Climate Change 2001:
Working Group II: Impacts, Adaptation and Vulnerability
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12.6. Settlements and Industry

12.6.1 Infrastructure

Climate change will affect settlements and industry through changes in mean climate and changes in the frequency and intensity of extreme events. Obviously, changes in average climate affect design and performance, including variables such as heating and cooling demand, drainage, structural standards, and so forth. However, in many cases average climate is only a proxy for design standards that are developed to cope with extreme demands or stresses such as flooding rains, gale-force wind gusts, heat waves, and cold spells.

If the severity, frequency, or geographic spread of extreme events changes, the impact of such changes on infrastructure may be severe. For instance, movement of tropical cyclones further south into areas where infrastructure is not designed to cope with them would have significant consequences.

The rate and nature of degradation of infrastructure is directly related to climatic factors. Computer models to predict degradation as a function of location, materials, and design and construction factors have been developed (Cole et al., 1999a,b,c,d). Because buildings and infrastructure that are being constructed now will have projected lives until 2050, placement, design, and construction changes to guarantee this life against climate change are needed. Moreover, the effects of degradation and severe meteorological events may have an unfortunate synergy. Increase in the rate of degradation as a result of climate change may promote additional failures when a severe event occurs. If the intensity or geographical spread of severe events changes, this effect may be compounded.

In New Zealand, a Climate Change Sustainability Index (CCSI) developed by Robinson (1999) rates the impact of climate change on a house and the contribution to climate change of GHG emissions from the house. The index includes GHG emissions from heating and cooling, comfort, tropical cyclone risk, and coastal and inland flooding. Basically, the closer the house is to sea level and/or a river or waterway, the lower the CCSI. Higher temperatures and rainfalls in general will shorten the life span of many buildings.

The impact of extreme climatic events already is very costly in both countries. This has been documented for Australia in Pittock et al. (1999), where it is shown that major causes of damage are hail, floods, tropical cyclones, and wildfire. In New Zealand, floods and landslides are the most costly climatically induced events, with strong winds and hail also important. The International Federation of Red Cross and Red Crescent Societies (1999) report estimates damages from a combination of drought, flood, and high wind (including cyclones, storms, and tornadoes) in Oceania (Australia, New Zealand, and the Pacific islands) to be about US$870 million yr-1 over the years 1988-1997. This figure apparently does not include hail damage, which is a major cost. Insured losses from a single severe hailstorm that struck Sydney in April 1999 were estimated at about AU$1.5 billion (roughly US$1 billion) (NHRC, 1999).

A scoping study for Queensland Transport (Queensland Transport et al., 1999) has identified vulnerabilities for the Queensland transport infrastructure that will require adaptation. Infrastructure considered include coastal highways and railways, port installations and operations (as a result of high winds, sea-level rise, and storm surges), inland railways and roads (washouts and high temperatures), and some airports in low-lying areas. Key climate variables considered were extreme rainfall, winds, temperatures, storm surge, flood frequency and severity, sea waves, and sea level. Three weather systems combining extremes of several of these variables—tropical cyclones, east coast lows, and tropical depressions—also were assessed.

Regional projections for each of these variables were created, with levels of confidence, for four regions of Queensland for 2030, 2070, and 2100. Overall, the potential effects of climate change were assessed as noticeable by 2030 and likely to pose significant risks to transport infrastructure by 2070, if no adaptation were undertaken. Setting new standards, in the form of new design criteria and carrying out specific assessments in prioritized areas where infrastructure is vulnerable, was recommended for roads and rail under threat of flooding, bridges, and ports. Detailed risk assessments for airports in low-lying coastal locations were recommended.


Figure 12-4: Simulated return periods (average time between events) of storm tides in Cairns, Queensland, for present climate (lower curve), and for enhanced greenhouse climate (upper curve), assuming 10 hPa lowering of central pressures and increased variability (additional 5 hPa standard deviation) of tropical cyclones. Anticipated mean sea-level rise should be added to these estimates. Uncertainty ranges of simulations are shown via grey shading (Walsh et al., 2000).

Many ports and coastal communities already suffer from occasional storm-surge flooding and wave damage. A series of studies identifies particular vulnerabilities in some Queensland coastal cities (Smith and Greenaway, 1994; AGSO, 1999). Inland and coastal communities also are vulnerable to riverine flooding (Smith et al., 1997; Smith, 1998a). A key feature of these studies is the nonlinear nature of damage response curves to increased magnitude and frequency of extreme events. This is partly because of exceedance of present design standards and the generally nonlinear nature of the damage/stress relationship, with the onset of building collapse and chain events from flying or floating debris (Smith, 1998a).

A study by McInnes et al. (2000; see also Walsh et al., 2000) estimates the height of storm tides at the city of Cairns, in northern Queensland, for the present climate and for an enhanced greenhouse climate in which—based on the findings of Walsh and Ryan (2000)—the central pressure of tropical cyclones was lowered by about 10 hPa and the standard deviation of central pressure (a measure of variability) was increased by 5 hPa but the numbers were unchanged. Cairns is a low-lying city and tourist center, with a population of about 100,000 that is growing at about 3% yr-1. Under present conditions, McInnes et al. (2000) found that the 1-in-100-year event is about 2.3 m in height; under the enhanced greenhouse conditions, it would increase to about 2.6 m, and with an additional 10- to 40-cm sea-level rise, the 1-in-100-year event would be about 2.7-3.0 m (see Figure 12-4). This would imply greatly increased inundation and wave damage in such an event, suggesting a possible need for changes in zoning, building regulations, and evacuation procedures.

Urban areas also are vulnerable to riverine flooding (Smith, 1998a) and flash floods exacerbated by fast runoff from paved and roofed areas (Abbs and Trinidad, 1996). Considerable effort has gone into methods to improve estimates of extreme precipitation under present conditions (Abbs and Ryan, 1997; Abbs, 1998). Schreider et al. (2000) applied a rainfall-runoff model to three different catchments upstream of Sydney and Canberra under doubled-CO2 conditions. They found increases in the magnitude and frequency of flood events, but these effects differed widely between catchments because of the different physical characteristics of each catchment.

The safety of publicly owned and private dams also is a major issue (ANCOLD, 1986; Webster and Wark, 1987; Pisaniello and McKay, 1998) that is likely to be exacerbated by increases in rainfall intensity and probable maximum precipitation (Pearce and Kennedy, 1993; Fowler and Hennessy, 1995; Abbs and Ryan, 1997; Hennessy et al., 1997).

Vulnerability depends not only on the severity of the potential impacts but on hazard mitigation measures put in place (including time- and location-specific hazard prediction), crisis management capability, and policies that avoid or minimize the hazard. These matters are discussed in Smith (1998a), Handmer (1997), and Kouzmin and Korac-Kakabadse (1999).


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