Browse > Article
http://dx.doi.org/10.7780/kjrs.2008.24.1.25

Assessment of Future Climate Change Impact on DAM Inflow using SLURP Hydrologic Model and CA-Markov Technique  

Kim, Seong-Joon (Dept. of Civil and Environmental System Engineering, Konkuk University)
Lim, Hyuk-Jin (Dept. of Rural Engineering, Konkuk University)
Park, Geun-Ae (Dept. of Rural Engineering, Konkuk University)
Park, Min-Ji (Dept. of Civil and Environmental System Engineering, Konkuk University)
Kwon, Hyung-Joong (Dept. of Rural Engineering, Konkuk University)
Publication Information
Korean Journal of Remote Sensing / v.24, no.1, 2008 , pp. 25-33 More about this Journal
Abstract
To investigate the hydrologic impacts of climate changes on dam inflow for Soyanggangdam watershed $(2694.4km^2)$ of northeastern South Korea, SLURP (Semi-distributed Land Use-based Runoff Process) model and the climate change results of CCCma CGCM2 based on SRES A2 and B2 were adopted. By the CA-Markov technique, future land use changes were estimated using the three land cover maps (1985, 1990, 2000) classified by Landsat TM satellite images. NDVI values for 2050 and 2100 land uses were estimated from the relationship of NDVI-Temperature linear regression derived from the observed data (1998-2002). Before the assessment, the SLURP model was calibrated and verified using 4 years (1998-2001) dam inflow data with the Nash-Sutcliffe efficiencies of 0.61 to 0.77. In case of A2 scenario, the dam inflows of 2050 and 2100 decreased 49.7 % and 25.0 % comparing with the dam inflow of 2000, and in case of B2 scenario, the dam inflows of 2050 and 2100 decreased 45.3 % and 53.0 %, respectively. The results showed that the impact of land use change covered 2.3 % to 4.9 % for the dam inflow change.
Keywords
SLURP; Climate change; CA-Markov technique; NDVI;
Citations & Related Records
연도 인용수 순위
  • Reference
1 Ahn, J. H., C. S. Yoo, and Y. N. Yoon, 2001. An Analysis of Hydrologic Changes in Daechung Dam Basin using GCM Simulation Results due to Global Warming, Journal of Korea Water Resources Association, 34(4): 335-345.
2 Kite, G. W., 1993. Application of a Land Class Hydrological Model to Climate Change, Water Resource Research, 29(7): 2377-2384.   DOI   ScienceOn
3 Duan, Q., S. Sorooshian, and V. K. Gupta, 1994. Optimal Use of the SCE-UA Global Optimization Method for Calibrating Watershed Models, Journal of Hydrology, 158: 265-284.   DOI   ScienceOn
4 Gellens, D. and E. Rouline, 1998. Streamflow Responses of Belgian Catchments to IPCC Climate Change Scenarios, Journal of Hydrology, 210: 242-258.   DOI   ScienceOn
5 Nash, J. E. and J. V. Sutcliffe, 1970. River Flow Forecasting through Conceptual Models, Part I- A Discussion of Principles, Journal of Hydrology, 10: 283-290.
6 Gleick, P. H. and D. B. Adams (Editors), 2000. Water: The Potential Consequences of Climate Variability and Change. A Report of the National Assessment, U.S. Global Change Research Program, U.S. Geological Survey, U.S. Department of the Interior, and the Pacific Institute for Studies in Development, Environment, and Security. Oakland, California.
7 Water Resources Update, 2003. Is Global Climate Change Research Relevant to Day-to-Day Water Resources Management, 124.
8 Kite, G. W., 1995. The SLURP Model, In: Singh. V.P. (Ed.). Computer Models of Watershed Hydrology, Water Resources Publications, Colorado, 521-562 (Chapter 15).
9 IPCC, 1996. Climate Change 1995: Impacts, Adaptation and Mitigation of Climate Change: Scientific-Technical Analyses. Contribution of Working Group II to the Second Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, New York.
10 Kite, G. W. and U. Haberlant, 1999. Atmospheric Model Data for Macroscale Hydrology, Journal of Hydrology, 217: 303-313.   DOI   ScienceOn
11 Kwadijk, J. and J. Rotmans, 1995. The Impact of Climate Change on the Discharge of the River. Rhine: a scenario study, Climate Change, 30: 397-426.   DOI
12 Kite, G. W., A. Dalton, and K. Dion, 1994. Simulation of Streamflow in a Macro-scale Watershed using GCM Data, Water Resources Research, 30(5): 1546-1559.