CGCM을 이용한 낙동강 유역 유량에 대한 기후변화 영향 평가

Abstract

An Assessment of Climate Change Impacts on Nakdong River Flow using CGCM Information 1.

Munsung Keem

Department of Environmental Engineering, Graduate school, Pukyong National University

Abstract

In this study a multi-site daily precipitation generator, MSPG, which generates the precipitation with similar spatial correlation, and at the same time, with conserving statistical properties of the observed data is developed. The proposed generator is intended to be a tool for down-scaling the data obtained from GCMs into local scales. The occurrences of precipitation are simultaneously modeled in multi-sites by 2-parameter first-order Markov chain using random variables of spatially correlated while temporally independent, and then, the amount of precipitation is simulated by 3-parameter mixed exponential probability density function that resolves the issue of maintaining intermittence of precipitation field. This approach is applied to the Nakdong river basin and the observed data are daily precipitation data of 19 locations. The results show that spatial correlations of precipitation series are relatively well simulated and statistical properties of observed precipitation series are simulated properly. For the assessment of climate change impacts on river flow condition, CGCM 3.1 T63 is selected as future climate information. The projections come from CGCM used to simulate the GHG emission scenario known as A2. Air temperature and precipitation information from the GCM simulations are converted to regional scale data using the statistical downscaling method known as MSPG. Downscaled climate data from GCM are then used as the input data for the modified TANK model to generate regional runoff estimates for 44 river locations in Nakdong river basin. Climate change is expected to reduce the reliability of water supplies in the period of 2021-2030. In the period of 2051-2060, stream flow is expected to be reduced in spring season and increased in summer season. However, it should be noted that there are a lot of uncertainties in such multiple-step analysis used to convert climate information from GCM-based future climate projections into hydrologic information.