Toward evaluating the effect of climate change on investments in the water resources sector: insights from the forecast and analysis of hydrological indicators in developing countries

The World Bank has recently developed a method to evaluate the effects of climate change on six hydrological indicators across 8951 basins of the world. The indicators are designed for decision-makers and stakeholders to consider climate risk when planning water resources and related infrastructure investments. Analysis of these hydrological indicators shows that, on average, mean annual runoff will decline in southern Europe; most of Africa; and in southern North America and most of Central and South America. Mean reference crop water deficit, on the other hand, combines temperature and precipitation and is anticipated to increase in nearly all locations globally due to rising global temperatures, with the most dramatic increases projected to occur in southern Europe, southeastern Asia, and parts of South America. These results suggest overall guidance on which regions to focus water infrastructure solutions that could address future runoff flow uncertainty. Most important, we find that uncertainty in projections of mean annual runoff and high runoff events is higher in poorer countries, and increases over time. Uncertainty increases over time for all income categories, but basins in the lower and lower-middle income categories are forecast to experience dramatically higher increases in uncertainty relative to those in the upper-middle and upper income categories. The enhanced understanding of the uncertainty of climate projections for the water sector that this work provides strongly support the adoption of rigorous approaches to infrastructure design under uncertainty, as well as design that incorporates a high degree of flexibility, in response to both risk of damage and opportunity to exploit water supply ‘windfalls’ that might result, but would require smart infrastructure investments to manage to the greatest benefit.

[1]  Gerrit Lohmann,et al.  Regional Climate Projections. , 2010 .

[2]  E. Strobl,et al.  Is Small Better? A Comparison of the Effect of Large and Small Dams on Cropland Productivity in South Africa , 2013 .

[3]  D. Gerten,et al.  Climate impacts on global irrigation requirements under 19 GCMs, simulated with a vegetation and hydrology model , 2013 .

[4]  K. Strzepek,et al.  Modeling the impact of climate change on global hydrology and water availability , 2010 .

[5]  Ina Ruck,et al.  USA , 1969, The Lancet.

[6]  R. Meeks,et al.  Exploring the effect of hydroclimate variability on economic growth in Sub-Saharan Africa: A water security index , 2008 .

[7]  J. Horowitz The Income–Temperature Relationship in a Cross-Section of Countries and its Implications for Predicting the Effects of Global Warming , 2009 .

[8]  Wolfgang Grabs,et al.  High‐resolution fields of global runoff combining observed river discharge and simulated water balances , 2002 .

[9]  A. V. Vecchia,et al.  Global pattern of trends in streamflow and water availability in a changing climate , 2005, Nature.

[10]  L. S. Pereira,et al.  Crop evapotranspiration : guidelines for computing crop water requirements , 1998 .

[11]  K. Strzepek,et al.  Climate change scenarios and climate data , 2010 .

[12]  Yong Q. Tian,et al.  Coastal flooding in the Northeastern United States due to climate change , 2008 .

[13]  Richard G. Allen,et al.  Estimating Reference Evapotranspiration Under Inaccurate Data Conditions , 2002 .

[14]  Cecilia M. Briceno-Garmendia,et al.  Africa's Infrastructure: A Time for Transformation , 2009 .

[15]  R. Kerr Predicting climate change. Vital details of global warming are eluding forecasters. , 2011, Science.

[16]  Benjamin F. Jones,et al.  Temperature and Income: Reconciling New Cross-Sectional and Panel Estimates , 2009 .

[17]  Stephanie Dutkiewicz,et al.  Winners and losers: Ecological and biogeochemical changes in a warming ocean , 2013 .

[18]  R. Lempert,et al.  Identifying and evaluating robust adaptive policy responses to climate change for water management agencies in the American west , 2010 .

[19]  Jeroen C. J. H. Aerts,et al.  Partial costs of global climate change adaptation for the supply of raw industrial and municipal water: a methodology and application , 2010 .

[20]  Richard S. J. Tol,et al.  Methodological aspects of recent climate change damage cost studies , 2006 .

[21]  Sebastian Rausch,et al.  A Numerical Investigation of the Potential for Negative Emissions Leakage , 2013 .

[22]  Martyn P. Chipperfield,et al.  Off-line algorithm for calculation of vertical tracer transport in the troposphere due to deep convection , 2012 .

[23]  Daron Acemoglu,et al.  Reversal of Fortune: Geography and Institutions in the Making of the Modern World Income Distribution , 2001 .

[24]  Felipe J. Colón-González,et al.  Multimodel assessment of water scarcity under climate change , 2013, Proceedings of the National Academy of Sciences.

[25]  T. Oki,et al.  Multimodel Estimate of the Global Terrestrial Water Balance: Setup and First Results , 2011 .

[26]  Cecilia M. Briceno-Garmendia,et al.  Africa's Infrastructure : A Time for Transformation [Infrastructures africaines] , 2010 .

[27]  Richard de Neufville,et al.  Flexibility in Engineering Design , 2011 .

[28]  Murray C. Peel,et al.  Global streamflows - Part 1: Characteristics of annual streamflows , 2007 .

[29]  Roger Jones,et al.  Regional climate projections , 2007 .

[30]  Qiuhong Tang,et al.  Multi-model assessment of water scarcity under climate change , 2013 .