Abstract
As one of the important components of hydrological cycle, evapotranspiration spatial distribution is of great significance to regional water resources planning and rational utilization. This research used Surface Energy Balance System model to estimate the daily evapotranspiration (ET) in Beijing based on Landsat 8 observations. Results showed that the daily ET in Beijing ranged from 3.469 to 5.474 mm/day. ET is known to decrease with the increase of land surface temperature (LST) and to increase with the increase of Normalized Difference Vegetation Index (NDVI). NDVI primarily decreased from the northwest to the southeast. When the NDVI value was 0.4–0.6, the average ET peaked at 4.88 mm/day, and then slightly decreased by 3.7%. The coefficient of determination of NDVI (0.95) was much greater than that of LST (0.30) upon linear fitting, showing LST was not the main factor controlling ET in Beijing. In contrast to the linear fitting results, the spatial correlation between LST and ET is more significant than that between NDVI and ET in the global bivariate spatial analysis, where the absolute value of global bivariate Moran’s I of LST (0.51) was higher than that of NDVI (0.21) at a resolution of 150 m. And the univariate spatial autocorrelation indices of LST, ET, and NDVI equaled 0.84, 0.65, and 0.51, respectively. Furthermore, the complex spatial distribution pattern of variables could significantly affect the correlation analysis results. Local bivariate spatial analysis showed that over 60% of the Beijing area had a significant correlation, of which the negative correlation area of LST accounted for about 85%, and the positive correlation area of NDVI accounted for 74%. By improving the correlation analysis accuracy, the regional conditions for the establishment of correlation analysis results were clarified from the overall correlation analysis results.
Similar content being viewed by others
Data availability
All the data used to support the findings of this study are available from the corresponding author upon request.
References
Anselin L (1995) local indicators of spatial association - LISA. Geogr Anal 27:93–115. https://doi.org/10.1111/j.1538-4632.1995.tb00338.x
Arnault J, Wei J, Rummler T, Fersch B, Zhang Z, Jung G, Wagner S, Kunstmann H (2019) A joint Soil-Vegetation-Atmospheric water tagging procedure with WRF-Hydro: implementation and application to the case of precipitation partitioning in the upper Danube River basin. Water Resour Res 55:6217–6243. https://doi.org/10.1029/2019wr024780
Askari M, Mustafa MA, Setiawan BI, Soom MAM, Harun S, Abidin MRZ, Yusop Z (2015) A combined sensitivity analysis of seven potential evapotranspiration models. Jurnal Teknologi 76:61–68
Athira P, Nanda C, Sudheer KP (2018) A computationally efficient method for uncertainty analysis of SWAT model simulations. Stoch Env Res Risk Assess 32:1479–1492. https://doi.org/10.1007/s00477-018-1538-9
Becker R, Koppa A, Schulz S, Usman M, Beek TAD, Schueth C (2019) Spatially distributed model calibration of a highly managed hydrological system using remote sensing-derived ET data. J Hydrol 577.https://doi.org/10.1016/j.jhydrol.2019.123944
Bhattarai N, Shaw SB, Quackenbush LJ, Im J, Niraula R (2016) Evaluating five remote sensing based single-source surface energy balance models for estimating daily evapotranspiration in a humid subtropical climate. Int J Appl Earth Obs Geoinf 49:75–86. https://doi.org/10.1016/j.jag.2016.01.010
Bosquilia RWD, Neale CMU, Duarte SN, Longhi SJ, Ferraz SFD, Muller-Karger FE, McCarthy MJ (2019) Evaluation of evapotranspiration variations as a function of relief and terrain exposure through multivariate statistical analysis. Ecohydrol Hydrobiol 19:307–315. https://doi.org/10.1016/j.ecohyd.2018.11.001
Brutsaert W (1999) Aspects of bulk atmospheric boundary layer similarity under free-convective conditions. Rev Geophys 37:439–451. https://doi.org/10.1029/1999rg900013
Cheng MH, Jiao XY, Li BB, Yu X, Shao MC, Jin XL (2021) Long time series of daily evapotranspiration in China based on the SEBAL model and multisource images and validation. Earth Syst Sci Data 13(8):3995–4017. https://doi.org/10.5194/essd-13-3995-2021
Duplancic Leder T, Leder N (2018) Land surface temperature determination in the town of mostar area. Tehnicki Vjesnik-Technical Gazette 25:1219–1226. https://doi.org/10.17559/tv-20160815131129
French AN, Schmugge TJ, Kustas WP, Brubaker KL, Prueger J (2003) Surface energy fluxes over El Reno, Oklahoma, using high-resolution remotely sensed data. Water Resour Res 39.https://doi.org/10.1029/2002wr001734
Ferreira E, Mannaerts CM, Dantas AA, Maathuis BH (2016) Surface Energy Balance System (SEBS) and satellite data for monitoring water consumption of irrigated sugarcane. Engenharia Agricola 36:1176–1185. https://doi.org/10.1590/1809-4430-Eng.Agric.v36n6p1176-1185/2016
Gebru TA, Tesfahunegn GB, (2020) GIS based water balance components estimation in northern Ethiopia catchment. Soil Tillage Res 197. https://doi.org/10.1016/j.still.2019.104514
Goncharuk VV (2018) Features of water origin on the planet earth. new aproaches to the assessment of water quality. J Water Chem Technol 40:1–10. https://doi.org/10.3103/s1063455x18010010
Goswami SB, Kar SC (2018) Simulation of water cycle components in the Narmada River basin by forcing SWAT model with CFSR data. Meteorol Hydrol Water Manag-Res Operational Appl 6:13–25. https://doi.org/10.26491/mhwm/76250
Han J, Wang J, Zhao Y, Wang Q, Zhang B, Li H, Zhai J (2018) Spatio-temporal variation of potential evapotranspiration and climatic drivers in the Jing-Jin-Ji region, North China. Agric for Meteorol 256:75–83. https://doi.org/10.1016/j.agrformet.2018.03.002
Han JY, Zhao Y, Wang JH, Zhang B, Zhu YN, Jiang S, Wang LZ (2019) Effects of different land use types on potential evapotranspiration in the Beijing-Tianjin-Hebei region, North China. J Geogr Sci 29:922–934. https://doi.org/10.1007/s11442-019-1637-7
Hong B, Zhang P, Ke L (2018) Ecological risk assessment and elastic response analysis of land use change in Beijing, China. J Environ Prot Ecol 19:1026–1036
Hu B, Wang Y, Liu G (2007) Measurements and estimations of photosynthetically active radiation in Beijing. Atmos Res 85:361–371. https://doi.org/10.1016/j.atmosres.2007.02.005
Huang T, Yu D, Cao Q, Qiao J (2019) Impacts of meteorological factors and land use pattern on hydrological elements in a semi-arid basin. Sci Total Environ 690:932–943. https://doi.org/10.1016/j.scitotenv.2019.07.068
Iqbal M (1983) Introduction Solar Radiation 39:387–390
Isabelle PE, Nadeau DF, Rousseau AN, Anctil F (2018) Water budget, performance of evapotranspiration formulations, and their impact on hydrological modeling of a small boreal peatland-dominated watershed. Can J Earth Sci 55:206–220. https://doi.org/10.1139/cjes-2017-0046
Jamshidi S, Zand-parsa S, Pakparvar M, Niyogi D (2019) Evaluation of evapotranspiration over a semiarid region using multiresolution data sources. J Hydrometeorol 20:947–964. https://doi.org/10.1175/jhm-d-18-0082.1
Rahmani J, Danesh-Yazdi M, (2022) Quantifying the impacts of agricultural alteration and climate change on the water cycle dynamics in a headwater catchment of Lake Urmia Basin. Agric Water Manage 270. https://doi.org/10.1016/j.agwat.2022.107749
Li F, Sun RH, Yang LR, Chen LD (2010) Assessment of freshwater ecosystem services in Beijing based on demand and supply. Ying yong sheng tai xue bao. J Appl Ecol 21:1146–1152
Li J, Duan Z, Huang J (2018) Multi-scale fluctuation analysis of precipitation in Beijing by Extreme-point Symmetric Mode Decomposition, in: Xu Z, Peng D, Sun W, Pang B, Zuo D, Schumann A, Chen Y (Eds.), Innovative water resources management - understanding and balancing interactions between humankind and nature, pp.187–192. https://doi.org/10.5194/piahs-379-187-2018
Liu F, Qin T, Yan D, Wang Y, Dong B, Wang J, Nie H, He S, Liu S (2020) Classification of instream ecological water demand and crucial values in a semi-arid river basin. Sci Total Environ 712:136409. https://doi.org/10.1016/j.scitotenv.2019.136409
Liu SH, Su HB, Zhang RH, Tian J, Chen SH, Wang WM, Yang LJ, Hang H, Ieee (2017) A study on deriving daily evapotranspiration from remotely sensed instantaneous evapotranspiration based on the gaussian fitting method. IEEE Int Geosci Remote Sens Symp (IGARSS) pp 1923–1926
Liu XR, Shen YJ, Li HJ, Guo Y, Pei HW, Dong W (2017b) Estimation of land surface evapotranspiration over complex terrain based on multi-spectral remote sensing data. Hydrol Process 31:446–461. https://doi.org/10.1002/hyp.11042
Liu YJ, Chen J, Pan T (2019) Analysis of changes in reference evapotranspiration, pan evaporation, and actual evapotranspiration and their influencing factors in the North China plain during 1998–2005. Earth Space Sci 6:1366–1377. https://doi.org/10.1029/2019ea000626
Losgedaragh SZ, Rahimzadegan M (2018) Evaluation of SEBS, SEBAL, and METRIC models in estimation of the evaporation from the freshwater lakes (Case study: Amirkabir dam, Iran). J Hydrol 561:523–531. https://doi.org/10.1016/j.jhydrol.2018.04.025
Ma YJ, Li XY, Liu L, Huang YM, Li Z, Hu X, Wu XC, Yang XF, Wang P, Zhao SJ, Zhang GH, Liu BY (2018) Measurements and modeling of the water budget in semiarid high-altitude Qinghai Lake basin, Northeast Qinghai-Tibet Plateau. J Geophys Res-Atmos 123:10857–10871. https://doi.org/10.1029/2018jd028459
Nash MS, Wickham J, Christensen J, Wade T (2017) Changes in landscape greenness and climatic factors over 25 years (1989-2013) in the USA. Remote Sens 9.https://doi.org/10.3390/rs9030295
Ngoc Duong V, Gourbesville P (2016) Application of deterministic distributed hydrological model for large catchment: a case study at Vu Gia Thu Bon catchment Vietnam. J Hydroinform 18:885–904. https://doi.org/10.2166/hydro.2016.138
Ning JC, Gao ZQ, Xu FX (2017) Effects of land cover change on evapotranspiration in the Yellow River Delta analyzed with the SEBAL model. J Appl Remote Sens 11.https://doi.org/10.1117/1.Jrs.11.016009
Niu ZG, Wang LC, Chen XX, Yang L, Feng L (2021) Spatiotemporal distributions of pan evaporation and the influencing factors in China from 1961 to 2017. Environ Sci Pollut R 28(48):68379–68397. https://doi.org/10.1007/s11356-021-15386-0
Ouellet-Proulx S, St-Hilaire A, Boucher MA (2019) Implication of evaporative loss estimation methods in discharge and water temperature modelling in cool temperate climates. Hydrol Process 33:2867–2884. https://doi.org/10.1002/hyp.13534
Ozonoff A, Jeffery C, Manjourides J, White LF, Pagano M (2007) Effect of spatial resolution on cluster detection: a simulation study. Int J Health Geogr 6.https://doi.org/10.1186/1476-072x-6-52
Priestley CHB, Taylor RJ (1972) Assessment of surface heat-flux and evaporation using large-scale parameters. Mon Weather Rev 100:81–92. https://doi.org/10.1175/1520-0493(1972)100%3c0081:Otaosh%3e2.3.Co;2
Qin H, Lai D, Wan W, Sun Z (2018) Water demand prediction and water deficit analysis in Beijing based on system dynamics. Sci Technol Eng 18(454):180–187
Qiu H, Niu J, Hu BX (2019) Quantifying the integrated water and carbon cycle in a data-limited karst basin using a process-based hydrologic model. Environ Earth Sci 78.https://doi.org/10.1007/s12665-019-8324-y
Ramon-Reinozo M, Ballari D, Cabrera JJ, Crespo P, Carrillo-Rojas G (2019) Altitudinal and temporal evapotranspiration dynamics via remote sensing and vegetation index-based modelling over a scarce-monitored, high-altitudinal Andean paramo ecosystem of Southern Ecuador. Environ Earth Sci 78.https://doi.org/10.1007/s12665-019-8337-6
Rao PS, Isaya K (2022) Effect of aggregation and disaggregation of land surface temperature imagery on evapotranspiration estimation. Society and Environment, Remote Sensing Applications, p 27
Roser LG, Ferreyra LI, Saidman BO, Vilardi JC (2017) EcoGenetics: an R package for the management and exploratory analysis of spatial data in landscape genetics. Mol Ecol Resour 17:e241–e250. https://doi.org/10.1111/1755-0998.12697
Rwasoka DT, Gumindoga W, Gwenzi J (2011) Estimation of actual evapotranspiration using the Surface Energy Balance System (SEBS) algorithm in the Upper Manyame catchment in Zimbabwe. Phys Chem Earth 36:736–746. https://doi.org/10.1016/j.pce.2011.07.035
Samsuri SFM, Ahmad R, Zakaria MZ (2018) Comparison of evolutionary computation and empirical Penman-Monteith equation for daily and monthly reference evapotranspiration estimation in tropical region. Int J Integ Eng 10:117–129. https://doi.org/10.30880/ijie.2018.10.07.011
Shrestha P, Sulis M, Simmer C, Kollet S (2018) Effects of horizontal grid resolution on evapotranspiration partitioning using TerrSysMP. J Hydrol 557:910–915. https://doi.org/10.1016/j.jhydrol.2018.01.024
Southworth J, Bunting E, Zhu LK, Ryan SJ, Herrero HV, Waylen P, Munoz-Carpena R, Campo-Bescos MA, Kaplan D (2018) Using a coupled dynamic factor - random forest analysis (DFRFA) to reveal drivers of spatiotemporal heterogeneity in the semi-arid regions of southern Africa. PLoS One 13(12). https://doi.org/10.1371/journal.pone.0208400.
Sokal RR, Oden NL (1978) Spatial autocorrelation in biology 1. Methodology. Biol J Linnean Soc 10:199–228
Ferreira Silva CDO, Manzione RL, Albuquerque Filho JL (2019) Combining remotely sensed actual evapotranspiration and GIS analysis for groundwater level modeling. Environ Earth Sci 78.https://doi.org/10.1007/s12665-019-8467-x
Strbac O, Milanovic M, Ogrizovic V (2017) Estimation the evapotranspiration of urban parks with field based and remotely sensed datasets. Carpathian J Earth Environ Sci 12:605–616
Su Z (2002) The Surface Energy Balance System (SEBS) for estimation of turbulent heat fluxes. Hydrol Earth Syst Sci 6:85–99. https://doi.org/10.5194/hess-6-85-2002
Sun Y, Wang Y, Yang W, Sun Z, Zhao J (2019) Variation in soil hydrological properties on shady and sunny slopes in the permafrost region, Qinghai-Tibetan Plateau. Environ Earth Sci 78.https://doi.org/10.1007/s12665-019-8067-9
Unnikrishnan CK, Rajeevan M (2018) Atmospheric water budget over the South Asian summer monsoon region. Meteorol Atmos Phys 130:175–190. https://doi.org/10.1007/s00703-017-0510-4
Vanderstraeten P, Hallez S, Derouane A, Verduyn G (1988) Application of linear regressions to the comparison of analytical procedures for the determination of SO2 in ambient air. Sci Total Environ 71:201–208. https://doi.org/10.1016/0048-9697(88)90167-2
Wartenberg D (1985) Multivariate spatial correlation - a method for exploratory geographical analysis. Geogr Anal 17(4):263–283. https://doi.org/10.1111/j.1538-4632.1985.tb00849.x
Delogu E, Boulet G, Olioso A, Garrigues S, Brut A, Tallec T, Demarty J, Soudani K, Lagouarde J-P (2018) Evaluation of the SPARSE dual-source model for predicting water stress and evapotranspiration from thermal infrared data over multiple crops and climates. Remote Sens 10.https://doi.org/10.3390/rs10111806
Wang L, Wang Z, Yu J, Zhang Y, Dang S (2018) Hydrological process simulation of inland river watershed: a case study of the heihe river basin with multiple hydrological models. Water 10.https://doi.org/10.3390/w10040421
Wang LC, Kisi O, Hu B, Bilal M, Zounemat-Kermani M, Li H (2017a) Evaporation modelling using different machine learning techniques. Int J Climatol 371076-1092.https://doi.org/10.1002/joc.5064
Wang LC, Kisi O, Zounemat-Kermani M, Li H (2017b) Pan evaporation modeling using six different heuristic computing methods in different climates of China. J Hydrol 544407-427.https://doi.org/10.1016/j.jhydrol.2016.11.059
Wang WG, Li CN, Xing WQ, Fu JY (2017c) Projecting the potential evapotranspiration by coupling different formulations and input data reliabilities: the possible uncertainty source for climate change impacts on hydrological regime. J Hydrol 555:298–313. https://doi.org/10.1016/j.jhydrol.2017.10.023
Xiong M, Liu P, Cheng L, Deng C, Gui Z, Zhang X, Liu Y (2019) Identifying time-varying hydrological model parameters to improve simulation efficiency by the ensemble Kalman filter: a joint assimilation of streamflow and actual evapotranspiration. J Hydrol 568:758–768. https://doi.org/10.1016/j.jhydrol.2018.11.038
Xue R, Yang Q, Miao F, Wang X, Shen Y (2018) Slope aspect influences plant biomass, soil properties and microbial composition in alpine meadow on the Qinghai-Tibetan Plateau. J Soil Sci Plant Nutr 18:1–12
Yang QC, Almendinger JE, Zhang X, Huang M, Chen X, Leng G, Zhou Y, Zhao K, Asrar GR, Srinivasan R, Li X (2018) Enhancing SWAT simulation of forest ecosystems for water resource assessment: a case study in the St Croix river basin. Ecol Eng 120:422–431. https://doi.org/10.1016/j.ecoleng.2018.06.020
Yi Z, Zhao H, Jiang Y, Yan H, Cao Y, Huang Y, Hao Z (2018) Daily evapotranspiration estimation at the field scale: using the modified SEBS model and HJ-1 data in a desert-oasis area, Northwestern China. Water 10.https://doi.org/10.3390/w10050640
Yin J, Zhan C, Wang H, Wang F (2017) Integration of remote sensing evapotranspiration (ET) model and hydrologic model for mapping daily ET time series at river basin scale. Hydrol Res 48:311–325. https://doi.org/10.2166/nh.2016.165
Yu Z, Zhou W, Zhang X (2019) An attribution analysis of changes in potential evapotranspiration in the Beijing-Tianjin-Hebei region under climate change. J Trop Meteorol 25:82–91. https://doi.org/10.16555/j.1006-8775.2019.01.008
Zhang D, Liu X, Bai P, Li X-H (2019) Suitability of Satellite-Based Precipitation Products for Water Balance Simulations Using Multiple Observations in a Humid Catchment. Remote Sens 11.https://doi.org/10.3390/rs11020151
Zhang K, Kimball JS, Running SW (2016) A review of remote sensing based actual evapotranspiration estimation. Wiley Interdisciplinary Reviews-Water 3:834–853. https://doi.org/10.1002/wat2.1168
Zhang Y, Li L, Qin K, Wang YC, Chen LQ, Yang XY (2018a) Remote sensing estimation of urban surface evapotranspiration based on a modified Penman-Monteith model. J Appl Remote Sens 12. https://doi.org/10.1117/1.Jrs.12.046006
Zhang ZM, Zinda JA, Yang ZJ, Yin M, Ou XK, Xu Q, Yu QC (2018b) Effects of topographic attributes on landscape pattern metrics based on redundancy ordination gradient analysis. Landsc Ecol Eng 14:67–77. https://doi.org/10.1007/s11355-016-0322-6
Zhao J, Chen X, Zhang J, Zhao H, Song Y (2019) Higher temporal evapotranspiration estimation with improved SEBS model from geostationary meteorological satellite data. Sci Rep 9. https://doi.org/10.1038/s41598-019-50724-w
Zheng YQ, Li YP (2017) Research on the influencing factors and countermeasures of water shortage in Beijing, China. Tang Z, Zhao S (eds.), Proceedings of 2017 international conference on public administration (12th) & international symposium on west african studies (1st), vol I, 12th International Conference on Public Administration / 1st International Symposium on West African Studies pp 707–713
Zhou Y, Cheng S, Chen D, Lang J, Wang G, Xu T, Wang X, Yao S (2015) Temporal and spatial characteristics of ambient air quality in Beijing, China. Aerosol Air Qual Res 15:1868–1880. https://doi.org/10.4209/aaqr.2014.11.0306
Zhuo G, La B, Pubu C, Luo B (2014) Study on daily surface evapotranspiration with SEBS in Tibet Autonomous Region. J Geogr Sci 24:113–128. https://doi.org/10.1007/s11442-014-1076-4
Zou L, Xia J, She D (2018) Analysis of impacts of climate change and human activities on hydrological drought: a case study in the Wei River basin, China. Water Resour Manage 32:1421–1438. https://doi.org/10.1007/s11269-017-1877-1
Acknowledgements
The authors thank the editors and anonymous reviewers for their valuable comments and suggestions.
Funding
This study was funded by the National Key Research and Development Program of China (2017YFA0605001).
Author information
Authors and Affiliations
Contributions
LiJun Jiao: conceptualization, methodology, software, writing—original draft. Ruimin Liu: conceptualization, writing—review and editing. Lin Li: visualization, investigation. Leiping Cao: resources, investigation.
Corresponding author
Ethics declarations
Ethics approval
Not applicable.
Consent to participate
Not applicable.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Additional information
Responsible Editor: Marcus Schulz
Publisher's note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Liu, R., Jiao, L., Liu, Y. et al. Multi-scale spatial analysis of satellite-retrieved surface evapotranspiration in Beijing, a rapidly urbanizing region under continental monsoon climate. Environ Sci Pollut Res 30, 20402–20414 (2023). https://doi.org/10.1007/s11356-022-23580-x
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11356-022-23580-x