Introducing QWaterModel, a QGIS plugin for predicting evapotranspiration from land surface temperatures
Evapotranspiration (ET) is a central flux in the hydrological cycle. Various approaches to compute ET via energy balance models exist, but their handling is often complex and challenging. We developed QWaterModel as an easy-to-use tool to make ET predictions available to broader audiences. QWaterMod...
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| Veröffentlicht in: | Environmental modelling & software : with environment data news 2020-08, Vol.130, p.104739, Article 104739 |
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| creator | Ellsäßer, Florian Röll, Alexander Stiegler, Christian Hendrayanto Hölscher, Dirk |
| description | Evapotranspiration (ET) is a central flux in the hydrological cycle. Various approaches to compute ET via energy balance models exist, but their handling is often complex and challenging. We developed QWaterModel as an easy-to-use tool to make ET predictions available to broader audiences. QWaterModel is based on the DATTUTDUT energy balance model and uses land surface temperature maps as an input. Such maps can e.g. be obtained from satellite, drone or handheld camera imagery. In the present study, we successfully tested QWaterModel for predicting ET in a tropical oil palm plantation against the well-established eddy covariance method. QWaterModel is compatible with all versions of QGIS3 and is available from the official QGIS Plugin Repository.
•QWaterModel is an easy-to-use QGIS3 plugin tool for predicting evapotranspiration.•It is based on the DATTUTDUT energy-balance model.•Input options include land surface temperature maps from satellites, drones and handheld cameras.•Predicted evapotranspiration rates are highly congruent with eddy covariance measurements. |
| doi_str_mv | 10.1016/j.envsoft.2020.104739 |
| format | Article |
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•QWaterModel is an easy-to-use QGIS3 plugin tool for predicting evapotranspiration.•It is based on the DATTUTDUT energy-balance model.•Input options include land surface temperature maps from satellites, drones and handheld cameras.•Predicted evapotranspiration rates are highly congruent with eddy covariance measurements.</description><subject>Covariance</subject><subject>DATTUTDUT</subject><subject>Drone</subject><subject>Energy balance</subject><subject>Evaporation</subject><subject>Evapotranspiration</subject><subject>Hydrologic cycle</subject><subject>Hydrological modeling</subject><subject>Hydrology</subject><subject>Land surface temperature</subject><subject>Open source</subject><subject>Satellite imagery</subject><subject>Thermal images</subject><subject>Thermography</subject><subject>Transpiration</subject><subject>UAV</subject><subject>Water cycle</subject><issn>1364-8152</issn><issn>1873-6726</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><recordid>eNqFkNFLwzAQxosoOKd_ghDw1c4kTdP2SUR0DiYyVHwMMb2OlK6pl3Tgf2_K9u7Td9x99x33S5JrRheMMnnXLqDfe9eEBad86okiq06SGSuLLJUFl6exzqRIS5bz8-TC-5ZSGmsxS7arPqCrR2P7Ldl86QD46mrobokmm-XqnQzduLU9aRySAaG2JkxO2OvBBdS9HyzqYF10oNuRTvc18SM22gAJsBsgTkcEf5mcNbrzcHXUefL5_PTx-JKu35arx4d1arJShDSnusoFl5JxBlDKb80ak2naaC0Fi1I2GRSylgXkTEMlaZFnggtd1QWUOcvmyc0hd0D3M4IPqnUj9vGk4kJQUfG8KKMrP7gMOu8RGjWg3Wn8VYyqialq1ZGpmpiqA9O4d3_Yg_jC3gIqbyz0JnJBMEHVzv6T8AdiUYOm</recordid><startdate>202008</startdate><enddate>202008</enddate><creator>Ellsäßer, Florian</creator><creator>Röll, Alexander</creator><creator>Stiegler, Christian</creator><creator>Hendrayanto</creator><creator>Hölscher, Dirk</creator><general>Elsevier Ltd</general><general>Elsevier Science Ltd</general><scope>6I.</scope><scope>AAFTH</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QH</scope><scope>7SC</scope><scope>7ST</scope><scope>7UA</scope><scope>8FD</scope><scope>C1K</scope><scope>FR3</scope><scope>JQ2</scope><scope>KR7</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>SOI</scope></search><sort><creationdate>202008</creationdate><title>Introducing QWaterModel, a QGIS plugin for predicting evapotranspiration from land surface temperatures</title><author>Ellsäßer, Florian ; 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Various approaches to compute ET via energy balance models exist, but their handling is often complex and challenging. We developed QWaterModel as an easy-to-use tool to make ET predictions available to broader audiences. QWaterModel is based on the DATTUTDUT energy balance model and uses land surface temperature maps as an input. Such maps can e.g. be obtained from satellite, drone or handheld camera imagery. In the present study, we successfully tested QWaterModel for predicting ET in a tropical oil palm plantation against the well-established eddy covariance method. QWaterModel is compatible with all versions of QGIS3 and is available from the official QGIS Plugin Repository.
•QWaterModel is an easy-to-use QGIS3 plugin tool for predicting evapotranspiration.•It is based on the DATTUTDUT energy-balance model.•Input options include land surface temperature maps from satellites, drones and handheld cameras.•Predicted evapotranspiration rates are highly congruent with eddy covariance measurements.</abstract><cop>Oxford</cop><pub>Elsevier Ltd</pub><doi>10.1016/j.envsoft.2020.104739</doi><oa>free_for_read</oa></addata></record> |
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| ispartof | Environmental modelling & software : with environment data news, 2020-08, Vol.130, p.104739, Article 104739 |
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| source | Access via ScienceDirect (Elsevier) |
| subjects | Covariance DATTUTDUT Drone Energy balance Evaporation Evapotranspiration Hydrologic cycle Hydrological modeling Hydrology Land surface temperature Open source Satellite imagery Thermal images Thermography Transpiration UAV Water cycle |
| title | Introducing QWaterModel, a QGIS plugin for predicting evapotranspiration from land surface temperatures |
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