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(Alcamo et al., 2003). WaterGAP integrate Global Water Use and Global Hydrology models and covers three water use sectors – households, industry and irrigation – using 0.5o grid cell resolution and allows for analysis in all large drainage basins worldwide covering 150 countries. The hydrological model calculates the daily water balance of each grid cell, taking into account physiographic characteristics of drainage basins (e.g. soil, vegetation, slope and aquifer type), the inflow from upstream, the extent and hydrological influence of lakes, reservoirs and wetlands, as
well as the reduction of river discharge by human water consumption. The effect of changing climate on runoff is taken into account via the impacts of temperature and precipitation. WaterGAP uses
a flow-routing scheme whereby the total runoff produced within each cell and the volume of water coming from the cell upstream is transported through a series of linear and nonlinear retention storages representing the groundwater, lakes, reservoirs, wetlands and the river itself. The flow routing covers all 67,000 grid cells representing the total land surface of the Earth and is based
on various continental drainage and elevation maps. The cells are connected to each other
by their respective drainage direction and are thus organized into drainage basins. WaterGAP computes net and gross irrigation requirements. Net irrigation is the part that is evapotranspired by the plants, while gross irrigation reflects the amount withdrawn from the source.
The Water Use model takes into account basic socio-economic factors that lead to domestic, industrial and agricultural water
use, while the Hydrology model incorporates physical and climate factors that lead to runoff and groundwater recharge. Water use modelling allows for changes in water intensity based on structural and technological change. “Structural change”, which can lead to increase or decrease in water use intensity, arises from the combination of water-using activities and consumer habits
as well as from the change in the mix of water- using power plants and manufacturers within a particular country. By contrast, “technological
change” almost always leads to improvements in the efficiency of water use and a decrease in water intensity.
4.3 Other pathway models
The body of research on other climate change pathways is less cohesive than crop yield research, and in some cases less readily translated into economic model shocks. Sea level rise and its effects on land area is a pathway whose research base is relatively well developed. Some recent economic analyses have utilized results from the Dynamic Interactive Vulnerability Assessment (DIVA) interactive modeling tool, which uses
a global-scale data system to project coastal impacts, vulnerability and adaptation to sea level rise, and estimates of adaptation costs in coastal areas (Hinkel, 2005, Hinkel and Klein, 2009). Projected coast land loss due to submersion or flooding is derived from simulating SRESs in DIVA.
More economic analyses are incorporating the labour productivity effects of climate change. A recent study by Kjellstrom, et al. (2009) quantifies the effects of climate change on labour productivity in 21 world regions. Hotter workplace temperatures lead workers to reduce work intensity or take more short breaks. Their study applies a physiological model that describes changes in the number
of work days due to changes in temperature
and humidity, also taking into account projected changes in types of employment as incomes grow in the future. Future changes in labour productivity are analysed under SRESs A2 and B2, with projected increases in global mean temperatures in 2080 of 3.4C and 2.4C, respectively, using
the HadCM3 GCM. Projected changes in labour productivity by 2080, relative to a baseline climate from 1961-1990, are projected with this approach to be significant, ranging from a loss as high as
25 percent in Central America to a 3 percent increase in productivity in tropical Latin America.
chapter 3: economic modelling of climate impacts and adaptation in agriculture: a survey of methods, results and gaps
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