Abstract
The universal phenomena of global warming caused by climate change have direct linkage with different hydro-meteorological variables which in turn affect the evaporative demand of the atmosphere. Therefore, this study evaluated the seasonal and spatial changes in reference crop evapotranspiration (ETo) during last 4.7 decades and identified the forcing mechanism behind the seasonal changes in ETo using a stepwise regression equation. To remove the effect of serial correlation, the modified Mann–Kendall test was adopted together with Sen's slope and linear regression method to identify and compare the spatial and temporal trends between Thornthwaite, Hargreaves and FAO Penman–Monteith (FAO-PM) methods. Results indicate that the annual average ETo value is higher along the south and east coastal areas and lower along the northwest side of South Korea. The highest number of stations with significant increasing trends was detected in Thornthwaite and significant decreasing trend in FAO-PM method. Spatial and temporal correlation analysis showed the existence of strong correlation between Hargreaves and FAO-PM methods with the Pearson r value ranging from 0.84 to 0.98 and R2 of 0.8. Wind speed is found to be the most influencing climatic variable, especially in autumn, early winter and early summer, and maximum temperature during spring and late summer.
Similar content being viewed by others
References
Abtew W (2007) Evapotranspiration measurements and modeling for three wetland systems in south Florida. J Am Water Resour Assoc 32:465–473. https://doi.org/10.1111/j.1752-1688.1996.tb04044.x
Adeloye AJ, Montaseri M (2003) Preliminary streamflow data analyses prior to water resources planning study. Hydrol Sci 47:679–692. https://doi.org/10.1080/02626660209492973
Alexandris S, Stricevic R, Petkovic S (2008) analysis of reference evapotranspiration from the surface of rain-fed grass in central Serbia, calculated by six empirical methods against the Penman–Monteith. J Eur Water Resour Assoc 21:17–18
Allen RG, Luis SP, Raes D, Smith M (1998) FAO Irrigation and Drainage Paper No. 56. Crop Evapotranspiration (guidelines for computing crop water requirements). Irrig Drain. https://doi.org/10.1016/j.eja.2010.12.001
Asfaw A, Simane B, Hassen A, Bantider A (2018) Variability and time series trend analysis of rainfall and temperature in northcentral Ethiopia: a case study in Woleka sub-basin. Weather Clim Extrem 19:29–41. https://doi.org/10.1016/j.wace.2017.12.002
Azam M, Maeng S, Kim H et al (2018) Spatial and temporal trend analysis of precipitation and drought in South Korea. Water 10:765
Baek HJ, Kim MK, Kwon WT (2017) Observed short- and long-term changes in summer precipitation over South Korea and their links to large-scale circulation anomalies. Int J Climatol 37:972–986. https://doi.org/10.1002/joc.4753
Bandyopadhyay A, Bhadra A, Raghuwanshi NS, Singh R (2009) Temporal trends in estimates of reference evapotranspiration over India. J Hydrol Eng 14:508–515. https://doi.org/10.1061/(ASCE)HE.1943-5584.0000006
Beguería S, Vicente-Serrano SM, Reig F, Latorre B (2014) Standardized precipitation evapotranspiration index (SPEI) revisited: parameter fitting, evapotranspiration models, tools, datasets and drought monitoring. Int J Climatol 34:3001–3023. https://doi.org/10.1002/joc.3887
Burn DH, Hesch NM (2007) Trends in evaporation for the Canadian Prairies. J Hydrol 336:61–73. https://doi.org/10.1016/j.jhydrol.2006.12.011
Chang H, Kwon W-T (2007) Spatial variations of summer precipitation trends in South Korea, 1973–2005. Environ Res Lett 2:45012. https://doi.org/10.1088/1748-9326/2/4/045012
Chen D, Gao G, Xu CY et al (2005) Comparison of the Thornthwaite method and pan data with the standard Penman–Monteith estimates of reference evapotranspiration in China. Clim Res 28:123–132. https://doi.org/10.3354/cr028123
Choi H, Zhang YH (2005) Monthly variation of sea-air temperature differences in the Korean coast. J Oceanogr 61:359–367. https://doi.org/10.1007/s10872-005-0046-y
Chung Y-S, Yoon M-B, Kim H-S (2004) On climate variations and changes observed in South Korea. Clim Change 66:151–161. https://doi.org/10.1023/B:CLIM.0000043141.54763.f8
Clarke RT (2010) On the (mis)use of statistical methods in hydro-climatological research. Hydrol Sci J 55:139–144. https://doi.org/10.1080/02626661003616819
Donohue RJ, McVicar TR, Roderick ML (2010) Assessing the ability of potential evaporation formulations to capture the dynamics in evaporative demand within a changing climate. J Hydrol 386:186–197. https://doi.org/10.1016/j.jhydrol.2010.03.020
Droogers P, Allen RG (2002) Estimating reference evapotranspiration under inaccurate data conditions. Irrig Drain Syst 16:33–45. https://doi.org/10.1023/A:1015508322413
Fang Y, Sun G, Caldwell P et al (2016) Monthly land cover-specific evapotranspiration models derived from global eddy flux measurements and remote sensing data. Ecohydrology 9:248–266. https://doi.org/10.1002/eco.1629
Federer CA, Vörösmarty C, Fekete B (1996) Intercomparison of methods for calculating potential evaporation in regional and global water balance models. Water Resour Res 32(7):2315–2321. https://doi.org/10.1029/96WR00801
Gao G, Chen D, Ren G et al (2006) Spatial and temporal variations and controlling factors of potential evapotranspiration in China: 1956–2000. J Geogr Sci 16:3–12. https://doi.org/10.1007/s11442-006-0101-7
Gocic M, Trajkovic S (2013) Analysis of precipitation and drought data in Serbia over the period 1980-2010. J Hydrol 494:32–42. https://doi.org/10.1016/j.jhydrol.2013.04.044
Hamed KH, Ramachandra Rao A (1998) A modified Mann–Kendall trend test for autocorrelated data. J Hydrol 204:182–196. https://doi.org/10.1016/S0022-1694(97)00125-X
Hargreaves GH (1994) Defining and using reference evapotranspiration. J Irrig Drain Eng 120:1132–1139. https://doi.org/10.1061/(ASCE)0733-9437(1994)120:6(1132)
Hari EN (2016) Estimation of evaporation with different methods for Bapatla region. Int J Emerg Trends Sci Technol 3:4406–4414. https://doi.org/10.18535/ijetst/v3i07.19
Hebbali A (2017) Olsrr: tools for building OLS regression models. R package version 0.4. 0
Hess TM (1998) Trends in reference evapo-transpiration in the North East Arid Zone of Nigeria, 1961-91. J Arid Environ 38:99–115. https://doi.org/10.1006/jare.1997.0327
Ho CH, Lee JY, Ahn MH, Lee HS (2003) A sudden change in summer rainfall characteristics in Korea during the late 1970s. Int J Climatol 23:117–128. https://doi.org/10.1002/joc.864
Ilesanmi OA, Oguntunde PG, Olufayo AA et al (2014) Evaluation of four ETo models for IITA stations in Ibadan, Onne. J Eviron Earth Sci 4:89–97
Intergovernmental Panel on Climate Change (2007) IPCC fourth assessment report: climate change 2007
Irmak S, Payero JO, Martin DL et al (2006) Sensitivity analyses and sensitivity coefficients of standardized daily ASCE–Penman–Monteith equation. J Irrig Drain Eng 132:564–578. https://doi.org/10.1061/(ASCE)0733-9437(2006)132:6(564)
Irmak S, Kabenge I, Skaggs KE, Mutiibwa D (2012) Trend and magnitude of changes in climate variables and reference evapotranspiration over 116-yr period in the Platte River Basin, central Nebraska-USA. J Hydrol 420–421:228–244. https://doi.org/10.1016/j.jhydrol.2011.12.006
Jung IW, Bae DH, Kim G (2011) Recent trends of mean and extreme precipitation in Korea. Int J Climatol 31:359–370. https://doi.org/10.1002/joc.2068
Kendall MG (1975) Rank correlation methods, 2nd impression. Charles Griffin and Company Ltd., London and High Wycombe
Kwon W, Lee S (2004) A variation of summer rainfall in Korea. J Korean Geogr Soc 39:819–832 (in Korean with English abstract)
Lang D, Zheng J, Shi J et al (2017) A comparative study of potential evapotranspiration estimation by eight methods with FAO Penman–Monteith method in southwestern China. Water (Switzerland) 9:734. https://doi.org/10.3390/w9100734
Mann HB (1945) Nonparametric tests against trend. Econometrica 13:245. https://doi.org/10.2307/1907187
Marquaridt DW (1970) Generalized inverses, ridge regression, biased linear estimation, and nonlinear estimation. Technometrics 12:591–612. https://doi.org/10.1080/00401706.1970.10488699
Moonen AC, Ercoli L, Mariotti M, Masoni A (2002) Climate change in Italy indicated by agrometeorological indices over 122 years. Agric For Meteorol 111:13–27. https://doi.org/10.1016/S0168-1923(02)00012-6
Nam WH, Hong EM, Choi JY (2015) Has climate change already affected the spatial distribution and temporal trends of reference evapotranspiration in South Korea? Agric Water Manag 150:129–138. https://doi.org/10.1016/j.agwat.2014.11.019
Olesen T (2011) Late 20th century warming in a coastal horticultural region and its effects on tree phenology. N Z J Crop Hortic Sci 39:119–129. https://doi.org/10.1080/01140671.2010.550627
Penman HL (1948) Natural evapotranspiration from open water, bare soil and grass. Proc R Soc Lond A Math Phys Sci 193:120–145. https://doi.org/10.1007/s13398-014-0173-7.2
Rayner DP (2007) Wind run changes: the dominant factor affecting pan evaporation trends in Australia. J Clim 20:3379–3394. https://doi.org/10.1175/JCLI4181.1
Roderick ML, Rotstayn LD, Farquhar GD, Hobbins MT (2007) On the attribution of changing pan evaporation. Geophys Res Lett 34:1–6. https://doi.org/10.1029/2007GL031166
Sen PK (1968) Estimates of the regression coefficient based on Kendall's Tau. J Am Stat Assoc 63:1379–1389. https://doi.org/10.1080/01621459.1968.10480934
Serinaldi F, Kilsby CG, Lombardo F (2018) Untenable nonstationarity: an assessment of the fitness for purpose of trend tests in hydrology. Adv Water Resour 111:132–155. https://doi.org/10.1016/j.advwatres.2017.10.015
Shenbin C, Yunfeng L, Thomas A (2006) Climatic change on the Tibetan Plateau: potential evapotranspiration trends from 1961–2000. Clim Change 76:291–319. https://doi.org/10.1007/s10584-006-9080-z
Singh RK, Pawar PS (2011) Comparative study of reference crop evapotranspiration (ETo) by different energy based method with FAO 56 Penman–Monteith method at New Delhi, India. Int J Eng Sci 3:7861–7868
Tabari H (2010) Evaluation of reference crop evapotranspiration equations in various climates. Water Resour Manag 24:2311–2337. https://doi.org/10.1007/s11269-009-9553-8
Tabari H, Marofi S (2010) Changes of pan evaporation in the West of Iran. Water Resour Manag 25:97–111. https://doi.org/10.1007/s11269-010-9689-6
Theil H (1950) A rank-invariant method of linear and polynomial regression analysis, Part I. Proc R Neth Acad Sci 53:386–392
Thomas A (2000) Spatial and temporal characteristics of potential evapotranspiration trends over China. Int J Climatol 20:381–396. https://doi.org/10.1002/(SICI)1097-0088(20000330)20:4%3c381:AID-JOC477%3e3.0.CO;2-K
Thornthwaite CW (1948) An approach toward a rational classification of climate. Geogr Rev 38:55–94. https://doi.org/10.2307/210739
Van Der Schrier G, Jones PD, Briffa KR (2011) The sensitivity of the PDSI to the Thornthwaite and Penman–Monteith parameterizations for potential evapotranspiration. J Geophys Res Atmos 116:1–16. https://doi.org/10.1029/2010JD015001
von Storch H (1995) Misuses of statistical analysis in climate. Anal Clim Var Appl Stat Tech. https://doi.org/10.1007/978-3-662-03744-7
Wang Y, Jiang T, Bothe O, Fraedrich K (2007) Changes of pan evaporation and reference evapotranspiration in the Yangtze River basin. Theor Appl Climatol 90:13–23. https://doi.org/10.1007/s00704-006-0276-y
Wang C, Yang J, Myint SW et al (2016) Empirical modeling and spatio-temporal patterns of urban evapotranspiration for the Phoenix metropolitan area, Arizona. GISci Remote Sens 53:778–792. https://doi.org/10.1080/15481603.2016.1243399
Widmoser P (2009) A discussion on and alternative to the Penman–Monteith equation. Agric Water Manag 96:711–721. https://doi.org/10.1016/j.agwat.2008.10.003
Xing Z, Chow L, Meng FR et al (2008) Validating evapotranspiration equations using bowen ratio in New Brunswick, Maritime, Canada. Sensors 8:412–428. https://doi.org/10.3390/s8010412
Xu C, Gong L, Jiang T et al (2006) Analysis of spatial distribution and temporal trend of reference evapotranspiration and pan evaporation in Changjiang (Yangtze River) catchment. J Hydrol 327:81–93. https://doi.org/10.1016/j.jhydrol.2005.11.029
Yu PS, Yang TC, Chou CC (2002) Effects of climate change on evapotranspiration from paddy fields in southern Taiwan. Clim Change 54:165–179. https://doi.org/10.1023/A:1015764831165
Yue S, Wang CY (2004) The Mann-Kendall test modified by effective sample size to detect trend in serially correlated hydrological series. Water Resour Manag 18:201–218. https://doi.org/10.1023/B:WARM.0000043140.61082.60
Yue S, Pilon P, Phinney B, Cavadias G (2002) The influence of autocorrelation on the ability to detect trend in hydrological series. Hydrol Process 16:1807–1829. https://doi.org/10.1002/hyp.1095
Zarei AR, Zare S, Parsamehr AH (2015) Comparison of several methods to estimate reference evapotranspiration. West Afr J Appl Ecol 23:17–25
Zhang Y, Liu C, Tang Y, Yang Y (2007) Trends in pan evaporation and reference and actual evapotranspiration across the Tibetan Plateau. J Geophys Res Atmos 112:1–12. https://doi.org/10.1029/2006JD008161
Zhang XT, Kang SZ, Zhang L, Liu JQ (2010) Spatial variation of climatology monthly crop reference evapotranspiration and sensitivity coefficients in Shiyang river basin of northwest China. Agric Water Manag 97:1506–1516. https://doi.org/10.1016/j.agwat.2010.05.004
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Hwang, J.H., Azam, M., Jin, M.S. et al. Spatiotemporal trends in reference evapotranspiration over South Korea. Paddy Water Environ 18, 235–259 (2020). https://doi.org/10.1007/s10333-019-00777-4
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10333-019-00777-4