The Heat Ratio Method (HRM) is a scientific principle for the measurement of sap flow, or water use, in plants. HRM was developed by scientists at the University of Western Australia in the late 1990's in response to the limitations of existing sap flow measurement techniques. The principal scientist in the development of HRM was Dr Stephen Burgess who was the lead author in the seminal paper published in Tree Physiology in 2001.
ICT International is the only manufacturer in the world of HRM sap flow sensors and data loggers. The SFM1 Sap Flow Meter is the instrument which contains everything needed to measure sap flow via HRM: sensors, data logger, software interface, and internal battery which is recharged via an external solar panel. The SFM1 Sap Flow Meter can store data as raw temperature measurements or heat velocity measurements according to HRM. These data can be downloaded into Sap Flow Tool software for conversion to sap velocity, sap flow and total plant water use.
Developed by the University of Western Australia and partner organisations, ICRAF and CSIRO, the HRM principle has been validated against gravimetric measurements of transpiration and used in published sap flow research since 1998. Burgess et al. (2001) developed the theory of HRM and Bleby et al. (2004) validated the technique:
Burgess, S.S.O., M.A. Adams, N.C. Turner, C.R. Beverly, C.K. Ong, A.A.H. Khan and T.M. Bleby (2001) An improved heat pulse method to measure low and reverse rates of sap flow in woody plants. Tree Physiology, 21: 589-598.
Bleby, T.M., S.S.O. Burgess and M. A. Adams (2004) A validation, comparison and error analysis of two heat-pulse methods for measuring sap flow in Eucalyptus marginata saplings. Functional Plant Biology, 36: 645-658.
Heat Ratio Method (HRM) is an improvement of the Compensation Heat Pulse Method (CHPM) and is now widely regarded as having superseded that technique. The major point of difference between HRM and CHPM is the former is based on a ratio principle whereas the latter is based on a time principle. Therefore, HRM has the ability to measure high, low, zero and reverse rates of sap flow. In contrast, CHPM can only measure high rates of flow. This limitation means the CHPM is highly inaccurate in determining total sap flow.
Burgess et al. (2001) thoroughly explain how HRM works from first principles. The SFM1 Sap Flow Meter Manual also details HRM in Chapter 6 and a summary of the theory is found in the HRM Explained presentation.
Briefly, temperature sensors spaced equidistant above (downstream) and below (upstream) a line heater measure initial temperature conditions for about 30 seconds. A pulse of heat is fired along the heater needle for 2.68 seconds. The system is left to equilibriate for 60 seconds and then temperature downstream and upstream the heater needle is measured again for 40 seconds. The rise in temperature from initial conditions to post heat pulse conditions in the downstream and upstream temperature sensors are noted.
The ratio of the downstream to upstream temperature rise is then calculated and entered into a formula to further calculate heat velocity (vh):
vh = heat velocity
k = thermal diffusivity
v1 = average increase temperature downstream
v2 = average increase temperature upstream
x = distance of temperature needles from heater needle
3600 = converting from seconds to hours
The Sap Flow Tool software is capable of converting vh into sap velocity and volumetric sap flow values once additional parameters are known. These parameters include thermal diffusivity, wood density and moisture content, bark depth, sapwood depth, and stem diameter.
|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|
|Computer Interface||USB, Wireless RF 2.4 GHz|
|Data Storage||MicroSD Card|
|Memory Capacity||Up to 16GB, 4GB microSD card included.|
|Heat Pulse||User Adjustable: 20 Joules (default) approx. Equivalent to a 2.5 second heat pulse duration, auto scaling.
User Adjustable: Minimum interval, 3 minutes, recommended minimum 10 minutes.
|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|
|Dimensions L x W X D||170 x 80 x 35 mm|
|Internal Battery Specifications|
|960mAh Lithium Polymer, 4.20 Volts fully charged|
|External Power Requirements|
|Bus Power||8-30 Volts DC, non-polarised, current draw is 190mA maximum at 17 volts per logger|
|USB Power||5 Volts DC|
|Internal Charge Rate|
|Bus Power||60mA – 200mA Variable internal charge rate, maximum charge rate of 200mA active when the external voltage rises above 16 Volts DC|
|USB Power||100mA fixed charge rate|
|Internal Power Management|
|Fully Charged Battery||4.20 Volts|
|Low Power Mode||3.60 Volts – Instrument ceases to take measurements|
|Discharged Battery||2.90 Volts – Instrument automatically switches off at and below this voltage when no external power connected.|
|Battery Life varies|
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
Bleby, T. M., Burgess, S. S. O., & 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. https://doi.org/10.1071/FP04013
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., & 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. https://doi.org/10.1002/ece3.44
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. O., Adams, M. A., Turner, N. C., Beverly, C. R., Ong, C. K., Khan, A. A. H., & 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
Burgess, S. S. O., & Dawson, T. E. (2004). The contribution of fog to the water relations of Sequoia sempervirens (D. Don): Foliar uptake and prevention of dehydration. Plant, Cell & Environment, 27(8), 1023–1034. https://doi.org/10.1111/j.1365-3040.2004.01207.x
Carbone, M. S., Williams, A. P., 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
Dawson, T. E., Burgess, S. S. O., Tu, K. P., Oliveira, R. S., Santiago, L. S., Fisher, J. B., … Ambrose, A. R. (2007). Nighttime transpiration in woody plants from contrasting ecosystems. Tree Physiology, 27(4), 561–575. https://doi.org/10.1093/treephys/27.4.561
de Dios, V. R., Díaz‐Sierra, R., Goulden, M. L., Barton, C. V. M., 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
Doronila, A. I., & Forster, M. A. (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
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
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.
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. O. (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
Rosado, B. H. P., Oliveira, R. S., Joly, C. A., Aidar, M. P. M., & Burgess, S. S. O. (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
Van de Wal, B. A. E., 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. B., Lewis, J. D., Medlyn, B., Barton, C. V. M., 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