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ARS Home » Plains Area » El Reno, Oklahoma » Oklahoma and Central Plains Agricultural Research Center » Livestock, Forage and Pasture Management Research Unit » Research » Publications at this Location » Publication #392880
Research Project: Integrated Agroecosystem Research to Enhance Forage and Food Production in the Southern Great Plains

Location: Livestock, Forage and Pasture Management Research Unit

Title: Influence of water use efficiency parameterizations on flux variance similarity-based partitioning of evapotranspiration

Author
item Wagle, Pradeep
item RAGHAV, PUSHPENDRA - University Of Alabama
item KUMAR, MUKESH - University Of Alabama
item Gunter, Stacey

Submitted to: Water Resources Research
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 11/18/2022
Publication Date: 11/22/2022
Citation: Wagle, P., Raghav, P., Kumar, M., Gunter, S.A. 2022. Influence of water use efficiency parameterizations on flux variance similarity-based partitioning of evapotranspiration. Water Resources Research. 328. Article 109254. https://doi.org/10.1016/j.agrformet.2022.109254.
DOI: https://doi.org/10.1016/j.agrformet.2022.109254

Interpretive Summary: Partitioning of evapotranspiration (ET) into evaporation (E, unproductive water use) and transpiration (T, productive water use) has numerous important implications. Several recent studies have reported a good performance of Flux Variance Similarity (FVS)–based ET partitioning method. Despite the high sensitivity of leaf-level water use efficiency (WUE) estimates to intracellular carbon dioxide concentrations (ci) in FVS partitioning, sensitivity analysis of ci parameterizations is lacking. Using high frequency eddy covariance data for wheat (Triticum aestivum L.) and canola (Brassica napus L.), we performed sensitivity analysis of four ci parameterizations (constant_ppm, constant_ratio, and linear and square root functions of vapor pressure deficit) and compared them with the optimized WUE approach with no adjustable parameter. Changing ci parameters resulted in varied partitioned outputs (i.e., T:ET ratios), due to direct impact on WUE estimates and T, for all four WUE algorithms. Three models (constant_ppm, constant_ratio, and optimum) were able to produce expected trends of T:ET ratios during dry and wet periods in both crops. Linear and square root models showed poor performances. The results indicated the potential for using constant_ppm and constant_ratio models for FVS partitioning by continuing to use the commonly used ci in both crops. The optimum model also showed its potential for inter-model comparison, especially in sensitivity analysis, for FVS partitioning in C3 species. Results illustrate that the choice of WUE algorithm and input value for ci parameterization in WUE algorithms for FVS partitioning can lead to large biases in partitioned fluxes.

Technical Abstract: Despite the high sensitivity of leaf-level water use efficiency (WUE) estimates to intracellular carbon dioxide concentrations (ci) in Flux Variance Similarity (FVS) partitioning method, sensitivity analysis of ci parameterizations is lacking. Using high frequency eddy covariance data for wheat (Triticum aestivum L.) and canola (Brassica napus L.), we performed sensitivity analysis of four ci parameterizations (constant_ppm, constant_ratio, and linear and square root functions of vapor pressure deficit) and compared them with the optimized WUE approach with no adjustable parameter. Results illustrated large dependencies of WUE estimates and transpiration (T) to evapotranspiration (ET) ratios with differences in ci parameterizations. Notably, constant_ppm and constant_ratio parametrizations for the fourth or fifth largest ci (commonly used default values in most previous studies) showed comparable T:ET ratios with the optimum model. Additionally, these three models produced decreased and increased T:ET ratios in wet and dry conditions, respectively. In contrast, linear and square root models failed to accurately capture expected trends of T:ET ratios during wet and dry periods, and also showed large discrepancies with respect to the optimal WUE approach. The results highlight that optimal parameterizations of ci should be derived in constant_ppm and constant_ratio methods to accurately capture temporal variations of WUE and T:ET. The results also indicated the potential of the optimum model for inter-model comparison, especially in sensitivity analysis, for FVS partitioning in C3 species. The study demonstrates the sensitivity of FVS partitioning to varying ci parameterizations in different WUE algorithms, and underscores the need to reduce uncertainty for more accurate partitioning.