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Research Articles

Vol. 12 No. sp3 (2025): Advances in Plant Health Improvement for Sustainable Agriculture

Assessing reference evapotranspiration trends in the Amaravathi river basin

DOI
https://doi.org/10.14719/pst.8259
Submitted
14 March 2025
Published
18-06-2025

Abstract

Evapotranspiration (ET) is a key component of the hydrological cycle and climate change has impacted its patterns, potentially leading to abnormal weather conditions. This study investigates the trends in reference evapotranspiration (ET0) over the Amaravathi river basin using monthly ET0 of AgERA5 dataset from 1979 to 2022. The result revealed that the mean annual ET0 was 1909.79 mm with a low coefficient of variation (CV) of 3.14 %, indicating stability despite seasonal fluctuations. The Southwest Monsoon (SWM) accounted for the largest share (36.20 %) of annual ETo, followed by summer (30.30 %), Northeast Monsoon (NEM) (18.48 %) and winter (15.02 %). Trend analysis using the Mann-Kendall test and Sen's slope estimation showed a significant decreasing trend in annual ET0 at a rate of 2.35 mm per year (p < 0.05), suggesting a long-term decline in evapotranspiration potential. Pettitt’s test identified a significant change point in the ET0 series, with a shift around 2003, indicating a change in the climatic regime. Principal Component Analysis (PCA) further corroborated these trends, with the first principal component (PC1) explaining 63.24 % of the variance, strongly correlating with ET0, solar radiation and mean temperature. The significant drop in ET0 over the previous few decades is highlighted in this study, highlighting the necessity of adaptive water management techniques considering shifting climatic conditions.

References

  1. 1. Dai A, Zhao T, Chen J. Climate change and drought: A precipitation and evaporation perspective. Curr Clim Change Rep. 2018;4:301-12. https://doi.org/10.1007/s40641-018-0101-6
  2. 2. Katul GG, Oren R, Manzoni S, Higgins C, Parlange MB. Evapotranspiration: A process driving mass transport and energy exchange in the soil‐plant‐atmosphere‐climate system. Rev Geophys. 2012;50(3). https://doi.org/10.1029/2011RG000366
  3. 3. Goyal RK. Sensitivity of evapotranspiration to global warming: a case study of arid zone of Rajasthan (India). Agric Water Manag 2004;69:1-1. https://doi.org/10.1016/j.agwat.2004.03.014
  4. 4. Fisher JB, Melton F, Middleton E, Hain Canderson M, Allen R, et al. The future of evapotranspiration: Global requirements for ecosystem functioning, carbon and climate feedbacks, agricultural management and water resources. Water Resour Res 2017;53:2618-26. https://doi.org/10.1002/2016WR020175
  5. 5. Zhang Y, Chiew FHS, Peña‐Arancibia J, Sun F, Li H, Leuning R. Global variation of transpiration and soil evaporation and the role of their major climate drivers. J Geophys Res Atmos. 2017;122:6868-81. https://doi.org/10.1002/2017JD027025
  6. 6. Wanniarachchi S, Sarukkalige R. A review on evapotranspiration estimation in agricultural water management: Past, present and future. Hydrol. 2022;9(7):123. https://doi.org/10.3390/hydrology9070123
  7. 7. Saxena D, Choudhary M, Sharma G. Spatiotemporal trends and evapotranspiration estimation using an improvised SEBAL convergence method for the semi-arid region of Western Rajasthan, India. AQUA – Water Infrastruct Ecosyst Soc. 2024;73(3):407-23. https://doi.org/10.2166/aqua.2024.220
  8. 8. Yang Z, Zhang Q, Hao X, Yue P. Changes in evapotranspiration over global semiarid regions 1984–2013. J Geophys Res Atmos. 2019;124:2946-63. https://doi.org/10.1029/2018JD029533
  9. 9. Allen RG, Pereira LS, Raes D, Smith M. FAO Irrigation and drainage paper No. 56. Rome: Food and Agriculture Organization of the United Nations 1998;56(97):e156.
  10. 10. Elkatoury A, Alazba AA, Radwan F, Kayad A, Mossad A. Evapotranspiration estimation assessment using various satellite-based surface energy balance models in arid climates. Earth Syst Environ. 2024;8:1347-69. https://doi.org/10.1007/s41748-024-00501-1
  11. 11. Pereira LS, Allen RG, Smith M, Raes D. Crop evapotranspiration estimation with FAO56: Past and future. Agric Water Manag 2015;147:4-20. https://doi.org/https://doi.org/10.1016/j.agwat.2014.07.031
  12. 12. McVicar TR, Roderick ML, Donohue RJ, Li LT, Van Niel TG, Thomas A, et al. Global review and synthesis of trends in observed terrestrial near-surface wind speeds: Implications for evaporation. J Hydrol. 2012;416:182–205. https://doi.org/https://doi.org/10.1016/j.jhydrol.2011.10.024
  13. 13. Zhang Y, Peña-Arancibia JL, McVicar TR, Chiew FHS, Vaze J, Liu C, et al. Multi-decadal trends in global terrestrial evapotranspiration and its components. Sci Rep 2016;6:19124. https://doi.org/10.1038/srep19124
  14. 14. Wang X, Liu H, Zhang L, Zhang R. Climate change trend and its effects on reference evapotranspiration at Linhe Station, Hetao Irrigation District. Water Sci Eng. 2014;7:250-66.
  15. 15. Taichi T, Junichi Y, Chanchai S. Time-space trend analysis in pan evaporation over Kingdom of Thailand. J Hydrol Eng 2005;10:205-15. https://doi.org/10.1061/(ASCE)1084-0699(2005)10:3(205)
  16. 16. da Silva V de PR. On climate variability in Northeast of Brazil. J Arid Environ 2004;58:575-96. https://doi.org/10.1016/j.jaridenv.2003.12.002
  17. 17. Asanuma J, Kamimera H. Long-term trends of the pan evaporation as an index of the global hydrological change. In: Proceedings of International Symposium on Disaster Mitigation and Basin-Wide Water Management; UNESCO, Niigata, Japan; 2003.
  18. 18. Roderick ML, Farquhar GD. Changes in New Zealand pan evaporation since the 1970s. Int J Climatol. 2005;25:2031–9. https://doi.org/10.1002/joc.1262
  19. 19. Vicente‐Serrano SM, Azorin‐Molina C, Sanchez‐Lorenzo A, Revuelto J, Morán‐Tejeda E, López‐Moreno JI, et al. Sensitivity of reference evapotranspiration to changes in meteorological parameters in S pain (1961–2011). Water Resour Res 2014;50:8458-80. https://doi.org/10.1002/2014WR015427
  20. 20. Feng G, Cobb S, Abdo Z, Fisher DK, Ouyang Y, Adeli A, et al. Trend analysis and forecast of precipitation, reference evapotranspirationand rainfall deficit in the blackland prairie of Eastern Mississippi. J Appl Meteorol Climatol. 2016;55:1425–39. https://doi.org/10.1175/JAMC-D-15-0265.1
  21. 21. Wang M, Liu C, Qiu R, Zhang P, Zhang F. Temporal and spatial variations of reference crop evapotranspiration and its influencing factors in Jiangsu province. J. Irrig Drain. 2020;39(4):124-34.
  22. 22. Rajavel M, Vengateswari M, Geethalakshmi V, Bhuvaneswari K, Vakeswaran V, Gowtham R, et al. Effect of ENSO on seasonal temperature over Tamil Nadu. Int J Environ Clim Change. 2022:12(10):1210-21. https://doi.org/10.9734/ijecc/2022/v12i1030918
  23. 23. Goroshi S, Pradhan R, Singh RP, Singh KK, Parihar JS. Trend analysis of evapotranspiration over India: Observed from long-term satellite measurements. J Earth Syst Sci. 2017;126:1-21. https://doi.org/10.1007/s12040-017-0891-2
  24. 24. Madhu S, Kumar TL, Barbosa H, Rao KK, Bhaskar VV. Trend analysis of evapotranspiration and its response to droughts over India. Theor Appl Climatol. 2015;121:41-51. https://doi.org/10.1007/s00704-014-1210-3
  25. 25. Pavithran P, Pazhanivelan S, Sivamurugan A, Ragunath K, Selvakumar S, Vanitha K, et al. Long-term analysis of reference evapotranspiration variations in the lower Bhavani basin. Plant Sci Today. 2024;11(4):1125-35. https://doi.org/10.14719/pst.5119
  26. 26. Zhao Z, Wang H, Wang C, Li W, Chen H, Deng C. Changes in reference evapotranspiration over Northwest China from 1957 to 2018: Variation characteristics, cause analysis and relationships with atmospheric circulation. Agric Water Manag. 2020;231:105958. https://doi.org/10.1016/j.agwat.2019.105958
  27. 27. Garcia-Prats A, Carricondo-Anton JM, Ippolito M, De Caro D, Jiménez-Bello MA, Manzano-Juárez J, et al. High-resolution spatially nterpolated Fao Penman-Monteith crop reference evapotranspiration maps using Agera5 and Era5-Land reanalysis datasets. SSRN. 2024. https://dx.doi.org/10.2139/ssrn.5065028
  28. 28. Jaagus J. Climatic changes in Estonia during the second half of the 20th century in relationship with changes in large-scale atmospheric circulation. Theor Appl Climatol 2006;83:77-88. https://doi.org/10.1007/s00704-005-0161-0
  29. 29. Libiseller C, Grimvall A. Performance of partial Mann–Kendall tests for trend detection in the presence of covariates. Environmetrics: The Official Journal of the International Environmetrics Society 2002;13:71-84. https://doi.org/10.1002/env.507
  30. 30. Sen PK. Estimates of the regression coefficient based on Kendall’s tau. J Am Stat Assoc 1968;63:1379–89. https://doi.org/10.1080/01621459.1968.10480934
  31. 31. Pettitt AN. A non‐parametric approach to the change‐point problem. Journal of the Royal Statistical Society: Series C (Applied Statistics). 1979;28(2):126-35. https://doi.org/10.2307/2346729
  32. 32. Kendall MG. Rank Correlation Methods. New York; 1975
  33. 33. Abdi H, Williams LJ. Principal component analysis. Wiley interdisciplinary reviews: computational statistics. 2010;2(4):433-59. https://doi.org/10.1002/wics.101

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