Earth:Evapotranspiration

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Short description: Process by when water moves into the air from plants and soil.
Water cycle of the Earth's surface, showing the individual components of transpiration and evaporation that make up evapotranspiration. Other closely related processes shown are runoff and groundwater recharge.
pet
Global distribution of potential evapotranspiration averaged over the years 1981–2010 from the CHELSA-BIOCLIM+ data set[1]

Evapotranspiration (ET) is the combined processes which move water from the Earth's surface into the atmosphere. It covers both water evaporation (movement of water to the air directly from soil, canopies, and water bodies) and transpiration (evaporation that occurs through the stomata, or openings, in plant leaves). Evapotranspiration is an important part of the local water cycle and climate, and measurement of it plays a key role in agricultural irrigation and water resource management.[2]

Definition of evapotranspiration

Evapotranspiration is a combination of evaporation and transpiration, measured in order to better understand crop water requirements, irrigation scheduling,[3] and watershed management.[4] The two key components of evapotranspiration are:

  • Evaporation: the movement of water directly to the air from sources such as the soil and water bodies. It can be affected by factors including heat, humidity, solar radiation and wind speed.[5]:{{{1}}}
  • Transpiration: the movement of water from root systems, through a plant, and exit into the air as water vapor. This exit occurs through stomata in the plant. Rate of transpiration can be influenced by factors including plant type, soil type, weather conditions and water content, and also cultivation practices.[5]:{{{1}}}

Evapotranspiration is typically measured in millimeters of water (i.e. volume of water moved per unit area of the Earth's surface) in a set unit of time.[5]:{{{1}}} Globally, it is estimated that on average between three-fifths and three-quarters of land precipitation is returned to the atmosphere via evapotranspiration.[6][7][8]:{{{1}}}

Evapotranspiration does not, in general, account for other mechanisms which are involved in returning water to the atmosphere, though some of these, such as snow and ice sublimation in regions of high elevation or high latitude, can make a large contribution to atmospheric moisture even under standard conditions.

Factors that impact evapotranspiration levels

Primary factors

Because evaporation and transpiration occur when water moves into the air, levels of evapotranspiration in a given area are primarily controlled by:[9]

  • the amount of water present;
  • the amount of energy present in the air and soil (e.g. heat); and
  • the ability of the atmosphere to take up water (humidity).

Secondary factors

Vegetation type

Vegetation type impacts levels of evapotranspiration.[10] For example:

  • Herbaceous plants generally transpire less than woody plants, because they usually have less extensive foliage.
  • Plants with deep reaching roots can transpire water more constantly, because those roots can pull more water into the plant and leaves.
  • Conifer forests tend to have higher rates of evapotranspiration than deciduous broadleaf forests, particularly in the dormant winter and early spring seasons, because they are evergreen.[11]

Vegetation coverage

Transpiration is a larger component of evapotranspiration (relative to evaporation) in vegetation-abundant areas.[12] As a result, denser vegetation, like forests, may increase evapotranspiration and reduce water yield.

Two exceptions to this are cloud forests and rainforests. In cloud forests, trees collect the liquid water in fog or low clouds onto their surface, which eventually drips down to the ground. These trees still contribute to evapotranspiration, but often collect more water than they evaporate or transpire.[13][14] In rainforests, water yield is increased (compared to cleared, unforested land in the same climatic zone) as evapotranspiration increases humidity within the forest (a portion of which condenses and returns quickly as precipitation experienced at ground level as rain). The density of the vegetation blocks sunlight and reduces temperatures at ground level (thereby reducing losses due to surface evaporation), and reduces wind speeds (thereby reducing the loss of airborne moisture). The combined effect results in increased surface stream flows and a higher ground water table whilst the rainforest is preserved. Clearing of rainforests frequently leads to desertification as ground level temperatures and wind speeds increase, vegetation cover is lost or intentionally destroyed by clearing and burning, soil moisture is reduced by wind, and soils are easily eroded by high wind and rainfall events.[15][16]

Soil and irrigation

In areas that are not irrigated, actual evapotranspiration is usually no greater than precipitation, with some buffer and variations in time depending on the soil's ability to hold water. It will usually be less because some water will be lost due to percolation or surface runoff. An exception is areas with high water tables, where capillary action can cause water from the groundwater to rise through the soil matrix back to the surface. If potential evapotranspiration is greater than the actual precipitation, then soil will dry out until conditions stabilize, unless irrigation is used.

Measurement of evapotranspiration

Direct measurement

Design for a lysimeter
Main page: Biology:Lysimeter

Evapotranspiration can be measured directly with a weighing or pan lysimeter. A lysimeter continuously measures the weight of a plant and associated soil, and any water added by precipitation or irrigation. The change in storage of water in the soil is then modeled by measuring the change in weight. When used properly, this allows for precise measurement of evapotranspiration over small areas.

Indirect estimation

Because atmospheric vapor flux is difficult or time-consuming to measure directly,[8]:{{{1}}} evapotranspiration is typically estimated by one of several different methods that do not rely on direct measurement.

Catchment water balance

Evapotranspiration may be estimated by evaluating the water balance equation for a given area:. The water balance equation relates the change in water stored within the basin (S) to its input and outputs:

[math]\displaystyle{ \Delta S = P - ET - Q - D \,\! }[/math]

In the equation, the change in water stored within the basin (ΔS) is related to precipitation (P) (water going into the basin), and evapotranspiration (ET), streamflow (Q), and groundwater recharge (D) (water leaving the basin). By rearranging the equation, ET can be estimated if values for the other variables are known:

[math]\displaystyle{ ET = P -\Delta S - Q - D \,\! }[/math]

Energy balance

A second methodology for estimation is by calculating the energy balance.

[math]\displaystyle{ \lambda E = R_n - G - H \,\! }[/math]

where λE is the energy needed to change the phase of water from liquid to gas, Rn is the net radiation, G is the soil heat flux and H is the sensible heat flux. Using instruments like a scintillometer, soil heat flux plates or radiation meters, the components of the energy balance can be calculated and the energy available for actual evapotranspiration can be solved.

The SEBAL and METRIC algorithms solve for the energy balance at the Earth's surface using satellite imagery. This allows for both actual and potential evapotranspiration to be calculated on a pixel-by-pixel basis. Evapotranspiration is a key indicator for water management and irrigation performance. SEBAL and METRIC can map these key indicators in time and space, for days, weeks or years.[17]

Estimation from meteorological data

Given meteorological data like wind, temperature, and humidity, reference ET can be calculated. The most general and widely used equation for calculating reference ET is the Penman equation. The Penman–Monteith variation is recommended by the Food and Agriculture Organization[18] and the American Society of Civil Engineers.[19] The simpler Blaney–Criddle equation was popular in the Western United States for many years but it is not as accurate in wet regions with higher humidity. Other equations for estimating evapotranspiration from meteorological data include the Makkink equation, which is simple but must be calibrated to a specific location, and the Hargreaves equations.

To convert the reference evapotranspiration to the actual crop evapotranspiration, a crop coefficient and a stress coefficient must be used. Crop coefficients, as used in many hydrological models, usually change over the year because crops are seasonal and, in general, plant behaviour varies over the year: perennial plants mature over multiple seasons, while annuals do not survive more than a few[clarification needed], so stress responses can significantly depend upon many aspects of plant type and condition.

Potential evapotranspiration

Monthly estimated potential evapotranspiration and measured pan evaporation for two locations in Hawaii, Hilo and Pahala
Main page: Earth:Potential evaporation

Potential evapotranspiration (PET) is the amount of water that would be evaporated and transpired by a specific crop, soil or ecosystem if there were sufficient water available. It is a reflection of the energy available to evaporate or transpire water, and of the wind available to transport the water vapor from the ground up into the lower atmosphere and away from the initial location. Often a value for the potential evapotranspiration is calculated at a nearby climatic station on a reference surface, conventionally on land dominated by short grass (though this may differ from station to station). This value is called the reference evapotranspiration (ET0). Actual evapotranspiration is said to equal potential evapotranspiration when there is ample water present. Evapotranspiration can never be greater than potential evapotranspiration, but can be lower if there is not enough water to be evaporated or plants are unable to transpire maturely and readily.

Some US states utilize a full cover alfalfa reference crop that is 0.5 m (1.6 ft) in height, rather than the general short green grass reference, due to the higher value of ET from the alfalfa reference.[20] Potential evapotranspiration is higher in the summer, on clearer and less cloudy days, and closer to the equator, because of the higher levels of solar radiation that provides the energy (heat) for evaporation. Potential evapotranspiration is also higher on windy days because the evaporated moisture can be quickly moved from the ground or plant surface before it precipitates, allowing more evaporation to fill its place.

Potential evapotranspiration is expressed in terms of a depth of water or soil moisture percentage, and can be graphed during the year (see figure).

Potential evapotranspiration is usually measured indirectly, from other climatic factors, but also depends on the surface type, such as free water (for lakes and oceans), the soil type for bare soil, and also the density and diversity of vegetation. Often a value for the potential evapotranspiration is calculated at a nearby climate station on a reference surface, conventionally on short grass (see above). This value is called the reference evapotranspiration, and can be converted to a potential evapotranspiration by multiplying by a surface coefficient. In agriculture, this is called a crop coefficient. The difference between potential evapotranspiration and actual precipitation is used in irrigation scheduling.

Average annual potential evapotranspiration is often compared to average annual precipitation, the symbol for which is P. The ratio of the two, P/PET, is the aridity index. A humid subtropical climate is a zone of climate with hot and humid summers, and cold to mild winters. Subarctic regions, between 50°N[21] and 70°N latitude, have short, mild summers and freezing winters depending on local climates. Precipitation and evapotranspiration is low (compared to warmer variants), and vegetation is characteristic of the coniferous/taiga forest.

List of remote sensing based evapotranspiration models

Classification of RS-based ET models based on sensible heat flux estimation approaches
Classification of RS-based ET models based on sensible heat flux estimation approaches

Calculation software

See also

References

  1. ↑ Brun, P., Zimmermann, N.E., Hari, C., Pellissier, L., Karger, D.N. (preprint): Global climate-related predictors at kilometre resolution for the past and future. Earth Syst. Sci. Data Discuss. https://doi.org/10.5194/essd-2022-212
  2. ↑ "Evapotranspiration - an overview | ScienceDirect Topics". https://www.sciencedirect.com/topics/agricultural-and-biological-sciences/evapotranspiration#:~:text=Evapotranspiration%20is%20considered%20as%20one,as%20well%20as%20agriculture%20practices.. 
  3. ↑ Goyal, Megh R.; Harmsen, Eric W. (2013-09-26) (in en). Evapotranspiration: Principles and Applications for Water Management. CRC Press. pp. xxi. ISBN 978-1-926895-58-1. https://books.google.com/books?id=iVHGAAAAQBAJ. 
  4. ↑ Vörösmarty, C. J.; Federer, C. A.; Schloss, A. L. (1998-06-25). "Potential evaporation functions compared on US watersheds: Possible implications for global-scale water balance and terrestrial ecosystem modeling" (in en). Journal of Hydrology 207 (3): 147–169. doi:10.1016/S0022-1694(98)00109-7. ISSN 0022-1694. Bibcode: 1998JHyd..207..147V. https://www.sciencedirect.com/science/article/pii/S0022169498001097. 
  5. ↑ 5.0 5.1 5.2 Allen, Rick G. (1998) (in en). Crop Evapotranspiration: Guidelines for Computing Crop Water Requirements. Food and Agriculture Organization of the United Nations. ISBN 978-92-5-104219-9. https://www.fao.org/3/X0490E/x0490e00.htm. 
  6. ↑ Jung, Martin; Reichstein, Markus; Ciais, Philippe; Seneviratne, Sonia I.; Sheffield, Justin; Goulden, Michael L.; Bonan, Gordon; Cescatti, Alessandro et al. (2010-10-21). "Recent decline in the global land evapotranspiration trend due to limited moisture supply" (in en). Nature 467 (7318): 951–954. doi:10.1038/nature09396. ISSN 1476-4687. PMID 20935626. Bibcode: 2010Natur.467..951J. https://www.nature.com/articles/nature09396. 
  7. ↑ Oki, Taikan; Kanae, Shinjiro (2006-08-25). "Global Hydrological Cycles and World Water Resources" (in EN). Science 313 (5790): 1068–1072. doi:10.1126/science.1128845. PMID 16931749. Bibcode: 2006Sci...313.1068O. https://www.science.org/doi/abs/10.1126/science.1128845. 
  8. ↑ 8.0 8.1 Alexandris, Stavros (2013-04-30) (in en). Evapotranspiration: An Overview. BoD – Books on Demand. ISBN 978-953-51-1115-3. https://books.google.com/books?id=m0mfDwAAQBAJ. 
  9. ↑ Alfieri, J.G.; Kustas, W.P.; Anderson, M.C. (2018-06-05), A Brief Overview of Approaches for Measuring Evapotranspiration, Agronomy Monographs, Madison, WI, USA: American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc., pp. 109–127, doi:10.2134/agronmonogr60.2016.0034, ISBN 9780891183587, http://doi.wiley.com/10.2134/agronmonogr60.2016.0034, retrieved 2022-03-10 
  10. ↑ Giardina, Francesco; Gentine, Pierre; Konings, Alexandra G.; Seneviratne, Sonia I.; Stocker, Benjamin D. (25 August 2023). "Diagnosing evapotranspiration responses to water deficit across biomes using deep learning". New Phytologist. doi:10.1111/nph.19197. PMID 37621238. https://doi.org/10.1111/nph.19197. Retrieved 30 August 2023. 
  11. ↑ Swank, Wayne T.; Douglass, James E. (1974-09-06). "Streamflow Greatly Reduced by Converting Deciduous Hardwood Stands to Pine" (in en). Science 185 (4154): 857–859. doi:10.1126/science.185.4154.857. ISSN 0036-8075. PMID 17833698. Bibcode: 1974Sci...185..857S. http://coweeta.uga.edu/publications/452.pdf. 
  12. ↑ Jasechko, Scott; Sharp, Zachary D.; Gibson, John J.; Birks, S. Jean; Yi, Yi; Fawcett, Peter J. (3 April 2013). "Terrestrial water fluxes dominated by transpiration". Nature 496 (7445): 347–50. doi:10.1038/nature11983. PMID 23552893. Bibcode: 2013Natur.496..347J. 
  13. ↑ Holder, Curtis D (2004-03-22). "Rainfall interception and fog precipitation in a tropical montane cloud forest of Guatemala" (in en). Forest Ecology and Management 190 (2): 373–384. doi:10.1016/j.foreco.2003.11.004. ISSN 0378-1127. https://www.sciencedirect.com/science/article/pii/S0378112703005139. 
  14. ↑ "Cloud Forest" (in en-US). https://cloudforestconservation.org/knowledge/cloud-forest/. 
  15. ↑ "How plants play a vital role for rainfall within the tropical rainforest | Britannica" (in en). https://www.britannica.com/video/185619/role-plants-cycle-evaporation-condensation-rainforest-biomes. 
  16. ↑ Sheil, Douglas (2009-04-01). "How Forests Attract Rain: An Examination of a New Hypothesis". https://academic.oup.com/bioscience/article/59/4/341/346941. 
  17. ↑ "SEBAL_ WaterWatch". http://www.waterwatch.nl/tools0/sebal.html. 
  18. ↑ Allen, R.G.; Pereira, L.S.; Raes, D.; Smith, M. (1998). Crop Evapotranspiration: Guidelines for Computing Crop Water Requirements. FAO Irrigation and drainage paper 56. Rome, Italy: Food and Agriculture Organization of the United Nations. ISBN 978-92-5-104219-9. http://www.fao.org/docrep/X0490E/x0490e00.htm. Retrieved 2011-06-08. 
  19. ↑ Rojas, Jose P.; Sheffield, Ronald E. (2013). "Evaluation of Daily Reference Evapotranspiration Methods as Compared with the ASCE-EWRI Penman-Monteith Equation Using Limited Weather Data in Northeast Louisiana". Journal of Irrigation and Drainage Engineering 139 (4): 285–292. doi:10.1061/(ASCE)IR.1943-4774.0000523. ISSN 0733-9437. 
  20. ↑ "Kimberly Research and Extension Center". http://extension.uidaho.edu/kimberly/files/2013/02/ascestzdetmain2005.pdf. 
  21. ↑ "Humid subtropical climate (Cfa) | SKYbrary Aviation Safety". https://skybrary.aero/articles/humid-subtropical-climate-cfa-0#:~:text=Description&text=A%20humid%20subtropical%20climate%20is,poleward%20from%20adjacent%20tropical%20climates.. 
  22. ↑ Anderson, M. C.; Kustas, W. P.; Norman, J. M.; Hain, C. R.; Mecikalski, J. R.; Schultz, L.; González-Dugo, M. P.; Cammalleri, C. et al. (2011-01-21). "Mapping daily evapotranspiration at field to continental scales using geostationary and polar orbiting satellite imagery" (in en). Hydrology and Earth System Sciences 15 (1): 223–239. doi:10.5194/hess-15-223-2011. ISSN 1607-7938. Bibcode: 2011HESS...15..223A. 
  23. ↑ Dhungel, Ramesh; Aiken, Robert; Colaizzi, Paul D.; Lin, Xiaomao; O'Brien, Dan; Baumhardt, R. Louis; Brauer, David K.; Marek, Gary W. (2019-07-15). "Evaluation of uncalibrated energy balance model (BAITSSS) for estimating evapotranspiration in a semiarid, advective climate" (in en). Hydrological Processes 33 (15): 2110–2130. doi:10.1002/hyp.13458. ISSN 0885-6087. Bibcode: 2019HyPr...33.2110D. 
  24. ↑ Dhungel, Ramesh; Allen, Richard G.; Trezza, Ricardo; Robison, Clarence W. (2016). "Evapotranspiration between satellite overpasses: methodology and case study in agricultural dominant semi-arid areas" (in en). Meteorological Applications 23 (4): 714–730. doi:10.1002/met.1596. ISSN 1469-8080. Bibcode: 2016MeApp..23..714D. 
  25. ↑ Allen Richard G.; Tasumi Masahiro; Trezza Ricardo (2007-08-01). "Satellite-Based Energy Balance for Mapping Evapotranspiration with Internalized Calibration (METRIC)—Model". Journal of Irrigation and Drainage Engineering 133 (4): 380–394. doi:10.1061/(ASCE)0733-9437(2007)133:4(380). 
  26. ↑ Abtew W. Evapotranspiration Measurements and Modeling for Three Wetland Systems in South Florida. J. Am. Water Resour. Assn. 1996;32:465–473.
  27. ↑ Bastiaanssen, W. G. M.; Menenti, M.; Feddes, R. A.; Holtslag, A. A. M. (1998-12-01). "A remote sensing surface energy balance algorithm for land (SEBAL). 1. Formulation". Journal of Hydrology 212-213: 198–212. doi:10.1016/S0022-1694(98)00253-4. ISSN 0022-1694. Bibcode: 1998JHyd..212..198B. 
  28. ↑ Su, Z. (2002). "The Surface Energy Balance System (SEBS) for estimation of turbulent heat fluxes". Hydrology and Earth System Sciences 6 (1): 85–100. doi:10.5194/hess-6-85-2002. ISSN 1607-7938. Bibcode: 2002HESS....6...85S. 
  29. ↑ Senay, Gabriel B.; Bohms, Stefanie; Singh, Ramesh K.; Gowda, Prasanna H.; Velpuri, Naga M.; Alemu, Henok; Verdin, James P. (2013-05-13). "Operational Evapotranspiration Mapping Using Remote Sensing and Weather Datasets: A New Parameterization for the SSEB Approach". JAWRA Journal of the American Water Resources Association 49 (3): 577–591. doi:10.1111/jawr.12057. ISSN 1093-474X. Bibcode: 2013JAWRA..49..577S. https://digitalcommons.unl.edu/usgsstaffpub/739. 
  30. ↑ 30.0 30.1 30.2 FAO. 2023. Remote sensing determination of evapotranspiration – Algorithms, strengths, weaknesses, uncertainty and best fit-for-purpose. Cairo. https://doi.org/10.4060/cc8150en
  31. ↑ Fisher J.B., Tu K.P. and Baldocchi D.D. 2008. Global estimates of the land–atmosphere water flux based on monthly AVHRR and ISLSCP-II data, validated at 16 FLUXNET sites. Remote sensing Environ., 112: 901–919
  32. ↑ Hu G. and Jia L. 2015. Monitoring of evapotranspiration in a semi-arid inland river basin by combining microwave and optical remote sensing observations. Remote sensing, 7: 3056-3087; https://doi.org/10.3390/rs70303056
  33. ↑ FAO. 2023. Remote sensing determination of evapotranspiration – Algorithms, strengths, weaknesses, uncertainty and best fit-for- purpose. Cairo. https://doi.org/10.4060/cc8150en
  34. ↑ Wu B., Zhu W., Yan N., Xing Q., Xu J., Ma Z. and Wang L. 2020. Regional actual evapotranspiration estimation with land and meteorological variables derived from multi-source satellite data. Remote sensing, 12, 332; https://doi.org/10.3390/rs12020332

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