OpenET : filling a critical data gap in water management for the western United States.

Detalhes bibliográficos
Autor(a) principal: Melton, Forrest S.
Data de Publicação: 2022
Outros Autores: Huntington, Justin L., Grimm, Robyn, Herring, Jamie, Hall, Maurice, Rollison, Dana, Erickson, Tyler, Allen, Richard G., Anderson, Martha, Fisher, Joshua, Kilic, Ayse, Senay, Gabriel B., Volk, John Michael, Hain, Christopher, Johnson, Lee, Ruhoff, Anderson Luis, Blankenau, Philip, Bromley, Matthew, Carrara, Will, Daudert, Britta, Doherty, Conor, Dunkerly, Christian, Friedrichs, MacKenzie, Guzman, Alberto, Halverson, Gregory, Hansen, Jody, Harding, Jordan, Kang, Yanghui, Ketchun, David, Minor, Blake, Morton, Charles, Ortega-Salazar, Samuel, Ott, Thomas, Ozdogan, Mutlu, Revelle, Peter, Schull, Mitchell, Wang, Carlos, Yang, Yun, Anderson, Ren
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UFRGS
Texto Completo: http://hdl.handle.net/10183/254417
Resumo: The lack of consistent, accurate information on evapotranspiration (ET) and consumptive use of water by irrigated agriculture is one of the most important data gaps for water managers in the western United States (U.S.) and other arid agricultural regions globally. The ability to easily access information on ET is central to improving water budgets across the West, advancing the use of data-driven irrigation management strategies, and expanding incentive-driven conservation programs. Recent advances in remote sensing of ET have led to the development of multiple approaches for field-scale ET mapping that have been used for local and regional water resource management applications by U.S. state and federal agencies. The OpenET project is a community-driven effort that is building upon these advances to develop an operational system for generating and distributing ET data at a field scale using an ensemble of six well-established satellite-based approaches for mapping ET. Key objectives of OpenET include: Increasing access to remotely sensed ET data through a web-based data explorer and data services; supporting the use of ET data for a range of water resource management applications; and development of use cases and training resources for agricultural producers and water resource managers. Here we describe the OpenET framework, including the models used in the ensemble, the satellite, meteorological, and ancillary data inputs to the system, and the OpenET data visualization and access tools. We also summarize an extensive intercomparison and accuracy assessment conducted using ground measurements of ET from 139 flux tower sites instrumented with open path eddy covariance systems. Results calculated for 24 cropland sites from Phase I of the intercomparison and accuracy assessment demonstrate strong agreement between the satellite-driven ET models and the flux tower ET data. For the six models that have been evaluated to date (ALEXI/DisALEXI, eeMETRIC, geeSEBAL, PT-JPL, SIMS, and SSEBop) and the ensemble mean, the weighted average mean absolute error (MAE) values across all sites range from 13.6 to 21.6 mm/month at a monthly timestep, and 0.74 to 1.07 mm/day at a daily timestep. At seasonal time scales, for all but one of the models the weighted mean total ET is within ±8% of both the ensemble mean and the weighted mean total ET calculated from the flux tower data. Overall, the ensemble mean performs as well as any individual model across nearly all accuracy statistics for croplands, though some individual models may perform better for specific sites and regions. We conclude with three brief use cases to illustrate current applications and benefits of increased access to ET data, and discuss key lessons learned from the development of OpenET.
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spelling Melton, Forrest S.Huntington, Justin L.Grimm, RobynHerring, JamieHall, MauriceRollison, DanaErickson, TylerAllen, Richard G.Anderson, MarthaFisher, JoshuaKilic, AyseSenay, Gabriel B.Volk, John MichaelHain, ChristopherJohnson, LeeRuhoff, Anderson LuisBlankenau, PhilipBromley, MatthewCarrara, WillDaudert, BrittaDoherty, ConorDunkerly, ChristianFriedrichs, MacKenzieGuzman, AlbertoHalverson, GregoryHansen, JodyHarding, JordanKang, YanghuiKetchun, DavidMinor, BlakeMorton, CharlesOrtega-Salazar, SamuelOtt, ThomasOzdogan, MutluRevelle, PeterSchull, MitchellWang, CarlosYang, YunAnderson, Ren2023-02-08T05:02:20Z20221093-474Xhttp://hdl.handle.net/10183/254417001160695The lack of consistent, accurate information on evapotranspiration (ET) and consumptive use of water by irrigated agriculture is one of the most important data gaps for water managers in the western United States (U.S.) and other arid agricultural regions globally. The ability to easily access information on ET is central to improving water budgets across the West, advancing the use of data-driven irrigation management strategies, and expanding incentive-driven conservation programs. Recent advances in remote sensing of ET have led to the development of multiple approaches for field-scale ET mapping that have been used for local and regional water resource management applications by U.S. state and federal agencies. The OpenET project is a community-driven effort that is building upon these advances to develop an operational system for generating and distributing ET data at a field scale using an ensemble of six well-established satellite-based approaches for mapping ET. Key objectives of OpenET include: Increasing access to remotely sensed ET data through a web-based data explorer and data services; supporting the use of ET data for a range of water resource management applications; and development of use cases and training resources for agricultural producers and water resource managers. Here we describe the OpenET framework, including the models used in the ensemble, the satellite, meteorological, and ancillary data inputs to the system, and the OpenET data visualization and access tools. We also summarize an extensive intercomparison and accuracy assessment conducted using ground measurements of ET from 139 flux tower sites instrumented with open path eddy covariance systems. Results calculated for 24 cropland sites from Phase I of the intercomparison and accuracy assessment demonstrate strong agreement between the satellite-driven ET models and the flux tower ET data. For the six models that have been evaluated to date (ALEXI/DisALEXI, eeMETRIC, geeSEBAL, PT-JPL, SIMS, and SSEBop) and the ensemble mean, the weighted average mean absolute error (MAE) values across all sites range from 13.6 to 21.6 mm/month at a monthly timestep, and 0.74 to 1.07 mm/day at a daily timestep. At seasonal time scales, for all but one of the models the weighted mean total ET is within ±8% of both the ensemble mean and the weighted mean total ET calculated from the flux tower data. Overall, the ensemble mean performs as well as any individual model across nearly all accuracy statistics for croplands, though some individual models may perform better for specific sites and regions. We conclude with three brief use cases to illustrate current applications and benefits of increased access to ET data, and discuss key lessons learned from the development of OpenET.application/pdfengJournal of the american water resources association. Vol. 58, n. 6 (Dec. 2022), p. 971-994EvapotranspiraçãoSensoriamento remotoCultura irrigadaGestão de recursos hídricosAgricultureConsumptive useEvapotranspirationField scaleLandsatOpen data systemsRemote sensingSatelliteWater sustainabilityOpenET : filling a critical data gap in water management for the western United States.Estrangeiroinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da UFRGSinstname:Universidade Federal do Rio Grande do Sul (UFRGS)instacron:UFRGSTEXT001160695.pdf.txt001160695.pdf.txtExtracted Texttext/plain110226http://www.lume.ufrgs.br/bitstream/10183/254417/2/001160695.pdf.txt38203bd485384bea0b09dc1486930f9fMD52ORIGINAL001160695.pdfTexto completoapplication/pdf4368605http://www.lume.ufrgs.br/bitstream/10183/254417/1/001160695.pdf97c8bd1b4d744b30513bda0431657766MD5110183/2544172023-02-10 05:56:32.920866oai:www.lume.ufrgs.br:10183/254417Repositório de PublicaçõesPUBhttps://lume.ufrgs.br/oai/requestopendoar:2023-02-10T07:56:32Repositório Institucional da UFRGS - Universidade Federal do Rio Grande do Sul (UFRGS)false
dc.title.pt_BR.fl_str_mv OpenET : filling a critical data gap in water management for the western United States.
title OpenET : filling a critical data gap in water management for the western United States.
spellingShingle OpenET : filling a critical data gap in water management for the western United States.
Melton, Forrest S.
Evapotranspiração
Sensoriamento remoto
Cultura irrigada
Gestão de recursos hídricos
Agriculture
Consumptive use
Evapotranspiration
Field scale
Landsat
Open data systems
Remote sensing
Satellite
Water sustainability
title_short OpenET : filling a critical data gap in water management for the western United States.
title_full OpenET : filling a critical data gap in water management for the western United States.
title_fullStr OpenET : filling a critical data gap in water management for the western United States.
title_full_unstemmed OpenET : filling a critical data gap in water management for the western United States.
title_sort OpenET : filling a critical data gap in water management for the western United States.
author Melton, Forrest S.
author_facet Melton, Forrest S.
Huntington, Justin L.
Grimm, Robyn
Herring, Jamie
Hall, Maurice
Rollison, Dana
Erickson, Tyler
Allen, Richard G.
Anderson, Martha
Fisher, Joshua
Kilic, Ayse
Senay, Gabriel B.
Volk, John Michael
Hain, Christopher
Johnson, Lee
Ruhoff, Anderson Luis
Blankenau, Philip
Bromley, Matthew
Carrara, Will
Daudert, Britta
Doherty, Conor
Dunkerly, Christian
Friedrichs, MacKenzie
Guzman, Alberto
Halverson, Gregory
Hansen, Jody
Harding, Jordan
Kang, Yanghui
Ketchun, David
Minor, Blake
Morton, Charles
Ortega-Salazar, Samuel
Ott, Thomas
Ozdogan, Mutlu
Revelle, Peter
Schull, Mitchell
Wang, Carlos
Yang, Yun
Anderson, Ren
author_role author
author2 Huntington, Justin L.
Grimm, Robyn
Herring, Jamie
Hall, Maurice
Rollison, Dana
Erickson, Tyler
Allen, Richard G.
Anderson, Martha
Fisher, Joshua
Kilic, Ayse
Senay, Gabriel B.
Volk, John Michael
Hain, Christopher
Johnson, Lee
Ruhoff, Anderson Luis
Blankenau, Philip
Bromley, Matthew
Carrara, Will
Daudert, Britta
Doherty, Conor
Dunkerly, Christian
Friedrichs, MacKenzie
Guzman, Alberto
Halverson, Gregory
Hansen, Jody
Harding, Jordan
Kang, Yanghui
Ketchun, David
Minor, Blake
Morton, Charles
Ortega-Salazar, Samuel
Ott, Thomas
Ozdogan, Mutlu
Revelle, Peter
Schull, Mitchell
Wang, Carlos
Yang, Yun
Anderson, Ren
author2_role author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
dc.contributor.author.fl_str_mv Melton, Forrest S.
Huntington, Justin L.
Grimm, Robyn
Herring, Jamie
Hall, Maurice
Rollison, Dana
Erickson, Tyler
Allen, Richard G.
Anderson, Martha
Fisher, Joshua
Kilic, Ayse
Senay, Gabriel B.
Volk, John Michael
Hain, Christopher
Johnson, Lee
Ruhoff, Anderson Luis
Blankenau, Philip
Bromley, Matthew
Carrara, Will
Daudert, Britta
Doherty, Conor
Dunkerly, Christian
Friedrichs, MacKenzie
Guzman, Alberto
Halverson, Gregory
Hansen, Jody
Harding, Jordan
Kang, Yanghui
Ketchun, David
Minor, Blake
Morton, Charles
Ortega-Salazar, Samuel
Ott, Thomas
Ozdogan, Mutlu
Revelle, Peter
Schull, Mitchell
Wang, Carlos
Yang, Yun
Anderson, Ren
dc.subject.por.fl_str_mv Evapotranspiração
Sensoriamento remoto
Cultura irrigada
Gestão de recursos hídricos
topic Evapotranspiração
Sensoriamento remoto
Cultura irrigada
Gestão de recursos hídricos
Agriculture
Consumptive use
Evapotranspiration
Field scale
Landsat
Open data systems
Remote sensing
Satellite
Water sustainability
dc.subject.eng.fl_str_mv Agriculture
Consumptive use
Evapotranspiration
Field scale
Landsat
Open data systems
Remote sensing
Satellite
Water sustainability
description The lack of consistent, accurate information on evapotranspiration (ET) and consumptive use of water by irrigated agriculture is one of the most important data gaps for water managers in the western United States (U.S.) and other arid agricultural regions globally. The ability to easily access information on ET is central to improving water budgets across the West, advancing the use of data-driven irrigation management strategies, and expanding incentive-driven conservation programs. Recent advances in remote sensing of ET have led to the development of multiple approaches for field-scale ET mapping that have been used for local and regional water resource management applications by U.S. state and federal agencies. The OpenET project is a community-driven effort that is building upon these advances to develop an operational system for generating and distributing ET data at a field scale using an ensemble of six well-established satellite-based approaches for mapping ET. Key objectives of OpenET include: Increasing access to remotely sensed ET data through a web-based data explorer and data services; supporting the use of ET data for a range of water resource management applications; and development of use cases and training resources for agricultural producers and water resource managers. Here we describe the OpenET framework, including the models used in the ensemble, the satellite, meteorological, and ancillary data inputs to the system, and the OpenET data visualization and access tools. We also summarize an extensive intercomparison and accuracy assessment conducted using ground measurements of ET from 139 flux tower sites instrumented with open path eddy covariance systems. Results calculated for 24 cropland sites from Phase I of the intercomparison and accuracy assessment demonstrate strong agreement between the satellite-driven ET models and the flux tower ET data. For the six models that have been evaluated to date (ALEXI/DisALEXI, eeMETRIC, geeSEBAL, PT-JPL, SIMS, and SSEBop) and the ensemble mean, the weighted average mean absolute error (MAE) values across all sites range from 13.6 to 21.6 mm/month at a monthly timestep, and 0.74 to 1.07 mm/day at a daily timestep. At seasonal time scales, for all but one of the models the weighted mean total ET is within ±8% of both the ensemble mean and the weighted mean total ET calculated from the flux tower data. Overall, the ensemble mean performs as well as any individual model across nearly all accuracy statistics for croplands, though some individual models may perform better for specific sites and regions. We conclude with three brief use cases to illustrate current applications and benefits of increased access to ET data, and discuss key lessons learned from the development of OpenET.
publishDate 2022
dc.date.issued.fl_str_mv 2022
dc.date.accessioned.fl_str_mv 2023-02-08T05:02:20Z
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dc.language.iso.fl_str_mv eng
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dc.relation.ispartof.pt_BR.fl_str_mv Journal of the american water resources association. Vol. 58, n. 6 (Dec. 2022), p. 971-994
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