This paper presents a new statistical technique for downscaling climate information from general circulation models so that this information can be used as an input to economic evaluation of options for reducing flood and drought risks and responding to the impacts of climate change.

Floods, droughts, and other weather related disasters are a major factor contributing to endemic poverty in regions such as South Asia, and this is likely to increase as climate change proceeds. Risk reduction interventions represent a major avenue for responding to both existing flood and drought hazards and the increases likely to emerge as a consequence of climate change. Yet investments in risk reduction are difficult to economically justify unless their returns can be assessed. Cost-benefit techniques are the primary set of economic tools through which such assessments are currently made. The ability to make such assessments depends, however, on the availability of probabilistic information, which is generally not available at the local level in developing countries where populations are large and particularly vulnerable.

The focus of this study is the Rohini Basin, which straddles the border of Nepal and India. Data paucity in this region makes it difficult to employ numerical downscaling techniques to provide forecasts of potential climate change impacts. Therefore, a robust stochastic technique was developed to generate precipitation ensembles that can be utilized to test climate change scenarios at the river basin level. Keywords: Climate Modeling and Scenario Planning; Disaster Risk Reduction/Hazard Management; Economics; Resilience and Climate Change Adaptation