Abstract:

Climate Change refers to any systematic change in the long-term statistics of climate elements (such as temperature, pressure, or winds) sustained over several decades or longer time periods. General Circulation Models (GCMs) are tools designed to simulate time series of climate variables globally, accounting for effects of greenhouse gases in the atmosphere and resulting global climate change. They are currently the most credible tools available for simulating the response of the global climate system to increasing greenhouse gas concentrations, and to provide estimates of climate variables (e.g. air temperature, precipitation, wind speed, pressure etc.) on a global scale. GCMs demonstrate a significant skill at the continental and hemispheric spatial scales and incorporate a large proportion of the complexity of the global system; they are, however, inherently unable to represent local subgrid-scale features and dynamics. The spatial scale on which a GCM can operate (e.g., 3.750 longitude X 3.750 latitude for Coupled Global Climate Model, CGCM2) is very coarse compared to that of a hydrologic process (e.g., precipitation in a region, streamflow in a river etc.) of interest in the climate change impact assessment studies. Moreover, accuracy of GCMs, in general, decreases from climate related variables, such as wind, temperature, humidity and air pressure to hydrologic variables such as precipitation, evapotranspiration, runoff and soil moisture, which are also simulated by GCMs. These limitations of the GCMs restrict the direct use of their output in hydrology. Hydrologic implications of global climate change are usually assessed by downscaling appropriate predictors simulated by General Circulation Models (GCMs). Conventionally rainfall is first downscaled with dynamic or statistical downscaling and then the predicted rainfall is used in hydrologic models to forecast hydrologic scenarios of future.

Although this methodology is widely practiced, there are some limitations: (a) uncertainty resulting from the use of multiple GCMs, scenarios, downscaling models is seldom considered; (b) local changes (e.g., urbanization, population growth, deforestation) which affect directly the hydrology of a region are considered in a very limited number of studies. The present paper focuses on these limitations and proposes different approaches to deal with the problems.