Management practices regulate the response of canopy and ecosystem water use efficiency in cropland ecosystems
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Water Use Efficiency
Cypress
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Abstract. Evapotranspiration plays a key role in the terrestrial water cycle, climate extremes and vegetation functioning. However, the understanding of spatio-temporal variability of evapotranspiration is limited by a lack of measurement techniques that are low-cost, and that can be applied anywhere at any time. Here we show that evapotranspiration can be estimated accurately using only observations made by smartphone sensors. Individual variables known to effect evapotranspiration generally showed a high correlation with routine observations during a multi-day field test. In combination with a simple ML-algorithm trained on observed evapotranspiration, the smartphone-observations had a mean RMSE of 0.10 and 0.05 mm/h when compared to lysimeter and eddy covariance observations, respectively. This is comparable to an error of 0.08 mm/h when estimating the eddy covariance ET from the lysimeter or vice versa. The results suggests that smartphone-based ET monitoring could provide a realistic and low-cost alternative for real-time ET estimation in the field.
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Based on the measurement of latent evapotranspiration (LE) and sensible heat flux by open-path eddy covariance (OPEC) system, the authors analyzed diurnal and seasonal variations of forest evapotranspiration in the broadleaved_Korean pine forests in Changbai Mountain in 2003. The results showed that the energy balance closure was 86.5%. This suggested that the latent heat flux and sensible heat flux measured by OPEC system at the forest site were reasonable according to the internationally reported energy closure range (60%-90%). The LE gaps were filled by multiple polynomial regressions on the net radiation (R_n) and air temperature (T_a). Forest evapotranspiration was higher in the daytime than that at night, with the highest value occurring at noon. The maximum of monthly forest evapotranspiration appeared in July and August, and the minimum appeared in winter months. The ratio of evapotranspiration to net radiation in the growing season was evidently higher than that in the non-growing season. The annual evapotranspiration amounted to 1 126.99 MJ/m2 (450.8 mm of rainfall), accounting for 83.7% of the annual rainfall (538.4 mm).
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In this study, actual evapotranspiration data estimated using the water balance and eddy-covariance methods were compared. Two different basins, i.e., the Seolmacheon and Cheongmicheon basins, were selected, and the actual evapotranspiration was observed using the eddy-covariance method. The rainfall, runoff depth, and actual evapotranspiration data between 2010 and 2018 were collected and analyzed. Daily evapotranspiration data and 10-minute rainfall and runoff data were then accumulated to analyze the annual data. The results showed that the annual actual evapotranspiration amount obtained using the eddy-covariance method was somewhat close to that using the water balance method. This result is interesting, as the monthly variation between the two methods was high. The difference between the actual monthly evapotranspiration and the total loss was not influenced by monthly temperature and rainfall. This tendency was the same throughout the year, but the variation increased during the summer rainy season. In conclusion, both the actual evapotranspiration data estimated using the water balance and eddy-covariance methods can be used as representative annual values for the basins, regardless of the difference between the two data sets.
Water balance
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Information regarding evapotranspiration, the combined pathways of evaporative water loss from both the soil and vegetation, is critical to a broad range of applications. Evapotranspiration is controlled by three factors: the availability of water, the amount of available energy, and the ability of the atmosphere to take up the additional water. This chapter provides an overview of different methods for monitoring evapotranspiration using within-field and remote sensing-based approaches. It discusses lysimetry and the eddy covariance method as representative techniques for two broad approaches for monitoring evapotranspiration in situ. Lysimetry is discussed as an example of the mass balance approach while eddy covariance is used as an example of the micrometeorological approach. Similarly, the ALEXI/DisALEXI modeling system is discussed as an example of remote sensing-based approaches that use imagery from airborne or satellite platforms to obtain spatially-distributed estimates of evapotranspiration.
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This article compared the evapotranspiration values of summer maize measured by lysimeter and eddy covariance,and also analyzed the correlation between meteorological factors and evapotranspiration values of two spatial scales.The evapotranspirations measured by lysimeter and eddy covariance represent observation results in different farmland scales.Study results show that(1) good correlation can be found between the measurement results of lysimeter and eddy covariance,but the daily values measured by lysimeterate significantly higher than that by eddy covariance due to different spatial scales;(2) good correlation can also be found between the evapotranspiration and the net radiation,but the correlations between evapotranspiration and other meteorological factors are dependent on temporal and spatial scales.
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<p>Global freshwater is becoming an increasingly valuable resource, both due to increased human use as well as due to ecological importance in a changing climate. Understanding the hydrological cycles which govern water availability requires broad scale estimates of terrestrial evaporation, or evapotranspiration, which incorporate the complex signals of plant water use via transpiration. In this regard, evapotranspiration estimated from eddy covariance has proven a valuable resource in understanding ecosystem scale water fluxes at sites around the world, and recent advances in methods for directly estimating transpiration from eddy covariance data provide the opportunity to understand the influence plants have on water cycles. However, linking these ecosystem scale estimates to global scale processes requires a model to act as an intermediary, such as the empirical models used in the FLUXCOM products which train machine learning models on eddy covariance data linked with remote sensing data.</p><p>Here we look at the next generation of global terrestrial water flux estimates from FLUXCOM, including both the total evapotranspiration and the individual components of transpiration and abiotic evaporation. We benchmark these new estimates against previous FLUXCOM products, as well as compare to the state-of-the-art evapotranspiration estimates from process based models and remote sensing products. The high spatial and temporal scale allows for a close look at how the transpiration to evapotranspiration ratio varies both in space and time. We also outline estimate uncertainties from potential measurement biases to feature selection, and discuss the next steps for high quality empirical water flux estimates.</p>
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Peanut is planted in a pattern of either single or twin rows in Georgia, USA. However, limited attention has been paid to the impact of planting pattern on the carbon footprint and how the net carbon uptake is intertwined with the amount of water used to determine the ecosystem water-use efficiency (WUE) in peanut. This paper reports on the relationship between the amount of carbon produced to the amount of water used in peanut, carbon dioxide flux, and crop evapotranspiration of peanut in a single- or in a twin-row planting pattern measured using the eddy-covariance method. To the best of our knowledge, the present study is unique in that it examines for the first time the effect of planting pattern on the net carbon uptake and WUE. The two-year study took place in contrasting weather conditions with the 2016 year experiencing a higher vapor pressure deficit and lower precipitation than in the 2018 year. In this study, field-scale daytime net carbon ecosystem exchange (CO 2 fluxes), ET and WUE of single- and twin-row peanut were compared using the eddy-covariance technique. Results showed that in 2018, both the net carbon uptake from the atmosphere and the WUE of twin-row peanut were significantly greater than those in the single-row peanut by 7-10% and ~9% respectively, for pod filling and seed maturity growth stages (aGDD 1000-2000 and aGDD > 2000). In 2016, the net daytime carbon uptake and WUE of peanut were similar for both planting patterns during pod filling (aGDD 1000-2000). Higher precipitation and lower VPD in 2018 likely resulted in greater peanut yield in twin-row as compared to single-row with abundant precipitation. Owing to the fast canopy growth rate in twin-row peanut, results suggest that during the vegetative stage (aGDD<500) in 2016, both daytime net carbon uptake from the atmosphere and WUE were considerably greater in twin-row than single-row by 32% and 27%, respectively. Given that in both years, the ET from both planting patterns was similar, it appears that the determination of WUE in both planting patterns was more impacted by changes in daytime net carbon uptake than evapotranspiration. The results of this study suggest the possibility that the higher WUE at the critical stages of twin-row peanut in 2018 are likely to lead to greater yield than single-row peanut. This should be confirmed with further year-to-year investigations.
Water Use Efficiency
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