This is an outdated version published on 09-10-2024. Read the most recent version.
Forthcoming

Computation of evapotranspiration using crop simulation models and comparison with leaf area index from multiple sources

Authors

  • Sabthapathy M Department of Remote Sensing and GIS, Tamil Nadu Agricultural University, Coimbatore - 641 003, Tamil Nadu, India
  • Ragunath KP Centre for Water and Geospatial Studies, Tamil Nadu Agricultural University, Coimbatore - 641 003, Tamil Nadu, India https://orcid.org/0000-0002-7851-4437
  • Pazhanivelan S Centre for Water and Geospatial Studies, Tamil Nadu Agricultural University, Coimbatore - 641 003, Tamil Nadu, India https://orcid.org/0000-0002-3596-3232
  • Selvakumar S Centre for Water and Geospatial Studies, Tamil Nadu Agricultural University, Coimbatore - 641 003, Tamil Nadu, India
  • Sivamurugan AP Centre for Water and Geospatial Studies, Tamil Nadu Agricultural University, Coimbatore - 641 003, Tamil Nadu, India https://orcid.org/0009-0007-2182-573X
  • Kumaraperumal R Department of Remote Sensing and GIS, Tamil Nadu Agricultural University, Coimbatore - 641 003, Tamil Nadu, India https://orcid.org/0000-0001-6659-9587
  • Mohammed Ahamed J RRSC-South, National Remote Sensing Centre, Indian Space Research Organization, Bengaluru - 560 017, Karnataka, India https://orcid.org/0000-0002-5677-182X
  • Chandrasekar K National Remote Sensing Centre, Indian Space Research Organization, Hyderabad - 500 037, Telangana, India https://orcid.org/0000-0001-7221-4671
  • Thiruvarassan S Oilseeds Research Station, Tamil Nadu Agricultural University, Tindivanam - 604 002, Tamil Nadu, India https://orcid.org/0000-0001-5047-1482

DOI:

https://doi.org/10.14719/pst.4444

Keywords:

Evapotranspiration, Leaf Area Index, Plant Canopy Analyser, Crop coefficient (Kc) values

Abstract

The study demonstrated the computation of evapotranspiration (ET) in cultivation of groundnut (Arachis hypogaea) through the application of crop simulation models, alongside a comparative analysis with leaf area index (LAI) from various sources. The cultivation period for groundnut was conducted during the calendar year 2023, during which 2 distinct growth patterns were noted, attributed to variations in environmental conditions. The study analyses the estimated evapotranspiration from AquaCrop model, utilizing crop coefficient (Kc) values in comparison with evapotranspiration data derived from satellite observations provided by the MOD16A2v061 product. Furthermore, LAI was measured through 3 methodologies: an empirical equation based on field data, the Li-Cor 2200 plant canopy analyzer and LAI calculations derived from cloud-free normalized difference vegetation index (NDVI). LAI obtained from Li-Cor 2200 instrument exhibited a higher degree of consistency in correlation with empirical LAI derived from ground observations. Conversely, LAI values calculated using the normalized difference vegetation index (NDVI) demonstrated a greater degree of variability, especially during times of cloud cover. The study emphasizes the relationship between LAI and ET and magnitude of LAI in amount of total evapotranspiration.

Downloads

Download data is not yet available.

References

Kamasani CR, Jyothy S, Mallikarjuna P. Evaluation of evapotranspiration estimation methods and development of crop coefficients for groundnut crop. IOSR Journal of Engineering. 2012;2:35-42. https://doi.org/10.9790/3021-02633542

Volk JM, Huntington JL, Melton FS, Allen R, Anderson M, Fisher JB, et al. Assessing the accuracy of OpenET satellite-based evapotranspiration data to support water resource and land management applications. Nature Water. 2024;2(2):193-205. https://doi.org/10.1038/s44221-023-00181-7

Aswini G, Arulbalachandran D, Latha S. Effect of gamma irradiation on quantitative traits and post harvesting analysis of groundnut (Arachis hypogaea L.) seed in M1 generation. Plant Science Today. 2022;9(4):1074-84. https://doi.org/10.14719/pst.1785

Lissy Vargheese R, Saravanan S, Hepziba SJ, Prem Kumari SM, et al. Genetic variability, correlation and path analysis in the BC2F2 population of groundnut. Plant Science Today. 2024;11(2). https://doi.org/10.14719/pst.3282

Lima GC, Martins MQ, Coelho RI. Response of oranje Natal Folha Murcha (Citrus sinensis (L.) Osbeck) at different levels of irrigation. Plant Science Today. 2015;2(2):74-76. https://doi.org/10.14719/pst.2015.2.2.111

Parmar HV, Gontia NK. Estimation of crop coefficients by remote sensing based vegetation index. Journal of Agricultural Engineering (India). 2024;53:28-33. https://doi.org/10.52151/jae2016533.1608

Jia Q, Wang Y-P. Relationships between leaf area index and evapotranspiration and crop coefficient of hilly apple orchard in the loess plateau. Water. 2021;13(14):1957. https://doi.org/10.3390/w13141957

Faisol A, Novita E, editors. An evaluation of MODIS global evapotranspiration product (MOD16A2) as terrestrial evapotranspiration in East Java-Indonesia. IOP Conference Series: Earth and Environmental Science; 2020: IOP Publishing. https://doi.org/10.1088/1755-1315/485/1/012002

Shekar NS, Hemalatha H. Performance comparison of Penman-Monteith and Priestley-Taylor models using MOD16A2 remote sensing product. Pure and Applied Geophysics. 2021;178(8):3153-67. https://doi.org/10.1007/s00024-021-02780-5

Kommagoni R, Devi KB, Vani K, Sailaja V. Evapotranspiration, yield attributes and growth parameters influenced by organic nutrient management of groundnut. 2018;7.

Ibrahim II, Umar U, Abubakar A. Growth and yield attributes of groundnut (Arachis hypogea) as influenced by population density and phosphorous fertilizer rates on the Jos Plateau. Journal of Environmental Bioremediation and Toxicology. 2021;4(1):19-23. https://doi.org/10.54987/jebat.v4i1.580

Farooq T, Yan W, Chen X, Shakoor A, Rashid M, Gilani M, et al. Dynamics of canopy development of Cunninghamia lanceolata mid-age plantation in relation to foliar nitrogen and soil quality influenced by stand density. Global Ecology and Conservation. 2020. https://doi.org/10.1016/j.gecco.2020.e01209

Geng J, Yuan G, Chen JM, Lyu C, Tu L, Fan W, et al. Error analysis of LAI measurements with LAI-2000 due to discrete view angular range angles for continuous canopies. Remote Sensing. 2021;13(7):1405. https://doi.org/10.3390/rs13071405

Andalibi L, Ghorbani A, Moameri M, Hazbavi Z, Nothdurft A, Jafari R, et al. Leaf area index variations in ecoregions of Ardabil province, Iran. Remote Sensing. 2021;13(15):2879. https://doi.org/10.3390/rs13152879

Wu H, Yue Q, Guo P, Xu X, Huang X. Improving the AquaCrop model to achieve direct simulation of evapotranspiration under nitrogen stress and joint simulation-optimization of irrigation and fertilizer schedules. Agricultural Water Management. 2022. https://doi.org/10.1016/j.agwat.2022.107599

Ramos TB, Darouich H, Pereira LS. Mulching effects on soil evaporation, crop evapotranspiration and crop coefficients: a review aimed at improved irrigation management. Irrigation Science. 2024;42(3):525-39. https://doi.org/10.1007/s00271-024-00924-8

Xiang K, Li Y, Horton R, Feng H. Similarity and difference of potential evapotranspiration and reference crop evapotranspiration - a review. Agricultural Water Management. 2020. https://doi.org/10.1016/j.agwat.2020.106043

Sood V, Patil D. Development of improved crop coefficients for precise estimates of groundnut evapotranspiration. 2015;8:6084-87.

Pereira LS, Allen RG, Smith M, Raes D. Crop evapotranspiration estimation with FAO56: Past and future. Agricultural Water Management. 2015;147:4-20. https://doi.org/10.1016/j.agwat.2014.07.031

Chen H, Zhu G, Zhang K, Bi J, Jia X, Ding B, et al. Evaluation of evapotranspiration models using different LAI and meteorological forcing data from 1982 to 2017. Remote Sensing. 2020;12(15):2473. https://doi.org/10.3390/rs12152473

Yu Z, Chen J, Chen J, Zhan W, Wang C, Ma W, et al. Enhanced observations from an optimized soil-canopy-photosynthesis and energy flux model revealed evapotranspiration-shading cooling dynamics of urban vegetation during extreme heat. Remote Sensing of Environment. 2024;305:114098. https://doi.org/10.1016/j.rse.2024.114098

Kala J, Decker M, Exbrayat J-F, Pitman AJ, Carouge C, Evans JP, et al. Influence of leaf area index prescriptions on simulations of heat, moisture and carbon fluxes. Journal of Hydrometeorology. 2014;15(1):489-503. https://doi.org/10.1175/JHM-D-13-063.1

Hemalatha S, Velchala P, Reddy BN. Groundnut, Arachis hypogaea growth and yield as influenced by evapotranspiration deficits. 2021.

Arulkar KP, Deogirikar AA, Kondey NM, Joshi PS. Estimation of crop evapotranspiration for groundnut (Kharif) in Chandrapur district. Agricultural Science Digest. 2008;28(1):67-68.

Published

09-10-2024

Versions

How to Cite

1.
M S, Ragunath KP, Pazhanivelan S, Selvakumar S, Sivamurugan AP, Kumaraperumal R, Mohammed Ahamed J, Chandrasekar K, Thiruvarassan S. Computation of evapotranspiration using crop simulation models and comparison with leaf area index from multiple sources. Plant Sci. Today [Internet]. 2024 Oct. 9 [cited 2024 Nov. 23];. Available from: https://horizonepublishing.com/journals/index.php/PST/article/view/4444

Issue

Section

Research Articles