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 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<sup>-1</sup> 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<sup>2</sup> = 0.71, mean biased error = 0.04 mm day<sup>-1</sup>, root mean squared error = 0.62 mm day<sup>-1</sup> 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.

Authors

Institutions

Publication Details

Journal
Scientific Reports
Published
2024-09-13
DOI
https://doi.org/10.1038/s41598-024-72299-x
Citations
7
Primary Topic
Plant Water Relations and Carbon Dynamics
Type
article
Field-Weighted Citation Impact
1.98

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Estimation of the crop evapotranspiration for Udham Singh Nagar district using modified Priestley-Taylor model and Landsat imagery

Salwan Ali Abed, Krishna Kumar Yadav, Abhishek Danodia, Amel Gacem et al.
7 citations
Scientific Reports
Plant Water Relations and Carbon Dynamics
1.98
article

Estimation of the crop evapotranspiration for Udham Singh Nagar district using modified Priestley-Taylor model and Landsat imagery

Salwan Ali Abed, Krishna Kumar Yadav, Abhishek Danodia, Amel Gacem, Rajeev Ranjan, Anurag Satpathi, Dinesh Kumar Vishwakarma, Nadhir Al‐Ansari, Ajeet Singh Nain, Lamjed Mansour
article en
7 citations

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<sup>-1</sup> 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<sup>2</sup> = 0.71, mean biased error = 0.04 mm day<sup>-1</sup>, root mean squared error = 0.62 mm day<sup>-1</sup> 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.

Scientific ReportsVol. 14(1)
Luleå University of Technology (SE), Thi Qar University (IQ), Govind Ballabh Pant University of Agriculture and Technology (IN), King Saud University (SA), Parul University (IN), University of Al-Qadisiyah (IQ), Indian Institute of Remote Sensing (IN), University of Skikda (DZ)
King Saud University, Govind Ballabh Pant University of Agriculture and Technology, U.S. Geological Survey
Zero hunger
Openalex Percentile: Top 14%
Plant Water Relations and Carbon Dynamics
1.98
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.