Integrating the Maximum Entropy Production model and airborne imagery for understorey evapotranspiration mapping

• An effective method is proposed for mapping understorey ET. • A new data-driven method for understorey temperature retrieval is tested. • Flooding alters understorey and short-vegetation ET patterns. • Understorey ET contributes 10–50% of total ecosystem ET. While extensive research has focused on evapotranspiration (ET) from land surface, the spatial distributions of ET of the woodland and forest understorey remain poorly understood. This study developed a method for estimating spatially distributed understorey ET by integrating the Maximum Entropy Production model with airborne thermal imagery. Validation against ground-truth estimation showed good model performance (R 2 = 0.93, RMSE = 0.03 mm/h), confirming its efficacy across different land cover types, including open and understorey areas. The results revealed significant spatial heterogeneity in understorey ET with varying vegetation cover and topographic attributes, and distinct responses to wetting events. This method provides a new tool for estimating the important understorey water consumption in forests and woodlands, contributing to assessing ecosystem water use efficiency and improving water resource and vegetation management strategies.

Authors

Institutions

Publication Details

Journal
Journal of Hydrology
Published
2025-03-17
DOI
https://doi.org/10.1016/j.jhydrol.2025.133076
Citations
1
Primary Topic
Plant Water Relations and Carbon Dynamics
Type
article
Field-Weighted Citation Impact
1.11
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Integrating the Maximum Entropy Production model and airborne imagery for understorey evapotranspiration mapping

Okke Batelaan, Jessica R. Thompson, Robert E. Keane, Huamán Gutiérrez et al.
1 citations
Journal of Hydrology
Plant Water Relations and Carbon Dynamics
1.11
article

Integrating the Maximum Entropy Production model and airborne imagery for understorey evapotranspiration mapping

Okke Batelaan, Jessica R. Thompson, Robert E. Keane, Huamán Gutiérrez, Huade Guan, Jianfeng Gou, Hailong Wang, David Bruce, Jingfeng Wang, Wenjie Liu, Robin Keegan-Treloar
article en
1 citations

Abstract

• An effective method is proposed for mapping understorey ET. • A new data-driven method for understorey temperature retrieval is tested. • Flooding alters understorey and short-vegetation ET patterns. • Understorey ET contributes 10–50% of total ecosystem ET. While extensive research has focused on evapotranspiration (ET) from land surface, the spatial distributions of ET of the woodland and forest understorey remain poorly understood. This study developed a method for estimating spatially distributed understorey ET by integrating the Maximum Entropy Production model with airborne thermal imagery. Validation against ground-truth estimation showed good model performance (R 2 = 0.93, RMSE = 0.03 mm/h), confirming its efficacy across different land cover types, including open and understorey areas. The results revealed significant spatial heterogeneity in understorey ET with varying vegetation cover and topographic attributes, and distinct responses to wetting events. This method provides a new tool for estimating the important understorey water consumption in forests and woodlands, contributing to assessing ecosystem water use efficiency and improving water resource and vegetation management strategies.

Journal of HydrologyVol. 657
Georgia Institute of Technology (US), Sun Yat-sen University (CN), The University of Texas at El Paso (US), National Centre for Groundwater Research and Training (AU), Murray Darling Basin Authority (AU)
Climate action
Openalex Percentile: Top 26%
Plant Water Relations and Carbon Dynamics
1.11
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.