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http://dx.doi.org/10.7851/Ksrp.2017.23.4.153

Evaluation of Reference Evapotranspiration in South Korea according to CMIP5 GCMs and Estimation Methods  

Park, Jihoon (Climate Application Team, Climate Application Department, APEC Climate Center)
Cho, Jaepil (Climate Application Team, Climate Application Department, APEC Climate Center)
Lee, Eun-Jeong (Climate Application Team, Climate Application Department, APEC Climate Center)
Jung, Imgook (Climate Application Team, Climate Application Department, APEC Climate Center)
Publication Information
Journal of Korean Society of Rural Planning / v.23, no.4, 2017 , pp. 153-168 More about this Journal
Abstract
The main objective of this study was to assess reference evapotranspiration based on multiple GCMs (General Circulation Models) and estimation methods. In this study, 10 GCMs based on the RCP (Representative Concentration Pathway) 4.5 scenario were used to estimate reference evapotranspiration. 54 ASOS (Automated Synoptic Observing System) data were constructed by statistical downscaling techniques. The meteorological variables of precipitation, maximum temperature and minimum temperature, relative humidity, wind speed, and solar radiation were produced using GCMs. For the past and future periods, we estimated reference evapotranspiration by GCMs and analyzed the statistical characteristics and analyzed its uncertainty. Five methods (BC: Blaney-Criddle, HS: Hargreaves-Samani, MK: Makkink, MS: Matt-Shuttleworth, and PM: Penman-Monteith) were selected to analyze the uncertainty by reference evapotranspiration estimation methods. We compared the uncertainty of reference evapotranspiration method by the variable expansion and analyzed which variables greatly influence reference evapotranspiration estimation. The posterior probabilities of five methods were estimated as BC: 0.1792, HS: 0.1775, MK: 0.2361, MS: 0.2054, and PM: 0.2018. The posterior probability indicated how well reference evapotranspiration estimated with 10 GCMs for five methods reflected the estimated reference evapotranspiration using the observed data. Through this study, we analyzed the overall characteristics of reference evapotranspiration according to GCMs and reference evapotranspiration estimation methods The results of this study might be used as a basic data for preparing the standard method of reference evapotranspiration to derive the water management method under climate change.
Keywords
Climate Change; GCMs; Reference Evapotranspiration; Uncertainty;
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Times Cited By KSCI : 8  (Citation Analysis)
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1 Prudhomme, C. and Williamson, J., 2013, Derivation of RCM-driven potential evapotranspiration for hydrological climate change impact analysis in Great Britain: a comparison of methods and associated uncertainty in future projections, Hydrology and Earth System Sciences 17: 1365-1377.   DOI
2 Raftery, A.E., Gneiting, T., Balabdaoui, F., and Polakowski, M., 2005, Using Bayesian Model Averaging to Calibrate Forecast Ensembles, Monthly Weather Review 133: 1155-1174.   DOI
3 Shuttleworth, W. and Wallace, J., 2009, Calculating the water requirements of irrigated crops in Australia using the Matt-Shuttleworth approach, Transactions of the ASABE, 52, 1895-1906.   DOI
4 Valiantzas, J.D., 2013, Simplified forms for the standardized FAO-56 Penman-Monteith reference evapotranspicration using limited weather data, Journal of Hydrology 505: 13-23.   DOI
5 Yoo, S.-H., Choi, J.-Y., and Jang, M.-W., 2006, Estimation of Paddy Rice Crop Coefficients for FAO Penman-Monteith and Modified Penman Method, Journal of the Korean Society of Agricultural Engineers 48(1): 13-23.   DOI
6 Yoo, S.-H., Kim, T., Lee, S.-H., and Choi, J.-Y., 2015, Trend Analysis of Projected Climate Data based on CMIP5 GCMs for Climate Change Impact Assessment on Agricultural Water Resources, Journal of the Korean Society of Agricultural Engineers 57(5): 69-80.   DOI
7 IPCC, 2014, Climate Change 2014: Impacts, Adaptation, and Vulnerability. Part A: Global and Sectoral Aspects. Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Field, C.B., V.R. Barros, D.J. Dokken, K.J. Mach, M.D. Mastrandrea, T.E. Bilir, M. Chatterjee, K.L. Ebi, Y.O. Estrada, R.C. Genova, B. Girma, E.S. Kissel, A.N. Levy, S. MacCracken, P.R. Mastrandrea, and L.L.White (eds.)], Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 1132 pp.
8 Kim, B.S., Sung, J.H., Lee, B.H., and Kim, D.J., 2013, Evaluation on the Impact of Extreme Droughts in South Korea using the SPEI and RCP8.5 Climate Change Scenario, Journal of the Korean Society of Hazard Mitigation 13(2):97-109.   DOI
9 Kim, S.J., Kim, M.-I., Lim, C.-H., Lee, W.-K., and Kim, B.-J., 2017, Applicability Analysis of FAO56 Penman-Monteith Methodology for Estimating Potential Evapotranspiration in Andong Dam Watershed Using Limited Meteorological Data, Journal of Climate Change Research 8(2): 125-143.   DOI
10 Lee, K.-H. and Park, J.-H., 2008, Calibration of the Hargreaves Equation for the Reference Evapotranspiration Estimation on a Nation-Wide Scale, Journal of the Korean Society of Civil Engineers 28(6B): 675-681.
11 McMahon, T., Peel, M., Lowe, L., Srikanthan, R., and McVicar, T., 2012, Estimating actual, potential, reference crop and pan evaporation using standard meteorological data: a pragmatic synthesis, Hydrology and Earth System Sciences Discussions 9: 11829-11910.   DOI
12 Ministry of Land, Infrastructure and Transport (MOLIT), 2016, Long-Term Comprehensive Water Plan (2001-2020), 11-1613000-001716-13, Ministry of Land, Infrastructure and Transport, Sejong, Republic of Korea.
13 Mishra, V., Kumar, R., Shah, H.L., Samaniego, L., Eisner, S., and Yang, T., 2017, Multimodel assessment of sensitivity and uncertainty of evapotranspiration and a proxy for available water resources under climate change, Climatic Change 141: 451-465.   DOI
14 Oh, N.S. and Lee, K.-H., 2004, Calculation of Evapotranspiration Based on Daily Temperature, Journal of Korea Water Resources Association 37(6): 479-485.   DOI
15 Oudin, L., Hervieu, F., Michel, C., Perrin, C., Andreassian, V., Anctil, F., and Loumagne, C., 2005, Which potential evapotranspiration input for a lumped rainfall-runoff model? Part 2-Towards a simple and efficient potential evapotranspiration model for rainfall-runoff modelling, Journal of Hydrology 303: 290-306.   DOI
16 Allen, R.G., Pereira, L.S., Raes, D., and Smith, M., 1998, Crop evapotranspiration-Guidelines for computing crop water requirements-FAO Irrigation and drainage. paper 56, FAO, Rome.
17 Allen, R.G., Walter, I.A., Elliott, R., Howell, T., Itenfisu, D., and Jensen, M., 2005, The ASCE standardized reference evapotranspiration equation, ASCE-EWRI Task Committee Report.
18 Bae, D.H., Jung, I.W., Lee, B.J., and Lee, M.H., 2011, Future Korean Water Resources Projection Considering Uncertainty of GCMs and Hydrological Models, Journal of Korea Water Resources Association 44(5): 389-406.   DOI
19 Cho, J., Ko, G., Kim, K., and Oh, C., 2016, Climate Change Impacts on Agricultural Drought with Consideration of Uncertainty in CMIP5 Scenarios, Irrigation and Drainage 65(S2): 7-15.   DOI
20 Choi, S.-K., Kim, M.-K., Jeong, J., Choi, D., and Hur, S.-O., 2017, Estimation of Crop Yield and Evapotranspiration in Paddy Rice with Climate Change Using APEX-Paddy Model, Journal of the Korean Society of Agricultural Engineers 59(4): 27-42.   DOI
21 Climate information portal, 2017, http://www.climate.go.kr/index.html, Accessed 25 Sep. 2017.
22 De Bruin, H.A.R. and Lablans, W.N. 1998, Reference crop evapotranspiration determined with a modified Makkink equation, Hydrological Processes 12, 1053-1062.   DOI
23 Eum, H.-I. and Cannon, A.J., 2017, Intercomparison of projected changes in climate extremes for South Korea: application of trend preserving statistical downscaling methods to the CMIP5 ensemble, International Journal of Climatology 37: 3381-3397.   DOI
24 FAO, 1998, Crop FAO Irrigation and Drainage Paper 56, Rome, Italy.
25 Kim, T., Suh, K., Nam, W.-H., Lee, J., Hwang, S., Yoo, S.-H., and Hong, S.-O., 2016, Design and Implementation of Reference Evapotranspiration Database for Future Climate Scenarios, Journal of Korean Society of Rural Planning 22(4): 71-80.   DOI
26 Kingston, D.G., Todd, M.C., Taylor, R.G., Thompson, J.R., and Arnell, N.W., 2009, Uncertainty in the estimation of potential evapotranspiration under climate change, GEOPHYSICAL RESEARCH LETTERS 36 L20403.   DOI
27 Hur, S.-O., Jung, K.-H., Ha, S.-K., and Kim, J.-G., 2006, Evaluation of Meteorological Elements Used for Reference Evapotranspiration Calculation of FAO Penman-Monteith Mode, Korean Journal of Soil Science and Fertilizer 39(5): 274-279l.
28 Priestly, C.H.B. and Taylor, R.J., 1972, On the assessment of surface heat flux and evaporation using large-scale parameters, Monthly Weather Review 100(2): 81-92.   DOI
29 Hargreaves, G.H. and Samani, Z.A., 1985, Reference crop evapotranspiration from temperature, Applied Engineering in Agriculture 1(2): 96-99.   DOI
30 Hoeting, J.A., Madigan, D., Raftery, A.E., and Volinsky, C.T., 1999, Bayesian model averaging: A tutorial, Statistical Science 14: 382-401.   DOI
31 Hong, E.M., Choi, J.Y., Lee, S.H., Yoo, S.H., and Kang, M.S., 2009, Estimation of Paddy Rice Evapotranspiration Considering Climate Change Using LARS-WG, Journal of the Korean Society of Agricultural Engineers 51(3): 25-35.   DOI