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.
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.
Accurate ground-based measurements of leaf area index (LAI) are needed for validation of remote sensing-based retrievals used in models estimating plant water use, stress, carbon assimilation and ...other land surface processes. Several methods for indirect LAI estimation with the Plant Canopy Analyzer (PCA, LAI-2200C, LI-COR, Lincoln, NE, USA) were evaluated using destructive (direct) leaf area measurements in three split-canopy vineyards and one double-vertical vineyard in California, as part of the Grape Remote sensing and Atmospheric Profile and Evapotranspiration eXperiment (GRAPEX). A method with the sensor facing the canopy, and four readings occurring evenly across the interrow space, had a coefficient of determination (
R
2
) of 0.87 and relative root mean square error (RRMSE) of 16%, when compared to direct LAI measurements via destructive sampling. A previously used method, with the sensor facing down-row, showed lower correlation to direct LAI (
R
2
= 0.75, RRMSE = 33%) and underestimation which was mitigated by removing the outer sensor rings from analysis. A PCA method is recommended for rapid and accurate LAI estimation in split-canopy vineyards, though local calibration may be required. The method was tested within small units of ground surface area, which compliments high-resolution datasets such as those acquired by small unmanned aerial vehicles. The utility of ground-based LAI measurements to validate remote sensing products is discussed.
In agriculture, leaf area index (LAI) is an important variable that describes occurring biomass and relates to the distribution of energy fluxes and evapotranspiration components. Current LAI ...estimation methods at subfield scale are limited not only by the characteristics of the spatial data (pixel size and spectral information) but also by the empiricity of developed models, mostly based on vegetation indices, which do not necessarily scale spatiality (among different varieties or planting characteristics) or temporally (need for different LAI models for different phenological stages). Widely used machine learning (ML) algorithms and high-resolution small unmanned aerial system (sUAS) information provide an opportunity for spatial and temporal LAI estimation addressing the spatial and temporal limitations. In this study, considering both accuracy and efficiency, a point-cloud-based feature-extraction approach (Full Approach) and a raster-based feature-extraction approach (Fast Approach) using sUAS information were developed based on multiple growing seasons (2014–2019) to extract and generate vine-scale information for LAI estimation in commercial vineyards across California. Three known ML algorithms, Random Forest (RF), eXtreme Gradient Boosting (XGB), and Relevance Vector Machine (RVM), were considered, along with hybrid ML schemes based on those three algorithms, coupled with different feature-extraction approaches. Results showed that the hybrid ML technique using RF and RVM and the Fast Approach with 9 input variables, called RVM-RF
Fast
model, performs better than others in a visual and statistical assessments of the generated LAI being also computationally efficient. Furthermore, using the generated LAI products in the quantification of energy balance using the two-source energy balance Priestley-Taylor version (TSEB-PT) model and EC tower data, the results indicated excellent estimation of net radiation (Rn) and latent heat flux (LE), good estimation of surface heat flux (G), and poor estimation of sensible heat flux (H). Additionally, TSEB-PT sensitivity analysis performed by regenerating LAI maps based on the generated LAI map (from − 15% of the original LAI map to + 15% with a 5% gap) showed that LAI uncertainty had a major impact on G, followed by evapotranspiration partitioning (T/ET), H, LE, and Rn. When considering the annual growth cycle of grapevines, the impact of LAI uncertainty on the T/ET in the veraison stage was larger than in the fruit set stage.
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.
Precision irrigation management requires operational monitoring of crop water status. However, there is still some controversy on how to account for crop water stress. To address this question, ...several physiological, several physiological metrics have been proposed, such as the leaf/stem water potentials, stomatal conductance, or sap flow. On the other hand, thermal remote sensing has been shown to be a promising tool for efficiently evaluating crop stress at adequate spatial and temporal scales, via the Crop Water Stress Index (CWSI), one of the most common indices used for assessing plant stress. CWSI relates the actual crop evapotranspiration ET (related to the canopy radiometric temperature) to the potential ET (or minimum crop temperature). However, remotely sensed surface temperature from satellite sensors includes a mixture of plant canopy and soil/substrate temperatures, while what is required for accurate crop stress detection is more related to canopy metrics, such as transpiration, as the latter one avoids the influence of soil/substrate in determining crop water status or stress. The Two-Source Energy Balance (TSEB) model is one of the most widely used and robust evapotranspiration model for remote sensing. It has the capability of partitioning ET into the crop transpiration and soil evaporation components, which is required for accurate crop water stress estimates. This study aims at evaluating different TSEB metrics related to its retrievals of actual ET, transpiration and stomatal conductance, to track crop water stress in a vineyard in California, part of the GRAPEX experiment. Four eddy covariance towers were deployed in a Variable Rate Irrigation system in a Merlot vineyard that was subject to different stress periods. In addition, root-zone soil moisture, stomatal conductance and leaf/stem water potential were collected as proxy for in situ crop water stress. Results showed that the most robust variable for tracking water stress was the TSEB derived leaf stomatal conductance, with the strongest correlation with both the measured root-zone soil moisture and stomatal conductance gas exchange measurements. In addition, these metrics showed a better ability in tracking stress when the observations are taken early after noon.
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.
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.
Water-limiting conditions in many California vineyards necessitate assessment of vine water stress to aid irrigation management strategies and decisions. This study was designed to evaluate the ...utility of a Crop Water Stress Index (CWSI) using multiple canopy temperature sensors and to study the diurnal signature in the stress index of an irrigated vineyard. A detailed instrumentation package comprised of eddy covariance instrumentation, ancillary surface energy balance components, soil water content sensors and a unique multi-canopy temperature sensor array were deployed in a production vineyard near Lodi, CA. The instrument package was designed to measure and monitor hourly growing season turbulent fluxes of heat and water vapor, radiation, air temperature, soil water content directly beneath a vine canopy, and vine canopy temperatures. April 30–May 02, June 10–12 and July 27–28, 2016 were selected for analysis as these periods represented key vine growth and production phases. Considerable variation in computed CWSI was observed between each of the hourly average individual canopy temperature sensors throughout the study; however, the diurnal trends remained similar: highest CWSI values in morning and lowest in the late afternoon. While meteorological conditions were favorable for plant stress to develop, soil water content near field capacity due to frequent irrigation allowed high evapotranspiration rates resulting in downward trending CWSI values during peak evaporative demand. While the CWSI is typically used to evaluate plant stress under the conditions of our study, the trend of the CWSI suggested a lowering of plant water stress as long as there was adequate soil water available to meet atmospheric demand.
•Effect of the calculation method for evaluation height using the flux-gradient approach was tested.•The analysis focused on metolachlor data collected over an eight year period.•Under unstable ...conditions, historical estimation methods caused a 15% error in the flux, on average.•The results indicate that the exact evaluation height should be used whenever possible.
Volatilization represents a significant loss pathway for many pesticides, herbicides and other agrochemicals. One common method for measuring the volatilization of agrochemicals is the flux-gradient method. Using this method, the chemical flux is estimated as the product of the vertical concentration gradient and a turbulent-transfer coefficient (eddy diffusivity). For computational simplicity, the evaluation height needed to calculate the eddy diffusivity is typically approximated as either the geometric or logarithmic mean. Both of these estimation methods are based on simplifying assumptions and can be a significant source of error, particularly when the separation distance between the measurement heights is large. Using data collected over an eight-year period at the USDA-ARS OPE3 experimental watershed, this study compared fluxes of metolachlor, a commonly-used herbicide, computed using the approximated evaluation heights with those calculated using the exact evaluation height. While it was found that the primary factor influencing the accuracy of the flux estimates using the approximate evaluation heights was atmospheric stability, errors in the estimate of the evaluation height can result in significant (>10%) errors in the flux estimates. Based on these results, it is recommended that the exact evaluation height be used with the flux-gradient technique.
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