Insights for the Partitioning of Ecosystem Evaporation and Transpiration in Short‐Statured Croplands. Issue 7 (19th July 2022)

• Record Type: Journal Article
• Authors: Paul‐Limoges, Eugenie; Revill, Andrew; Maier, Regine; Buchmann, Nina; Damm, Alexander
• Is Part Of: Journal of geophysical research. Volume 127:Issue 7(2022)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-07-19
• Subjects: evapotranspiration -- partitioning -- transpiration -- crop -- eddy covariance; Geobiology -- Periodicals; Biogeochemistry -- Periodicals; Biotic communities -- Periodicals; Geophysics -- Periodicals; 577.14
• DOI: 10.1029/2021JG006760
• Languages: English
• ISSNs: 2169-8953

Abstract

Abstract: Reducing water losses in agriculture needs a solid understanding of when evaporation (E) losses occur and how much water is used through crop transpiration (T). Partitioning ecosystem T is however challenging, and even more so when it comes to short‐statured crops, where many standard methods lead to inaccurate measurements. In this study, we combined biometeorological measurements with a Soil‐Plant‐Atmosphere Crop (SPA‐Crop) model to estimate T and E at a Swiss cropland over two crop seasons with winter cereals. We compared our results with two data‐driven approaches: The Transpiration Estimation Algorithm (TEA) and the underlying Water Use Efficiency (uWUE). Despite large differences in the productivity of both years, the T to evapotranspiration (ET) ratio had relatively similar seasonal and diurnal dynamics, and averaged to 0.72 and 0.73. Our measurements combined with a SPA‐Crop model provided T estimates similar to the TEA method, while the uWUE method produced systematically lower T even when the soil and leaves were dry. T was strongly related to the leaf area index, but additionally varied due to climatic conditions. The most important climatic drivers controlling T were found to be the photosynthetic photon flux density ( R 2 = 0.84 and 0.87), and vapor pressure deficit ( R 2 = 0.86 and 0.70). Our results suggest that site‐specific studies can help establish T/ET ratios, as well as identify dominant climatic drivers, which could then be used to partition T from reliable ET measurements. Moreover, our results suggest that the TEA method is a suitable tool for ET partitioning in short‐statured croplands. Plain Language Summary: To reduce water losses linked to agriculture, we need to understand how much water the crops transpire and how much water is evaporated from irrigation surplus. Measuring how much water plants transpire is however difficult, especially for short‐statured crops like wheat or barley, because they are too small for the usual measurement techniques. In our study, we use detailed climate and vegetation measurements at a cropland in Switzerland combined with a model, and compare with two other data‐driven partitioning approaches (Transpiration Estimation Algorithm (TEA), underlying Water Use Efficiency (uWUE)). Our results show that the measurements combined with a model compared well with one of the approach (TEA), while the other (uWUE) was less well suited for our cropland. Our results demonstrate that there are ratios of the transpiration to evapotranspiration (i.e., including evaporation) that tend to be stable for specific ecosystems, and that could therefore be used once they are known for an ecosystem. Our results also show that the amount of light and the atmospheric demand for water vapor are important drivers for transpiration on a daily basis, while the plant cover determines the overall rate. Key Points: High agreement between transpiration (T) from measurements combined with a process‐based model (Soil‐Plant‐Atmosphere Crop) and a data‐driven method (Transpiration Estimation Algorithm) Diurnal and seasonal T to evapotranspiration ratios were relatively similar despite differences in crop and productivity between years Detailed crop specific models are a powerful method for partitioning T in short‐statured croplands to address lack of measurement methods