Abstract
Mapping of spatiotemporal distribution of evapotranspiration becomes important for sustainable water management as water scarcity is nowadays a growing concern in almost all the continents. In general, researchers estimate evapotranspiration by multiplying the computed reference evapotranspiration (ETo) with the corresponding crop coefficient. Such estimation of ETo requires data related to spatiotemporal meteorological and vegetation field characteristics, and however, these data are rarely available in most developing countries such as India. Thus, researchers constantly develop various methods and evaluate the applicability of these methods to accurately capture spatiotemporal distribution. The purposes of this study are to (a) examine the applicability of Hargreaves and MODIS ETo method to map the spatiotemporal distribution over Thamirabarani basin located in Southern India and (b) evaluate the performances of Hargreaves and MODIS ETo methods and compare it to FAO 56 Penman–Monteith method. To achieve these purposes, ETo data of Hargreaves method and MODIS ETo method over Cheranmadevi meteorological observatory are extracted and performances of these methods are compared with FAO 56 Penman–Monteith method. Results show that a match exists among all the three ETo datasets, and no major deviations have been observed. However, this study suggests local calibration of Hargreaves and MODIS ETo method as considerable mismatch has been observed at ETo daily value. Overall, the conclusion of this study encourages the application of the Hargreaves method and MODIS ETo method in developing countries, where the data shortage condition prevails.
![](http://media.springernature.com/m312/springer-static/image/art%3A10.1007%2Fs12517-022-10019-3/MediaObjects/12517_2022_10019_Fig1_HTML.png)
![](http://media.springernature.com/m312/springer-static/image/art%3A10.1007%2Fs12517-022-10019-3/MediaObjects/12517_2022_10019_Fig2_HTML.png)
![](http://media.springernature.com/m312/springer-static/image/art%3A10.1007%2Fs12517-022-10019-3/MediaObjects/12517_2022_10019_Fig3_HTML.png)
![](http://media.springernature.com/m312/springer-static/image/art%3A10.1007%2Fs12517-022-10019-3/MediaObjects/12517_2022_10019_Fig4_HTML.png)
![](http://media.springernature.com/m312/springer-static/image/art%3A10.1007%2Fs12517-022-10019-3/MediaObjects/12517_2022_10019_Fig5_HTML.png)
![](http://media.springernature.com/m312/springer-static/image/art%3A10.1007%2Fs12517-022-10019-3/MediaObjects/12517_2022_10019_Fig6_HTML.png)
![](http://media.springernature.com/m312/springer-static/image/art%3A10.1007%2Fs12517-022-10019-3/MediaObjects/12517_2022_10019_Fig7_HTML.png)
![](http://media.springernature.com/m312/springer-static/image/art%3A10.1007%2Fs12517-022-10019-3/MediaObjects/12517_2022_10019_Fig8_HTML.png)
Similar content being viewed by others
References
Abdi H (2007) Multiple correlation coefficient. In: Salkind NJ (ed) Encyclopedia of measurement and statistics, pp 648–651
Allen RG, Pereira LS, Raes D, Smith M (1998) Crop evapotranspiration-guidelines for computing crop water requirements-FAO Irrigation and drainage paper 56. Fao, Rome, 300(9), p D05109. http://www.fao.org/docrep/X0490E/x0490e00.htm
Almorox J, Quej VH, Martí P (2015) Global performance ranking of temperature-based approaches for evapotranspiration estimation considering Köppen climate classes. J Hydrol 528:514–522. https://doi.org/10.1016/j.jhydrol.2015.06.057
Almorox J, Senatore A, Quej VH et al (2018) Worldwide assessment of the Penman-Monteith temperature approach for the estimation of monthly reference evapotranspiration. Theor Appl Climatol 131(1–2):693–703. https://doi.org/10.1007/s00704-016-1996-2
Bchir A, M’nassri S, Dhib S et al (2021) Estimating and mapping evapotranspiration in olive groves of semi-arid Tunisia using empirical formulas and satellite remote sensing. Arab J Geosci 4:2717. https://doi.org/10.1007/s12517-021-08860-z
Dadashi-Roudbari A, Ahmadi M (2020) Evaluating temporal and spatial variability and trend of aerosol optical depth (550 nm) over Iran using data from MODIS on board the Terra and Aqua satellites. Arab J Geosci 13:277. https://doi.org/10.1007/s12517-020-5232-0
Droogers P, Allen RG (2002) Estimating reference evapotranspiration under inaccurate data conditions. J Irrig Drain Sys 16:33–45. https://doi.org/10.1023/A:1015508322413
Gavilán P, Lorite IJ, Tornero S, Berengena J (2006) Regional calibration of Hargreaves equation for estimating reference ET in a semiarid environment. Agric Water Manag 81(3):257–281. https://doi.org/10.1016/j.agwat.2005.05.001
Goparaju L, Ahmad F (2019) Analysis of seasonal precipitation, potential evapotranspiration, aridity, future precipitation anomaly and major crops at district level of India. KN - J Cartograph Geograph Inf 69:143–154. https://doi.org/10.1007/s42489-019-00020-4
Gosain AK, Rao S, Arora A (2011) Climate change impact assessment of water resources of India. Curr Sci101(3):356–371. https://www.jstor.org/stable/24078515
Hargreaves GH, Samani ZA (1985) Reference crop evapotranspiration from temperature. Appl Eng Agric 1(2):96–99. https://doi.org/10.13031/2013.26773
Hargreaves GL, Hargreaves GH, Riley JP (1985) Irrigation water requirements for Senegal River Basin. J Irrig Drain Sys 111:3(265).https://doi.org/10.1061/(ASCE)0733-9437
Horan R, Gowri R, Wable PS et al (2021) A comparative assessment of hydrological models in the Upper Cauvery catchment. Water 13(2):151. https://doi.org/10.3390/w13020151
Khan MS, Liaqat UW, Baik J, Choi M (2018) Stand-alone uncertainty characterization of GLEAM, GLDAS and MOD16 evapotranspiration products using an extended triple collocation approach. Agric for Meteorol 252:256–268. https://doi.org/10.1016/j.agrformet.2018.01.022
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 9(10):734. https://doi.org/10.3390/w9100734
Masuoka E, Roy D, Wolfe R (2011) MODIS Land data products: generation, quality assurance and validation, In: Ramachandran, B, Justice, C, Abrams, M. (eds.), Land remote sensing and global environmental change. Springer; New York, pp 509–31. https://doi.org/10.1007/978-1-4419-6749-7_22
Mendicino G, Senatore A (2013) Regionalization of the Hargreaves coefficient for the assessment of distributed reference evapotranspiration in Southern Italy. J Irrig Drain Sys 139(5):349–362. https://doi.org/10.1061/(ASCE)IR.1943-4774.0000547
Mu Q, Heinsch FA, Zhao M, Running SW (2007) Development of a global evapotranspiration algorithm based on MODIS and global meteorology data. Rem Sens Environ 111:519–536. https://doi.org/10.1016/j.rse.2007.04.015
Mu Q, Zhao M, Running SW (2011) Improvements to a MODIS global terrestrial evapotranspiration algorithm. Remote Sens Environ 115(8):1781–1800. https://doi.org/10.1016/j.rse.2011.02.019
Nageswararao MM, Sannan MC, Mohanty UC (2019) Characteristics of various rainfall events over South Peninsular India during Northeast Monsoon using high-resolution gridded dataset. Theor Appl Climatol 137(3–4):2573–2593. https://doi.org/10.1007/s00704-018-02755-y
Najarzadeh D (2020) Conservative confidence intervals on multiple correlation coefficient for high-dimensional elliptical data using random projection methodology. J Appl Stat 1-22.https://doi.org/10.1080/02664763.2020.1796937
Pandi D, Kothadaramanan S, Kuppusamy M (2021) Hydrological models: a review. Int J Hydrol Sci Technol 12(3):223–242. https://doi.org/10.1504/IJHST.2021.117540
Pandi D, Kothandaraman S, Kuppusamy M (2017) Identifying runoff harvesting sites over the Pennar Basin, Andhra Pradesh using SCS-CN method. Int J Civ Eng 8:65–73
Pandi D, Kothandaraman S, Kuppusamy M (2020) Delineation of potential groundwater zones based on multicriteria decision making technique. J Groundw Sci Eng 8(2):180–194. https://doi.org/10.19637/j.cnki.2305-7068.2020.02.009
Paredes P, Pereira LS, Almorox J et al (2020) Reference grass evapotranspiration with reduced data sets: parameterization of the FAO Penman-Monteith temperature approach and the Hargeaves-Samani equation using local climatic variables. Agric Water Manag 240:106210. https://doi.org/10.1016/j.agwat.2020.106210
Raoufi R, Beighley E (2017) Estimating daily global evapotranspiration using Penman-Monteith equation and remotely sensed land surface temperature. Remote Sens 9(11):1138. https://doi.org/10.3390/rs9111138
Zhao SH, Yang YH, Zhang F et al (2015) Rapid evaluation of reference evapotranspiration in Northern China. Arab J Geosci 8(2):647–657. https://doi.org/10.1007/s12517-013-1263-0
Acknowledgements
The authors thank School of Civil Engineering, Vellore Institute of Technology, Chennai, Tamil Nadu, India, for providing infrastructure support to complete this research study. We are thankful to NASA Earth Observing System MODIS project for making USGS Earth explorer website freely accessible for researchers. The authors also thank anonymous reviewers for their suggestions to improve this manuscript.
Author information
Authors and Affiliations
Contributions
Dinagarapandi Pandi is mainly responsible for modelling, image processing, and writing the first draft of manuscript. Kothadaramanan Saravanan provided theoretical guidance and technical support. Mohan Kuppusamy extended his support for data collection and supervised the findings of this work. M. Birasnav provided constructive comments to improve the manuscript and editorial comments on the final draft report. All authors have read and approved the final manuscript.
We declare and approve that this manuscript has not been previously published and is not under consideration for publication in any journals. All authors have contributed sufficiently to this manuscript to be listed as authors.
Corresponding author
Ethics declarations
Competing interests
The authors declare no competing interests.
Additional information
Responsible Editor: Broder J. Merkel
Rights and permissions
About this article
Cite this article
Pandi, D., Saravanan, K., Kuppusamy, M. et al. Performance evaluation of geospatially assisted reference evapotranspiration models. Arab J Geosci 15, 787 (2022). https://doi.org/10.1007/s12517-022-10019-3
Received:
Accepted:
Published:
DOI: https://doi.org/10.1007/s12517-022-10019-3