Can weighing lysimeter ET represent surrounding field ET well enough to test flux station measurements of daily and sub-daily ET?

Evett, Steven R.; Schwartz, Robert C.; Howell, Terry A.; Baumhardt, R. Louis; Copeland, Karen S.

doi:10.1016/j.advwatres.2012.07.023

Cited by 137 publications

(122 citation statements)

References 21 publications

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“…Voltage outputs from load cells (SM-50, Interface, Inc., Scottsdale, Ariz.) with 22 kg full-range capacity were measured and recorded by data loggers (CR-7X, Campbell Scientific, Logan, Utah) at 0.5 Hz (2 s) frequency. The lysimeter's accuracy has ranged from 0.05 mm [22,23] to 0.01 mm. Experienced support technicians and scientists were responsible for routine lysimeter maintenance and ensuring representativeness of the surrounding field.…”

Section: Lysimeter Lai and Crop Yield Data Collection And Analysismentioning

confidence: 99%

Assessing the Efficacy of the SWAT Auto-Irrigation Function to Simulate Irrigation, Evapotranspiration, and Crop Response to Management Strategies of the Texas High Plains

Chen

Marek

Marek³

et al. 2017

Water

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Abstract:In the semi-arid Texas High Plains, the underlying Ogallala Aquifer is experiencing continuing decline due to long-term pumping for irrigation with limited recharge. Accurate simulation of irrigation and other associated water balance components are critical for meaningful evaluation of the effects of irrigation management strategies. Modelers often employ auto-irrigation functions within models such as the Soil and Water Assessment Tool (SWAT). However, some studies have raised concerns as to whether the function is able to adequately simulate representative irrigation practices. In this study, observations of climate, irrigation, evapotranspiration (ET), leaf area index (LAI), and crop yield derived from an irrigated lysimeter field at the USDA-ARS Conservation and Production Research Laboratory at Bushland, Texas were used to evaluate the efficacy of the SWAT auto-irrigation functions. Results indicated good agreement between simulated and observed daily ET during both model calibration (2001-2005) and validation (2006-2010) periods for the baseline scenario (Nash-Sutcliffe efficiency; NSE ≥ 0.80). The auto-irrigation scenarios resulted in reasonable ET simulations under all the thresholds of soil water deficit (SWD) triggers as indicated by NSE values > 0.5. However, the auto-irrigation function did not adequately represent field practices, due to the continuation of irrigation after crop maturity and excessive irrigation when SWD triggers were less than the static irrigation amount.

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Section: Lysimeter Lai and Crop Yield Data Collection And Analysismentioning

confidence: 99%

Assessing the Efficacy of the SWAT Auto-Irrigation Function to Simulate Irrigation, Evapotranspiration, and Crop Response to Management Strategies of the Texas High Plains

Chen

Marek

Marek³

et al. 2017

Water

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“…In the center of each field was a large weighing lysimeter (nominally 3 Â 3 Â 2.4-m deep). Details of the monolithic weighing lysimeters are given by Marek et al [28], and a discussion of the measurements and procedures used to upscale the lysimeter (LY) measurements to reflect average field conditions is given by Evett et al [29]. Since the LY sites only measure LE, H was computed by residual using locally measured R N -G.…”

Section: Datamentioning

confidence: 99%

Evaluating the two-source energy balance model using local thermal and surface flux observations in a strongly advective irrigated agricultural area

Kustas

Alfieri

Anderson

et al. 2012

Advances in Water Resources

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Evett, Steven R.; Neale, Christopher M. U.; French, Andrew N.; Hipps, Lawrence E.; Chávez, José L.; Copeland, Karen S.; and Howell, Terry A., "Evaluating the two-source energy balance model using local thermal and surface flux observations in a strongly advective irrigated agricultural area" (2012 a b s t r a c tApplication and validation of many thermal remote sensing-based energy balance models involve the use of local meteorological inputs of incoming solar radiation, wind speed and air temperature as well as accurate land surface temperature (LST), vegetation cover and surface flux measurements. For operational applications at large scales, such local information is not routinely available. In addition, the uncertainty in LST estimates can be several degrees due to sensor calibration issues, atmospheric effects and spatial variations in surface emissivity. Time differencing techniques using multi-temporal thermal remote sensing observations have been developed to reduce errors associated with deriving the surface-air temperature gradient, particularly in complex landscapes. The Dual-Temperature-Difference (DTD) method addresses these issues by utilizing the Two-Source Energy Balance (TSEB) model of [1], and is a relatively simple scheme requiring meteorological input from standard synoptic weather station networks or mesoscale modeling. A comparison of the TSEB and DTD schemes is performed using LST and flux observations from eddy covariance (EC) flux towers and large weighing lysimeters (LYs) in irrigated cotton fields collected during BEAREX08, a large-scale field experiment conducted in the semi-arid climate of the Texas High Plains as described by [2]. Model output of the energy fluxes (i.e., net radiation, soil heat flux, sensible and latent heat flux) generated with DTD and TSEB using local and remote meteorological observations are compared with EC and LY observations. The DTD method is found to be significantly more robust in flux estimation compared to the TSEB using the remote meteorological observations. However, discrepancies between model and measured fluxes are also found to be significantly affected by the local inputs of LST and vegetation cover and the representativeness of the remote sensing observations with the local flux measurement footprint.Published by Elsevier Ltd.

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“…Attempts to adjust the LAI at the lysimeter from the field average LAI (i.e., to account for early season spatial variability) did not improve agreement between ET measured at the lysimeter and ET calculated by the TSEB model (data not shown). Additional quantification and discussion of plant spatial variability are provided by Agam et al (2012), Alfieri et al (2012), Colaizzi et al (2012b), and Evett et al (2012b). Simultaneous measurements of E, T, and ET were available during only two days without interference from irrigation, precipitation, or maintenance and repair of instruments.…”

Section: Plant Growth and Developmentmentioning

confidence: 99%

“…ET measurements made during irrigation, precipitation, plant measurements, or instrument maintenance and repair were excluded from consideration herein. Additional details of the lysimeter design, management, and experimental protocols are given by Marek et al (1988), Howell et al (1995), and Evett et al (2012b). E was measured by microlysimeters installed in interrows approximately 30 m to the northeast of the lysimeter ( fig.…”

Section: Datamentioning

confidence: 99%

Two-Source Energy Balance Model to Calculate E, T, and ET: Comparison of Priestley-Taylor and Penman-Monteith Formulations and Two Time Scaling Methods

2014

Trans.ASABE

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Can weighing lysimeter ET represent surrounding field ET well enough to test flux station measurements of daily and sub-daily ET?

Cited by 137 publications

References 21 publications

Assessing the Efficacy of the SWAT Auto-Irrigation Function to Simulate Irrigation, Evapotranspiration, and Crop Response to Management Strategies of the Texas High Plains

Assessing the Efficacy of the SWAT Auto-Irrigation Function to Simulate Irrigation, Evapotranspiration, and Crop Response to Management Strategies of the Texas High Plains

Evaluating the two-source energy balance model using local thermal and surface flux observations in a strongly advective irrigated agricultural area

Two-Source Energy Balance Model to Calculate E, T, and ET: Comparison of Priestley-Taylor and Penman-Monteith Formulations and Two Time Scaling Methods

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