Estimation of the crop evapotranspiration for Udham Singh Nagar district using modified Priestley-Taylor model and Landsat imagery
The main challenges for utilizing daily evapotranspiration (ET) estimation in the study area revolve around the need for accurate and reliable data inputs, as well as the interpretation of ET dynamics within the context of local agricultural practices and environmental conditions. Factors such as cl...
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Published in | Scientific reports Vol. 14; no. 1; pp. 21463 - 19 |
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Main Authors | , , , , , , , , , |
Format | Journal Article |
Language | English |
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London
Nature Publishing Group UK
13.09.2024
Nature Publishing Group Nature Portfolio |
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Abstract | The main challenges for utilizing daily evapotranspiration (ET) estimation in the study area revolve around the need for accurate and reliable data inputs, as well as the interpretation of ET dynamics within the context of local agricultural practices and environmental conditions. Factors such as cloud cover, atmospheric aerosols, and variations in land cover pose challenges to the precise estimation of ET from remote sensing data. This research aimed to utilize Landsat 8 and 9 datasets from the 2022–23 period in the Udham Singh Nagar district to apply the modified Priestley-Taylor (MPT) model for estimating ET. An average ET was estimated 1.33, 1.57, 1.70, 2.99, and 3.20 mm day
−1
with 0.29, 0.33, 0.41, 0.69, and 1.03 standard deviation for December, January, February, March, and April month, respectively. In the validation phase, a strong correlation was found between the evaporative fraction derived from MPT and that observed by lysimeter, with R
2
= 0.71, mean biased error = 0.04 mm day
−1
, root mean squared error = 0.62 mm day
-1
and agreement index of 0.914. These results collectively support the effectiveness of the MPT model in accurately estimating ET across Udham Singh Nagar district. In essence, this research not only confirms the MPT model’s capability in ET estimation but also offers detailed insights into the spatial and temporal fluctuations of energy fluxes and daily ET rates. |
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AbstractList | Abstract The main challenges for utilizing daily evapotranspiration (ET) estimation in the study area revolve around the need for accurate and reliable data inputs, as well as the interpretation of ET dynamics within the context of local agricultural practices and environmental conditions. Factors such as cloud cover, atmospheric aerosols, and variations in land cover pose challenges to the precise estimation of ET from remote sensing data. This research aimed to utilize Landsat 8 and 9 datasets from the 2022–23 period in the Udham Singh Nagar district to apply the modified Priestley-Taylor (MPT) model for estimating ET. An average ET was estimated 1.33, 1.57, 1.70, 2.99, and 3.20 mm day−1 with 0.29, 0.33, 0.41, 0.69, and 1.03 standard deviation for December, January, February, March, and April month, respectively. In the validation phase, a strong correlation was found between the evaporative fraction derived from MPT and that observed by lysimeter, with R2 = 0.71, mean biased error = 0.04 mm day−1, root mean squared error = 0.62 mm day-1 and agreement index of 0.914. These results collectively support the effectiveness of the MPT model in accurately estimating ET across Udham Singh Nagar district. In essence, this research not only confirms the MPT model’s capability in ET estimation but also offers detailed insights into the spatial and temporal fluctuations of energy fluxes and daily ET rates. The main challenges for utilizing daily evapotranspiration (ET) estimation in the study area revolve around the need for accurate and reliable data inputs, as well as the interpretation of ET dynamics within the context of local agricultural practices and environmental conditions. Factors such as cloud cover, atmospheric aerosols, and variations in land cover pose challenges to the precise estimation of ET from remote sensing data. This research aimed to utilize Landsat 8 and 9 datasets from the 2022–23 period in the Udham Singh Nagar district to apply the modified Priestley-Taylor (MPT) model for estimating ET. An average ET was estimated 1.33, 1.57, 1.70, 2.99, and 3.20 mm day −1 with 0.29, 0.33, 0.41, 0.69, and 1.03 standard deviation for December, January, February, March, and April month, respectively. In the validation phase, a strong correlation was found between the evaporative fraction derived from MPT and that observed by lysimeter, with R 2 = 0.71, mean biased error = 0.04 mm day −1 , root mean squared error = 0.62 mm day -1 and agreement index of 0.914. These results collectively support the effectiveness of the MPT model in accurately estimating ET across Udham Singh Nagar district. In essence, this research not only confirms the MPT model’s capability in ET estimation but also offers detailed insights into the spatial and temporal fluctuations of energy fluxes and daily ET rates. The main challenges for utilizing daily evapotranspiration (ET) estimation in the study area revolve around the need for accurate and reliable data inputs, as well as the interpretation of ET dynamics within the context of local agricultural practices and environmental conditions. Factors such as cloud cover, atmospheric aerosols, and variations in land cover pose challenges to the precise estimation of ET from remote sensing data. This research aimed to utilize Landsat 8 and 9 datasets from the 2022-23 period in the Udham Singh Nagar district to apply the modified Priestley-Taylor (MPT) model for estimating ET. An average ET was estimated 1.33, 1.57, 1.70, 2.99, and 3.20 mm day-1 with 0.29, 0.33, 0.41, 0.69, and 1.03 standard deviation for December, January, February, March, and April month, respectively. In the validation phase, a strong correlation was found between the evaporative fraction derived from MPT and that observed by lysimeter, with R2 = 0.71, mean biased error = 0.04 mm day-1, root mean squared error = 0.62 mm day-1 and agreement index of 0.914. These results collectively support the effectiveness of the MPT model in accurately estimating ET across Udham Singh Nagar district. In essence, this research not only confirms the MPT model's capability in ET estimation but also offers detailed insights into the spatial and temporal fluctuations of energy fluxes and daily ET rates.The main challenges for utilizing daily evapotranspiration (ET) estimation in the study area revolve around the need for accurate and reliable data inputs, as well as the interpretation of ET dynamics within the context of local agricultural practices and environmental conditions. Factors such as cloud cover, atmospheric aerosols, and variations in land cover pose challenges to the precise estimation of ET from remote sensing data. This research aimed to utilize Landsat 8 and 9 datasets from the 2022-23 period in the Udham Singh Nagar district to apply the modified Priestley-Taylor (MPT) model for estimating ET. An average ET was estimated 1.33, 1.57, 1.70, 2.99, and 3.20 mm day-1 with 0.29, 0.33, 0.41, 0.69, and 1.03 standard deviation for December, January, February, March, and April month, respectively. In the validation phase, a strong correlation was found between the evaporative fraction derived from MPT and that observed by lysimeter, with R2 = 0.71, mean biased error = 0.04 mm day-1, root mean squared error = 0.62 mm day-1 and agreement index of 0.914. These results collectively support the effectiveness of the MPT model in accurately estimating ET across Udham Singh Nagar district. In essence, this research not only confirms the MPT model's capability in ET estimation but also offers detailed insights into the spatial and temporal fluctuations of energy fluxes and daily ET rates. The main challenges for utilizing daily evapotranspiration (ET) estimation in the study area revolve around the need for accurate and reliable data inputs, as well as the interpretation of ET dynamics within the context of local agricultural practices and environmental conditions. Factors such as cloud cover, atmospheric aerosols, and variations in land cover pose challenges to the precise estimation of ET from remote sensing data. This research aimed to utilize Landsat 8 and 9 datasets from the 2022–23 period in the Udham Singh Nagar district to apply the modified Priestley-Taylor (MPT) model for estimating ET. An average ET was estimated 1.33, 1.57, 1.70, 2.99, and 3.20 mm day−1 with 0.29, 0.33, 0.41, 0.69, and 1.03 standard deviation for December, January, February, March, and April month, respectively. In the validation phase, a strong correlation was found between the evaporative fraction derived from MPT and that observed by lysimeter, with R2 = 0.71, mean biased error = 0.04 mm day−1, root mean squared error = 0.62 mm day-1 and agreement index of 0.914. These results collectively support the effectiveness of the MPT model in accurately estimating ET across Udham Singh Nagar district. In essence, this research not only confirms the MPT model’s capability in ET estimation but also offers detailed insights into the spatial and temporal fluctuations of energy fluxes and daily ET rates. Abstract The main challenges for utilizing daily evapotranspiration (ET) estimation in the study area revolve around the need for accurate and reliable data inputs, as well as the interpretation of ET dynamics within the context of local agricultural practices and environmental conditions. Factors such as cloud cover, atmospheric aerosols, and variations in land cover pose challenges to the precise estimation of ET from remote sensing data. This research aimed to utilize Landsat 8 and 9 datasets from the 2022–23 period in the Udham Singh Nagar district to apply the modified Priestley-Taylor (MPT) model for estimating ET. An average ET was estimated 1.33, 1.57, 1.70, 2.99, and 3.20 mm day −1 with 0.29, 0.33, 0.41, 0.69, and 1.03 standard deviation for December, January, February, March, and April month, respectively. In the validation phase, a strong correlation was found between the evaporative fraction derived from MPT and that observed by lysimeter, with R 2 = 0.71, mean biased error = 0.04 mm day −1 , root mean squared error = 0.62 mm day -1 and agreement index of 0.914. These results collectively support the effectiveness of the MPT model in accurately estimating ET across Udham Singh Nagar district. In essence, this research not only confirms the MPT model’s capability in ET estimation but also offers detailed insights into the spatial and temporal fluctuations of energy fluxes and daily ET rates. The main challenges for utilizing daily evapotranspiration (ET) estimation in the study area revolve around the need for accurate and reliable data inputs, as well as the interpretation of ET dynamics within the context of local agricultural practices and environmental conditions. Factors such as cloud cover, atmospheric aerosols, and variations in land cover pose challenges to the precise estimation of ET from remote sensing data. This research aimed to utilize Landsat 8 and 9 datasets from the 2022-23 period in the Udham Singh Nagar district to apply the modified Priestley-Taylor (MPT) model for estimating ET. An average ET was estimated 1.33, 1.57, 1.70, 2.99, and 3.20 mm day with 0.29, 0.33, 0.41, 0.69, and 1.03 standard deviation for December, January, February, March, and April month, respectively. In the validation phase, a strong correlation was found between the evaporative fraction derived from MPT and that observed by lysimeter, with R = 0.71, mean biased error = 0.04 mm day , root mean squared error = 0.62 mm day and agreement index of 0.914. These results collectively support the effectiveness of the MPT model in accurately estimating ET across Udham Singh Nagar district. In essence, this research not only confirms the MPT model's capability in ET estimation but also offers detailed insights into the spatial and temporal fluctuations of energy fluxes and daily ET rates. |
ArticleNumber | 21463 |
Author | Satpathi, Anurag Abed, Salwan Ali Mansour, Lamjed Danodia, Abhishek Ranjan, Rajeev Vishwakarma, Dinesh Kumar Nain, Ajeet Singh Gacem, Amel Yadav, Krishna Kumar Al-Ansari, Nadhir |
Author_xml | – sequence: 1 givenname: Anurag surname: Satpathi fullname: Satpathi, Anurag organization: Department of Agrometeorology, College of Agriculture, Govind Ballabh Pant University of Agriculture and Technology – sequence: 2 givenname: Abhishek surname: Danodia fullname: Danodia, Abhishek organization: Indian Institute of Remote Sensing, Indian Space Research Organisation – sequence: 3 givenname: Salwan Ali surname: Abed fullname: Abed, Salwan Ali organization: Department of Environment, College of Science, University of Al-Qadisiyah – sequence: 4 givenname: Ajeet Singh surname: Nain fullname: Nain, Ajeet Singh organization: Department of Agrometeorology, College of Agriculture, Govind Ballabh Pant University of Agriculture and Technology – sequence: 5 givenname: Nadhir surname: Al-Ansari fullname: Al-Ansari, Nadhir email: nadhir.alansari@ltu.se organization: Department of Civil, Environmental, and Natural Resources Engineering, Lulea University of Technology – sequence: 6 givenname: Rajeev surname: Ranjan fullname: Ranjan, Rajeev organization: Department of Agrometeorology, College of Agriculture, Govind Ballabh Pant University of Agriculture and Technology – sequence: 7 givenname: Dinesh Kumar orcidid: 0000-0002-2421-6995 surname: Vishwakarma fullname: Vishwakarma, Dinesh Kumar email: dinesh.vishwakarma4820@gmail.com organization: Department of Irrigation and Drainage Engineering, Govind Ballabh Pant University of Agriculture and Technology – sequence: 8 givenname: Amel surname: Gacem fullname: Gacem, Amel organization: Department of Physics, Faculty of Sciences, University of Skikda – sequence: 9 givenname: Lamjed surname: Mansour fullname: Mansour, Lamjed organization: Department of Zoology, College of Science, King Saud University – sequence: 10 givenname: Krishna Kumar surname: Yadav fullname: Yadav, Krishna Kumar email: envirokrishna@gmail.com organization: Department of Environmental Science, Parul Institute of Applied Sciences, Parul University, Environmental and Atmospheric Sciences Research Group, Scientific Research Center, Al-Ayen University |
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Snippet | The main challenges for utilizing daily evapotranspiration (ET) estimation in the study area revolve around the need for accurate and reliable data inputs, as... Abstract The main challenges for utilizing daily evapotranspiration (ET) estimation in the study area revolve around the need for accurate and reliable data... |
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SubjectTerms | 704/106 704/172 704/242 Agricultural practices Agrometeorology Atmospheric aerosols Cloud cover Environmental conditions Evapotranspiration Geoteknik Humanities and Social Sciences Landsat Modified Priestley-Taylor Landsat multidisciplinary Remote sensing Science Science (multidisciplinary) Soil Mechanics |
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Title | Estimation of the crop evapotranspiration for Udham Singh Nagar district using modified Priestley-Taylor model and Landsat imagery |
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