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Enabling better global research outcomes in soil, plant & environmental monitoring.

SFM1 Sap Flow Meter

The measurement of sap flow in trees enables the calculation of daily and seasonal water use. Using this, irrigation requirements (urban parks, orchards & forests), tree health, the impact of climate change and calculation of carbon storage can all be derived through sap flow measurement. The SFM1x Sap Flow Meter quantifies tree water use in litres by measurement of sap flow.

The SFM1x is a self-contained instrument comprising sensor, signal processing, data storage and data transmission. The SFM1x is available with Internet of Things (IoT) connection, including LoRaWAN, CAT-M1 and NBIoT. The standard Bluetooth connectivity enables quick wireless device configuration, and data transfer in the field once installed.

IoT connectivity enables the SFM1x to transmit data directly to the cloud. This allows for further processing and analysis, visualisation and presentation, or integration into existing dashboards through an Application Programming Interface (API).

Using the established Heat Ratio Method, the SFM1x can measure high, low, and reverse flow rates in small woody stems and roots, as well as large trees. The SFM1x remains key for both researchers and industry to understand tree water use. Typically raw temperatures are stored and converted to sap velocity.

The SFM1x can optionally measure sap flow using the Compensated Heat Pulse Method (CHPM) and TMax methods. These methods can be used because the SFM1x stores the raw temperature data (recorded every 1 second) as JSON or CSV files. The JSON or CSV file result in ease of data access for the additional processing required outside of the instrument. The use of Senaps can allow this processing to be undertaken in the cloud in real time (this will incur additional charges).

The Sap Flow Meter (HRM30 and SFM1) has over 400 listings in Google Scholar, highlighting the wide acceptance by the research community. ICT International has an active library of over 75 leading publications that can be accessed here.

Communication Technology Options

The SFM1x is an IoT enabled Sap Flow Meter is available in the following versions:

  • SFM1C uses CATM1
  • SFM1L uses LoRaWAN
  • SFM1B uses a dedicated, long range Bluetooth with external antenna

The use of these communication technologies enables the SFM1x to be deployed wherever there is cellular network coverage, or if there is no cellular coverage, a network using LoRaWAN and subsequent internet connection via 4G or satellite backhaul.

All SFM1x versions contain a Bluetooth module with an internal antenna for wireless data access and configuration of the unit. The SFM1B has a dedicated external Bluetooth antenna allowing long range connection.

Applications

The principles behind the SFM1x – the Heat Ratio Method – have been used to measure plant and tree water use in many applications. Example applications of the SFM1 and HRM30 can be found in:

Data Analysis and Visualisation

Data from the SFM1x can be downloaded to be analysed in many statistical packages or sent via an API to a data visualisation (dashboard) of choice. Data can be downloaded directly from the SFM1x, or from the cloud when using the SFM1C or SFM1L.

Analysis

When data is downloaded from the cloud, subsequent analysis can be performed using statistical packages. Advanced cloud integration solutions, which provide programming and modelling environments for further scientific analysis, machine learning and management decision making applications are available. Please consult ICT International for more details.

ICT International have integration solutions for the analysis of SFM1x data (CSV or JSON) using:

  • R and R Studio
  • Python
  • ArcGIS/QGIS
  • Various Dashboards (customer supplied)

Advanced cloud integration programming and modelling environments include:

  • SENAPS
  • Hitachi Vantara

These provide the ability to undertake all analysis in a cloud environment, removing the need for static processing with downloaded data.

For the static processing of data, data from the SFM1x can be downloaded and analysed using the proven ICT International Dataview and Sap Flow Tool software. This is ideal for those who are upgrading their SFM1 to an SFM1x.

Visualisation

Providing real time information of the tree condition and water use, SFM1x data can be integrated into specific tools. These tools can be web based or dedicated apps using the API and JSON feeds. The results are suitable for arborists and the public when visiting an arboretum or tree canopy walk.

Visualisation solutions include:

  • Geospatial Integration (ArcGIS/QGIS or similar)
  • Various Dashboards (customer supplied)

Data from the SFM1x can also be downloaded and processed using ICT International Sap Flow Tool software. The software also allows for instant visualising of sap flow in 2- and 3- dimensions.

The Measurement Principle

Using the Heat Ratio Method, the SFM1x can measure plant water use when the stem or root diameter is greater than 10mm, including:

  • Low & zero sap flow rates
  • Reverse sap flow rates
  • Night-time water use
  • High flow rates

Advanced users may choose to use JSON files containing the raw temperature data for subsequent processing and analysis.

The dynamic reference list maintained by ICT International can be found here.

Specifications common to all Variants of the SFM1x:

MEASUREMENT

Output Options Raw Temperatures: °C
Heat Pulse Velocity: cm hr-1
Sap Velocity: cm hr-1
Sap Flow: cm3 hr-1 (Litres hr-1)
Range -100 to +100 cm hr-1
Resolution 0.01 cm hr-1
Accuracy 0.5 cm hr-1
Measurement Duration 120 seconds
User Adjustable Heat Pulse 20 Joules (default) approx. Maximum 40 Joules. 20 Joule pulse is equivalent to a 2.5 second heat pulse duration, auto scaling.
User Adjustable Logging Interval Minimum interval 3 minutes, recommended minimum 10 minutes.

NEEDLE DESIGN

Needle Diameter 1.3 mm
Needle Length 35 mm
Measurement Positions 2 per measurement needle
Measurement Spacings 7.5 mm and 22.5 mm from the needle tip

INSTRUMENT DESIGN

Dimensions L x W X D 170 x 80 x 35 mm
Weight 400 g

OPERATING CONDITIONS

Temperature Range -10 to 50°C
R/H Range 0-99%

INTERNAL POWER AND POWER MANAGEMENT

Battery Specifications 3300mAh Lithium Ion, 4.20 Volts fully charged
Fully Charged Battery 4.20 Volts
Low Power Mode 3.60 Volts – Instrument ceases to take measurements. Resumes measurement at 3.70 Volts
Discharged Battery 2.90 Volts – Instrument automatically switches off at and below this voltage when no external power connected. Reconnects when battery returns to 3.1 Volts.
Battery Life At the recommended configuration of 20 Joules at 10-minute intervals, upto 40 hours battery life has been observed without additional power supply. With a recommended power source connected, operation can be continuous.
Bus Power Source 60mA – 200mA Variable internal charge rate, maximum charge rate of 200mA active when the external voltage rises above 16 Volts DC
USB Power Source 100mA fixed charge rate
External Power Requirements
Bus Power 8-30 Volts DC, non-polarised, current draw is 100mA at 20 volts per SFM
USB Power 5 Volts DC

 
 

SFM1 – SFM1x Product Variations

SFM1x Variants SFM1B SFM1C SFM1L
Communications Short Range Bluetooth Yes Yes Yes
Long Range Bluetooth Yes
CAT-M1/LTE-M Yes
LoRaWAN Yes (L1 = Global, L2 = China)
Data Output File Types BIN, CSV CSV, JSON BIN, CSV
Data Storage MicroSD Card
Memory Capacity Up to 16GB, 8GB MicroSD card included.
Manufacturer’s Product Codes SFM1x-UB SFM1x-C SFM1x-L1 or -L2
  • CH24 - 24 Volt Power Supply
    The CH24 is a 100 - 240Volts AC Mains to 24Volts DC power supply adapter; capable of outputting up to 2.5Amps. For most ICT Instruments.
  • ICT CIS - Cloud Data Analysis and Display
    The ICT CIS and DataView.
  • SFM-SK1 Installation Kit
    SFM-SK1 Installation kit
  • SFM-DR Dremel 8000
    Dremel 8000 for SFM1 installation
  • DR Dremel 800 Chuck Collet
    This DR Dremel 800 Collet is necessary in order that the small diameter drill bits, as used for the installation of the SFM1 needles, can be inserted into the SFM-DR Dremel Drill Chuck.
  • SFT1 Sap Flow Tool
    Sap Flow Tool software for HFD and HRM. Single License. Unlimited access to any number HRM or HFD datasets. Configured to analyse HRMx, CHPM, Tmax data from the SFM Sap Flow Meter. Visualise PSY1, soil moisture, and meteorological data.
  • SP22 - 20 Watt Solar Panel
    SP22 - 20 Watt Solar Panel with 4m cable suitable for powering our SFM1, PSY1, HFD, SOM1, SMM1 etc products.
  • The HRM Test Block
    The HRM Sap Flow Meter Test Block is a functional verification standard for use with the HRM Sap Flow Meter.

Ambrose, A. R., Sillett, S. C., Koch, G. W., Van Pelt, R., Antoine, M. E., & Dawson, T. E. (2010). Effects of height on treetop transpiration and stomatal conductance in coast redwood (Sequoia sempervirens). Tree Physiology, 30(10), 1260–1272. https://doi.org/10.1093/treephys/tpq064

Bader, M. K.-F., & Leuzinger, S. (2019). Hydraulic Coupling of a Leafless Kauri Tree Remnant to Conspecific Hosts. iScience. https://doi.org/10.1016/j.isci.2019.05.009

Barron-Gafford, G. A., Sanchez-Cañete, E. P., Minor, R. L., Hendryx, S. M., Lee, E., Sutter, L. F., Tran, N., Parra, E., Colella, T., Murphy, P. C., Hamerlynck, E. P., Kumar, P. and Scott, R. L. (2017), Impacts of hydraulic redistribution on grass–tree competition vs facilitation in a semi-arid savanna. New Phytologist, 215(4), 1451–1461. https://doi.org/10.1111/nph.14693

Bleby, T. M., Burgess, S. S., & Adams, M. A. (2004). A validation, comparison and error analysis of two heat-pulse methods for measuring sap flow in Eucalyptus marginata saplings. Functional Plant Biology, 31(6), 645-658. http://www.publish.csiro.au/paper/FP04013.htm

Buckley, T. N., Turnbull, T. L., Pfautsch, S., & Adams, M. A. (2011). Nocturnal water loss in mature subalpine Eucalyptus delegatensis tall open forests and adjacent E. pauciflora woodlands. Ecology and evolution, 1(3), 435-450. http://onlinelibrary.wiley.com/doi/10.1002/ece3.44/pdf

Buckley, T. N., Turnbull, T. L., & Adams, M. A. (2012). Simple models for stomatal conductance derived from a process model: Cross-validation against sap flux data. Plant, Cell & Environment, 35(9), 1647–1662. https://doi.org/10.1111/j.1365-3040.2012.02515.x

Buckley, T. N., Turnbull, T. L., Pfautsch, S., Gharun, M., & Adams, M. A. (2012). Differences in water use between mature and post-fire regrowth stands of subalpine Eucalyptus delegatensis R. Baker. Forest Ecology and Management, 270, 1–10. https://doi.org/10.1016/j.foreco.2012.01.008

Burgess, S. S., Adams, M. A., Turner, N. C., Beverly, C. R., Ong, C. K., Khan, A. A., & Bleby, T. M. (2001). An improved heat pulse method to measure low and reverse rates of sap flow in woody plants. Tree Physiology, 21(9), 589–598. https://doi.org/10.1093/treephys/21.9.589

Burgess, S. S. O., M. A. Adams, N. C. Turner, C. K. Ong, A. A. H. Khan, C. R. Beverly and T. M. Bleby (2001) Corrections: An improved heat pulse method to measure low and reverse rates of sap flow in woody plants. Tree Physiology, 21(16), 1157. doi:10.1093/treephys/21.16.1157 http://treephys.oxfordjournals.org/content/21/16/1157.full.pdf

Carbone, M. S., Park Williams, A., Ambrose, A. R., Boot, C. M., Bradley, E. S., Dawson, T. E., … & Still, C. J. (2013). Cloud shading and fog drip influence the metabolism of a coastal pine ecosystem. Global Change Biology, 19(2), 484–497. https://doi.org/10.1111/gcb.12054

De Groote, S. (2013). Impact of dew and rain on the water relations of the mangrove species Avicennia marina (Forssk.) Vierh (Doctoral dissertation, Master’s thesis, University Ghent, Faculty of Bioscience Engineering). Click to view Paper

Doronila, A. I. (2015). Performance Measurement Via Sap Flow Monitoring of Three Eucalyptus Species for Mine Site and Dryland Salinity Phytoremediation. International Journal of Phytoremediation, 17(2), 101–108. https://doi.org/10.1080/15226514.2013.850466

Downey A., Winter, W., Cull, P. (2013). Smart trees, smart kids – empowering a generation through the science of sap flow. ICT International. Downey et al Smart Trees Smart Kids – Empowering a Generation through the Science of Sap Flow

Drake, P. L., Coleman, B. F., & Vogwill, R. (2013). The response of semi-arid ephemeral wetland plants to flooding: Linking water use to hydrological processes. Ecohydrology, 6(5), 852–862. https://doi.org/10.1002/eco.1309

Eliades, M., Bruggeman, A., Djuma, H., and Lubczynski, M. W. (2018). Tree Water Dynamics in a Semi-Arid, Pinus brutia Forest. Water, 10(8), 1039. https://doi.org/10.3390/w10081039

Eliades, M., Bruggeman, A., Lubczynski, M. W., Christou, A., Camera, C., Djuma, H. (2017). The water balance components of Mediterranean pine trees on a steep mountain slope during two hydrologically contrasting years. Journal of Hydrology, 562, 712–724. https://doi.org/10.1016/j.jhydrol.2018.05.048

Eller, C. B., Lima, A. L., & Oliveira, R. S. (2013). Foliar uptake of fog water and transport belowground alleviates drought effects in the cloud forest tree species, Drimys brasiliensis (Winteraceae). New Phytologist, 199(1), 151–162. https://doi.org/10.1111/nph.12248

Falge, E., & Meixner, F. X. (2008). Validation of a 3D gas exchange model for a Picea abies canopy in the Fichtelgebirge, Germany. In Geophys. Res. Abstr (Vol. 10). Download PDF.

Fuchs, S., Leuschner, C., Link, R., Coners, H., Schuldt, B. (2017). Calibration and comparison of thermal dissipation, heat ratio and heat field deformation sap flow probes for diffuse-porous trees. Agricultural and Forest Meteorology, 244–245, 151–161. https://doi.org/10.1016/j.agrformet.2017.04.003

Gharun, M., Turnbull, T. L., & Adams, M. A. (2013). Stand water use status in relation to fire in a mixed species eucalypt forest. Forest Ecology and Management, 304, 162–170. https://doi.org/10.1016/j.foreco.2013.05.002

Gharun, M., Turnbull, T. L., Pfautsch, S., & Adams, M. A. (2015). Stomatal structure and physiology do not explain differences in water use among montane eucalypts. Oecologia, 177(4), 1171–1181. https://doi.org/10.1007/s00442-015-3252-3

Mitchell, P. J., Veneklaas, E., Lambers, H., & Burgess, S. S. (2009). Partitioning of evapotranspiration in a semi-arid eucalypt woodland in south-western Australia. Agricultural and Forest Meteorology, 149(1), 25–37. https://doi.org/10.1016/j.agrformet.2008.07.008

Palmer, A. R., Fuentes, S., Taylor, D., Macinnis‐Ng, C., Zeppel, M., Yunusa, I., & Eamus, D. (2010). Towards a spatial understanding of water use of several land-cover classes: An examination of relationships amongst pre-dawn leaf water potential, vegetation water use, aridity and MODIS LAI. Ecohydrology, 3(1), 1–10. https://doi.org/10.1002/eco.63

Patankar, R., Quinton, W. L., Hayashi, M., & Baltzer, J. L. (2015). Sap flow responses to seasonal thaw and permafrost degradation in a subarctic boreal peatland. Trees, 29(1), 129–142. https://doi.org/10.1007/s00468-014-1097-8

Pfautsch, S., Dodson, W., Madden, S., & Adams, M. A. (2015). Assessing the impact of large-scale water table modifications on riparian trees: A case study from Australia. Ecohydrology, 8(4), 642–651. https://doi.org/10.1002/eco.1531

Pfautsch, S., Keitel, C., Turnbull, T. L., Braimbridge, M. J., Wright, T. E., Simpson, R. R., … & Adams, M. A. (2011). Diurnal patterns of water use in Eucalyptus victrix indicate pronounced desiccation–rehydration cycles despite unlimited water supply. Tree Physiology, 31(10), 1041–1051. https://doi.org/10.1093/treephys/tpr082

Pfautsch, S., Peri, P. L., Macfarlane, C., van Ogtrop, F., & Adams, M. A. (2014). Relating water use to morphology and environment of Nothofagus from the world’s most southern forests. Trees, 28(1), 125–136. https://doi.org/10.1007/s00468-013-0935-4

Reddy, K. S., Sekhar, K. M., Reddy, A. R. (2017). Genotypic variation in tolerance to drought stress is highly coordinated with hydraulic conductivity–photosynthesis interplay and aquaporin expression in field-grown mulberry (Morus spp.). Tree Physiology, 37(7), 926–937. https://doi.org/10.1093/treephys/tpx051

Resco de Dios, V., Díaz‐Sierra, R., Goulden, M. L., Barton, C. V., Boer, M. M., Gessler, A., … & Tissue, D. T. (2013). Woody clockworks: Circadian regulation of night-time water use in Eucalyptus globulus. New Phytologist, 200(3), 743–752. https://doi.org/10.1111/nph.12382

Rosado, B. H., Oliveira, R. S., Joly, C. A., Aidar, M. P., & Burgess, S. S. (2012). Diversity in nighttime transpiration behavior of woody species of the Atlantic Rain Forest, Brazil. Agricultural and Forest Meteorology, 158–159, 13–20. https://doi.org/10.1016/j.agrformet.2012.02.002

Staudt, K., Serafimovich, A., Siebicke, L., Pyles, R. D., & Falge, E. (2011). Vertical structure of evapotranspiration at a forest site (a case study). Agricultural and Forest Meteorology, 151(6), 709–729. https://doi.org/10.1016/j.agrformet.2010.10.009

Thom, J. K., Szota, C., Fletcher, T. D., Grey, V., Coutts, A. M., & Livesley, S. J. (2019). Transpiration and the water balance of tree-based stormwater control measures. Novatech 2019: Urban Water Planning and Technologies for Sustainable Management. Presented at the Novatech 2019, Lyon, France. Retrieved from www.novatech.graie.org/documents/auteurs/1D24-096THO.pdf

Van de Wal, B. A., Guyot, A., Lovelock, C. E., Lockington, D. A., & Steppe, K. (2015). Influence of temporospatial variation in sap flux density on estimates of whole-tree water use in Avicennia marina. Trees, 29(1), 215–222. https://doi.org/10.1007/s00468-014-1105-z

Zeppel, M. J., Lewis, J. D., Medlyn, B., Barton, C. V., Duursma, R. A., Eamus, D., … & Tissue, D. T. (2011). Interactive effects of elevated CO2 and drought on nocturnal water fluxes in Eucalyptus saligna. Tree Physiology, 31(9), 932–944. https://doi.org/10.1093/treephys/tpr024

 

Japanese Research Articles (written in Japanese)

Takeuchi, S., Matsuda, A., & Nishi, Y. (2014). Sap flow movement on Magnolia grandiflora L. and Acer palmatum Thunb. after transplanting for two years. Journal of the Japanese Society of Revegetation Technology, 40(1), 60–65. https://doi.org/10.7211/jjsrt.40.60

Takeuchi, S., Morita, K., Kishimoto, T., & Shinozaki, K. (2012). Sap Flow movement on Magnolia grandiflora L. through the process of transplanting work. Journal of the Japanese Society of Revegetation Technology, 38(1), 27–32. https://doi.org/10.7211/jjsrt.38.27

Takeuchi, S., Takahashi, R., & Iida, S. (2016). Growth diagnosis of a transplanted tree based on sap flow measurement: A case study of Magnolia grandiflora L. for four years after transplantation. Journal of the Japanese Society of Revegetation Technology, 42(1), 110–115. https://doi.org/10.7211/jjsrt.42.110