Flux variance similarity-based partitioning of evapotranspiration over a rainfed alfalfa field using high frequency eddy covariance data

https://doi.org/10.1016/j.agrformet.2020.107907Get rights and content

Highlights

  • Alfalfa evapotranspiration (ET) was partitioned using Fluxpart software.

  • Evaporation (E) and transpiration (T) were consistent with expected trends.

  • T accounted for roughly 80% of the total ET during the alfalfa growing season.

  • This study can provide a foundation for future applications of this procedure.

Abstract

Although the eddy covariance (EC) technique provides direct and continuous measurements of evapotranspiration (ET), separate measurement of evaporation (E) and transpiration (T) at the ecosystem level is not possible. For partitioning ET into E and T, high frequency (10 Hz) time series EC observations collected from Apr 2016 to May 2018 over a rainfed alfalfa (Medicago sativa L.) field in central Oklahoma, USA were analyzed using the open source software Fluxpart. Fluxpart partitions ET by examining the correlation (Rqc) between water vapor (q) and carbon dioxide (c) fluxes as prescribed by the Flux Variance Similarity (FVS) partitioning method. Patterns of Rqc and partitioned E and T were consistent with expected trends associated with vegetation dynamics and short-term transient features (i.e., hay harvesting and rainfall events). The Rqc grew stronger with increasing alfalfa leaf area and exhibited a strong anti-correlation (Rqc close to -1) during peak growth when T and photosynthesis (P) were dominant and co-regulated by the leaf stomata. Consequently, a strong linear relationship (R2 = 0.96) was found between monthly midday average values of Rqc and monthly average Moderate Resolution Imaging Spectroradiometer (MODIS)-derived leaf area index (LAIMOD). Decorrelation of q and c or dominance of non-photosynthetic (e.g., E and respiration, R) fluxes resulted in less negative or positive Rqc values during winter, hay harvest, rainy, and nighttime periods. Growing season (Apr-Oct) average T:ET was approximately 0.82 and 0.77 in 2016 and 2017, respectively. Diurnal cycles and temporal variations of leaf-level water use efficiency (WUE, an input of the FVS method) estimates were consistent with the seasonal dynamics of ecosystem WUE, computed from EC-derived gross primary production (GPP) and EC-measured ET. These results validate the performance of the FVS ET partitioning method using high frequency EC data.

Introduction

Quantifying evapotranspiration (ET) is fundamental for a better understanding of agro-ecosystems and allocation of scare water resources since ET is a key component of the hydrological cycle that accounts for up to 95% of the water budget in dry agriculture (Wilcox et al., 2003). In recent years, the eddy covariance (EC) method has been widely used to measure high frequency (i.e., 10 Hz or higher) observations of the exchange of carbon dioxide (c) and water vapor (q) fluxes simultaneously at the landscape level (Baldocchi, 2014). Although EC can provide direct and continuous measurements of ET, it cannot provide separate measurements of the two components of ET: evaporation (E, nonproductive water use) and transpiration (T, productive water use enhancing plant productivity). It is difficult to determine individual components E and T at the landscape level through measurement (Burt et al., 2005; Wang et al., 2016; Williams et al., 2004). The partitioning of ET has important implications not only for the water budget but also for a mechanistic understanding of biological and climatic controls of E and T (Ferretti et al., 2003; Wang et al., 2015) since these two components are controlled by different processes and respond differently to climatic factors (Kool et al., 2014). Thus, the partitioning of ET into E and T is crucial to minimize the nonproductive loss of water and to improve water management practices and productivity of agroecosystems. Partitioning can also offer greater insights into the function of agroecosystems by reducing uncertainties in the interpretation of the coupling between water and carbon/nutrient cycles (Austin et al., 2004). In addition, partitioning is useful for improving the performance of land surface models as they are poorly constrained due to a lack of observations of the diurnal and seasonal variations of ET partitioning (Lawrence et al., 2007). However, the partitioning of ET into E and T is still theoretically and technically challenging.

The exchanges of q and c are tightly coupled ecosystem processes (Morales et al., 2005). Direct measurements of carbon gain and water loss by EC allow us to quantify water use efficiency (WUE) at the ecosystem level (Law et al., 2002; Wagle and Kakani, 2014a), which reflects the trade-off between water loss and carbon uptake in carbon assimilation process. However, direct measurement of WUE solely based on T (i.e., productive water use) is not possible by EC due to the lack of separate measurements of E and T.

There are various methods to partition ET into E and T (Kool et al., 2014; Sutanto et al., 2014). The ET partitioning methods range from the conventional technique of integrating hydrometric T measurements (i.e., sap flow) with E measurements (i.e., weighing lysimeter) (Herbst et al., 1996; Kelliher et al., 1992) to more recent techniques based on analyzing the isotopic composition of liquid water and water vapor (Sutanto et al., 2012; Yepez et al., 2005), and to modeling approaches such as global land surface models (Miralles et al., 2011), the HYDRUS-1D model (Simunek et al., 2005), and two source surface energy balance (SEB) models (Norman et al., 1995). However, all these methods have limitations due to experimental difficulties or uncertainties or issues of spatial and temporal coverages in the measurement of E and T.

The Flux Variance Similarity (FVS) ET partitioning method had been proposed nearly a decade ago to partition E and T using high frequency EC data (Scanlon and Kustas, 2010, 2012; Scanlon and Sahu, 2008). A few recent studies have employed the FVS partitioning method to compare with other partitioning approaches (Klosterhalfen et al., 2019a; Palatella et al., 2014; Peddinti and Kambhammettu, 2019; Perez‐Priego et al., 2018; Sulman et al., 2016). Some studies evaluated the performance of the FVS partitioning method for different land cover types: a suburban grass field (Wang et al., 2016), citrus orchards (Peddinti and Kambhammettu, 2019), a Mediterranean cropping system (Rana et al., 2018), and across gradients of woody plant cover (Wang et al., 2010). A few studies have performed sensitivity analysis of partitioning results using various estimates of leaf-level WUE (Klosterhalfen et al., 2019b; Sulman et al., 2016). Although EC measurements are available across the world through several EC networks (e.g., FLUXNET, AmeriFlux, EUROFLUX, AsiaFlux, ChinaFlux), wider testing and validation of the FVS partitioning method is still scarce, most likely due to the computational complexity of analyzing high frequency EC data. To permit wider practical applicability, the open source software Fluxpart has recently been developed to implement the FVS partitioning method (Skaggs et al., 2018). Details on the FVS flux partitioning method are available in the above-mentioned studies.

This study employed Fluxpart to partition and quantify the dynamics of E and T by examining q-c correlations (Rqc), and to characterize the biological and physical processes controlling the temporal dynamics of E, T, and Rqc over an alfalfa field (Medicago sativa L.). The alfalfa field was harvested periodically (4–5 times per year) and the study period consisted of two contrasting years: dry year 2016 (~32% less rainfall compared to the 30-year, 1981–2010, mean of 925 mm) and wet year 2017 (~20% more rainfall compared to the 30-year mean). Thus, this study can serve as a suitable case study for testing FVS ET partitioning method using the q-c correlation from high frequency (10 Hz) EC data.

Section snippets

EC data description and processing

Using an EC system, high frequency (10 Hz) observations of exchange of c and q between a 48 ha Alfalfa field (cv. Cimarron 400 planted in Fall 2012) and the atmosphere were recorded from Apr 2016 to May 2018 at the United States Department of Agriculture-Agricultural Research Service, Grazinglands Research Laboratory, El Reno, Oklahoma, USA. The EC system, mounted at a height of 2.5 m above the ground surface, comprised of an open path infrared gas analyzer (LI-7500 RS, LI-COR Inc., NE, USA)

Patterns of ET, E, and T

The 2017 growing season was wetter than the 2016 growing season (Fig. 1). The site received total rainfall of 501 mm and 930 mm during the 2016 and 2017 growing seasons (Apr-Oct), respectively. Thus, cumulative forage yield of alfalfa was also higher in 2017 (~10 dry t ha−1) than in 2016 (~7.5 dry t ha−1) (Wagle et al., 2019b). Total rain for Jan-Apr 2018 was only 101 mm (~0.6 times less than the 30-year mean of ~250 mm). As a result, ET values were higher during the 2017 growing season than

Conclusions

The correlation between water vapor (q) and carbon dioxide (c) fluxes were examined with the FVS ET partitioning method using 10 Hz time series eddy covariance (EC) measurements over a non-irrigated alfalfa field. This ET partitioning method successfully reproduced the seasonal and inter-annual variations of partitioned E and T fluxes. Temporal variability of Rqc was consistent with the expected shifts in the dominance of T or E. The Rqc was strongly regulated by vegetation status, hay

Disclaimer

“Mention of trade names or commercial products in this publication is solely for the purpose of providing specific information and does not imply recommendation or endorsement by the U.S. Department of Agriculture.”

“The U.S. Department of Agriculture (USDA) prohibits discrimination in all its programs and activities on the basis of race, color, national origin, age, disability, and where applicable, sex, marital status, familial status, parental status, religion, sexual orientation, genetic

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgments

This study was partly supported by a research grant (Project No. 2019-68012-29888) through the USDA-NIFA. We would like to thank a research technician, Shelby Robertson, for her assistance in screening the input files and running the Fluxpart partitioning codes.

References (52)

  • W.H. Schlesinger et al.

    Transpiration in the global water cycle

    Agric. Meteorol.

    (2014)
  • T. Skaggs et al.

    Fluxpart: open source software for partitioning carbon dioxide and water vapor fluxes

    Agric. Meteorol.

    (2018)
  • B.N. Sulman et al.

    Comparing methods for partitioning a decade of carbon dioxide and water vapor fluxes in a temperate forest

    Agric. Meteorol.

    (2016)
  • P. Wagle et al.

    Annual dynamics of carbon dioxide fluxes over a rainfed alfalfa field in the US Southern Great Plains

    Agric. Meteorol.

    (2019)
  • P. Wagle et al.

    Dynamics of evapotranspiration over a non-irrigated alfalfa field in the Southern Great Plains of the United States

    Agric. Water Manag.

    (2019)
  • P. Wang et al.

    Partitioning evapotranspiration in a temperate grassland ecosystem: numerical modeling with isotopic tracers

    Agric. Meteorol.

    (2015)
  • D. Williams

    Evapotranspiration components determined by stable isotope, sap flow and eddy covariance techniques

    Agric. Meteorol.

    (2004)
  • E.A. Yepez

    Dynamics of transpiration and evaporation following a moisture pulse in semiarid grassland: a chamber-based isotope method for partitioning flux components

    Agric. Meteorol.

    (2005)
  • A.T. Austin

    Water pulses and biogeochemical cycles in arid and semiarid ecosystems

    Oecologia

    (2004)
  • D. Baldocchi

    Measuring fluxes of trace gases and energy between ecosystems and the atmosphere–the state and future of the eddy covariance method

    Glob. Chang. Biol.

    (2014)
  • A.K. Betts et al.

    The land surface‐atmosphere interaction: a review based on observational and global modeling perspectives

    J. Geophys. Res..

    (1996)
  • C.M. Burt et al.

    Evaporation research: review and interpretation

    J. Irrig. Drain. Eng.

    (2005)
  • L.A. Cernusak

    Unsaturation of vapour pressure inside leaves of two conifer species

    Sci. Rep.

    (2018)
  • M. Detto et al.

    Simplified expressions for adjusting higher-order turbulent statistics obtained from open path gas analyzers

    Bound. Layer Meteorol.

    (2007)
  • D. Ferretti

    Partitioning evapotranspiration fluxes from a Colorado grassland using stable isotopes: seasonal variations and ecosystem implications of elevated atmospheric CO2

    Plant Soil

    (2003)
  • S.P. Good

    δ2H isotopic flux partitioning of evapotranspiration over a grass field following a water pulse and subsequent dry down

    Water Resour. Res

    (2014)
  • Cited by (0)

    View full text