Covariance System Research Articles

Determination of the Water use Efficiency of a Pecan Nut Orchard based on the Irrigation Scheduling and the Evapotranspiration Rate in Northern Mexico

Background: Adult pecan trees require a significant water supply for high yields and nut quality. Pecan nut orchards are established in semi-arid regions where water is the primary limiting resource for agriculture. Therefore, in these regions, improving water use efficiency is essential. Objective: Evaluate the water use efficiency of a pecan tree orchard based on the comparison of irrigation scheduling with the evapotranspiration rate data. Methods: The study was conducted in a pecan nut (Carya illinoinensis) orchard of 7.2 ha with 7-year-old Western and Wichita cv tress. The volume of water applied to each tree (drip irrigation) was converted to a daily irrigation depth and compared against the daily rate of actual (measured with an Eddy covariance system) and the FAO Penman-Monteith evapotranspiration. Results: Comparing the monthly water depth applied to each tree against the monthly FAO-Penman Monteith ET, surplus or deficit irrigation episodes were detected. Because the canopy trees only covered 18.7% of the orchard area, the daily rate of actual evapotranspiration during the months of the trees growing was very small (1 to 2 mm) compared with the orchards of mature pecan trees. The corresponding monthly crop coefficients (Kc) were also small (0.315 on average). Conclusion: This study showed that by comparing the rate of ETref against the irrigation depth applied to the trees in the irrigation scheduling, it is possible to reveal cases of surplus or deficit of water supplied to a pecan nut orchard.

Estimation of daily evapotranspiration in gully area scrub ecosystems on Loess Plateau of China based on multisource observation data

Evapotranspiration is an important process in the hydrologic cycle. In this study, different types of daily evapotranspiration were accurately estimated and comparatively analyzed for 2020–2021 in the gully area of Loess Plateau, China with multisource observation data. The daily actual evapotranspiration was directly observed by the eddy covariance system and then compared with the daily evapotranspiration simulated by HYDRUS-1D, and they showed reasonable agreement and similar variability characteristics it with a correlation coefficient of 0.71. The FAO-56 Penman-Monteith equation was used to calculate the reference evapotranspiration and compared with the pan evaporation in the study area. The reference evapotranspiration has a single-peak pattern and seasonal variation, similar to the actual evapotranspiration process during the annual period. The crop coefficient had seasonal-variation characteristics and remained 0.8 in the mid-growth period. The correlation analysis between evapotranspiration and environmental factors at different time scales suggested that energy was the dominant factor affecting evapotranspiration in the study area. The validation results of the complementary relationship of evaporation indicated a significant asymmetric complementary relationship in the study area. Both generalized nonlinear complementary relationship functions have good applicability, but the performance of the sigmoid function was slightly better than that of the polynomial function. The results provided a reference for local water resource management and agricultural production.

Carbon flux in supraglacial debris over two ablation seasons at Miage Glacier, Mont Blanc massif, European Alps

The cryosphere plays an important role in the global carbon cycle, but few studies have examined carbon fluxes specifically on debris-covered glaciers. To improve understanding of the magnitude and variability of the atmospheric carbon flux in supraglacial debris, and its environmental controls, near-surface CO2 fluxes and meteorological variables were monitored over thick (0.23 m) and thin (0.04 m) debris at Miage Glacier, European Alps, over two ablation seasons, using an eddy covariance system. The CO2 flux alternates between downward and upward orientation in the day and night, respectively, and is dominated by uptake of CO2 in thick debris (mean flux = 1.58 g CO2 m−2 d−1), whereas flux magnitude is smaller and near net zero on thin debris (mean flux = −0.06 g CO2 m−2 d−1). These values infer a potential drawdown of >150 t CO2 km−2 over an ablation season, and >500 t CO2 (0.5 Gg CO2) for the whole debris-covered zone. The strong correlation of daytime CO2 flux magnitude with debris surface temperature suggests that atmospheric CO2 is consumed in hydrolysis and carbonation reactions at sediment-water interfaces in debris. Incoming shortwave radiation is key in heating debris, generating dilute meltwater, and providing energy for chemical reactions. CO2 drawdown on thin debris increases by an order of magnitude on days following frost events, implying that frost shattering generates fresh reactive sediment, which is rapidly chemically weathered with the onset of ice melting. Net CO2 release in the night, and in the daytime when debris surface temperature is below 7°C, is likely due to respiration by debris microorganisms. The combination of dilute meltwater, high temperature, and reactive mineral surfaces open to the atmosphere, makes supraglacial debris an ideal environment for rock chemical weathering. Debris-covered glaciers could be important to local and regional carbon cycling, and measurement of CO2 fluxes and controlling processes at other sites is warranted.

Wind mediates the responses of net ecosystem carbon balance to climatic change in a temperate semiarid steppe of Northern China

As an important carbon sink to mitigate global climate change, the role of arid and semiarid grassland ecosystem has been widely reported. Precipitation and temperature changes have a dramatic impact on the carbon balance. However, the study of wind speed has long been neglected. Intuitively, wind speed regulates the carbon balance of grassland ecosystems by affecting the opening of vegetation stomata as well as near-surface moisture and temperature. It is sufficient that there is a need to conduct field observations to explore the effect of wind speed on the carbon balance in arid and semiarid grassland. Therefore, we conducted observations of carbon fluxes and corresponding climate factors using an eddy covariance system in a typical steppe in Inner Mongolia from 2017 to 2021. The research contents include that, (i) we depicted the changing patterns of carbon fluxes and climate factors at multiple time scales; (ii) we simulated the net ecosystem carbon balance (NECB) based rectangular hyperbolic model and compared it with the observed net ecosystem exchange values; (iii) we quantified the mediated effect of wind speed on NECB by adopting structural equation modeling; (iv) we used the constrained line method to explore what wind speed intervals might have the greatest carbon sequestration capacity of vegetation. The results were as follows, (i) the values of NECB for the five years of the study period were 101.95, −48.21, −52.57, −67.78, and −30.00 g C m−2 yr−1, respectively; (ii) if we exclude the inorganic carbon component of the ecosystem, we would underestimate the annual carbon balance by 41.25, 2.36, 20.59, 22.06 and 43.94 g C m−2 yr−1; (iii) the daytime wind speed during the growing season mainly influenced the NECB of the ecosystem by regulating soil temperature and vapor pressure deficit, with a contribution rate as high as 0.41; (iv) the grassland ecosystem had the most robust carbon sequestration capacity of 4.75 μmol m−2 s−1 when the wind speed was 2–3 m s−1. This study demonstrated the significant implications of wind speed variations on grassland ecosystems.

Development and deployment of a long‐term aquatic eddy covariance system

AbstractThe aquatic eddy covariance (AEC) technique is a versatile tool for understanding benthic fluxes, and calculating primary production, respiration, and net ecosystem metabolism rates of benthic communities. A limitation for researchers has been the length of deployments where the major constraints have primarily been sensor breakage and degradation over time and battery consumption. This paper evaluates the design and deployment of a long‐term eddy covariance system (LECS) that was deployed in a temperate seagrass meadow for 6 months that resulted in reliable data 79% of the time. The system consisted of a fixed bottom lander that measured the AEC and a surface buoy that transmitted real time data and provided solar power. This study found a gradual reduction in sensor response time, likely due to fouling, that reduced the response time from 1 to 22 s and resulted in a normalized root square mean error of 8% when comparing the LECS with a second short‐term AEC system. New spectral analysis techniques allow for these changes in sensor response time to be monitored in real time so the sensor can be replaced or cleaned as needed. This ensures future deployments will be able to collect high‐quality data and allow for long‐term analyses of benthic fluxes using the new technology and analyses of the presented LECS.

Evaluating the potential of achieving carbon neutrality at the neighborhood scale in urban areas

With increasing concern about global climate change, quite a few cities have established the target of achieving carbon neutrality in decades. However, urban blocks, as the fundamental units of the city, are rarely evaluated for the potential of achieving dynamical carbon neutrality due to the difficulty in exhaustively collecting multi-source data and determining the exact spatial scope of these data at a neighborhood scale. To address this problem, we combined the eddy covariance system and bottom-up models to explore the correlations between CO2 sources/sinks and the total CO2 flux by the general additive model (GAM) at the neighborhood scale. Based on the GAM results, this study further established four scenarios to quantitatively evaluate the potential and the possibility for the study area of achieving carbon neutrality. The simulation of the total CO2 emissions of the study area in 2050 under the four scenarios (Baseline, Transportation, Building, and Multi-sector-joint) would reach 7.64, 2.32, 6.11, and -1.27 kg CO2 m−2 year−1, respectively, which suggested that Multi-sector-joint Scenario would successfully realize the goal of emitting zero CO2 in 2050 in the study area. This study offers empirical evidence that helps policymakers to facilitate cities’ transition towards sustainable and carbon-neutral development.

Partitioning Evapotranspiration in a Cotton Field under Mulched Drip Irrigation Based on the Water-Carbon Fluxes Coupling in an Arid Region in Northwestern China

Measuring evapotranspiration (ET) components in cotton fields under mulched drip irrigation is needed to improve water use efficiency and promote the development of water-saving agriculture. In this study, an Eddy Covariance (EC) system was used to observe the water-carbon fluxes of cotton fields under mulched drip irrigation in an arid region during two years (2021–2022). The Underlying Water Use Efficiency (uWUE) method was used to partition the ET into transpiration (T) and evaporation (E) in order to reveal the changing characteristics of ET and its components in cotton fields under mulched drip irrigation and analyze the effects of environmental factors on each component. The results showed that the diurnal variation of ET was the same as gross primary productivity (GPP), and their course of change showed a bimodal curve at budding, blooming, and boll stages. The relationship of T at different growth stages was the same as ET, which is blooming and boll stage > budding stage > boll opening stage > seedling stage. ET and its components were mainly affected by temperature (Tair) and net radiation (Rn). This study can provide a theoretical and practical basis for the application of uWUE in cotton fields under mulched drip irrigation and a scientific basis for the rational allocation of water resources and the formulation of a scientific water-saving irrigation system for farmland in an arid region.

Eddy Covariance Measurements of Turbulent Heat Fluxes over a Grass-covered Surface in a Tropical Location

In this study, an Eddy Covariance (EC) system was deployed to measure the turbulent heat fluxes (sensible and latent heat fluxes) at a farmland located at Obafemi Awolowo University, Ile-Ife, Nigeria. The period of measurement was between 2016 and 2019. The surface of the measurement area was covered by grass (Axonopus fissifolius) and changes from leafy-green during the wet season to dry twigs during the dry season. The sensible heat flux, Hs obtained ranged between -0.8 and 181.9 Wm-2 while the latent heat flux, Hl varied between 0.9 and 218.0 Wm-2. The maximum daytime value of Hs peaked in January while the maximum daytime value of Hl peaked in October. The sensible heat flux was 59 % higher than the latent heat flux during the Harmattan months (January, February and December), while the latent heat flux was 63 % higher than the sensible heat flux during the wet months (April - November). The study concluded that 91 % of the energy available at the surface during the period of study, was used for evapotranspiration while only 9 % was used for sensible heating as shown by the distribution of the Bowen ratio.

Comparing the eddy covariance and gradient methods for measuring water and heat fluxes in paddy fields

Rice is distributed worldwide; thus, quantitative analyses of water and heat fluxes between the land and air in paddy fields are vital for understanding basin-scale water cycles. In this study, eddy covariance and meteorological gradient systems on a 20-meter flux tower in the Jianghan Plain, Yangtze River Basin, China, were used to measure turbulent and meteorological parameters in paddy fields in 2021. Three micrometeorological methods, namely the eddy covariance (EC), Bowen Ratio-Energy Balance (BREB), and aerodynamic (AERO) methods, were used to calculate the latent heat flux (LE) and sensible heat flux (H); BREB and AERO are collectively referred to as gradient methods. The effects of measurement heights, growth stage, and weather conditions on the consistency among them were analyzed. The difference in meteorological measurement heights affected the results of gradient methods. Among the five height combinations, the error in the 2 and 4 m combination was the smallest, and the coefficients of determination of LEEC–LEBREB/AERO and HEC–HBREB/AERO reached 0.96 and 0.84, respectively. The stratification of the near-surface layer was formed due to the heterogeneous underlying surface of the experimental area, and the instrument needed to be installed within the range between roughness layer and new equilibrium layer. The height difference of gradient methods can be amplified within this range to avoid the influence of instrument resolution. The difference among methods was affected by growth stage, and weather conditions (sunny, cloudy, rainy days and different wind speed class). Both factors influenced atmospheric stability, and the error was the maximum in neutral stratification. This study provides a reference for the selection of flux calculation methods and error analyses for paddy fields in humid areas.

Variations in CO2 and CH4 Exchange in Response to Multiple Biophysical Factors from a Mangrove Wetland Park in Southeastern China

Mangrove ecosystems can be both significant sources and sinks of greenhouse gases. The restoration of mangrove forests is increasingly used as a natural climate solution tool to mitigate climate change. However, the estimates of carbon exchanges remain unclear, especially from restored mangroves. In this study, we observed the temporal variations in carbon dioxide (CO2) and methane (CH4) fluxes and their biophysical controls for 4 years, based on a closed-path eddy covariance (EC) system. The measurements were conducted in a mangrove wetland park with 14-year-old restored mangroves surrounded by open waters in Guangdong Province, China. The EC measurements showed that the mangrove ecosystem acted as a CO2 source with a net CO2 ecosystem exchange (NEE) of 305 g C m−2 from January 2019 to May 2020 by the 5-m tower measurement. After the tower was adjusted to 10 m, the mangrove showed a CO2 sink with an NEE of −345 g C m−2 from June 2020 to December 2022. The change in tower height influenced the interpretation of interannual trends on NEE. There were no significant interannual trends in the gross primary productivity (GPP) and the ecosystem respiration (Re) values. The change from CO2 source to sink may be attributed to the decrease in land surface proportion by the tower replacement, which reduces the proportion of the mangrove canopy respiration and, therefore, captures lower CO2 fluxes from open waters. The restored mangroves indicated strong CH4 sources of 23.2–26.3 g C m−2 a−1. According to the random forest analysis, the land surface proportion, radiation, and relative humidity were the three most important predictors of NEE, while the CH4 flux was most sensitive to air temperature. Compared to the natural and long-term restored mangroves, this 14-year-old restored mangrove had not yet achieved a maximum carbon sequestration capability. Our study highlights the need for the careful design of long-term observations from restored mangroves and proposes future needs in the context of carbon neutrality.

Eddy Covariance Data Reveal That a Small Freshwater Reservoir Emits a Substantial Amount of Carbon Dioxide and Methane

AbstractSmall freshwater reservoirs are ubiquitous and likely play an important role in global greenhouse gas (GHG) budgets relative to their limited water surface area. However, constraining annual GHG fluxes in small freshwater reservoirs is challenging given their footprint area and spatially and temporally variable emissions. To quantify the GHG budget of a small (0.1 km2) reservoir, we deployed an Eddy covariance (EC) system in a small reservoir located in southwestern Virginia, USA over 2 years to measure carbon dioxide (CO2) and methane (CH4) fluxes near‐continuously. Fluxes were coupled with in situ sensors measuring multiple environmental parameters. Over both years, we found the reservoir to be a large source of CO2 (633–731 g CO2‐C m−2 yr−1) and CH4 (1.02–1.29 g CH4‐C m−2 yr−1) to the atmosphere, with substantial sub‐daily, daily, weekly, and seasonal timescales of variability. For example, fluxes were substantially greater during the summer thermally stratified season as compared to the winter. In addition, we observed significantly greater GHG fluxes during winter intermittent ice‐on conditions as compared to continuous ice‐on conditions, suggesting GHG emissions from lakes and reservoirs may increase with predicted decreases in winter ice‐cover. Finally, we identified several key environmental variables that may be driving reservoir GHG fluxes at multiple timescales, including, surface water temperature and thermocline depth followed by fluorescent dissolved organic matter. Overall, our novel year‐round EC data from a small reservoir indicate that these freshwater ecosystems likely contribute a substantial amount of CO2 and CH4 to global GHG budgets, relative to their surface area.

Characteristic time scales of evaporation from a subarctic reservoir

AbstractWater bodies such as lakes and reservoirs affect the regional climate by acting as heat sinks and sources through the evaporation of substantial quantities of water over several months of the year. Unfortunately, energy exchange observations between deep reservoirs and the atmosphere remain rare in northeastern North America, which has one of the highest densities of water bodies in the world. This study characterizes the dynamics of turbulent heat fluxes by analysing in‐situ observations of a compact and dimictic reservoir (50.69° N, 63.24° W) located in a subarctic environment. The reservoir is characterized by a mean depth of 44 m and a surface area of 85 km2. Two eddy covariance (EC) systems, one on a raft and one onshore, were deployed from 27 June 2018 to 12 June 2022. The thermal regime of the reservoir was monitored using two vertical chains of thermistors. Results indicate a mean annual evaporation rate of 590 ± 66 mm, which is equivalent to ≈51% of the annual precipitation, with 84% of the evaporation occurring at a high rate from August to freeze‐up in late December through episodic pulses. It was difficult to close the energy balance because of the magnitude and the large time lag of the heat storage term. To circumvent this problem, we opted to perform calculations for a year that started from the first of March, as the heat storage in the water column was at its lowest at that point and could thus be ignored. From June to December, monthly Bowen ratios increased from near‐zero negative values to about 1.5. After September, due to smaller vapour pressure deficits, latent heat fluxes steadily decreased until the reservoir had a complete ice cover. Opposite diurnal cycles of sensible and latent heat fluxes were revealed during the open water period, with sensible heat fluxes peaking at night and latent heat fluxes peaking in the afternoon.

Dataset of Comparative Observations for Land Surface Processes over the Semi-Arid Alpine Grassland against Alpine Lakes in the Source Region of the Yellow River

Thousands of lakes on the Tibetan Plateau (TP) play a critical role in the regional water cycle, weather, and climate. In recent years, the areas of TP lakes underwent drastic changes and have become a research hotspot. However, the characteristics of the lake-atmosphere interaction over the high-altitude lakes are still unclear, which inhibits model development and the accurate simulation of lake climate effects. The source region of the Yellow River (SRYR) has the largest outflow lake and freshwater lake on the TP and is one of the most densely distributed lakes on the TP. Since 2011, three observation sites have been set up in the Ngoring Lake basin in the SRYR to monitor the lake-atmosphere interaction and the differences among water-heat exchanges over the land and lake surfaces. This study presents an eight-year (2012–19), half-hourly, observation-based dataset related to lake–atmosphere interactions composed of three sites. The three sites represent the lake surface, the lakeside, and the land. The observations contain the basic meteorological elements, surface radiation, eddy covariance system, soil temperature, and moisture (for land). Information related to the sites and instruments, the continuity and completeness of data, and the differences among the observational results at different sites are described in this study. These data have been used in the previous study to reveal a few energy and water exchange characteristics of TP lakes and to validate and improve the lake and land surface model. The dataset is available at National Cryosphere Desert Data Center and Science Data Bank.

Temporal Dynamics of CO2 Fluxes Measured with Eddy Covariance System in Maize, Winter Oilseed Rape and Winter Wheat Fields

The full understanding of variation and temporal changes in carbon dioxide (CO2) fluxes in cropland may contribute to a reduction in CO2 emissions from agriculture. The aim of this study was to determine the CO2 exchange intensity in the three most popular crops in Poland. The CO2 fluxes in summer maize, winter oilseed rape and winter wheat fields were measured using the eddy covariance system. The seasonal dynamics of CO2 fluxes for all studied crops varied from each other due to individual dynamics in atmospheric CO2 assimilation of each species through the growing season. The weighted average values of CO2 fluxes calculated for the entire vegetation period were −22.22 µmol CO2 m−2 s−1, −14.27 µmol CO2 m−2 s−1 and −11.95 µmol CO2 m−2 s−1 for maize, oilseed rape and wheat, respectively. All the studied agro-ecosystems were carbon sinks during the growing season. The highest negative values of CO2 fluxes (−36.31 µmol CO2 m−2 s−1 and −33.56 µmol CO2 m−2 s−1) were observed in the maize field due to the high production of biomass. However, the maize field was also the most significant carbon source due to slow growth of plants at the beginning of the growing season, and due to leaving the field fallow after harvest until the next sowing. In these two periods, the CO2 fluxes ranged from 0.59 µmol CO2 m−2 s−1 to 3.72 µmol CO2 m−2 s−1. CO2 exchange over wheat and oilseed rape fields was less intense, but more even throughout the growing season. In the wheat field, the CO2 fluxes ranged from −1.70 µmol CO2 m−2 s−1 to −23.49 µmol CO2 m−2 s−1 and in the oilseed rape field they ranged from −1.40 µmol CO2 m−2 s−1 to −22.08 µmol CO2 m−2 s−1. In addition, the catch crop in the oilseed rape field contributed to the intensive absorption of CO2 after harvesting the main crop.

Estimating Carrot Gross Primary Production Using UAV-Based Multispectral Imagery

Gross primary productivity (GPP) is an essential parameter to assess the efficiency of terrestrial ecosystems on carbon transfer. Although GPP is regularly measured with eddy covariance (EC) systems, these are restricted to the tower footprint area, and remote sensing (RS) products have estimated GPP using multispectral vegetation indexes (VIs) from farms to whole ecosystems. Indeed, nowadays, unmanned aerial vehicle (UAV)-based RS technology is becoming more accessible. Accordingly, we propose the estimation of GPP using VIs at high spatial resolutions using UAVs and multi-spectral cameras. A small typical farm in Colombia was cultivated with carrot as our base crop. An EC system was installed to estimate GPP and was used as a reference. A total of 24 VIs from UAV-based RS products were selected and compared with the GPP of the EC system. A cross-validation process was performed, and seven VIs obtained a high R2 score (0.76–0.78). The accumulated GPP, estimated with the best index (NIRv) was 520.3 g C m−2, while the GPP-EC estimate was 580.4 g C m−2 (10.3% error). This work showed that it is possible to estimate the GPP of carrot crops using UAV-based RS, VIs, and linear regression models, which can be used in further research on GPP using UAVs.

On securing continuity of eddy covariance flux time-series after changing the measurement height: Correction for flux differences due to the footprint difference

During long-term flux monitoring, we occasionally encounter situations where the existing measurement setup must be changed. Considering that one of the main purposes of long-term flux monitoring is identifying long-term variability and trends, which are relatively small, it is important to understand or correct for flux differences caused by the measurement setting changes. In this study, before changing the flux measurement height of the CRK (Cheorwon Rice paddy, Korea) site from 10 m to 5 m, we installed another eddy covariance system at 5 m and compared the sensible and H2O/CO2/CH4 fluxes at both heights from April 2020 to April 2021. Although random errors could explain substantial portions of the flux differences between the two heights, it was confirmed that systematic errors also existed because the means of the flux differences were not zero, and the distributions of the flux differences were also significantly skewed. Further analysis showed that the primary cause of these systematic errors was the footprint differences rather than the difference in turbulent transport between the two heights. Based on the results, we proposed a strategy for securing the continuity of the flux time-series, which is necessary to understand the long-term variability using all data before and after a measurement change, and discussed the necessity of such a comparative observation.

Comparison of sensible and latent heat fluxes from optical-microwave scintillometers and eddy covariance systems with respect to surface energy balance closure

The eddy-covariance (EC) method has been widely used to measure sensible (H) and latent (LE) heat fluxes, however, it has limited spatial representativeness (hundreds of meters’ scale). Optical-microwave scintillometers (OMS) can directly measure kilometer-scale H and LE, which can be used to validate satellite remote sensing products and model simulations. Therefore, quantitative comparisons and analyses between H and LE measured by OMS and EC are important. In this study, the H and LE values measured by OMS and EC were compared and analyzed over two different surfaces: alpine meadow (homogeneous underlying surface) and irrigated cropland (heterogeneous underlying surface). Results showed that the H (LE) difference between OMS and EC measurements was approximately 17% (18%) and 27% (37%) over the homogeneous and heterogeneous underlying surfaces during the vegetation growing season, respectively. Furthermore, the difference in measured LE from OMS and EC (ΔLEOMS−EC) is caused by the combination of the difference in land surface hydrothermal conditions (LSHCs) and the different principles of OMS and EC measurements. On the one hand, ΔLEOMS−EC varied with the changing LSHCs within the instruments’ source areas over the heterogeneous surface, and the value could be decreased by irrigation and precipitation events. On the other hand, OMS averages large-scale measurements over both space and time and does not need to capture all-scale eddies (e.g., large-scale eddies), so the occurrence of advection increases ΔLEOMS−EC. Finally, compared with that of EC system, the energy balance closure ratio of OMS system was similar over the homogeneous underlying surface but significantly increased by 26% over the heterogeneous underlying surface. These results indicate that OMS has a potential advantage in measuring sensible and latent heat fluxes, particularly over heterogeneous underlying surfaces.

Development of a Benchmark Eddy Flux Evapotranspiration Dataset for Evaluation of Satellite-Driven Evapotranspiration Models Over the CONUS

A large sample of ground-based evapotranspiration (ET) measurements made in the United States, primarily from eddy covariance systems, were post-processed to produce a benchmark ET dataset. The dataset was produced primarily to support the intercomparison and evaluation of the OpenET satellite-based remote sensing ET (RSET) models and could also be used to evaluate ET data from other models and approaches. OpenET is a web-based service that makes field-delineated and pixel-level ET estimates from well-established RSET models readily available to water managers, agricultural producers, and the public. The benchmark dataset is composed of flux and meteorological data from a variety of providers covering native vegetation and agricultural settings. Flux footprint predictions were developed for each station and included static flux footprints developed based on average wind direction and speed, as well as dynamic hourly footprints that were generated with a physically based model of upwind source area. The two footprint prediction methods were rigorously compared to evaluate their relative spatial coverage. Data from all sources were post-processed in a consistent and reproducible manner including data handling, gap-filling, temporal aggregation, and energy balance closure correction. The resulting dataset included 243,048 daily and 5,284 monthly ET values from 194 stations, with all data falling between 1995 and 2021. We assessed average daily energy imbalance using 172 flux sites with a total of 193,021 days of data, finding that overall turbulent fluxes were understated by about 12% on average relative to available energy. Multiple linear regression analyses indicated that daily average latent energy flux may be typically understated slightly more than sensible heat flux. This dataset was developed to provide a consistent reference to support evaluation of RSET data being developed for a wide range of applications related to water accounting and water resources management at field to watershed scales.

Comparison of three modified models in evapotranspiration and its components over a rainfed spring maize cropland on the Loess Plateau, China

Accurately estimated evapotranspiration (ET) and its components in the growing season of cropland are required to optimize agricultural practices and improve water use efficiency. In this study, we developed a modified Shuttleworth–Wallace (SWm) model, a modified Priestley-Taylor (PTm) model, and a modified dual crop coefficient (DKm) model based on the characteristics of a rainfed spring maize cropland on the Loess Plateau. The estimated ET and its components by the three models were compared with the measured ET and its components using an eddy covariance system and microlysimeters. The results indicated that the three models performed well in estimating the 30 min ET and daily ET and its components during the growing seasons of the rainfed spring maize field in 2015 and 2016. The diurnal course of the measured 30 min ET was closest to that of the estimated 30 min ET from the DKm model, and this model performed best to estimate 30 min ET with a regression coefficient (b0) of 1.01 (R2 = 0.89) in 2015 and 0.97 (R2 = 0.88) in 2016. According to statistical analysis, the PTm model outperformed the other two modified models on estimating daily ET with b0 of 0.97 (R2 = 0.89) and 0.94 (R2 = 0.89) and daily plant transpiration (Tp) with b0 of 1.07 (R2 = 0.93) and 1.11 (R2 = 0.93) during the both growing seasons. The performance of the three modified models on daily soil evaporation (Es) was not as good as that of daily ET and Tp, and the DKm model performed best to reproduce daily Es with a b0 of 0.91 (R2 = 0.37) and 0.88 (R2 = 0.54) in 2015 and 2016, respectively. As the PTm model required the fewest input variables among the three modified models, this model was finally recommended for rainfed spring maize on the Loess Plateau, China.

Different spatial and temporal arrangements for validating the latent heat flux obtained using the MOD16 product in a forest in the Western Amazon

The Amazon rainforest is an important source of evapotranspiration and is essential in the global atmospheric circulation and hydrological cycle. However, measurements on vegetated surfaces are difficult, and methods such as remote sensing are promising in the micrometeorological data area. We aimed to assess the applicability of the MOD16 product to estimate evapotranspiration in a vegetated area. MOD16 data (LEMOD) derive from the Moderate Resolution Imaging Spectroradiometer sensor. For comparison, we used data from the eddy covariance system (LEEC) of the tower of the Large-scale Biosphere-Atmosphere Program in the Amazon of the Jaru Biological Reserve. To measure the linearity among variables, the Pearson correlation test (α=0.05) was used, and the T test was applied to assess the statistical significance between LEMOD and LEEC means (α=0.05); the root mean square error was also calculated. Regarding LEMOD, a similarity was found between the annual means of model and data, in which the best LEMOD estimates were obtained for annual averaging, when mean values were 96.51 W m–2 (0.7% lower than LEEC). LEMOD overestimates ranged from 1.05 W m–2 (1%) in 2007 to 15.78 W m–2 (18%) in 2005. Variations in short periods were not represented by the LEMOD product.