The Uncertainty Impact of Statistical Downscaling on River Runoff

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• Samadi, S (Islamic-Azad University)
• Thursday 09 December 2010, 09:00-09:30
• Seminar Room 1, Newton Institute.

If you have a question about this talk, please contact Mustapha Amrani.

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The global climate change may have serious impacts on the hydrological extremes. Change hydrological extremes will have important implications on the sustainability of lands, floodplain development, and water resource management. This study assesses the potential impact of climate change on the timing and magnitude of hydrological extremes in Karkheh river catchment, Iran. An ensemble of future climate scenarios is developed by using Statistical Downscaling Model (SDSM) and Artificial Neural Network (ANN) models linked with GCM outputs and then the downscaled data was used in rainfall-runoff model. Assessing model error and qualification of uncertainty in downscaled meteorological variables are particularly useful in identifying the most accurate and most reliable downscaling model that can be used in hydrological modeling of climate change impacts on river runoff. The uncertainty analysis includes daily precipitation as well as daily temperature at Kermanshah synoptic station in the north of Karkheh catchment. Parametric and non parametric tests applied for downscaled data, the analysis of data indicates, the distribution of daily precipitation is not normal and even not nearly normal and also has no serial correlation at 95% confidence level. So these characters indicate that a non-parametric test is a suitable approach for daily precipitation analysis. The distribution of daily temperature is nearly normal and nor serially correlated at 95% significance level, this allowed both parametric and non-parametric approaches had been used for daily temperature data. The results show that flow sensitivity to atmospheric factors is significantly different between hydrological systems which are mainly influenced respectively, by precipitation and atmospheric temperature. The results suggest a global decrease of flow in river regime, especially in spring and winter. According to the evaluated scenarios, climate change may have unfavorable impacts on the distribution of hydrological extremes in the study area, so the effect of climate change on the frequency and intensity of floods and droughts is expected to increase the challenges for water and flooding in the 21st century.

Key Words: Climate Change; Statistical Downscaling Model; Uncertainty Analysis; Hydrological Extremes; Iran.

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