Category: Ecological Research
Title: Evapotranspiration comparisons between eddy covariance measurements and meteorological and remote-sensing-based models in disturbed ponderosa pine forests
Author: Ha, W., Kolb, T.E. , Springer, A.E. , Dore, S., O’Donnell, F., Morales, R.M., * Masek Lopez, S., Koch, G.W.
Subject: Evapotranspiration, Remote Sensing, Meteorological
Abstract: Evapotranspiration (ET) comprises a major portion of the water budget in forests, yet few studies have measured or estimated ET in semi-arid, high-elevation ponderosa pine forests of the south-western USA or have investigated the capacity of models to predict ET in disturbed forests. We measured actual ET with the eddy covariance (eddy) method over 4 years in three ponderosa pine forests near Flagstaff, Arizona, that differ in disturbance history (undisturbed control, wildfire burned, and restoration thinning) and compared these measurements (415–510mmyear1 on average) with actual ET estimated from five meteorological models [Penman–Monteith (P-M), P-M with dynamic control of stomatal resistance (P-M-d), Priestley–Taylor (P-T), McNaughton–Black (M-B), and Shuttleworth–Wallace (S-W)] and from the Moderate Resolution Imaging Spectroradiometer (MODIS) ET product. The meteorological models with constant stomatal resistance (P-M, M-B, and S-W) provided the most accurate estimates of annual eddy ET (average percent differences ranged between 11 and 14%), but their accuracy varied across sites. The P-M-d consistently underpredicted ET at all sites. The more simplistic P-T model performed well at the control site (18% overprediction) but strongly overpredicted annual eddy ET at the restoration sites (92%) and underpredicted at the fire site (26%). The MODIS ET underpredicted annual eddy ET at all sites by at least 51% primarily because of underestimation of leaf area index. Overall, we conclude that with accurate parameterization, micrometeorological models can predict ET within 30% in forests of the south-western USA and that remote sensing-based ET estimates need to be improved through use of higher resolution products.
Identifier: DOI: 10.1002/eco.1586
Publisher: Wiley Online Library