A comparative study of crop evapotranspiration estimation in maize using empirical methods, pan evaporation and satellite-based remote sensing technique
DOI:
https://doi.org/10.14719/pst.4569Keywords:
Maize, Evapotranspiration, FAO Penman Monteith method, Thornthwaite method, NDVI method, Pan Evaporation methodAbstract
A research study was conducted at the Agricultural College and Research Institute, Coimbatore to estimate the evapotranspiration (ET) of maize crop (Zea mays) over 2 consecutive seasons in 2022-2023. Among the different methods used to estimate crop evapotranspiration, the Food and Agricultural Organization Penman-Monteith model (FAO P-M) is widely recognized as the standard approach for ET estimation. This study aimed to compare the effectiveness of three alternative methods - Thornthwaite (TW), NDVI-based and pan methods against the FAO Penman-Monteith (P-M) model in estimating maize evapotranspiration. Meteorological data were collected from the TNAU weather station spanning the period from 2022 to 2023.The performance of the estimation methods was assessed using statistical metrics such as coefficient of determination (R2), root mean squared error (RMSE), percentage error and mean bias error. The findings revealed that the NDVI-based method, relying on satellite data, provided higher accuracy in estimating maize evapotranspiration compared to the FAO PM method. Specifically, the NDVI-based method achieved the highest coefficient of determination (R2) of 0.87 and 0.89, the lowest RMSE of 12.44 mm/month and 15.5 mm/month, the lowest percentage error of 4.8 % and 9.00 % and the lowest mean bias error of 5.5 and 7.85 for the first and second seasons respectively. This study highlights the effectiveness of the NDVI-based ET estimation method for accurately assessing maize evapotranspiration. While the FAO-56 Penman-Monteith method is highly regarded for its accuracy in both theoretical and practical contexts, the comparative evaluation presented in this paper offers valuable insights for selecting alternative methods that require less data, particularly in regions with limited data availability.
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References
Blöschl G, Hall J, Viglione A, Perdigão RA, Parajka J, et al. Changing climate both increases and decreases European river floods. Nature. 2019;573(7772):108-11. https://doi.org/10.1038/s41586-019-1495-6
Mavi HS, Tupper GJ. Agrometeorology: principles and applications of climate studies in agriculture. CRC Press; 2004. https://doi.org/10.1201/9781482277999
Boyer JS. Plant productivity and environment. Science. 1982;218(4571):443-48. https://doi.org/10.1126/science.218.4571.443
Qiu R, Liu C, Cui N, Wu Y, et al. Evapotranspiration estimation using a modified Priestley-Taylor model in a rice-wheat rotation system. Agric Water Manag. 2019;224. https://doi.org/10.1016/j.agwat.2019.105755
Farzanpour H, Shiri J, Sadraddini AA, Trajkovic S. Global comparison of 20 reference evapotranspiration equations in a semi-arid region of Iran. Hydrol Res. 2019;50(1):282-00. https://doi.org/10.2166/nh.2018.174
Guo D, Westra S, Maier HR. Sensitivity of potential evapotranspiration to changes in climate variables for different Australian climatic zones. Hydrol Earth Syst Sci. 2017;21(4):2107-26. https://doi.org/10.5194/hess-21-2107-2017
Rana G, Katerji N. Measurement and estimation of actual evapotranspiration in the field under Mediterranean climate: a review. Eur J Agron. 2000;13(2-3):125-53. https://doi.org/10.1016/S1161-0301(00)00070-8
Lu Y, Ma D, Chen X, Zhang J. A simple method for estimating field crop evapotranspiration from pot experiments. Water. 2018;10(12). https://doi.org/10.3390/w10121823
Milly PC, Dunne KA. Potential evapotranspiration and continental drying. Nat Clim Chang. 2016;6(10):946-49. https://doi.org/10.1038/nclimate3046
Wang Y, Zhang Y, Yu X, Jia G, Liu Z, et al. Grassland soil moisture fluctuation and its relationship with evapotranspiration. Ecol Indic. 2021;131. https://doi.org/10.1016/j.ecolind.2021.108196
Ngongondo C, Xu C-Y, Tallaksen LM, Alemaw B. Evaluation of the FAO Penman-Monteith, Priestley-Taylor and Hargreaves models for estimating reference evapotranspiration in southern Malawi. Hydrol Res. 2013;44(4):706-22. https://doi.org/10.2166/nh.2012.224
Bai L, Cai J, Liu Y, Chen H, et al. Responses of field evapotranspiration to the changes of cropping pattern and groundwater depth in large irrigation district of Yellow River basin. Agric Water Manag. 2017;188:1-11. https://doi.org/10.1016/j.agwat.2017.03.028
Trajkovic S, Gocic M, Pongracz R, Bartholy J. Adjustment of Thornthwaite equation for estimating evapotranspiration in Vojvodina. Theor Appl Climatol. 2019;138:1231-40. https://doi.org/10.1007/s00704-019-02873-1
Ren D, Xu X, Hao Y, Huang G. Modeling and assessing field irrigation water use in a canal system of Hetao, upper Yellow River basin: Application to maize, sunflower and watermelon. J Hydrol. 2016;532:122-39. https://doi.org/10.1016/j.jhydrol.2015.11.040
Maeda EE, Wiberg DA, Pellikka PK. Estimating reference evapotranspiration using remote sensing and empirical models in a region with limited ground data availability in Kenya. Appl Geogr. 2011;31(1):251-58. https://doi.org/10.1016/j.apgeog.2010.05.011
Trivedi A, Pyasi S, Galkate R. Estimation of evapotranspiration using CROPWAT 8.0 model for Shipra River basin in Madhya Pradesh, India. Int J Curr Microbiol Appl Sci. 2018;7(5):1248-59. https://doi.org/10.20546/ijcmas.2018.705.151
?adro S, Uzunovi? M, Žurovec J, Žurovec O. Validation and calibration of various reference evapotranspiration alternative methods under the climate conditions of Bosnia and Herzegovina. Int Soil Water Conserv Res. 2017;5(4):309-24. https://doi.org/10.1016/j.iswcr.2017.07.002
Chavan M, Khodke U, Patil A. Comparison of several reference evapotranspiration methods for hot and humid regions in Maharashtra. Int J Agric Eng. 2010;2(2):259-65.
Tahashildar M, Bora PK, Ray LI, Thakuria D. Comparison of different reference evapotranspiration (ET0) models and determination of crop-coefficients of French bean (Phesiolus vulgaris) in mid hill region of Meghalaya. J Agrometeorol. 2017;19(3):233-37. https://doi.org/10.54386/jam.v19i3.645
Sentelhas PC, Gillespie TJ, Santos EA. Evaluation of FAO Penman-Monteith and alternative methods for estimating reference evapotranspiration with missing data in Southern Ontario, Canada. Agric Water Manag. 2010;97(5):635-44. https://doi.org/10.1016/j.agwat.2009.12.001
Mintz Y, Walker G. Global fields of soil moisture and land surface evapotranspiration derived from observed precipitation and surface air temperature. J Appl Meteorol Climatol. 1993;32(8):1305-34. https://doi.org/10.1175/1520-0450(1993)032<1305:GFOSMA>2.0.CO;2
Zhang K, Kimball JS, Running SW. A review of remote sensing based actual evapotranspiration estimation. Wiley Interdiscip Rev Water. 2016;3(6):834-53. https://doi.org/10.1002/wat2.1168
Xue J, Bali KM, Light S, Hessels T, Kisekka I. Evaluation of remote sensing-based evapotranspiration models against surface renewal in almonds, tomatoes and maize. Agric Water Manag. 2020;238. https://doi.org/10.1016/j.agwat.2020.106228
Olivera-Guerra L, Merlin O, Er-Raki S, Khabba S, Escorihuela MJ. 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. 2018;208:120-31. https://doi.org/10.1016/j.agwat.2018.06.014
Mahmoud SH, Gan TY. Irrigation water management in arid regions of Middle East: Assessing spatio-temporal variation of actual evapotranspiration through remote sensing techniques and meteorological data. Agric Water Manag. 2019;212:35-47. https://doi.org/10.1016/j.agwat.2018.08.040
Abdrabbo M, El Afandi G. Comparison of reference evapotranspiration equations under climate change conditions. Glob J Adv Res. 2015;2:556-68.
Escarabajal-Henarejos D, Molina-Martínez J, Fernández-Pacheco D, Cavas-Martínez F, García-Mateos G. Digital photography applied to irrigation management of Little Gem lettuce. Agric Water Manag. 2015;151:148-57. https://doi.org/10.1016/j.agwat.2014.08.009
Banik P, Tiwari N, Ranjan S. Comparative crop water assessment using CROPWAT. Int J Sustain Mater Process ECO-efficient-IJSMPE. 2014;1(3).
Allen RG, Tasumi M, Trezza R. Satellite-based energy balance for mapping evapotranspiration with internalized calibration (METRIC)-Model. J Irrig Drain Eng. 2007;133(4):380-94. https://doi.org/10.1061/(ASCE)0733-9437(2007)133:4(380)
Neale CM, Jayanthi H, Wright JL. Irrigation water management using high-resolution airborne remote sensing. Irrig Drain Syst. 2005;19:321-36. https://doi.org/10.1007/s10795-005-5195-z
Glenn EP, Neale CM, Hunsaker DJ, Nagler PL. Vegetation index-based crop coefficients to estimate evapotranspiration by remote sensing in agricultural and natural ecosystems. Hydrol Process. 2011;25(26):4050-62. https://doi.org/10.1002/hyp.8392
Romero-Trigueros C, Nortes PA, Alarcón JJ, Hunink JE, et al. Effects of saline reclaimed waters and deficit irrigation on Citrus physiology assessed by UAV remote sensing. Agric Water Manag. 2017;183:60-69. https://doi.org/10.1016/j.agwat.2016.09.014
Toureiro C, Serralheiro R, Shahidian S, Sousa A. Irrigation management with remote sensing: Evaluating irrigation requirement for maize under Mediterranean climate condition. Agric Water Manag. 2017;184:211-20. https://doi.org/10.1016/j.agwat.2016.02.010
Kullberg EG, DeJonge KC, Chávez JL. Evaluation of thermal remote sensing indices to estimate crop evapotranspiration coefficients. Agric Water Manag. 2017;179:64-73. https://doi.org/10.1016/j.agwat.2016.07.007
Niaghi AR, Majnooni-Heris A, Haghi DZ, Mahtabi G. Evaluate several potential evapotranspiration methods for regional use in Tabriz, Iran. J Appl Environ Biol Sci. 2013;3(6):31-41.
Allen RG. Crop evapotranspiration. FAO Irrigation and Drainage Paper. 1998;56:60-64.
Thornthwaite CW. An approach toward a rational classification of climate. Geogr Rev. 1948;38(1):55-94. https://doi.org/10.2307/210739
Thornthwaite CW, Mather JR. Instructions and tables for computing potential evapotranspiration and the water balance. 1957.
Brunsell NA, Gillies RR. Scale issues in land-atmosphere interactions: implications for remote sensing of the surface energy balance. Agric For Meteorol. 2003;117(3-4):203-21. https://doi.org/10.1016/S0168-1923(03)00064-9
Lang D, Zheng J, Shi J, Liao F, Ma X, Wang W, et al. A comparative study of potential evapotranspiration estimation by eight methods with FAO Penman-Monteith method in south-western China. Water. 2017;9(10):734. https://doi.org/10.3390/w9100734
Toriman ME, Mokhtar M, Gasim MB, Abdullah SMS, et al. Water resources study and modeling at North Kedah: a case of Kubang Pasu and Padang Terap water supply schemes. Res J Earth Sci. 2009;1(2):35-42.
Tukimat NNA, Harun S, Shahid S. Comparison of different methods in estimating potential evapotranspiration at Muda Irrigation Scheme of Malaysia. J Agric Rural Dev Trop Subtrop (JARTS). 2012;113(1):77-85.
Camargo A, Marin F, Sentelhas P, Picini A. Adjust of the Thornthwaite’s method to estimate the potential evapotranspiration for arid and superhumid climates, based on daily temperature amplitude. Rev Bras Agrometeorol. 1999;7(2):251-57.
Thomason WE, Phillips SB, Raymond FD. Defining useful limits for spectral reflectance measures in corn. J Plant Nutr. 2007;30(8):1263-77. https://doi.org/10.1080/01904160701555176
Kamble B, Kilic A, Hubbard K. Estimating crop coefficients using remote sensing-based vegetation index. Remote Sens. 2013;5(4):1588-602. https://doi.org/10.3390/rs5041588
Ke Y, Im J, Lee J, Gong H, Ryu Y. Characteristics of Landsat 8 OLI-derived NDVI by comparison with multiple satellite sensors and in-situ observations. Remote Sens Environ. 2015;164:298-13. https://doi.org/10.1016/j.rse.2015.04.004
Roy DP, Kovalskyy V, Zhang H, Vermote EF, et al. Characterization of Landsat-7 to Landsat-8 reflective wavelength and normalized difference vegetation index continuity. Remote Sens Environ. 2016;185:57-70. https://doi.org/10.1016/j.rse.2015.12.024
Reyes-González A, Trooien T, Kjaersgaard J, Hay C, Reta-Sánchez DG. Development of crop coefficients using remote sensing-based vegetation index and growing degree days. In: 2016 ASABE Annual International Meeting 2016. American Society of Agricultural and Biological Engineers.
Holden CE, Woodcock CE. An analysis of Landsat 7 and Landsat 8 underflight data and the implications for time series investigations. Remote Sens Environ. 2016;185:16-36. https://doi.org/10.1016/j.rse.2016.02.052
Singh RK, Irmak A. Estimation of crop coefficients using satellite remote sensing. J Irrig Drain Eng. 2009;135(5):597-08. https://doi.org/10.1061/(ASCE)IR.1943-4774.0000052
Gontia NK, Tiwari KN. Estimation of crop coefficient and evapotranspiration of wheat (Triticum aestivum) in an irrigation command using remote sensing and GIS. Water Resour Manag. 2010;24:1399-414.
Adamala S, Rajwade YA, Reddy YK. Estimation of wheat crop evapotranspiration using NDVI vegetation index. J Appl Nat Sci. 2016;8(1):159-66. https://doi.org/10.31018/jans.v8i1.767
Rossato L, Alvala RC, Ferreira NJ, Tomasella J. Evapotranspiration estimation in the Brazil using NDVI data. Remote Sensing for Agriculture, Ecosystems and Hydrology VII. 2005. https://doi.org/10.1117/12.626793
Lei H, Yang D. Combining the crop coefficient of winter wheat and summer maize with a remotely sensed vegetation index for estimating evapotranspiration in the North China plain. J Hydrol Eng. 2014;19(1):243-51. https://doi.org/10.1061/(ASCE)HE.1943-5584.0000765
Zipper SC, Loheide II SP. Using evapotranspiration to assess drought sensitivity on a subfield scale with HRMET, a high-resolution surface energy balance model. Agric For Meteorol. 2014;197:91-102. https://doi.org/10.1016/j.agrformet.2014.06.009
Senay GB, Friedrichs M, Singh RK, Velpuri NM. Evaluating Landsat 8 evapotranspiration for water use mapping in the Colorado River Basin. Remote Sens Environ. 2016;185:171-85. https://doi.org/10.1016/j.rse.2015.12.043
Li H, Jiang J, Chen B, Li Y, et al. Pattern of NDVI-based vegetation greening along an altitudinal gradient in the eastern Himalayas and its response to global warming. Environ Monit Assess. 2016;188:1-10. https://doi.org/10.1007/s10661-016-5196-4
Owusu-Sekyere JD, Ampofo EA, Asamoah O. Comparison of five different methods in estimating reference evapotranspiration in Cape Coast, Ghana. Afr J Agric Res. 2017;12(40):2976-85. https://doi.org/10.5897/AJAR2017.12594
Rao BB, Sandeep V, Chowdary PS, Pramod V, Rao V. Reference crop evapotranspiration over India: A comparison of estimates from open pan with Penman-Monteith method. J Agrometeorol. 2013;15(2):108-14. https://doi.org/10.54386/jam.v15i2.1455
Tyagi N, Sharma D, Luthra S. Determination of evapotranspiration and crop coefficients of rice and sunflower with lysimeter. Agric Water Manag. 2000;45(1):41-54. https://doi.org/10.1016/S0378-3774(99)00071-2
Lage M, Bamouh A, Karrou M, El Mourid M. Estimation of rice evapotranspiration using a microlysimeter technique and comparison with FAO Penman-Monteith and Pan evaporation methods under Moroccan conditions. Agronomie. 2003;23(7):625-31. https://dx.doi.org/10.1051/agro:2003040
Nandagiri L, Kovoor GM. Performance evaluation of reference evapotranspiration equations across a range of Indian climates. J Irrig Drain Eng. 2006;132(3):238-49. https://doi.org/10.1061/(ASCE)0733-9437(2006)132:3(238)
Chatterjee S, Stoy PC, Debnath M, Nayak AK, Swain CK, et al. Actual evapotranspiration and crop coefficients for tropical lowland rice (Oryza sativa L.) in eastern India. Theor Appl Climatol. 2021;146:155-71. https://doi.org/10.1007/s00704-021-03710-0
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