Browse > Article
http://dx.doi.org/10.5389/KSAE.2015.57.5.001

Assessing the Climate Change Impacts on Agricultural Reservoirs using the SWAT model and CMIP5 GCMs  

Cho, Jaepil (Climate Research Department, APEC Climate Center)
Hwang, Syewoon (Department of Agricultural Engineering, Gyeongsng National University)
Go, Gwangdon (Agricultural Infrastructure Development Division, Korea Rural Community Corporation)
Kim, Kwang-Young (Water Resources Research Division, Rural Research Institute)
Kim, Jeongdae (Water Resources Research Division, Rural Research Institute)
Publication Information
Journal of The Korean Society of Agricultural Engineers / v.57, no.5, 2015 , pp. 1-12 More about this Journal
Abstract
The study aimed to project inflows and demmands for the agricultural reservoir watersheds in South Korea considering a variety of regional characteristics and the uncertainty of future climate information. The study bias-corrected and spatially downscaled retrospective daily Global Climate Model (GCM) outputs under Representative Concentration Pathways (RCP) 4.5 and 8.5 emission scenarios using non-parametric quantile mapping method to force Soil and Water Assessment Tool (SWAT) model. Using the historical simulation, the skills of un-calibrated SWAT model (without calibration process) was evaluated for 5 reservoir watersheds (selected as well-monitored representatives). The study then, evaluated the performance of 9 GCMs in reproducing historical upstream inflow and irrigation demand at the five representative reservoirs. Finally future inflows and demands for 58 watersheds were projected using 9 GCMs projections under the two RCP scenarios. We demonstrated that (1) un-calibrated SWAT model is likely applicable to agricultural watershed, (2) the uncertainty of future climate information from different GCMs is significant, (3) multi-model ensemble (MME) shows comparatively resonable skills in reproducing water balances over the study area. The results of projection under the RCP 4.5 and RCP 8.5 scenario generally showed the increase of inflow by 9.4% and 10.8% and demand by 1.4% and 1.7%, respectively. More importantly, the results for different seasons and reservoirs varied considerably in the impacts of climate change.
Keywords
RCP scenario; GCM; SWAT; agricultural reservoirs; climate change impacts;
Citations & Related Records
Times Cited By KSCI : 12  (Citation Analysis)
연도 인용수 순위
1 De Silva, C. S., E. K. Weatherhead, J. W. Knox, and J. A. Rodriguez-Diaz, 2007. Predicting the impacts of climate change-A case study of paddy irrigation water requirements in Sri Lanka. Agricultural Water Management 93: 19-29.   DOI
2 Chung S. O., 2009a. Climate change impacts on paddy irrigation requirement in the Nakdong river basin. Journal of the Korean Society of Agricultural Engineers 51(2): 35-41 (in Korean).   DOI
3 Chung S. O., 2009b. Prediction of paddy irrigation demand in Nakdong river basin using regional climate model outputs. Journal of the Korean Society of Agricultural Engineers 51(4): 7-13 (in Korean).   DOI
4 Cheong T. S., S, U. Kang, M. H. Hwang, and I. H. Ko, 2008. Development and validation of reservoir operation rules for integrated water resources management in the Geum river basin. Journal of Korea Water Resources Association 41(4): 433-444 (in Korean).   DOI   ScienceOn
5 Fischer, G., F. N. Tubiello, H. Van Velthuizen, and D. A. Wiberg, 2007. Climate change impacts on irrigation water requirements: effects of mitigation, 1990-2080. Technological Forecasting and Social Change 74: 1083-1107.   DOI
6 Hwang, S. W, 2014a. Assessing the performance of CMIP5 GCMs for various climatic elements and indicators over the southeast US. Journal of Korea Water Resources Association 47(11): 1039-1050 (in Korean).   DOI
7 Hwang, S. W, 2014b. Summary and inter-comparison of GHG scenarios and the results of climate change forecasts in the IPCC Assessment Reports. Rural Resources 56(2): 26-32 (in Korean).
8 Hwang, S. W., and Kang, M. S, 2013. The methodologies of climate change impact assessment and uncertainty in each procedure. Rural Resources 55(1): 30-39 (in Korean).
9 Im, S. J., K. M. Brannan, S. Mostaghimi, and J. Cho, 2004. Simulating fecal coliform bacteria loading from an urbanizing watershed. Journal of Environmental Science and Health, PartAToxic /Hazardous Substances & Environmental Engineering 39(3): 663-679.   DOI
10 Kang, M. G., J. H. Lee, and K. W. Park, 2013. Parameter regionalization of a TANK model for simulating runoffs from ungauged watersheds. Journal of Korea Water Resources Association 46(5): 519-530 (in Korean).   DOI
11 Kim H. Y., and S. W. Park, 1988. Simulating daily inflow and release rates for irrigation reservoirs(III). Journal of the Korean Society of Agricultural Engineers 30(3): 95-105 (in Korean).
12 Kim, C. G., and N. W. Kim, 2012. Comparison of natural flow estimates for the Han river basin using TANK and SWAT models. Journal of Korea Water Resources Association 45(3): 301-316 (in Korean).   DOI   ScienceOn
13 Lee Y. J., M. J. Park, K. W. Park, and S. J. Kim, 2008. Analysis of hydrologic behavior including agricultural reservoir operation using SWAT model. Journal of the Korean Association of Geographic Information Studies 11(1): 20-30 (in Korean).
14 Oh, Y. G., S. H. Yoo, S. H. Lee, N. Y. Park, J. Y. Choi, and D. K. Yun, 2012. Prediction of land-cover change and analysis of paddy fields changes based on climate change scenario (A1B) in agricultural reservoir watersheds. Journal of the Korean Society of Agricultural Engineers 54(2): 77-86 (in Korean).   DOI
15 Park, G. A., S.-R. Anh, Y.-J. Lee, H.-j. Shin, M.-J. Park, and S.-J. Kim, Assessment of climate change impact on the inflow and outflow of two agricultural reservoirs in Korea. American Society of Agricultural and Biological Engineers 52(5): 1869-1883.
16 Rural Research Institute (RRI), 2013. Saemangeum basin modeling study considering future water quality characteristics analysis and agricultural non-point source pollution mechanism. Korean Rural Community Corporation, Republic of Korea (in Korean).
17 Park, J., M. S. Kang, I. Song, S. H. Hwang, and J. H. Song, 2013. Development of IDF curve based on RCP4.5 scenario for 30-reservoirs in South Korea. Journal of Korean Society Hazard Mitigation 13(6): 145-159 (in Korean).   DOI
18 Rural Agricultural Water Resource Information System, https://rawris.ekr.or.kr/.
19 Rural Research Institute (RRI), 2011. A study on the impact assessment of climate change on agricultural water. Korean Rural Community Corporation, Republic of Korea (in Korean).
20 Tebaldi, C. and R. Knutti, 2007. The use of the multi-model ensemble in probabilistic climate projections. Philosophical Transactions of the Royal Society 365: 2053-2075.   DOI
21 Yun D. H., S. O. Chumg, and S. J. Kim, 2011. Climate change impacts on paddy water requirement. Journal of the Korean Society of Agricultural Engineers 53(4): 39-47 (in Korean).   DOI
22 Cho, J., 2013. Impact assessment of climate change for agricultural reservoirs considering uncertainty. Research report, APEC Climate Center, Busan, Republic of Korea (in Korean).
23 Ahn, T. J., D. H. Cho, S. H. Lee, G. W. Choi, and Y. N. Yoon, 2004. Evaluation of the effective storage of existing agricultural reservoir. Journal of Korea Water Resources Association 37(5): 353-361 (in Korean).   DOI
24 Arnold, J. G., R. Srinivasan, R. S. Muttiah, and J. R. Williams, 1998. Large-area hydrologic modeling and assessment: Part I. Model development. J. Amer. Water Resources Association 34(1): 73-89.   DOI
25 Nam, W. H., E. M. Hong, T. Kim, and J. Y. Choi, 2014. Projection of future water supply sustainability in agricultural reservoirs under RCP climate change ccenarios. Journal of the Korean Society of Agricultural Engineers 56(4): 59-68 (in Korean).   DOI