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Sectoral Impacts<br />
stunting indicate substantial increases, particularly in severe<br />
stunting in Sub-Saharan Africa (23 percent) and South Asia<br />
(62 percent) (Lloyd, Kovats, and Chalabi 2011).<br />
Water Resources<br />
It is well established that climate change will bring about substantial<br />
changes in precipitation patterns, as well as in surface<br />
temperature and other quantities that govern evapotranspiration<br />
(see for example, Meehl, Stocker, and Collins 2007). The associated<br />
changes in the terrestrial water cycle are likely to affect the nature<br />
and availability of natural water resources and, consequently,<br />
human societies that rely on them. As agriculture is the primary<br />
water consumer globally, potential future water scarcity would put<br />
at risk many societies’ capacity to feed their growing populations.<br />
However, other domestic and industrial water uses, including cooling<br />
requirements, for example, for thermal power plants, as well as the<br />
functioning of natural ecosystems also depend on the availability<br />
of water. The magnitude and timing of surface water availability<br />
is projected to be substantially altered in a warmer world. It is<br />
very likely that many countries that already face water shortages<br />
today will suffer from increased water stress in a 4°C world and<br />
that major investments in water management infrastructure would<br />
be needed in many places to alleviate the adverse impacts, and<br />
tap the potential benefits, of changes in water availability. In the<br />
following, recent model predictions are referenced in order to<br />
provide an outline of the nature and direction of change expected<br />
for warming of 4°C and beyond.<br />
Changes to Levels of Precipitation and<br />
Water Stress in a 2°C World and in a 4°C+<br />
World<br />
Fung et al. (2011) explicitly investigate the difference between<br />
a 4°C world and a 2°C world, using the MacPDM hydrological<br />
model, which is driven by a large perturbed-physics climate model<br />
ensemble based on the HadCM3L climate model. Because they<br />
define the 1961–1990 average temperature as their baseline, their<br />
4°C world is actually about 4.4°C warmer than the preindustrial one.<br />
The bottom line of this study is that globally changes in<br />
annual runoff are expected to be amplified once warming has<br />
reached 4°C compared to one in which it has reached 2°C; that<br />
is, on a large scale, the hydrological response to global warming<br />
appears rather linear. Regions experiencing drier conditions<br />
—namely, generating less runoff—under 2°C warming are projected<br />
to become even drier under 4°C (and vice versa). Drier<br />
conditions are projected for southern Europe, Africa (except<br />
some areas in the northeast), large parts of North America and<br />
South America, and Australia, among others. Wetter conditions<br />
are projected for the northern high latitudes, that is, northern<br />
North America, northern Europe, and Siberia. In the ensemble<br />
average, mean annual runoff decreases in a 2°C world by around<br />
30, 20, 40, and 20 percent in the Danube, Mississippi, Amazon,<br />
and Murray Darling river basins, respectively, while it increases<br />
by around 20 percent in both the Nile and the Ganges basins,<br />
compared to the 1961–190 baseline period. Thus, according to<br />
Fung et al. (2011), all these changes are approximately doubled<br />
in magnitude in a 4°C world.<br />
Fung et al. (2011) also look at a simple water stress index, using<br />
the ratio of annual mean runoff to population in a given basin as<br />
a measure of water resources per capita. The SRES A1B emissions<br />
scenario, from which the 2°C and 4°C climate projections are<br />
derived, is set in relation to a scenario of future population growth<br />
based on a medium UN population projection. In a 2°C world,<br />
relatively small runoff changes combined with large population<br />
growth over the next few decades mean that changes in water stress<br />
would mostly be dominated by population changes, not climate<br />
changes. Increasing water demand would exacerbate water stress<br />
in most regions, regardless of the direction of change in runoff.<br />
However, in a 4°C world, climate changes would become large<br />
enough to dominate changes in water stress in many cases. Again,<br />
water stress is expected to increase in southern Europe, the United<br />
States, most parts of South America, Africa, and Australia, while<br />
it is expected to decrease in high latitude regions. A fragmented<br />
picture emerges for South and East Asia, where increased runoff<br />
from monsoon rainfall in some areas competes with populationdriven<br />
increases in demand (while other areas may see reduced<br />
monsoon runoff).<br />
There are complexities beyond this large-scale, annual mean<br />
picture. In five of the six major river basins studied in detail by<br />
Fung et al. (2011), the seasonality of runoff increases along with<br />
global warming, that is, wet seasons become wetter and dry seasons<br />
become drier. This means that while an increase in annual<br />
mean runoff, for example, in the Nile or the Ganges basin may<br />
appear beneficial at first sight, it is likely to be distributed unevenly<br />
across the seasons, possibly leading to increased flooding in the<br />
high-flow season, while hardly improving water stress in the<br />
low-flow season. This would have severe adverse consequences<br />
for affected populations, especially if the seasonality of runoff<br />
change would be out of phase with that of demand, such as for<br />
crop growing or the cooling of thermal power plants. Major investments<br />
in storage facilities would be required in such cases in order<br />
to control water availability across the year and actually reap the<br />
local benefits of any increases in runoff. For such basins as the<br />
Ganges, another reason to strengthen water management capacities<br />
is that hydrological projections for the Indian monsoon region<br />
are particularly uncertain because of the inability of most climate<br />
models to simulate accurately the Indian monsoon. Quantitative<br />
results for this region based on a single climate model (as used by<br />
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