particularly agriculture. Thus, prescribing it as coping strategy for temperature in the district might not be very impactful to the majority of households.
However, According to [80] as cited in [81] Green infrastructure is very useful in contributing to mitigate the effects of hard surfacing by modifying ambient temperatures as well as creating recreational opportunities among other advantages. Our investigation revealed that every households in Hoedspruit town adopted the strategy, while 98.8%, 80% and 51.5% households in Phalaborwa, Modjadjisklooof and Giyani towns adopted the green infrastructure strategy respectively too. Flower and grass planting seems to be a widespread and suitable temperature coping strategy in the selected towns, except in Nkowankowa where only 18.3% of the household embraced the strategy.
The use of Fan and Air conditioner appeared to be a very satisfactory strategy that was favored by every households traversing the selected towns in Mopani. This was adduced to by the respondents that the former (fan) is affordable, accessible and environmentally friendly. However, while the latter (air conditioners) was enhanced by the stability of electricity, it does not only escalates the energy bills because of the increased loads resulting from cooling, but it equally exacerbates urban heat island in its own capacity. Thus [82] submit that for effective alleviation of urban warming and enhanced cooling, there is, as a necessity the need to reduce air-conditioning anthropogenic heat.
The responses obtained from the survey conducted on the creation of Neighbourhood Parks and Garden as a temperature coping strategy by the households across the selected towns is presented in Table 1. The result shows a consensus among the households that the siting and development of neighborhood parks and garden was the responsibility of the governments at different levels. This was reflected in households’ responses where no household indicated creating Parks and Garden as a personal temperature coping approach. However, children who desire to recreate use available spaces like access road around them to play soccer, not minding risks involved.
With respect to water scarcity, the households were required to indicate the strategy they use during climate related drought or long heat waves that reduce the water quantity in their area. The variable used to capture the households’ responses include: rain water harvesting, water embankment, use of storage tanks, water treatment to improve quality and use of water vendor service. These results are presented in Figure 2.
Coping strategies for change in water level across towns and Mopani. Source: Author’s Field Data, 2019.
An examination of household coping strategies regarding change in water level in the selected towns, as summarized in Figure 2, shows that rainwater harvesting as a strategy was not popular among the households. The results shows that 5.1% respondents in Tzaneen and 5% in Nkowankowa adopted water harvesting as a strategy, while in Phalaborwa and Giyani both accounted for 5% and 3.1% respectively. However, both Modjadjiskloof and Hoedsrpruit towns did not use such a strategy because according to them, it is time consuming and that the quality of harvested water was most times compromised.
However, Figure 2 shows the results of the examination of the use of storage tanks to cope with reducing water level. It was discovered that 100% and 81% of households in Hoedspruit and Phalaborwa respectively used the strategy to backup, to forestall the impacts of water shortages. In Tzaneen and Nkowankowa 54.4% and 51% of their respective household used same strategy. Similarly, in Modjadjiskloof and Giyani the households that used storage tanks were respectively 50% and 61.5%. On the average 61.1% of the respondents have used or still using storage tanks to adapt to reducing water level in their communities. The study implied that the storage of water in tanks is an acceptable strategy because water provision is not always at RDP level.
A significant indicator of health is water scarcity, which includes both its availability and quality [83]. Water use is beyond drinking, it is intimately linked to food security, sanitation and hygiene contributing to health burdens. Poor and vulnerable communities suffer the most from the adverse effects of climate change on water and health related issues and that the adaptation strategy which can effectively reduce the strain on water resources include wastewater recycling and reuse [84]. This was tested in the selected towns, and was found that when water became scarce, such as in 2016 and 2017 droughts periods in Limpopo province, most households turned to the re-use of water due to the scarcity of water for domestic and others uses. Our investigation further showed that 100% of the respondents re-use water as was advised by the Department of Water Affairs, when Limpopo Province, was declared a disaster province.
Water treatment was one of the variables we requested the households to give their response if they use such strategy. Although according to the science of water treatment which involved reverse osmosis etc, we were more interested in treatment such as water boiling, using aqua active bleaching agents such as hypochlorite to disinfect the water before use. The results in Figure 2 shows that 100% of the respondents use non-complicated methods to treat their water when it becomes very scarce and necessary.
The general practice particularly in the peri-urban areas of the selected towns is that most of them buy water from water vendors who sell water in containers ranging from R5 to R25 depending on the quantity sold. The study showed that not all respondent were disposed to buying water from vendors maybe because some could not be guaranteed the quality of the water. Patronage of water vendors was common among those households who did not have stand pipes in their yards. However, in Modjadjiskloof and Giyani 43% and 48% respectively used water vendor services to cope with water scarcity (Figure 2).
As rightly noted [85] that with increasing havoc of floods in the urban center, and its negative impacts particularly on the poorest and the most susceptible, effective coping strategies require the combination of protective infrastructure, nature-based approaches, and risk financing (insurance) schemes to curtail floods and cushion their adversities. Flash floods has resulted into several degrees of damages in South Africa [65] as well-as some parts of the selected towns in Mopani District Municipality [75]. This occurred at different times, frequencies and intensities. This phenomenon has in the past resulted in households loosing properties ranging from home assets to farm crops and farm produce. The results of the survey showed that with respect to flood control strategies, the most popular include the construction of embankment to prevent over flow of rivers, the use of Furrow around their house, building of walls to protect houses during flash floods, growing of lawns, removal of solid waste from the storm water drainages, re-enforcement of dwellings with stones and concretes.
Our findings suggest that building embankment around houses is a popular strategy particularly among those residing close or whose offices are in close proximity to rivers, along erosion line, or terrain threatening sites. Embankments are usually constructed by the community or the local municipality. One aspect of the embankment as a strategy to cope with floods is that it fends off water and shelters settlements from flooding. About 58% of respondents was recorded in Modjadjiskloof and 32% in Phalaborwa, Hoedspruit was 23%, while Giyani and Nkowankowa both depicted 27% and 36% accordingly. In a further probe to why majority did not adopt the strategy, respondents noted it to be an expensive option, which often failed when the construction was not done to structural specifications.
With respect to the use of Sandbags, as a strategy, in Giyani 24% of the households indicated its adoption as the option to protect their properties against flood. In Nkowankowa 17%, Tzaneen was 11%, while Modjadjiskloof households accounted for 22% that used sandbags. The households’ justification for the use of sandbags as a coping strategy to protect against flooding was hinged on its affordability, ease of building and availability of the material components.
The use of furrow was equally investigated to ascertain whether or not is an acceptable strategy among the households in the district. The result indicates that 5% of Tzaneen residents are using Furrows around their properties, while about one in every four households in Nkowankowa adopted the same strategy. Households in Hoedspruit and Modjadjskloof that used the strategy accounted respectively for 16% and 36% and both Phalaborwa and Giyani accounted for 12% and 18%. The result suggest that the strategy was not embraced by the majority of the households across the selected towns. According to the respondents, the option was considered costly and not an effective strategy compared to others.
The proportion of households’ that adopts the building of protective walls around their houses to cope with flood in the six selected towns indicates that this is a commonly used strategy in the study area. Both Modjadjiskloof and Nkowankowa used it as a strategy mostly. With 76% of its household, Modjadjiskloof recorded the highest proportion of household that used the protective walls as strategy, while 18% of the households in Nkowankowa used the strategy. These results was significantly influenced by the terrain of individual towns under consideration as towns with relatively low lying terrain recorded lower patronage of the strategy, while town with steep slope like Modjadjiskloof adopted it most.
According to [80], Green infrastructure is useful in curtailing surface runoff among other benefits [81]. From the results of analysis, households’ response with respect to growing grasses to reduce the effects of floods in the selected towns revealed that 60% of households in Hoedspruit grew lawn to reduce the flow of surface run off that erodes the top soil. The study showed that 37% of the households in Modjadjiskloof and 36% in Tzaneen grew lawn to reduce erosion while 2.5% and 20% employed the same strategy in Nkowankowa and Giyani towns respectively. This strategy apart from protecting the surface top soil from erosion, it also keep a good ambient of the environment.
The respondents’ answers to the cleaning and removal of waste from drainage channels and systems appeared an acceptable coping strategy across the selected towns in Mopani. 32% of households in Tzaneen do evacuate waste from drainages, while as low as 5% of Nkowankowa households used the strategy to avoid over flow of drainages. However, more than two out of every five Phalaborwa residents engaged in clearing of their drainages to prevent flooding. The study further shows that one tenth of Giyani household embraced the strategy as well. Further to this, drainage and stream channelization was popular, accounting for 25% of Tzaneen households, while one fifth of Hoedspruit households embraced drainage channelization in coping with the incidence of flood.
The use of concrete and stones by households to reinforce their housing foundation serves dual purposes as a way to stabilize the building as well-as safeguard it against any unexpected floods that can erode the building foundation. About 88% of Hoedspruit household endorsed it, while 87% of the households in Modjadjiskloof as well-as 78% of them in Phalaborwa used it as a strategy to cope with floods. However, Tzaneen account for 40% of houses in this category, while Giyani town accounted for 34%.
Obviously without waiting endlessly for government, households across the district have taken creative initiatives to respond within the available resources at their disposal to climate change related hazards. However, households’ capacities are limited by several factors, ranging from economic, social, and attitudinal. Unless pioneered, championed and facilitated by government, household adaptation may not achieve the desired goal. Although several factors collaborate to hamper the success of urban adaptation in the semi-arid region of Mopani, South Africa. These limiting factors are identified in the next section.
This section identifies the factors that inhibit the successes of urban adaptation to climate change hazards. Through our interactions with the households in the selected towns, the key informant (particularly the municipal staff and professionals) and other stakeholders, buttressed by the findings from the planning instruments (IDPs) of the five local municipalities in Mopani District, several inhibiting factors clogging the successes of urban climate change adaptation in these municipalities were uncovered. These out of others can be stratified into both internal and external factors. These are discussed as follow:
Internal factors are those factors that the local municipalities recognized as being within their mandates and powers, on one hand. These include but are not limited to paucity of fund, principally from budgetary allocation. Limited human capacity to embark on the required types of planning for integrated adaptation mainstreaming, compounded by the paucity of knowledge of adequate climate issues at the local municipal level. Higher competition that exist between the mandates of government, resulting in less priority being accorded to long-term planning issues (like climate change) in favor of short-term actions and gains. The Situation is further compounded by the South African need to tackle the backlogs of service amidst coping with both current and future needs of the people. Thus, rendering long-term interventions unattractive to politicians who run a short political tenure to execute. With long-term horizon nature of climate change projections, it contradicts with the short-term political and development programs of these municipalities.
In addition, system’s failure manifest across the selected towns, for instance drainages and water ways blockages, absence of drainages in many instances, sewer leakages (like the case of Nkowankowa and Phalaborwa), and backlogs of service across the municipalities are clear indicators. Others factors include policy inadequacies resulting from municipal reliance on national policies (such as urban and other climate adaptation-related policies). The dichotomized land management and operational deficiencies where traditional institutions are in charge of unproclaim land with no responsibility to provide services. Absence of interface programs between the municipalities and the Universities and other research institutions for information and knowledge sharing as well-as research activities regarding climate change and urban development. There was equally no evidence to show collaborations with private sector (banks, insurance and individual philanthropists) on adaptation issues.
Furthermore, external factors include high poverty rate, low literacy level and unemployment. Lack of reliable and verifiable hazard incident reporting systems that can guarantee disaster hotspot identification and monitoring for early warning. Nevertheless, some of these identified factors (policy shortcomings, institutional weakness etc.), lack of political will plays a significant role.
There is no doubt that the new climate is here so also are the attendant hazard that we have to live with in decades to come. With the long-term nature of ongoing global mitigation efforts, adaptation remains the available strategy that must be collaboratively embraced to cope with climate change prone hazards in the urban centers of semi-arid region of South Africa.
Thus, we emphasize the need for a participatory urban management strategy for sustainable adaptation to climate-related hazards, while calling on Scholars to develop models of urban adaptation to climate change that may not necessarily be highly mathematical, but recognize the technological level, social and economic peculiarities of urban Africa, particularly in the semi-arid region of Mopani, South Africa.
The need to urgently review the procedure for reporting climate change hazards and emergencies to promote early warning system, should be revisited. Hazards reporting should be facilitated by the incorporation of instant reporting components in to the existing or a new reporting protocols. This chapter referred to this as “hotspot reporting and monitoring system”, through the implementation and development of a mobile phone facilitated protocol that makes citizens the reporters of climate hazards.
It is therefore important to identify and simplify trends and carry out assessment of the effectiveness of prevailing and future policies that may be directed towards urban households’ adaptation to climate change hazard in semi-arid region of Mopani South Africa for impactful delivery. In addition, such adaptation policies should be locally-driven and must address climate change as a multifaceted phenomenon and not limited as solely to being tackled as an environmental issue, while integrating local knowledge approaches.
Although, it may be uneasy to convince politicians to prioritize climate change (a long-term development agenda) over and above short tenure political agenda, conversations and strategies to encourage the implantation of long-term sustainable projects should be persuaded. But, because climate change phenomenon as well-as its related consequences are real and already manifesting [58], thus, research institutions, private sector (corporate organization) and NGOs are urged to assist in facilitating training of municipal staff and reorientation program for politicians, particularly by promoting the inclusion of climate change hazard management agenda in the political parties manifestoes while facilitating private adaptation strategies at community level.
Strategies like tree planting, urban greening, drainage channelization, and harmonization of the dichotomized land management in the district are some of the strategic window to curtail climate change hazards in the semi-arid region of Mopani South Africa.
University of Venda, Thohoyandou, South Africa is acknowledge for funding the research. The University of Ilorin is equally acknowledge for granting me the permission and sponsorship of the Ph.D program.
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