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Net Radiation Drives Evapotranspiration Dynamics in a Bottomland Hardwood Forest in the Southeastern United States: Insights from Multi-modeling Approaches
Kandel, B.; Bhattacharjee, J. Net Radiation Drives Evapotranspiration Dynamics in a Bottomland Hardwood Forest in the Southeastern United States: Insights from Multi-Modeling Approaches. Atmosphere2024, 15, 527.
Kandel, B.; Bhattacharjee, J. Net Radiation Drives Evapotranspiration Dynamics in a Bottomland Hardwood Forest in the Southeastern United States: Insights from Multi-Modeling Approaches. Atmosphere 2024, 15, 527.
Kandel, B.; Bhattacharjee, J. Net Radiation Drives Evapotranspiration Dynamics in a Bottomland Hardwood Forest in the Southeastern United States: Insights from Multi-Modeling Approaches. Atmosphere2024, 15, 527.
Kandel, B.; Bhattacharjee, J. Net Radiation Drives Evapotranspiration Dynamics in a Bottomland Hardwood Forest in the Southeastern United States: Insights from Multi-Modeling Approaches. Atmosphere 2024, 15, 527.
Abstract
Evapotranspiration (ET) is a major component of water budget in Bottomland Hardwood Forests (BHF) and is driven by a complex intertwined suite of meteorological variables. The understanding of these interdependencies leading to seasonal variations in ET is crucial in better informing water resource management in the region. We used a structural equation modeling approach to analyze the drivers of ET using Eddy covariance water and heat flux data collected from a BHF, located in the Russel Sage Wildlife Management Area (RSWMA). It consists of mature closed-canopy deciduous hardwood trees with an average canopy height of 27 m. Factor analysis was used to characterize the shared variance among drivers and path analysis was used to quantify independent contributions of individual drivers. In our results, ET and net radiation (Rn) showed similar variability patterns with Vapor Pressure Deficit (VPD) and temperature in Spring, Summer, and Autumn seasons while they differ in Winter season. The path analysis shows that Rn has the strongest influence on ET variations via direct and indirect pathways. In the deciduous forests like BHFs, our results suggest ET is more energy-dependent during growing season (Spring and Summer) and early non-growing season (Autumn) while more temperature-dependent during winter season.
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