Abstract
Actual evapotranspiration (AET) is a key factor in land-atmosphere interactions and a major hydrological cycle component. Variations in AET have resulted from a combination of climate change (CC) and human activities (HA). Quantifying the contributions of these two factors to AET dynamics is essential for better understanding hydrometeorological and ecohydrological processes under both natural and anthropogenic conditions. In this study, an analytical framework was adopted for AET variance analysis, and the influences of CC and HA on regional AET variabilities were separated by using this method. AET variance is determined by the variance in CC (\({\sigma }_{AETc}^{2}\)) and HA (\({\sigma }_{AETh}^{2}\)); the former is estimated through a synthesis of the variance/covariance of potential evapotranspiration (ET0) and precipitation (P), and the latter is determined from the residual between the total AET variance and \({\sigma }_{AETc}^{2}\). Based on a 36-year dataset (1980–2015), this framework is applied to the different regions of the Tao River Basin (TRB). The results reveal that climate was the primary factor influencing AET variance in most parts of the basin. Precipitation (P) dominated the \({\sigma }_{AETc}^{2}\) and had a positive effect, while the interactions between P and ET0 tended to suppress this effect, especially in the semihumid areas of the TRB. The contribution rates of CC and HA to basin AET variance were estimated to be 0.76 and 0.24, respectively. The developed analytical framework and its application are beneficial to the management and exploitation of water resources from the perspective of basin ecohydrology.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Abu-Awwad AM (1999) Irrigation water management for efficient water use in mulched onion. J Agron Crop Sci 183:1–7. https://doi.org/10.1046/j.1439-037x.1999.00304.x
Allen RG, Pereira LS, Raes D et al (1998) Crop evapotranspiration-guidelines for computing crop water requirements. FAO Irrigation and Drainage Paper 56. Rome
Ayyad S, Zayed A, Ha V, Ribbe L (2019) The performance of satellite-based actual evapotranspiration products and the assessment of irrigation efficiency in Egypt. Water 11:1913. https://doi.org/10.3390/w11091913
Bai P, Liu X (2018) Intercomparison and evaluation of three global high-resolution evapotranspiration products across China. J Hydrol 566:743–755. https://doi.org/10.1016/j.jhydrol.2018.09.065
Baker IT, Sellers PJ, Denning AS, Medina I, Kraus P, Haynes KD, Biraud SC (2017) Closing the scale gap between land surface parameterizations and GCMs with a new scheme, SiB3-Bins. J Adv Model Earth Syst 9:691–711. https://doi.org/10.1002/2016ms000764
Bu J, Lu C, Niu J, Gao Y (2018) Attribution of runoff reduction in the Juma River Basin to climate variation, direct human intervention, and land use change. Water 10:1775. https://doi.org/10.3390/w10121775
Budyko MI (1974) Climate and life. Miller D H, Translated. Academic Press, San Diego
Budyko M, Berlyand T, Yefimova N, Zubenok L, Strokina L (1980) Heat balance of the Earth. Res Geophys. Solid Earth Interface Phenom 2:1–55
Chen J, Yu Z, Zhu Y, Yang C (2011a) Relationship between land use and evapotranspiration—a case study of the Wudaogou area in Huaihe River basin. Proc Environ Sci 10:491–498
Chen Y, Yang K, He J, Qin J, Shi J, Du J, He Q (2011b) Improving land surface temperature modeling for dry land of China. J Geophys Res 116:D20104. https://doi.org/10.1029/2011jd015921
Chen X, Alimohammadi N, Wang D (2013) Modeling interannual variability of seasonal evaporation and storage change based on the extended Budyko framework. Water Resour Res 49:6067–6078. https://doi.org/10.1002/wrcr.20493
Chen H, Zhang W, Shalamzari MJ (2019) Remote detection of human-induced evapotranspiration in a regional system experiencing increased anthropogenic demands and extreme climatic variability. Int J Remote Sens 40:1887–1908. https://doi.org/10.1080/01431161.2018.1523590
Choi M, Kim TW, Kustas WP (2011) Reliable estimation of evapotranspiration on agricultural fields predicted by the Priestley–Taylor model using soil moisture data from ground and remote sensing observations compared with the common land model. Int J Remote Sens 32:4571–4587. https://doi.org/10.1080/01431161.2010.489065
Cox PM, Betts RA, Jones CD, Spall SA, Totterdell IJ (2000) Acceleration of global warming due to carbon-cycle feedbacks in a coupled climate model. Nature 408:184–187. https://doi.org/10.1038/35041539
Ding J, Zhang Y, Guo Y, Ma N (2018) Quantitative comparison of river inflows to a rapidly expanding lake in central Tibetan Plateau. Hydrol Process 32:3241–3253. https://doi.org/10.1002/hyp.13239
Doorenbos J, Pruitt W (1977) Guidelines for predicting crop water requirements. Food and Agriculture Organization of the United Nations, Rome
Fu B (1981) On the calculation of the evaporation from land surface. Sci Atmos Sin 5(1):23–32 (in Chinese)
Gao M, Chen X, Liu J, Zhang Z (2018) Regionalization of annual runoff characteristics and its indication of co-dependence among hydro-climate–landscape factors in Jinghe River Basin, China. Stoch Environ Res Risk Assess 32:1613–1630. https://doi.org/10.1007/s00477-017-1494-9
Gao X, Sun M, Luan Q, Zhao X, Wang J, He G, Zhao Y (2020) The spatial and temporal evolution of the actual evapotranspiration based on the remote sensing method in the Loess Plateau. Sci Total Environ 708:135111
Giorgi F (2005) Interdecadal variability of regional climate change: implications for the development of regional climate change scenarios. Meteorol Atmos Phys 89:1–15. https://doi.org/10.1007/s00703-005-0118-y
Granata F, Gargano R, Marinis G (2020) Artificial intelligence based approaches to evaluate actual evapotranspiration in wetlands. Sci Total Environ 703:135653. https://doi.org/10.1016/j.scitotenv.2019.135653
Guo Y, Li Z, Amo-Boateng M, Deng P, Huang P (2014) Quantitative assessment of the impact of climate variability and human activities on runoff changes for the upper reaches of Weihe River. Stoch Environ Res Risk Assess 28:333–346. https://doi.org/10.1007/s00477-013-0752-8
Han S, Xu D, Yang Z (2017) Irrigation-induced changes in evapotranspiration demand of Awati Irrigation District, Northwest China: weakening the effects of water saving? Sustainability 9:1531. https://doi.org/10.3390/su9091531
Hao L, Sun G, Liu Y, Wan J, Qin M, Qian H, Liu C, Zheng J, John R, Fan P, Chen J (2015) Urbanization dramatically altered the water balances of a paddy field-dominated basin in southern China. Hydrol Earth Syst Sci 19:3319–3331. https://doi.org/10.5194/hess-19-3319-2015
He J (2010) Development of a surface meteorological dataset of China with high temporal and spatial resolution [D]. Beijing. The Graduate School of the Chinese Academy of Sciences 1–78 (In Chinese)
He M, Kimball J, Yi Y, Running S, Guan K, Moreno A, Wu X, Maneta M (2019) Satellite data-driven modeling of field scale evapotranspiration in croplands using the MOD16 algorithm framework. Remote Sens Environ 230:111201. https://doi.org/10.1016/j.rse.2019.05.020
Huang Y, Salama MS, Su Z, van der Velde R, Zheng D, Krol MS, Hoekstra AY, Zhou Y (2016) Effects of roughness length parameterizations on regional-scale land surface modeling of alpine grasslands in the Yangtze river basin. J Hydrometeorol 17:1069–1085. https://doi.org/10.1175/jhm-d-15-0049.1
Huang S, Huang Q, Chang J, Leng G, Chen Y (2017) Variations in precipitation and runoff from a multivariate perspective in the Wei River Basin, China. Quat Int 400:30–39
Huang Z, Hejazi M, Tang Q, Vernon C, Liu Y, Chen M, Calvin K (2019) Global agricultural green and blue water consumption under future climate and land use changes. J Hydrol 574:242–256. https://doi.org/10.1016/j.jhydrol.2019.04.046
Immerzeel W, Droogers P (2008) Calibration of a distributed hydrological modelbased on satellite evapotranspiration. J Hydrol 349:411–424. https://doi.org/10.1016/j.jhydrol.2007.11.017
Jiménez C, Prigent C, Mueller B et al (2011) Global intercomparison of 12 land surface heat flux estimates. J Geophys Res 116:D02102. https://doi.org/10.1029/2010jd014545
Khosa F, Feig G, Merwe M, Mateyisi M, Mudau A, Savage M (2019) Evaluation of modeled actual evapotranspiration estimates from a land surface, empirical and satellite-based models using in situ observations from a South African semi-arid savanna ecosystem. Agric Forest Meteorol 279:107706
Koster RD, Suarez MJ (1999) A simple framework for examining the interannual variability of land surface moisture fluxes. J Clim 12:1911–1917
Kummerow C, Barnes W, Kozu T, Shiue J, Simpson J (1998) The tropical rainfall measuring mission (TRMM) sensor package. J Atmos Ocean Technol 15:809–817
Li D (2014) Assessing the impact of interannual variability of precipitationand potential evaporation on evapotranspiration. Adv Water Resour 70:1–11. https://doi.org/10.1016/j.advwatres.2014.04.012
Li B, Chen F (2015) Using the aridity index to assess recent climate change: a case study of the Lancang River Basin, China. Stoch Environ Res Risk Assess 29:1071–1083. https://doi.org/10.1007/s00477-014-0998-9
Li C, Wang S, Yang L, Yang W, Li W (2013) Spatial and temporal variation of main hydrologic meteorological elements in the taohe river basin from 1951 to 2010. J Glaciol Geocryol 35:1259–1266. https://doi.org/10.7522/j.issn.1000-0240.2013.0142
Li G, Zhang F, Jing Y, Liu Y, Sun G (2017) Response of evapotranspiration to changes in land use and land cover and climate in China during 2001–2013. Sci Total Environ 596–597:256–265. https://doi.org/10.1016/j.scitotenv.2017.04.080
Li C, Wang L, Wanrui W, Qi J, Linshan Y, Zhang Y, Lei W, Cui X, Wang P (2018) An analytical approach to separate climate and human contributions to basin streamflow variability. J Hydrol 559:30–42. https://doi.org/10.1016/j.jhydrol.2018.02.019
Liu S, Xu Z, Song L, Zhao Q, Ge Y, Xu T, Ma Y, Zhu Z, Jia Z, Zhang F (2016a) Upscaling evapotranspiration measurements from multi-site to the satellite pixel scale over heterogeneous land surfaces. Agric Forest Meteorol 230–231:97–113. https://doi.org/10.1016/j.agrformet.2016.04.008
Liu W, Wang L, Zhou J, Li Y, Sun F, Fu G, Li X, Sang Y-F (2016b) A worldwide evaluation of basin-scale evapotranspiration estimates against the water balance method. J Hydrol 538:82–95. https://doi.org/10.1016/j.jhydrol.2016.04.006
Liu X, Liu W, Yang H, Tang Q, Flörke M, Masaki Y, Schmied HM, Ostberg S, Pokhrel Y, Satoh Y, Wada Y (2019) Multimodel assessments of human and climate impacts on mean annual streamflow in China. Hydrol Earth Syst Sci 23:1245–1261. https://doi.org/10.5194/hess-23-1245-2019
Lv X, Zou Z, Sun J, Ni Y, Wang Z (2019) Climatic and human-related indicators and their implications for evapotranspiration management in a watershed of Loess Plateau, China. Ecol Ind 101:143–149
Ma Z, Yan N, Wu B, Stein A, Zhu W, Zeng H (2019) Variation in actual evapotranspiration following changes in climate and vegetation cover during an ecological restoration period (2000–2015) in the Loess Plateau, China. Sci Total Environ 689:534–545. https://doi.org/10.1016/j.scitotenv.2019.06.155
Mahmoud S, Alazba A (2016) A coupled remote sensing and the Surface Energy Balance based algorithms to estimate actual evapotranspiration over the western and southern regions of Saudi Arabia. J Asian Earth Sci 124:269–283
Martel M, Glenn A, Wilson H, Krobel R (2018) Simulation of actual evapotranspiration from agricultural landscapes in the Canadian Prairies. J Hydrol Reg Stud 15:105–118
Martens B, Miralles DG, Lievens H, van der Schalie R, de Jeu RAM, Fernández-Prieto D, Beck HE, Dorigo WA, Verhoest NEC (2017) GLEAM v3: satellite-based land evaporation and root-zone soil moisture. Geosci Model Dev 10:1903–1925. https://doi.org/10.5194/gmd-10-1903-2017
Mo S, Li Z, Gou K, Qin L, Shen B (2018) Quantifying the effects of climate variability and direct human activities on the change in mean annual runoff for the Bahe River (Northwest China). J Coast Res 341:81–89. https://doi.org/10.2112/jcoastres-d-16-00159.1
Mostowik K, Siwek J, Kisiel M, Kowalik K, Krzysik M, Plenzler J, Rzonca B (2019) Runoff trends in a changing climate in the Eastern Carpathians (Bieszczady Mountains, Poland). Catena 182:104174
Mu M, Zhang X, Gao P, Wang F (2010) Theory of double mass curves and its applications in hydrology and meteorology. J China Hydrol 30:47–51
Mu Q, Zhao M, Running SW (2011) Improvements to a MODIS global terrestrial evapotranspiration algorithm. Remote Sens Environ 115:1781–1800. https://doi.org/10.1016/j.rse.2011.02.019
Ning T, Li Z, Liu W (2016) Separating the impacts of climate change and land surface alteration on runoff reduction in the Jing River catchment of China. Catena 147:80–86
Ning T, Li Z, Feng Q, Liu W, Li Z (2018) Comparison of the effectiveness of four Budyko-based methods in attributing long-term changes in actual evapotranspiration. Sci Rep 8:12665. https://doi.org/10.1038/s41598-018-31036-x
Ning T, Zhou S, Chang F, Shen H, Li Z, Liu W (2019) Interaction of vegetation, climate and topography on evapotranspiration modelling at different time scales within the Budyko framework. Agric Forest Meteorol 275:59–68. https://doi.org/10.1016/j.agrformet.2019.05.001
Olivera-Guerra L, Merlin O, Er-Raki S, Khabba S, Escorihuela MJ (2018) Estimating the water budget components of irrigated crops: combining the FAO-56 dual crop coefficient with surface temperature and vegetation index data. Agric Water Manag 208:120–131. https://doi.org/10.1016/j.agwat.2018.06.014
Pan Y, Zhang C, Gong H, Yeh PJF, Shen Y, Guo Y, Huang Z, Li X (2017) Detection of human-induced evapotranspiration using GRACE satellite observations in the Haihe River basin of China. Geophys Res Lett 44:190–199. https://doi.org/10.1002/2016gl071287
Pandeya B, Mulligan M (2013) Modelling crop evapotranspiration and potential impacts on future water availability in the Indo-Gangetic Basin. Agric Water Manag 129:163–172. https://doi.org/10.1016/j.agwat.2013.07.019
Penman H (1948) Natural evaporation from open water, hare soil and grass. Proc R Soc Lond 193:120–145. https://doi.org/10.1098/rspa.1948.0037
Pirkner M, Dicken U, Tanny J (2014) Penman–Monteith approaches for estimating crop evapotranspiration in screen houses—a case study with table-grape. Int J Biometeorol 58:725–737. https://doi.org/10.1007/s00484-013-0653-z
Prăvălie R, Piticar A, Rosca B, Sfîcă L, Bandoc G, Tiscovschi A, Patriche C (2019) Spatio-temporal changes of the climatic water balance in Romania as a response to precipitation and reference evapotranspiration trends during 1961–2013. Catena 172:295–312. https://doi.org/10.1016/j.catena.2018.08.028
Rodell M, Houser PR, Jambor U et al (2004) The global land data assimilation system. Bull Am Meteorol Soc 85:381–394. https://doi.org/10.1175/bams-85-3-381
Roderick ML, Farquhar GD (2004) Changes in Australian pan evaporation from 1970 to 2002. Int J Climatol 24:1077–1090. https://doi.org/10.1002/joc.1061
Seiller G, Anctil F (2014) Climate change impacts on the hydrologic regime of a Canadian river: comparing uncertainties arising from climate natural variability and lumped hydrological model structures. Hydrol Earth Syst Sci 18:2033–2047. https://doi.org/10.5194/hess-18-2033-2014
Sen K, Pranab (1968) Estimates of the regression coefficient based on Kendall’s tau. J Am Stat Assoc 63(324):1379–1389
Stannard DI (1993) Comparison of Penman–Monteith, Shuttleworth–Wallace, and modified Priestley–Taylor evapotranspiration models for wildland vegetation in semiarid rangeland. Water Resour Res 29:1379–1392. https://doi.org/10.1029/93wr00333
Sun S, Chen B, Ge M, Qu J, Che T, Zhang H, Lin X, Che M, Zhou Z, Guo L, Wang B (2016) Improving soil organic carbon parameterization of land surface model for cold regions in the Northeastern Tibetan Plateau, China. Ecol Model 330:1–15. https://doi.org/10.1016/j.ecolmodel.2016.03.014
Sun P, Zhang Q, Singh VP, Xiao M, Zhang X (2017) Transitional variations and risk of hydro-meteorological droughts in the Tarim River basin, China. Stoch Environ Res Risk Assess 31:1515–1526. https://doi.org/10.1007/s00477-016-1254-2
Tang Y, Hooshyar M, Zhu T et al (2017) Reconstructing annual groundwater storage changes in a large-scale irrigation region using GRACE data and Budyko model. J Hydrol 551:397–406
Timmermans J, Su Z, van der Tol C, Verhoef A, Verhoef W (2013) Quantifying the uncertainty in estimates of surface-atmosphere fluxes through joint evaluation of the SEBS and SCOPE models. Hydrol Earth Syst Sci 17:1561–1573. https://doi.org/10.5194/hess-17-1561-2013
Wang D (2012) Evaluating interannual water storage changes at watersheds in Illinois based on long-term soil moisture and groundwater level data. Water Resour Res 48:W03502. https://doi.org/10.1029/2011WR010759
Wang D, Alimohammadi N (2012) Responses of annual runoff, evaporation, and storage change to climate variability at the watershed scale. Water Resour Res 48:W05546. https://doi.org/10.1029/2011WR011444
Wang K, Dickinson RE (2012) A review of global terrestrial evapotranspiration: observation, modeling, climatology, and climatic variability. Rev Geophys 50:RG2005. https://doi.org/10.1029/2011rg000373
Wang D, Tang Y (2014) A one-parameter Budyko model for water balance captures emergent behavior in Darwinian hydrologic models. Geophys Res Lett 41:4569–4577
Wang Y, Liu G, Guo E (2019a) Spatial distribution and temporal variation of drought in Inner Mongolia during 1901–2014 using Standardized Precipitation Evapotranspiration Index. Sci Total Environ 654:850–862. https://doi.org/10.1016/j.scitotenv.2018.10.425
Wang F, Duan K, Fu S et al (2019b) Partitioning climate and human contributions to changes in mean annual streamflow based on the Budyko complementary relationship in the Loess Plateau, China. Sci Total Environ 665:579–590
Wen Y, Liu X, Yang J, Lin K, Du G (2019) NDVI indicated inter-seasonal non-uniform time-lag responses of terrestrial vegetation growth to daily maximum and minimum temperature. Glob Planet Change 177:27–38
Westerhoff RS (2015) Using uncertainty of Penman and Penman–Monteith methods in combined satellite and ground-based evapotranspiration estimates. Remote Sens Environ 169:102–112. https://doi.org/10.1016/j.rse.2015.07.021
Wu C, Hu BX, Huang G, Zhang H (2017) Effects of climate and terrestrial storage on temporal variability of actual evapotranspiration. J Hydrol 549:388–403. https://doi.org/10.1016/j.jhydrol.2017.04.012
Wu L, Li C, Wang L et al (2020a) Spatiotemporal variability of alpine precipitable water over arid northwestern China. Hydrol Process 34:3524–3528. https://doi.org/10.1002/hyp.13835
Wu L, Li C, Xie X et al (2020b) The impact of increasing land productivity on groundwater dynamics: a case study of an oasis located at the edge of the Gobi Desert. Carbon Balance Manag 15(7):1–13. https://doi.org/10.1186/s13021-020-00142-7
Yamanaka T, Kaihotsu I, Oyunbaatar D, Ganbold T (2007) Summertime soil hydrological cycle and surface energy balance on the Mongolian steppe. J Arid Environ 69:65–79
Yang K, He J, Tang WJ, Qin J, Cheng CCK (2010) On downward shortwave and longwave radiations over high altitude regions: observation andmodeling in the Tibetan Plateau. Agric For Meteorol 150(1):38–46
Yao Y, Liang S, Li X et al (2017) Improving global terrestrial evapotranspiration estimation using support vector machine by integrating three process-based algorithms. Agric Forest Meteorol 242:55–74. https://doi.org/10.1016/j.agrformet.2017.04.011
Yebra M, Dijk A, Leuning R, Huete A, Guerschman J (2013) Evaluation of optical remote sensing to estimate actual evapotranspiration and canopy conductance. Remote Sens Environ 129:250–261
You G, Arain M, Wang S, Lin N, Wu D, Mckenzie S, Zou C, Liu B, Zhang X, Gao J (2019) Trends of actual and potential evapotranspiration based on Bouchet’s complementary concept in a cold and arid steppe site of Northeastern Asia. Agric Forest Meteorol 279:107684. https://doi.org/10.1016/j.agrformet.2019.107684
Zeng R, Cai X (2015) Assessing the temporal variance of evapotranspiration considering climate and catchment storage factors. Adv Water Resour 79:51–60. https://doi.org/10.1016/j.advwatres.2015.02.008
Zeng R, Cai X (2016) Climatic and terrestrial storage control on evapotranspiration temporal variability: analysis of river basins around the world. Geophys Res Lett 43:185–195. https://doi.org/10.1002/2015gl066470
Zeng S, Xia J, Du H (2014) Separating the effects of climate change and human activities on runoff over different time scales in the Zhang River basin. Stoch Environ Res Risk Assess 28:401–413. https://doi.org/10.1007/s00477-013-0760-8
Zhan J, Huang J, Zhao T, Geng X, Xiong Y (2013) Modeling the impacts of urbanization on regional climate change: a case study in the Beijing–Tianjin–Tangshan metropolitan area. Adv Meteorol 2013:1–8. https://doi.org/10.1155/2013/849479
Zhang L, Dawes WR, Walker GR (2001) Response of mean annual evapotranspiration to vegetation changes at catchment scale. Water Resour Res 37(3):701–708
Zhang D, Liu X, Liu C, Bai P (2013a) Responses of runoff to climatic variation and human activities in the Fenhe River, China. Stoch Environ Res Risk Assess 27:1293–1301
Zhang T, Stackhouse PW, Gupta SK, Cox SJ, Colleen Mikovitz J, Hinkelman LM (2013b) The validation of the GEWEX SRB surface shortwave flux data products using BSRN measurements: a systematic quality control, production and application approach. J Quant Spectrosc Radiat Transf 122:127–140. https://doi.org/10.1016/j.jqsrt.2012.10.004
Zhou Y, Li X, Yang K, Zhou J (2018) Assessing the impacts of an ecological water diversion project on water consumption through high-resolution estimations of actual evapotranspiration in the downstream regions of the Heihe River Basin, China. Agric Forest Meteorol 249:210–227. https://doi.org/10.1016/j.agrformet.2017.11.011
Zimmerman D, Pavlik C, Ruggles A, Armstrong MP (1999) An experimental comparison of ordinary and universal kriging and inverse distance weighting. Math Geol 31:375–390. https://doi.org/10.1023/a:1007586507433
Zou C, Chen B, Wang S, Guo Y, Zou B, Wu L, Gao X (2016) Observational study on complementary relationship between panevaporation and actual evapotranspiration and its variation with pan type. Agric Forest Meteorol 222:1–9. https://doi.org/10.1016/j.agrformet.2016.03.002
Zou L, Zhan C, Xia J, Wang T, Gippel C (2017) Implementation of evapotranspiration data assimilation with catchment scale distributed hydrological model via an ensemble Kalman Filter. J Hydrol 549:685–702
Zou M, Kang S, Niu J, Lu H (2019) Untangling the effects of future climate change and human activity on evapotranspiration in the Heihe agricultural region, Northwest China. J Hydrol 7:12432
Acknowledgements
We are grateful to various institutions, including the Institute of Tibetan Plateau Research, CAS, Meteorological Bureau of China and the GLEAM data sever (www.gleam.eu), for providing open access to data collections and archives. We also appreciate the editors and the reviewers for their suggestions and comments on the paper.
Funding
This study was supported by the National Natural Science Foundation of China (Grant No. 41671017) and the National Key Research and Development Programs of China (Nos. 2017YFC0504801 and 2017YFC0504306).
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
The authors declare that they have no conflicts of interest.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Wu, L., Wang, L., Li, C. et al. Separating the contributions of climate change and human activities to regional AET variability by using a developed analytical framework. Stoch Environ Res Risk Assess 34, 1831–1845 (2020). https://doi.org/10.1007/s00477-020-01876-z
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00477-020-01876-z