Remote sensing-based models are the most viable means of collecting the high-resolution spatially distributed estimates of evaporative water loss needed to manage irrigation and ensure the effective ...use of limited water resources. However, due to the unique canopy structure and configuration of vineyards, these models may not be able to adequately describe the physical processes driving evapotranspiration from vineyards. Using data collected from 2014 to 2016 as a part of the Grape Remote sensing Atmospheric Profile and Evapotranspiration Experiment (GRAPEX), the twofold objective of this study was to (1) identify the relationship between the roughness parameters, zero-plane displacement height (
d
o
) and roughness length for momentum (
z
o
), and local environmental conditions, specifically wind direction and vegetation density and (2) determine the effect of using these relationships on the ability of the remote sensing-based Two-Source Energy Balance (TSEB) model to estimate the sensible (
H
) and latent (
λE
) heat fluxes. Although little variation in
d
o
was identified during the growing season, a well-defined sigmoidal relationship was observed between
z
o
and wind direction. When the output from a version of the TSEB model incorporating these relationships (TSEB
VIN
) was compared to output from the standard model (TSEB
STD
), there were large changes to the roughness parameters, particularly
z
o
, but only modest changes in the turbulent fluxes. When the output from TSEB
VIN
was compared to that of a version using a parameterization scheme representing open canopies (TSEB
OPN
), the mean absolute difference between the estimates of
d
o
and
z
o
were 0.44 m and 0.25 m, respectively. While these values represent differences in excess of 45%, the turbulent fluxes differed by just 13 W m
−2
or 10%, on average. The results suggest that the TSEB model is largely insensitive to changes in the roughness parameters for the range in roughness values evaluated in this study. This also suggests that the requirement for highly accurate roughness values has limited utility in the application of the TSEB model in vineyard systems. Since there is no significant advantage to using the more complex TSEB
OPN
and TSEB
VIN
models, it is recommended that the standard model be used.
California is among the largest wine-producing regions in the world. It is also a region with limited water resources. To ensure that scarce water resources are used effectively, the ongoing Grape ...Remote sensing Atmospheric Profile and Evapotranspiration eXperiment (GRAPEX) project seeks to improve irrigation management within vineyards by providing remote sensing-based tools that can monitor ET across the continuum from sub-vineyard to regional scales. This study, which was conducted as a part of the GRAPEX project, compares the surface fluxes collected over a pair of vineyards separated by approximately 1 km from 2013 to 2017 to better understand the role of environmental conditions in controlling evapotranspiration. A comparison of the meteorological conditions, which include wind speed, wind direction, air temperature, water vapor pressure, and atmospheric pressure, showed there was no statistically meaningful difference in the measurements of these quantities either between the two vineyards or year to year. In contrast, the comparison of the surface fluxes, and in particular the sensible heat (
H
) and latent heat (
λE
) fluxes, showed that there were large inter-site and inter-annual differences. On average, during the growing seasons,
H
differed by 28 W m
−2
, while
λE
differed by 32 W m
−2
. With coefficients of determination (
r
2
) in excess of 0.90, the differences in the surface fluxes can be largely explained by differences in leaf area index (LAI) and soil moisture content. Since these quantities are, in turn, dependent on vineyard management practices, this work highlights the importance of management decisions for ensuring that limited water resources are used effectively.
Sustainable use of available water resources in viticulture can be aided by frequent high-resolution information on vineyard water status. Recently, a new Shuttleworth–Wallace evapotranspiration (ET) ...model, which uses a contextual framework to determine dry and wet extremes from the Sentinel-2 surface reflectance data (SW-S2), showed promising results when tested over a GRAPEX (Grape Remote-sensing Atmospheric Profile and ET eXperiment) site in California. However, current knowledge on its applicability across the climate gradient in California and how the selections of modeling domain and meteorological data influence model outputs are limited. This study expands the evaluation of the SW-S2 model across multiple domains and meteorological inputs covering all three GRAPEX sites over the 2018–2020 growing seasons. In comparison with flux tower observations, the size of the modeling domain did not have a strong influence on model performance, although the model performed marginally better under a larger domain (yielding root mean square error within 1.03–1.11 mm d
−1
and mean biases within 2%). The source and quality of meteorological forcing data, in particular vapor pressure deficit (VPD) and wind speed (
u
), were found to have a strong influence on model output as indicated by the poor performance of the model with less accurate regional and coarse-scale gridded meteorological inputs. Results suggest that simple regression for local bias correction of VPD and
u
significantly improved model performance. Overall, this study supports future research aiming to merge outputs from more frequent spectral and less frequent thermal-based ET models and reduce latency in ET monitoring of California vineyards.
This study compares evapotranspiration (ET) measurements from eddy covariance (EC), lysimetry (LY), and water balance using a network of neutron probe (NP) sensors and investigates the role of ...within-field variability in the vegetation density in explaining the differences among the various techniques. Measurements were collected over irrigated cotton fields during a period of rapid crop growth under advective conditions. Using NP-based ET estimates as reference, differences in cumulative ET measurements from the EC systems and NP ranged between 2 and 14Â %, while differences between LY and NP ranged from 22 to 25Â %. The discrepancy in the ET between the three methods was largely attributed to variations in vegetation cover within the source areas of the sensors, which was reliably assessed using high-resolution remote sensing imagery. This analysis indicates that the source area contributing to the measurements must be considered, even in instances where one might consider field conditions uniform. Consequently, differences in measured ET require accounting for variability of vegetation cover conditions in measurement source areas, particularly when used for model validation. This point concerning model validation is exemplified by the difference in performance of a thermal-based energy balance model in estimating ET evaluated using LY versus EC measurements.
Robust information on consumptive water use (evapotranspiration, ET) derived from remote sensing can significantly benefit water decision-making in agriculture, informing irrigation schedules and ...water management plans over extended regions. To be of optimal utility for operational usage, these remote sensing ET data should be generated at the sub-field spatial resolution and daily-to-weekly timesteps commensurate with the scales of water management activities. However, current methods for field-scale ET retrieval based on thermal infrared (TIR) imaging, a valuable diagnostic of canopy stress and surface moisture status, are limited by the temporal revisit of available medium-resolution (100 m or finer) thermal satellite sensors. This study investigates the efficacy of a data fusion method for combining information from multiple medium-resolution sensors toward generating high spatiotemporal resolution ET products for water management. TIR data from Landsat and ECOSTRESS (both at ~ 100-m native resolution), and VIIRS (375-m native) are sharpened to a common 30-m grid using surface reflectance data from the Harmonized Landsat-Sentinel dataset. Periodic 30-m ET retrievals from these combined thermal data sources are fused with daily retrievals from unsharpened VIIRS to generate daily, 30-m ET image timeseries. The accuracy of this mapping method is tested over several irrigated cropping systems in the Central Valley of California in comparison with flux tower observations, including measurements over irrigated vineyards collected in the GRAPEX campaign. Results demonstrate the operational value added by the augmented TIR sensor suite compared to Landsat alone, in terms of capturing daily ET variability and reduced latency for real-time applications. The method also provides means for incorporating new sources of imaging from future planned thermal missions, further improving our ability to map rapid changes in crop water use at field scales.
Characterization of model errors is important when applying satellite-driven evapotranspiration (ET) models to water resource management problems. This study examines how uncertainty in ...meteorological forcing data and land surface modeling propagate through to errors in final ET data calculated using the Satellite Irrigation Management Support (SIMS) model, a computationally efficient ET model driven with satellite surface reflectance values. The model is applied to three instrumented winegrape vineyards over the 2017–2020 time period and the spatial and temporal variation in errors are analyzed. We illustrate how meteorological data inputs can introduce biases that vary in space and at seasonal timescales, but that can persist from year to year. We also observe that errors in SIMS estimates of land surface conductance can have a particularly strong dependence on time of year. Overall, meteorological inputs introduced RMSE of 0.33–0.65 mm/day (7–27%) across sites, while SIMS introduced RMSE of 0.55–0.83 mm/day (19–24%). The relative error contribution from meteorological inputs versus SIMS varied across sites; errors from SIMS were larger at one site, errors from meteorological inputs were larger at a second site, and the error contributions were of equal magnitude at the third site. The similar magnitude of error contributions is significant given that many satellite-driven ET models differ in their approaches to estimating land surface conductance, but often rely on similar or identical meteorological forcing data. The finding is particularly notable given that SIMS makes assumptions about the land surface (no soil evaporation or plant water stress) that do not always hold in practice. The results of this study show that improving SIMS by eliminating these assumptions would result in meteorological inputs dominating the error budget of the model on the whole. This finding underscores the need for further work on characterizing spatial uncertainty in the meteorological forcing of ET.
The unique vertical canopy structure and clumped plant distribution/row structure of vineyards and orchards creates an environment that is likely to cause the wind profile inside the canopy air space ...to deviate from how it is typically modelled for most crops. This in turn affects the efficiency of turbulent flux exchange and energy transport as well as their partitioning between the plant canopy and soil/substrate layers. The objective of this study was to evaluate a new wind profile formulation in the canopy air space that explicitly considers the unique vertical variation in plant biomass of vineyards. The validity of the new wind profile formulation was compared to a simpler wind attenuation profile that assumes attenuation through a homogeneous canopy. We evaluated both attenuation models using measurements of wind speed in a vineyard interrow, as well as turbulent flux estimates retrieved from a two-source energy balance model, which uses land surface temperature as the key boundary condition for flux estimation. This is relevant in developing a robust remote sensing-based energy balance modelling system for accurately monitoring vineyard water use or evapotranspiration that can be applied using satellite and airborne imagery for field-to-regional scale applications. These tools are needed in intensive agricultural production regions with arid climates such as the Central Valley of California, which experiences water shortages during extended drought periods requiring an effective water management policy based on robust water use estimates for allocating water resources. Results showed that the new wind profile model improved sensible heat flux estimates (RMSE reduction from 42 to 35
W
m
-
2
) when the vine canopy is in early growth stage resulting in a strongly clumped canopy.
Evapotranspiration (ET) is a crucial part of commercial grapevine production in California, and the partitioning of this quantity allows the separate assessment of soil and vine water and energy ...fluxes. This partitioning has an important role in agriculture since it is related to grapevine stress, yield quality, irrigation efficiency, and growth. Satellite remote sensing-based methods provide an opportunity for ET partitioning at a subfield scale. However, medium-resolution satellite imagery from platforms such as Landsat is often insufficient for precision agricultural management at the plant scale. Small, unmanned aerial systems (sUAS) such as the AggieAir platform from Utah State University enable ET estimation and its partitioning over vineyards via the two-source energy balance (TSEB) model. This study explores the assessment of ET and ET partitioning (i.e., soil water evaporation and plant transpiration), considering three different resistance models using ground-based information and aerial high-resolution imagery from the Grape Remote sensing Atmospheric Profile and Evapotranspiration eXperiment (GRAPEX). We developed a new method for temperature partitioning that incorporated a quantile technique separation (QTS) and high-resolution sUAS information. This new method, coupled with the TSEB model (called TSEB-2TQ), improved sensible heat flux (H) estimation, regarding the bias, with around 61% and 35% compared with the H from the TSEB-PT and TSEB-2T, respectively. Comparisons among ET partitioning estimates from three different methods (Modified Relaxed Eddy Accumulation—MREA; Flux Variance Similarity—FVS; and Conditional Eddy Covariance—CEC) based on EC flux tower data show that the transpiration estimates obtained from the FVS method are statistically different from the estimates from the MREA and the CEC methods, but the transpiration from the MREA and CEC methods are statistically the same. By using the transpiration from the CEC method to compare with the transpiration modeled by different TSEB models, the TSEB-2TQ shows better agreement with the transpiration obtained via the CEC method. Additionally, the transpiration estimation from TSEB-2TQ coupled with different resistance models resulted in insignificant differences. This comparison is one of the first for evaluating ET partitioning estimation from sUAS imagery based on eddy covariance-based partitioning methods.
Assessment of water consumption is a crucial task for irrigation management in grapevines, especially in areas with limited water resources, which is the case of California Central Valley. This study ...evaluated the utility of the Simple Algorithm for Evapotranspiration Retrievement (SAFER) model to estimate daily and seasonal actual evapotranspiration (ET
a
) using Sentinel 2 images at 10-m spatial resolution and 5-day revisit time in 3 vineyards located at two sites in California. A unique characteristic of this model is the estimation of “synthetic” temperature maps, which are used as part of the estimation of ET and energy balance. The SAFER energy balance results were validated with six eddy covariance (EC) flux towers as part of the Grape Remote-sensing Atmospheric Profile and Evapotranspiration eXperiment (GRAPEX). The estimated surface temperature derived from upwelling longwave radiation measurements was closely correlated with the observed sensor surface temperature with
R
2
higher than 0.86 for the analyzed EC towers. After performing an internal calibration, SAFER root mean square error (RMSE) values on daily ET
a
were between 0.64 and 0.75 mm day
−1
. Additionally, the seasonal ET
a
was estimated and compared with the EC observations showing an average
R
2
ranging from 0.64 to 0.52 mm/season. Spatial patterns of ET
a
showed variability between sites and producer management activities. The results found indicate both limitations and potential utility of SAFER for irrigation management in vineyards using daily or seasonal ET
a
under different irrigation treatments.
We evaluate local differences in thermal regimes and turbulent heat fluxes across the heterogeneous canopy of a black spruce boreal forest on discontinuous permafrost in interior Alaska. The data ...were taken during an intensive observing period in the summer of 2013 from two micrometeorological towers 600 m apart in a central section of boreal forest, one in a denser canopy (DC) and the other in a sparser canopy, but under approximately similar atmospheric boundary layer (ABL) flow conditions. Results suggest that on average 34% of the half‐hourly periods in a day are nonstationary, primarily during night and during ABL transitions. Also, thermal regimes differ between the two towers; specifically between midnight and 0500 Alaska Standard Time (AKST) it is about 3°C warmer at DC. On average, the sensible heat flux at DC was greater. For midday periods, the difference between those fluxes exceeded 30% of the measured flux and over 30 W m−2 in magnitude more than 60% of the time. These differences are due to higher mechanical mixing as a result of the increased density of roughness elements at DC. Finally, the vertical distribution of turbulent heat fluxes verifies a maximum atop the canopy crown (2.6 h) when compared with the subcanopy (0.6 h) and above canopy (5.1 h), where h is the mean canopy height. We argue that these spatial and vertical variations of sensible heat fluxes result from the complex scale aggregation of energy fluxes over a heterogeneous canopy.
Key Points
Sensible heat flux varies with canopy architecture and surface properties
Sensible heat flux dominates over latent heat flux in the boreal forest
The vertical profile of sensible heat fluxes is not constant with height
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