Eddy Covariance Evapotranspiration Research Articles

Prediction of rainfed corn evapotranspiration and soil moisture using the STICS crop model in eastern Canada

The accurate simulation of crop evapotranspiration (ET) and volumetric soil moisture (SM) is key for agro-environmental simulation of rainfed crops. We compared two ET calculation methods available in the STICS crop model, i.e., the crop coefficient (FAO-56, CC) and the resistance (Shuttleworth and Wallace, SW) methods, over six contrasting rainfed grain corn growing seasons. The ET predictions using the SW method were in good agreement with eddy covariance ET measurements and overall ET predictions were slightly higher than observations by 3% while the CC method overestimated ET by 18%. STICS better predicted daily ET for wet years than for dry years. Ten-day corn ET showed that the SW method performed better when transpiration was dominant (nRMSE of 21.3%) than otherwise (nRMSE of 47.2%). The choice of ET calculation methods had little impact on SM predictions, which are computed in STICS using a tipping bucket approach. SM predictions over the entire soil profile were good for both wet (nRMSE of 15.1%) and dry (nRMSE of 18.2%) years. Larger discrepancies between measured and predicted SM were observed in the surface layer (0–10 cm). A new method was proposed to improve crop model simulations of the soil water transport in the shrinkage cracks during dry years, named Improving Shrinkage Cracks Impact (ISCI). The ISCI method enhanced the performance of SM predictions in the surface soil layer, for which nRMSE decreased to 29.7% for 2002, 18.1% for 2010 and 10.4% for 2018 in comparison with SM results without the use of ISCI method. The steps for implementing ISCI method in crop models using the tipping bucket approach for computing soil moisture are presented. • Two evapotranspiration calculation methods using STICS crop model were compared. • The resistance method predicted corn evapotranspiration better than the crop coefficient one. • Surface soil moisture predicted by STICS departed from observations during dry growing season. • We proposed a new method to account for the impact of shrinkage cracks on surface soil moisture.

Daily Evapotranspiration Estimations by Direct Calculation and Temporal Upscaling Based on Field and MODIS Data

Daily evapotranspiration (ET) integration is essential to various applications of agricultural water planning and management, ecohydrology, and energy balance studies. The constant reference evaporative fraction (EFr) temporal upscaling method has been proven to be efficient in extrapolating instantaneous ET to a daily timescale. Unlike upscaling methods, the direct calculation (DC) method developed in our previous study directly estimates daily ET without calculating instantaneous ET. The present study aimed to compare daily estimations of ET using the EFr and DC methods based on field and MODIS data at a site from the ChinaFLUX network. The estimation results were validated by eddy covariance (EC) ET both with and without the correction of energy imbalance. Based on field data, the results show that (i) the DC method performed with higher accuracy when compared to uncorrected EC measurements, while daily ET from both methods was overestimated; (ii) the DC method still performed better after the EC ET was corrected by the Residual Energy scheme, and the overestimations were significantly decreased; (iii) both methods performed best when compared with corrected ET by the Bowen Ratio scheme. The results from satellite data reveal that (i) the constant EFr method overestimated daily ET by a mean-bias-error (MBE) of 5.6 W/m2, and a root-mean-square error (RMSE) of 18.6 W/m2; and (ii) the DC method underestimated daily ET by a smaller MBE of −4.8 W/m2 and an RMSE of 22.5 W/m2. Therefore, the DC method has similar or better performance than the widely used constant EFr upscaling method and can estimate daily ET directly and effectively.

Assessing Daily Evapotranspiration Methodologies from One-Time-of-Day sUAS and EC Information in the GRAPEX Project.

Daily evapotranspiration (ETd) plays a key role in irrigation water management and is particularly important in drought-stricken areas, such as California and high-value crops. Remote sensing allows for the cost-effective estimation of spatial evapotranspiration (ET), and the advent of small unmanned aerial systems (sUAS) technology has made it possible to estimate instantaneous high-resolution ET at the plant, row, and subfield scales. sUAS estimates ET using “instantaneous” remote sensing measurements with half-hourly/hourly forcing micrometeorological data, yielding hourly fluxes in W/m2 that are then translated to a daily scale (mm/day) under two assumptions: (a) relative rates, such as the ratios of ET-to-net radiation (Rn) or ET-to-solar radiation (Rs), are assumed to be constant rather than absolute, and (b) nighttime evaporation (E) and transpiration (T) contributions are negligible. While assumption (a) may be reasonable for unstressed, full cover crops (no exposed soil), the E and T rates may significantly vary over the course of the day for partially vegetated cover conditions due to diurnal variations of soil and crop temperatures and interactions between soil and vegetation elements in agricultural environments, such as vineyards and orchards. In this study, five existing extrapolation approaches that compute the daily ET from the “instantaneous” remotely sensed sUAS ET estimates and the eddy covariance (EC) flux tower measurements were evaluated under different weather, grapevine variety, and trellis designs. Per assumption (b), the nighttime ET contribution was ignored. Each extrapolation technique (evaporative fraction (EF), solar radiation (Rs), net radiation-to-solar radiation (Rn/Rs) ratio, Gaussian (GA), and Sine) makes use of clear skies and quasi-sinusoidal diurnal variations of hourly ET and other meteorological parameters. The sUAS ET estimates and EC ET measurements were collected over multiple years and times from different vineyard sites in California as part of the USDA Agricultural Research Service Grape Remote Sensing Atmospheric Profile and Evapotranspiration eXperiment (GRAPEX). Optical and thermal sUAS imagery data at 10 cm and 60 cm, respectively, were collected by the Utah State University AggieAir sUAS Program and used in the Two-Source Energy Balance (TSEB) model to estimate the instantaneous or hourly sUAS ET at overpass time. The hourly ET from the EC measurements was also used to validate the extrapolation techniques. Overall, the analysis using EC measurements indicates that the Rs, EF, and GA approaches presented the best goodness-of-fit statistics for a window of time between 1030 and 1330 PST (Pacific Standard Time), with the Rs approach yielding better agreement with the EC measurements. Similar results were found using TSEB and sUAS data. The 1030–1330 time window also provided the greatest agreement between the actual daily EC ET and the extrapolated TSEB daily ET, with the Rs approach again yielding better agreement with the ground measurements. The expected accuracy of the upscaled TSEB daily ET estimates across all vineyard sites in California is below 0.5 mm/day, (EC extrapolation accuracy was found to be 0.34 mm/day), making the daily scale results from TSEB reliable and suitable for day-to-day water management applications.

Evaluation of prediction and forecasting models for evapotranspiration of agricultural lands in the Midwest U.S

Evapotranspiration (ET) prediction and forecasting play a vital role in improving water use in agriculturally intensive areas. Metrological and biophysical predictors that drive ET in managed landscapes have complex nonlinear relationships. Deep learning and data-driven methods have shown promising performance for identifying the dependencies among variables. Here, we evaluated the potentials of random forest (RF) and long short-term memory (LSTM) neural networks to estimate and forecast daily ET for corn, soybeans, and potatoes in diverse agricultural farms during 2003–2019. The modeling framework was applied for nineteen fields where eddy covariance ET and meteorological observations in the Midwest USA for growing season (April-October) is available. In this study, we applied data-driven models (RF and LSTM) with 3 sets of predictors (5, 11, and 16 predictors). Results show that a 16 predictor RF model (RF_16 R2 = 0.7, Willmott’s skill score = 0.90) outperformed a process-based land surface model (LSM R2 = 0.57, Willmott’s skill score = 0.86) for predicting daily ET, while LSTM performance was lower (LSTM_16 R2 = 0.65, Willmott’s skill score = 0.89 and LSTM_11 R2 = 0.62, Willmott’s skill score = 0.86) than RF using the same sets of predictors. Vapor pressure and crop coefficients were identified as the most important predictors for irrigated crops, while short wave radiation and enhanced vegetation index were key predictors for non-irrigated crops. For certain crop types, such as corn and soybeans on fine-grained soils (silt loam), a simpler version RF, using only 11 drivers, can provide comparable results (R2 = 0.70 vs 0.69 and Willmott’s skill score = 0.90 vs 0.88). For short-term 3-day ET forecasting, LSTM is more sensitive to uncertainty in ensemble forecast meteorology than RF. ET forecasts were strongly sensitive to forecast uncertainty of vapor pressure. The proposed modeling architecture provides a field-scale, locally calibrated tool for accurate prediction and short-term forecasting of daily ET in areas where in situ ET, metrological, and biophysical data are lacking.

Synthesizing a Regional Territorial Evapotranspiration Dataset for Northern China

As a vital role in the processes of the energy balance and hydrological cycles, actual evapotranspiration (ET) is relevant to many agricultural, ecological and water resource management studies. The available global or regional ET products provide ET estimations with various temporal ranges, spatial resolutions and calculation methods (algorithms, inputs and parameterization, etc.), leading to varying degrees of introduced uncertainty. Northern China is the main agriculturally productive region supporting the whole country; thus, understanding the spatial and temporal changes in ET is essential to ensure water resource and food security. We developed a synthesis ET dataset for Northern China at a 1000 m spatial resolution, with a monthly temporal resolution covering a period ranging from 1982 to 2017, using an in-depth assessment of several ET products. Specifically, assessments were performed using in situ measured ET from eddy covariance (EC) observation towers at the site-pixel scale over interannual months under the conditions of different land cover types, climatic zones and elevation levels to select the most optimally performing ET products to be used in the synthesized ET dataset. Eight indicators under 21 conditions were involved in the assessment sheet, while the statistics of the different ET product occurrences and corresponding ratios were analyzed to select the best-performing ET products to build the synthesis ET dataset using the weighted mean method. The weights were determined by the Taylor skill score (TSS), calculated with ET products and EC ET observation data. Based on the assessment results, the Penman–Monteith–Leuning (PML_v2), ETWatch and Operational Simplified Surface Energy Balance (SSEBop) datasets were selected for implementation in the synthesis ET dataset from 2003 to 2017, while Global Land Evaporation Amsterdam Model (GLEAM) v3.3a, complementary relationship (CR) ET, and Numerical Terradynamic Simulation Group (NTSG) datasets were chosen for the synthesis ET dataset from 1982 to 2002. The weighted mean synthesized results from 2003 to 2017 performed well when compared to the in situ measured EC ET values produced under all of the above conditions, while the synthesized results from 1982 to 2002 performed well through the water balance method in Heihe River Basin. These results can provide more stable ET estimations for Northern China, which can contribute to relevant agricultural, ecological and hydrological studies.

Using SMAP Level-4 soil moisture to constrain MOD16 evapotranspiration over the contiguous USA

Evapotranspiration (ET) is a key hydrologic variable linking the Earth's water, carbon and energy cycles. At large spatial scales, remote sensing-based (RS) models are often used to quantify ET. Despite the large number of RS ET models available, few include soil moisture as a key environmental input, which can degrade model accuracy and utility. Here, we use model assimilation enhanced soil moisture estimates from the NASA SMAP (Soil Moisture Active Passive) mission as a water supply control in the MOD16 ET algorithm framework. SMAP-derived daily surface (0-5 cm depth) and root zone (0-1 m depth) soil moisture are used with MODIS (Moderate Resolution Imaging Spectroradiometer) vegetation observations, and 4 km gridded regional surface meteorology (Gridmet) as primary inputs for estimating daily ET and underlying model soil and stomatal conductance terms. We calibrated the model environmental response parameters using tower eddy covariance ET observations representing major North American biomes. The model ET results were validated using a holdout set of tower observations spanning a large regional climate gradient. The updated ET estimates outperform the baseline MOD16 product across all tower validation sites (RMSE = 0.758 vs 1.108 mm day−1; R2 = 0.68 vs 0.45, respectively). Smaller relative improvements were obtained using a recalibrated model with 4 km Gridmet meteorology, but no soil moisture control (RMSE = 0.813 mm day−1; R2 = 0.66), indicating that these changes are essential for the improved model performance. The soil moisture-constrained model improvements and relative benefits from the SMAP observations are greater in arid climates, consistent with stronger soil moisture control on ET in water-limited regions. The use of SMAP soil moisture as an additional model constraint improves MOD16 regional performance and provides a new framework for investigating both soil and atmosphere controls on ET.

Energy Imbalance and Evapotranspiration Hysteresis Under an Advective Environment: Evidence From Lysimeter, Eddy Covariance, and Energy Balance Modeling

AbstractSurface energy imbalance problems have been underexplored especially under advective environments. Here, we present a novel analysis of surface energy fluxes from three distinct approaches—weighing lysimeter, eddy covariance (EC), and surface energy balance modeling for the 2014 sorghum and 2016 corn crop seasons in Bushland, Texas. Our results suggest that energy imbalance problems in the EC system were evidently associated with two opposite evapotranspiration (ET) hysteresis patterns with respect to net radiation and water vapor pressure deficit (VPD). The lysimeter ET had the smallest ET hysteresis while the eddy covariance ET results indicated the strongest hysteresis with respect to net radiation. Conversely, the lysimeter ET hysteresis related to water VPD was stronger than that of the eddy covariance method. This study provides understanding of ET hysteresis patterns, energy imbalance, and advective conditions associated with turbulent flux dynamics for both diel and crop growing seasonal timescales in Bushland, Texas.

Stone Content Influence on Land Surface Model Simulation of Soil Moisture and Evapotranspiration at Reynolds Creek Watershed

AbstractConsiderable advancement in spatiotemporal resolution of remote sensing and ground-based measurements has enabled refinement of parameters used in land surface models for simulating surface water fluxes. However, land surface modeling capabilities are still inadequate for accurate representation of subsurface properties and processes, which continue to limit the accuracy of land surface model simulation. Our objective in this study was to examine the performance of the variously parameterized Noah land surface model with multiphysics option (Noah-MP) in simulating evapotranspiration (ET) and soil moisture dynamics in stony soils using verification from eddy covariance ET and in situ soil moisture data during the growing season of year 2015, obtained from the Lower Sheep subcatchment within the Reynolds Creek Experimental Watershed in southwestern Idaho. We evaluated the performance of Noah-MP considering four different scenarios with 1) a one-layer soil profile with Noah-MP default soil hydraulic parameters and three more five-layer soil profiles using 2) Noah-MP default soil hydraulic parameters; 3) soil hydraulic parameters derived from a pedotransfer function using field observations; and 4) hydraulic parameters from scenario 3, which also accounted for stone content in each layer. Each modeling experiment was forced with the same set of initial conditions, atmospheric input, and vegetation parameters. Our results indicate that enhanced representation of soil profile properties and stone content information noticeably improve the Noah-MP land surface model simulation of soil moisture content and evapotranspiration.

Evaluating the accuracy of satellite-derived evapotranspiration estimates acquired during conditions of water stress

ABSTRACT Surface energy balance models such as the surface energy balance system (SEBS) assume that the influence of soil moisture and biophysical parameters on evapotranspiration (ET), are implicitly encompassed in model input variables such as the land surface temperature. This simplification may generally be suitable for environments in which the available energy constrains ET but may prove to be inadequate during suboptimal environmental conditions. To address this limitation, the SEBSESF approach was proposed to better represent the influence of environmental stress on surface energy fluxes, using an empirically derived calibration factor to adjust the evaporative fraction previously determined in SEBS. SEBSESF was evaluated by comparing the modelled ET estimates against Eddy Covariance ET measurements (ECET) at two sites, with contrasting environmental conditions. Comparisons between ECET and modelled ET indicated that the implementation of SEBSESF resulted in an improved correlation between ECET and modelled ET estimates, as well as an increase in the percentage of modelled ET estimates within an acceptable accuracy range (± 15 to 30%). Overall, the results of the study demonstrate how potential improvements in the mapping of ET within arid and semi-arid environments can be achieved by accounting for environmental stress. This in turn provides an opportunity to better understand and quantify energy and water fluxes, using satellite-based ET estimation approaches.

Evapotranspiration Estimates Derived Using Multi-Platform Remote Sensing in a Semiarid Region

Evapotranspiration (ET) is a key component of the water balance, especially in arid and semiarid regions. The current study takes advantage of spatially-distributed, near real-time information provided by satellite remote sensing to develop a regional scale ET product derived from remotely-sensed observations. ET is calculated by scaling PET estimated from Moderate Resolution Imaging Spectroradiometer (MODIS) products with downscaled soil moisture derived using the Soil Moisture Ocean Salinity (SMOS) satellite and a second order polynomial regression formula. The MODis-Soil Moisture ET (MOD-SMET) estimates are validated using four flux tower sites in southern Arizona USA, a calibrated empirical ET model, and model output from Version 2 of the North American Land Data Assimilation System (NLDAS-2). Validation against daily eddy covariance ET indicates correlations between 0.63 and 0.83 and root mean square errors (RMSE) between 40 and 96 W/m2. MOD-SMET estimates compare well to the calibrated empirical ET model, with a −0.14 difference in correlation between sites, on average. By comparison, NLDAS-2 models underestimate daily ET compared to both flux towers and MOD-SMET estimates. Our analysis shows the MOD-SMET approach to be effective for estimating ET. Because it requires limited ancillary ground-based data and no site-specific calibration, the method is applicable to regions where ground-based measurements are not available.

Assessing FAO-56 dual crop coefficients using eddy covariance flux partitioning

Current approaches to scheduling crop irrigation using reference evapotranspiration (ET0) recommend using a dual-coefficient approach using basal (Kcb) and soil (Ke) coefficients along with a stress coefficient (Ks) to model crop evapotranspiration (ETc), [e.g. ETc=(Ks*Kcb+Ke)*ET0]. However, determining Ks, Kcb, and Ke from the combined evapotranspiration (ET) is challenging, particularly for Ke, and a new method is needed to more rapidly determine crop coefficients for novel cultivars and cultivation practices. In this study, we partition eddy covariance ET observations into evaporation (E) and transpiration (T) components using correlation structure analysis of high frequency (10–20Hz) observations of carbon dioxide and water vapor (Scanlon and Sahu, 2008) at three irrigated agricultural sites. These include a C4 photosynthetic-pathway species (sugarcane—Sacharum officinarum L.) and a C3 pathway species (peach—Prunus persica) under sub-surface drip and furrow irrigation, respectively. Both sites showed high overall Kc consistent with their height (>4m). The results showed differences in Ke, with the sub-surface drip-irrigated sugarcane having a low Ke (0.1). There was no significant relationship (r2<0.05) between root zone soil volumetric water content (VWC) in sugarcane and observed Kcb*Ks, indicating that there was no stress (Ks=1), while the peach orchard showed mid-season declines in Kcb*Ks when VWC declined below 0.2. Partitioning of Kc into Kcb and Ke resulted in a better regression (r2=0.43) between the Normalized Differential Vegetation Index (NDVI) and Kcb in sugarcane than between NDVI and Kc (r2=0.11). The results indicate the potential for correlation structure flux partitioning to improve crop ET coefficient determination by improved use of eddy covariance observations compared to traditional approaches of lysimeters and microlysimeters and sap flow observations to determine Kc, Ke, Ks, and Kcb.

Partitioning Evaporation and Transpiration in a Maize Field Using Heat-Pulse Sensors for Evaporation Measurement

. Evapotranspiration (ET) is the sum of soil water evaporation (E) and plant transpiration (T). E and T occur simultaneously in many systems with varying levels of importance, yet it is often very challenging to distinguish these fluxes separately in the field. Few studies have measured all three terms (ET, E, and T), and in the few cases where such measurements have been obtained, E is typically determined via destructive lysimetery. For 43 days in a fully developed maize ( L.) field, we continuously measured E using heat-pulse sensors and soil sensible heat balance, T using sap-flow gauges, and ET using an eddy covariance system. Crop evapotranspiration (ET c ) was also calculated from the crop coefficient (K c ) and the reference evapotranspiration (ET o ), which was determined with the standardized Penman-Monteith equation. During the measurement period, E and T accounted for 13% and 87% of E+T, respectively. E responded to variations in soil moisture and net radiation, whereas T changed primarily with net radiation. All three ET estimation methods (individually measured E+T, eddy covariance ET, and crop ET c ) demonstrated similar temporal trends and strong correlations (R 2 of 0.76 for ET c vs. E+T and 0.77 for ET vs. E+T), with the values of individually measured E+T close to crop ET c but larger than eddy covariance ET during the measurement period. Disparities in measurements were likely due to variations in measurement scale, which did not reflect the full range of field variability for individually measured E and T, and differences in response to declining soil moisture among the three approaches. Overall, the results support the need for individual measurement of each term (E, T, and ET) when attempting to interpret ET partitioning and suggest that soil heat-pulse sensors provide a viable complement to previously tested approaches for continuously determining E for ET partitioning during wetting-drying periods.

The way the wind blows matters to ecosystem water use efficiency

In many regions, atmospheric conditions change frequently with shifts of wind direction, extending maritime influences far inland or continental influences to coastal ecosystems. Climate models predict changes in both wind direction and velocity; these changes could potentially impact ecosystems mass and energy exchanges with the atmosphere. Using data on climate (wind speed and direction, air temperature and humidity) and ecosystem-scale fluxes (eddy-covariance evapotranspiration and CO2 flux) from the Mediterranean island of Sardinia, we evaluated whether the frequency of certain wind characteristics, potentially affecting ecosystem CO2 uptake, have changed over five decades, and whether these characteristics are indeed linked to ecosystem gas-exchange responses of the studied ecosystem. The analyses show that days dominated by summer Mistral winds decreased on average 3% per decade, and that wind direction affects biosphere–atmosphere exchange of carbon but not water. High velocity cool Mistral winds from continental Europe undergo limited thermal equilibration with the land surface after embarking on the land, trebling vapor pressure deficit (D) as they cross the island. In contrast, arriving with a similar D, lower velocity, warmer Saharan Sirocco winds heat up, thus increasing D 5-fold only 50km inland. Over a mixed pasture–woodland (grass-wild olive), while soil moisture was low and constant, daytime net carbon exchange (NEEd) averaged 2.3-fold higher (p<0.001) in Mistral than Sirocco days, largely reflecting the theoretically expected response of canopy conductance (gc) to variation of D. Because the product of gc and D encodes the key ecosystem compensatory mechanism, the reciprocal gc–D response maintained similar ecosystem evapotranspiration (Ee). Thus, summertime ecosystem water-use efficiency (We=NEEd/Ee) was ∼66% higher during Mistral than other days. The historical decrease of Mistral frequency reduced the estimated summertime NEEd>30%. The analyses demonstrate that alteration of dominance of air masses predicted with future climate will amplify or negate the positive effect of increased atmospheric [CO2] on We, and should be considered when assessing climate change impact on NEE.

Reduced evapotranspiration from leaf beetle induced tamarisk defoliation in the Lower Virgin River using satellite‐based energy balance

AbstractTamarisk (Tamarix spp.) is an invasive shrubby tree native to Eurasia. Since its introduction to the United States, it has established itself along Southwestern American riparian systems. Control programs aimed at removing tamarisk were initiated in an effort to restore riparian areas, and potentially salvage water. Biological control of tamarisk with the Diorhabda spp. (leaf beetles) defoliates tamarisk and reduces evapotranspiration (ET). In 2009, the beetle arrived at Mesquite, Nevada, along the Virgin River, and dispersed to the Lower Virgin River riparian area in 2011. This study estimates reduced Lower Virgin River riparian ET caused by leaf beetle activity. Multi‐temporal spectral angle mapper was used to detect established leaf beetle communities in the Lower Virgin River riparian area. The Mapping Evapotranspiration at High Resolution with Internal Calibration (METRIC) land surface energy balance model was used to estimate Lower Virgin River riparian ET. METRIC ET results were compared with eddy covariance ET estimates made in tamarisk along the Lower Virgin River. Comparisons indicated that METRIC accurately estimates pre‐beetle ET and post‐beetle reduced ET. The 2007–2010 (pre‐beetle) average ET for the Lower Virgin River riparian area was 1245 mm/yr compared with 1041 mm/yr for the 2011–2012 (post‐beetle) period. Given the 4700 acre riparian area, leaf beetle induced defoliation results in a mean annual ET reduction of 3161 acre‐ft. In 2011 and 2012, volumetric reductions to ET were estimated to be 817 and 5505 acre‐ft, respectively. The METRIC model was shown to be a useful tool for monitoring ET during pre‐beetle and post‐beetle defoliation periods. Copyright © 2015 John Wiley &amp; Sons, Ltd.

Partitioning forest evapotranspiration: Interception evaporation and the impact of canopy structure, local and regional advection

Spatial and temporal variation in interception evaporation, energy balance during rain and total water loss was explored in a structurally heterogeneous Norway spruce [Picea abies (L.) H. Karst.] plantation in western Denmark. The trees are arranged in a distinctive small scale mosaic (0.25 ha) of young open canopy stands interspaced with older mature closed canopy stands. The mature stands are bound by a single line of taller Grand Fir [Abies grandis] on their northern edge. Interception loss (I) was measured and modeled in the open and closed canopy stands and under a Grand Fir row using net precipitation gauges and the Gash rain interception model. Incorporating complementary data on individual stand transpiration, forest floor evaporation and total ET (Ringgaard et al., 2012) we show that (a) I is 3% points higher in the closed canopy than in the open canopy (34% and 31% of PG respectively) while the Grand Fir row promotes a zone of relative drought with I = 47%, (b) in terms of total water loss, the open canopy has an annual ET of about 7.5% higher than the closed canopy stand and (c) in months with little precipitation there is good agreement between the individual components of the evaporation balance and the gap-filled eddy-covariance evapotranspiration (EC-ET) estimate while in months with high precipitation the EC-ET data underestimate both the magnitude and variability of I. The Gash model had to be parameterized separately for summer and winter. In winter, the available energy for evaporation during rain was dominated by regional scale advection of heat from the North Sea, while in summer half the available energy came from local advection. The mean evaporation rate during rain was 0.09 mm h−1 in winter and 0.21 mm h−1 in summer.

Estimation of urban subtropical bahiagrass (Paspalum notatum) evapotranspiration using crop coefficients and the eddy covariance method

Eddy covariance (EC) and micro-meteorological data were collected from May 2010 to January 2013 from urban, non-irrigated bahiagrass (Paspalum notatum) in subtropical south Florida. The objectives were to determine monthly crop coefficients (Kc) for non-irrigated bahiagrass by using EC evapotranspiration (ET) data and the Food and Agriculture Organization 56 Penman–Monteith reference evapotranspiration equation; compare crop ET (ETc) calculated with new Kc values to ETc obtained using Kc values available in the literature; and compare results and methodologies for statistical differences. New Kc values ranged from 0.62 to 0.92 and were different from Kc values found in the scientific literature for bahiagrass. Resulting ETc calculated using literature Kc values were significantly different from EC ET data, whereas ETc using the new Kc values was not. Specifically, literature Kc values were temporally biased to miscalculate the timing of convergence between potential and actual ET, assuming that our new Kc values calculated with EC methods were most accurate. As a consequence, ETc calculated using the literature Kc values was either too large or too small. However, one set of literature Kc values from a similar climate and water table depth were closer to our new Kc values, indicating that climate should be considered when selecting urban non-irrigated Kc from the literature to estimate ET. Results also indicated that more than 1 year of EC ET data was needed when establishing monthly Kc values because of annual variability in factors controlling ET, such as water availability. The new Kc values reported herein could be used as an estimate for urban non-irrigated bahiagrass within similar climates. Copyright © 2013 John Wiley & Sons, Ltd.

Micro-Bowen ratio system for measuring evapotranspiration in a vineyard interrow

Sparse canopy systems such as vineyards are comprised of multiple components (e.g., vines, interrow soil and/or groundcover) that each contribute to system water and energy balance. Understanding component water and energy fluxes is critical for informing management decisions aimed at improving productivity and water use efficiency. Few methods are available to accurately and continuously measure component fluxes. We tested a novel micro-Bowen ratio (MBR) energy balance system for determining interrow evapotranspiration (ET) flux within a vineyard. Our objectives were to develop MBR methodology to measure ET flux from the vineyard interrow and to compare MBR ET measurements for bare soil and fescue interrow conditions to independent ET estimates. MBR methodology utilized measurement of air temperature and water vapor concentration at 1 and 6cm heights within 2.7m wide interrows. Measured ET rates were well correlated between MBR systems and micro-lysimeters for both fescue (R2=0.99) and bare surface (R2=0.89) interrow conditions, though MBR ET rates were larger than those determined from micro-lysimeters in both cases (20 and 60%, respectively). MBR daily ET estimates, determined by compositing measurements from fescue interrows and bare soil under vines, were also well correlated to (R2=0.70) and of similar magnitude as vineyard eddy covariance ET measurements during periods when the vines were dormant. Overall, MBR systems appeared to provide a reasonable approach to determine ET for the interrow component within the vineyard. Similar methodology may be useful to better understand components’ contributions to water and energy fluxes in other complex or sparse canopy systems.

Operational Evapotranspiration Mapping Using Remote Sensing and Weather Datasets: A New Parameterization for the SSEB Approach

AbstractThe increasing availability of multi‐scale remotely sensed data and global weather datasets is allowing the estimation of evapotranspiration (ET) at multiple scales. We present a simple but robust method that uses remotely sensed thermal data and model‐assimilated weather fields to produce ET for the contiguous United States (CONUS) at monthly and seasonal time scales. The method is based on the Simplified Surface Energy Balance (SSEB) model, which is now parameterized for operational applications, renamed as SSEBop. The innovative aspect of the SSEBop is that it uses predefined boundary conditions that are unique to each pixel for the “hot” and “cold” reference conditions. The SSEBop model was used for computing ET for 12 years (2000‐2011) using the MODIS and Global Data Assimilation System (GDAS) data streams. SSEBop ET results compared reasonably well with monthly eddy covariance ET data explaining 64% of the observed variability across diverse ecosystems in the CONUS during 2005. Twelve annual ET anomalies (2000‐2011) depicted the spatial extent and severity of the commonly known drought years in the CONUS. More research is required to improve the representation of the predefined boundary conditions in complex terrain at small spatial scales. SSEBop model was found to be a promising approach to conduct water use studies in the CONUS, with a similar opportunity in other parts of the world. The approach can also be applied with other thermal sensors such as Landsat.

ECOSYSTEM WATER USE EFFICIENCY OF NORWAY SPRUCE MONOCULTURE FROM EDDY-COVARIANCE AND ECOPHYSIOLOGICAL MEASUREMENTS

Water release and biomass production of young Norway spruce stand were investigated by different approaches during 2004-2009. Closed-path eddy-covariance system (LI-7000) was found to be suitable for accurate net ecosystem production evaluation (NEP). NEP was in a good correspondence with the biomass inventory data. In contrary, water vapour eddy-covariance fluxes were found underestimating a real water release of the stand. Global radiation and air water vapour pressure deficit at 75% of the stand height were main micrometeorological control drivers for stand transpiration (T) and evapotranspiration (ET). Thus, missing or bad quality data of eddy-covariance ET can be simulated according to these parameters. Water use efficiency (WUE) values calculated from net and gross primary production data highly differed in absolute values as well as in seasonal course mainly due to respiration. Annual WUE values from eddy-covariance and from ecophysiological measurements of T and stand biomass increment were unfortunately incomparable. Therefore, precise research of eddy-covariance H2O fluxes and WUE evaluation need to continue.

涡度相关观测的能量闭合状况及其对农田蒸散测定的影响

涡度相关法被认为是测定农田蒸散量的标准方法。然而,能量不闭合现象在涡度相关测量中普遍存在。分析能量不闭合对涡度相关观测的影响,对于提高涡度相关观测精度具有重要意义。以蒸渗仪法为参照,探讨涡度相关观测的能量闭合状况对农田蒸散测定的影响,在导致涡度相关观测能量不闭合的诸多因素中,寻找对蒸散测定有影响的因素。结果表明:涡度相关观测的白天能量平衡比率(<em>EBR</em>)呈秋冬高、春夏低的变化特征,麦季日均<em>EBR</em>范围在0.26-2.84之间,平均1.15;玉米季日均<em>EBR</em>范围在0.19-2.59之间,平均0.78。无论麦季或玉米季,涡度相关法测定的平均蒸散量(<em>ET</em>_ec)均明显低于蒸渗仪法观测值(<em>ET</em>_L),但两者显著相关(<em>P</em> < 0.01),并有相似的季节变化。平均蒸散比(<em>ET</em>_ec/<em>ET</em>_L)麦季约为0.61,玉米季约为0.50。在冬小麦田和夏玉米田,<em>ET</em>_ec/<em>ET</em>_L均与<em>EBR</em>显著相关(<em>P</em> < 0.01)。麦田种植密度大,下垫面较均匀,蒸散比与<em>EBR</em>成正比(<em>P</em> < 0.01),且不受叶面积指数(<em>LAI</em>)大小影响;反之,玉米田种植密度小,只有当<em>LAI </em>> 1,下垫面变得较均匀后,蒸散比与<em>EBR</em>的关系才变得显著(<em>P</em> < 0.01)。风速小时<em>ET</em>_ec/<em>ET</em>_L与<em>EBR</em>显著相关,风速增加时二者相关性减弱。尤其在玉米田,当摩擦风速(<em>u</em>^*)大于0.3 m/s时,<em>ET</em>_ec/<em>ET</em>_L与<em>EBR</em>的相关性不再显著。风速小时,大气湍流微弱,湍流的涡旋较大。在有限的观测时段(0.5h)内,涡度相关仪的传感器难以捕捉足够的湍涡能量,所测湍流能量偏低,导致能量不闭合。以上结果为应用能量平衡比率校正农田蒸散提供了可能途径。;The eddy covariance (EC) technique is generally regarded as a standard method for crop evapotranspiration measurements. However, the imbalance of energy closure prevails in the EC observations. Evaluating the effect of energy balance closure on EC measurement is critical for improving the accuracy of this method. In this paper, a weighting method (the Lysimeter method) was used as reference to evaluate the effect of energy balance ratio (<em>EBR</em>) on EC evapotranspiration. The results revealed that daytime <em>EBR</em> varied seasonally in the field, where wheat and maize were rotated in the winter and summer, respectively. The <em>EBR</em> was higher in autumn and winter but lower in the spring and summer. For the wheat field, mean daytime <em>EBR</em> varied from 0.26 to 2.84 with an average of 1.15. As for the maize field, <em>EBR</em> varied from 0.19 to 2.59 with a mean value of 0.78. The evapotranspiration (<em>ET</em>) using EC (<em>ET</em>_ec) was clearly lower than derived by Lysimeter (<em>ET</em>_L). The mean ratio of <em>ET</em>_ec to <em>ET</em>_L (<em>ET</em>_ec/<em>ET</em>_L) was 0.61 and 0.50 during the wheat growing season and the maize season, respectively. The <em>ET</em> observed with these two approaches significantly correlated with each other (<em>P</em> < 0.01), with their characteristics of seasonal variation performing in a similar manner. The <em>ET</em>_ec/<em>ET</em>_L was found to be proportional to <em>EBR</em> (<em>P</em> < 0.01) in both the winter wheat field and the summer maize field. Furthermore, the effect of the leaf area index (<em>LAI</em>) on the relationship between <em>ET</em> ratios and <em>EBR</em> was significant in the even crop field during the entire growing season of winter wheat and the maize growing stage when the <em>LAI</em> was higher than 1. However, the effect was insignificant in the uneven maize field when the <em>LAI</em> was less than 1. On the other hand, friction velocity (<em>u</em>^*) exerted a strong impact on <em>EBR</em> and its relationship with <em>ET</em> ratios. <em>EBR</em> was observed to be proportional to <em>u</em>^* in both the winter wheat field and the summer maize field. <em>ET</em> ratios were proportional to <em>EBR</em> when <em>u</em>^* was small. Nonetheless, the correlation between these two parameters showed recession while <em>u</em>^* increasing, especially in summer maize field, <em>ET</em>_ec/<em>ET</em>_L was not significantly correlated with <em>EBR</em> when <em>u</em>^* was bigger than 0.3 m/s. Due to the weak turbulent intensity and the large eddy under the condition of low friction velocity, the EC sensor could not catch enough turbulent energy in a limited observation period (30 minutes), which caused lower measured turbulent fluxes and imbalanced energy closure. The results offer a possible way to correct the underestimated <em>ET</em>_ec using <em>EBR</em>.