Integrating sap flow and eddy covariance to improve vegetation representation in a process-based hydrologic model

Authors: Schreiner-Mcgraw, Adam; WOOD, JEFFREY - University Of Missouri; Abendroth, Lori

Submitted to: ASA-CSSA-SSSA Annual Meeting Abstracts
Publication Type: Abstract Only
Publication Acceptance Date: 7/12/2022
Publication Date: 11/6/2022
Citation: Schreiner-Mcgraw, A.P., Wood, J.D., Abendroth, L.J. 2022. Integrating sap flow and eddy covariance to improve vegetation representation in a process-based hydrologic model [abstract]. 2022 ASA-CSSA-SSSA Annual Meeting, November 6-9, 2022. Baltimore, Maryland. Paper No. 146353. Available: https://scisoc.confex.com/scisoc/2022am/meetingapp.cgi/Paper/146353

Interpretive Summary:

Technical Abstract: Accurate simulation of plant water use across agro-ecosystems is essential for various applications, including precision agriculture, quantifying groundwater recharge, and optimizing irrigation rates. Previous approaches to integrating plant water use data into hydrologic models have relied on evapotranspiration (ET) observations. But evaporation and transpiration (T) are processes with fundamentally different controls and observations of total ET cannot separate the behavior of the individual processes. The recently developed flux variance similarity approach partitions eddy covariance (EC) observations of ET to T and evaporation, providing an opportunity to use T data to parameterize vegetation in hydrologic models. The accurate use of the flux variance similarity approach relies on the estimation of leaf level water use efficiency (WUE) at the half-hourly timestep. Several approaches to parameterize WUE have been proposed. In this contribution we perform measurements of leaf level WUE under various levels of vapor pressure deficit and incoming light intensity. We use these measurements to parameterize WUE for the growing season and evaluate flux variance similarity partitioning against measurements from sap flow sensors in an agricultural field in Missouri. We then use the validated T/ET data from 4 EC towers in the Central Claypan Region of Missouri, to parameterize vegetation in an integrated land surface – groundwater model. We discuss the value of T/ET data for parameterizing hydrologic models over various environments, including rainfed agriculture, native prairie, and broadleaf forest. Finally, we simulate ET under climate change scenarios and assess the extent to which vegetation parameterization approaches impact the simulated ET response. Insights from this work can help researchers understand how land management practices in major agricultural systems affect the water cycle and land-atmosphere interactions.