Surface renewal is a micrometeorological method that is being used increasingly to determine energy fluxes, but its technical complexity makes it inaccessible to a broad audience. We describe the steps needed to set up and calibrate a surface renewal field station, to acquire and process data, and to correctly interpret results.
Advanced micrometeorological methods have become increasingly important in soil, crop, and environmental sciences. For many scientists without formal training in atmospheric science, these techniques are relatively inaccessible. Surface renewal and other flux measurement methods require an understanding of boundary layer meteorology and extensive training in instrumentation and multiple data management programs. To improve accessibility of these techniques, we describe the underlying theory of surface renewal measurements, demonstrate how to set up a field station for surface renewal with eddy covariance calibration, and utilize our open-source turnkey data logger program to perform flux data acquisition and processing. The new turnkey program returns to the user a simple data table with the corrected fluxes and quality control parameters, and eliminates the need for researchers to shuttle between multiple processing programs to obtain the final flux data. An example of data generated from these measurements demonstrates how crop water use is measured with this technique. The output information is useful to growers for making irrigation decisions in a variety of agricultural ecosystems. These stations are currently deployed in numerous field experiments by researchers in our group and the California Department of Water Resources in the following crops: rice, wine and raisin grape vineyards, alfalfa, almond, walnut, peach, lemon, avocado, and corn.
Water scarcity threatens agricultural sustainability in dry growing regions. This situation will likely worsen with changing climatic conditions and increasing competition between agricultural, municipal, industrial, and conservation entities for limited water supplies. To deal with this ongoing dilemma, growers continually search for ways to improve irrigation efficiency, and technology that better estimates crop water use (i.e. evapotranspiration, ET) in real time, and better agrometeorological methods will certainly help these efforts. Current technologies used by growers to estimate ET depend on the use of reference evapotranspiration (ET0) and an empirical crop coefficient (Kc), both of which are highly susceptible to estimation errors. Agrometeorologists also measure ET to evaluate experimental treatments for improving crop water use efficiency1 and to parameterize regional water allocation strategies2, but these methods are highly technical and expensive. Efforts are currently underway to translate existing research-based ET measurement methods into cost-effective and user-friendly technologies for growers.
Surface renewal (SR) is one agrometeorological method used to measure crop ET. SR is based on analyzing the energy budget of air parcels that reside ephemerally within the crop canopy during the turbulent exchange process3 as measured with the station shown in Figure 1 and illustrated theoretically in Figure 2 and Movie 1. The air parcels are manifested as ramp-like shapes in turbulent temperature time series data, and the amplitude and period of the ramps are used to calculate the flux density (Figures 2 and 3). With the SR method, ET for a given crop surface is determined by calculating latent heat flux density (LE) as the residual of the following energy balance equation
LE=Rn-G-H,
Here, LE is the energy flux density associated with the phase change of water from a crop surface, Rn is the net radiation, G is the soil heat flux density (i.e. energy conducted into or out of the ground), and H is the sensible heat flux density (i.e. energy flux density from the surface to the air or vice-versa that results in a temperature change). Rn is a positive number when the net flux is downward (energy added to the surface), LE and H are positive numbers when the flux is upwards (energy added to the air), and G is a positive number when the flux is downward (energy added to the soil). LE (MJ/m2sec) is then divided by the latent heat of evaporation (L=2.45 MJ/kg) to obtain the mass flux density of water vapor from the surface (i.e. ET).
Measurements of Rn and G are relatively straightforward and inexpensive. Direct measurements of H are more complex and require high frequency data acquisition. The most common method to determine H is with eddy covariance; however, the sonic anemometer required for this method is expensive, complex and, consequently, not widely used by agronomists, horticulturalists, or engineers to determine H and LE. On the other hand, H derived from the SR technique is obtained by a simpler and less expensive method, which uses fine wire thermocouples to measure high frequency air temperatures at the surface-atmosphere interface. Despite the simplicity of the SR, current measurements still require calibration against a sonic anemometer's eddy covariance estimate of H to obtain sensible heat flux density.
The successful deployment of an SR flux tower for ET measurements can be a daunting challenge, especially for many agricultural researchers without formal training in atmospheric science. SR and eddy covariance measurements require sophisticated technical skills in both programming data loggers to execute tasks with complex instrumentation and writing computer programs to post-process the raw turbulence data into meaningful fluxes. Here, we describe how to setup a field station, install sensors, and utilize our new turnkey data logger program for data collection and post-processing procedures.
Acquiring the Rn and G components of the energy balance equation are relatively straightforward and inexpensive. Measurements of H are more complex and require high frequency temperature traces measured with a fine wire thermocouple for surface renewal or a sonic anemometer for eddy covariance. An example temperature trace measured with a fine wire thermocouple is represented in Figure 9, and it shows the need for mathematical analysis to extract the signal from this raw data (see details of the analysis in 3,8-13). Visual inspection of this data reveals three or four primary ramps ending at approximately 12, 35, 46, and 72 sec (Figure 9).
All of the energy balance components follow a similar diurnal pattern with peak values occurring in the middle of the day. Rn is positive during the day as the surface receives more radiation than it loses, and negative at night as the surface loses more radiation than it receives, exhibiting the diurnal curve expected for sunny springtime days in northern California (Figure 10). G also follows a diurnal pattern (Figure 10) it is positive during the day as energy is conducted from the surface into the ground, and negative at night as more energy is conducted from below to the cooler surface. The diurnal pattern in G is generally smooth except for small deviations likely resulting from sunflecks impinging directly over the ground heat flux plates. LE follows the expected diurnal curve over a crop with adequate water during fair weather (Figure 10). Rn is the dominant energy source for ET, so the LE values track the changes in Rn during the daytime. Over an actively transpiring crop, it is expected that the majority of the available energy during positive Rn conditions is partitioned into LE rather than H and G. During windy nights (i.e., days 110, 113, and 114 in Figure 10), LE was near zero, whereas it was negative during calm nights, possibly indicating condensation (Figure 10). Nevertheless, the daytime contribution to LE greatly outweighs the nighttime contribution, so uncertainties in nighttime values are interesting but relatively unimportant.
The daily cumulative ET values agree well for the SR station and a weighing lysimeter situated side by side in a field of wheat (Figure 11) weighing lysimeters are considered a gold standard for ET estimates from crop surfaces. On most days, the cumulative ET from the SR station was slightly higher than values from the lysimeter. Tower measurements represent fluxes from a broader area than the lysimeter measurements, and at the time of these measurements the wheat in the lysimeter was ~10 cm shorter and less dense than the plants in remainder of the field, so higher ET values from the flux tower were expected.
Figure 1. Solar powered field station established in a vineyard in California to measure surface renewal with a sonic anemometer for calibration using eddy covariance.
Figure 2. Theoretical representation of surface renewal describing how air parcels interact with a plant canopy surface. The air parcels are assumed to be the same height as the canopy. After an air parcel comes in contact with a surface 'a', the parcel experiences a quiescent period, where little energy exchange occurs and is reflected by minimal temperature change with time 'e'. Eventually, the parcel exchanges energy and mass with the surface and, in this period, the parcel heats up as indicated by the red color in 'b' as captured by temperature measured with fine wire thermocouples 'f'. A new, cool parcel of air will sweep in and force the warmer air parcel to eject out from the surface 'c'. This action is captured as a sharp decline in the temperature trace 'g' as the cool air parcel replaces the warmer one. The cycle then continues to repeat itself (d and h).
Movie 1. Animation of the wind interacting with a plant canopy that was generated using a Large-Eddy Simulation model (created by Li Fitzmaurice and KT Paw U). Top panel is represents the view from the side of the canopy and the bottom panel represents the view looking down on the canopy. Click here to view movie.
Figure 3. Theoretical representation of air temperature trace capturing the sensible heat flux portion of surface renewal. The Van Atta procedure8 is used to resolve the ramp amplitude and ramp period from the air temperature data for the surface renewal calculation details of the mathematics used to extract this signal from real data is described in3,11-13.
Figure 4. Instrumentation needed to measure soil heat flux (G). On the left, a soil heat flux plate is being inserted at a depth 0.05 m. The soil thermocouples, on the right, are inserted at an angle from about 0.04-0.01 m depth where the cable end is at the deeper depth. The thermocouples measure the temperature change from the beginning to the end of the sampling period (30 min).
Figure 5. Net radiometer used for Rn measurements in the surface renewal system. The leveling bubble is apparent in this image.
Figure 6. Fine wire chromel-constantan thermocouples (13 μm diameter) used for sensible heat measurements (H) in the surface renewal system.
Figure 7. Sonic anemometer used for eddy covariance measurements to calibrate surface renewal. Instrument shown here is installed on a tower over a bare soil surface.
Figure 8. Data logger with the compact flash module (right hand side of image) used for the SR system. See Table 1 for wire details for all sensors. Click here to view larger figure.
Figure 9. Plot of air temperature captured with a fine wire thermocouple. Compare actual data to the theoretical data (presented in Figures 2 and 3) demonstrating the need for mathematical solutions to extract the ramp signals from these traces. See details in12,13. Click here to view larger figure.
Figure 10. Energy balance outputs (net radiation, Rn; ground heat flux, G; sensible heat flux, H; and latent heat flux, LE) measured over five days. Data taken from6. Click here to view larger figure.
Figure 11. Cumulative daily evapotranspiration measured by the SR flux tower and a weighing lysimeter in a wheat field. Data taken from6. Click here to view larger figure.
Figure 12. Captured window image from Surface Renewal/Eddy Covariance Facebook page established to capture web based resources in a single location. Click here to view larger figure.
Sensor | Sensor wire color or Port | Datalogger channel or Port |
Air thermocouple | Purple | 1H |
Red | 1L | |
Limpar | Signal ground | |
Net radiometer | White | 2H |
Green | 2L | |
Shield (bare) | Signal ground | |
Jumper wire | 2L to Signal ground | |
Ground heat flux plate | Black | 3H |
Red | 3L | |
Shield (bare) | Signal ground | |
Ground heat flux plate | Black | 4H |
Red | 4L | |
Shield (bare) | Signal ground | |
Soil thermocouple | Purple | 5H |
Red | 5L | |
Shield (bare) | Signal ground | |
Sonic anemometer | RX | C7 |
TX | C8 | |
Serial reference | G | |
+PWR | 12V | |
PWR reference | G | |
Earth ground | G |
Table 1. Sensor wiring details for a dual setup of SR and Eddy Covariance.
The surface renewal method presents a tangible opportunity to develop a stand-alone and inexpensive technique to quantify crop water use in real time. Recent advances in signal processing, data logger programming, calibration, and data management have brought this goal into clearer focus. This manuscript and our recently developed turnkey data logger program6 render advanced micrometeorological methods more accessible for agricultural researchers. The output table from the turnkey data program that contains the energy balance terms and the diagnostics variables can be downloaded using a remote or direct connection, adding significant convenience for program users during site visits. We anticipate future releases of updated versions of the program as this is an ongoing project in our research efforts (stay tuned at the Surface Renewal Eddy Covariance Facebook page Figure 12).
In its current state, SR still requires calibration by eddy covariance, which involves the use of expensive and highly technical sonic anemometers. SR can only become a stand-alone technique by the elimination of this calibration. We are currently focused on solving this problem and hope to advance SR as a self-calibrated technique in the near future.
The fine wire thermocouple used for SR analysis presents a few problems for ease of use of this method under field conditions. Spider webs growing on the thermocouple, or nearby plant shoots, can cause the measuring junction to break particularly in windy conditions. Regular cleaning of the thermocouple is needed to alleviate this problem. The net radiometer surfaces also require regular cleaning, particularly at field sites with many birds. The current tower setup is also quite bulky and for some growing situations (e.g. vineyards) its positioning within an interrow blocks the passage of tractors and other equipment. Tractor passes through adjacent rows (particularly the row just south of the station) can also damage sensors, and in some situations equipment needs to be partially removed prior to this grower practice. We recommend that scientists visit the site and maintain the instruments weekly or biweekly.
Current technologies for data acquisition and storage have exhibited important flaws that limit the potential of SR. For instance, data loss can occur when memory cards become corrupted. Also, the data logger software is rigid and requires complex programming to be adapted to SR. User friendly data acquisition devices built specifically for SR would drastically improve performance of the system.
The authors have nothing to disclose.
Partial support for this research was provided by J. Lohr Vineyards & Wines, the National Grape and Wine Institute, a NIFA Specialty Crops Research Initiative grant to AJM, and USDA-ARS CRIS funding (Research Project #5306-21220-004-00).
Equipment/Material | Company | Catalog Number | |
Datalogger | Campbell Scientific, Inc. | CR1000 | |
Datalogger Enclosure | Campbell Scientific, Inc. | ENC12/14-SC | |
Tower (6 ft) with grounding & lightning rods | Campbell Scientific, Inc. | CM6 | |
Cross arm (4 ft) | Campbell Scientific, Inc. | CM204 | |
Nu-rail crossover fitting | Campbell Scientific, Inc. | 17953 | |
Power supply (12 V) with regulator & battery | Campbell Scientific, Inc. | PS100 | |
Charger Regulator (12 V) | Campbell Scientific, Inc. | CH100 | |
Battery Extension Cable | Campbell Scientific, Inc. | 6186 | |
Thermocouple Extension Cable | Campbell Scientific, Inc. | FWC-20 | |
Thermocouples | Campbell Scientific, Inc. | FW3 | |
3D sonic anemometer with long neck | RM Young Company | 81000 RE | |
8 conductor cable for anemometer | RM Young Company | 18660 | |
Soil heat flux plates | REBS, Inc. | HFT3.1 | |
Soil thermocouples | Campbell Scientific, Inc. | TCAV | |
Net radiometer with cable | Kipp and Zonen, Inc. | NR Lite 2 | |
Heavy duty pole mount for radiometer | Kipp and Zonen, Inc. | L-CMB1 |