On Parameterizing Soil Evaporation in a Direct Remote Sensing Model of ET: PT-JPL

Autores
Marshall, Michael; Tu, Kevin; Andreo, Verónica Carolina
Año de publicación
2020
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Remote sensing models that measure evapotranspiration directly from the Penman-Monteith or Priestley-Taylor equations typically estimate the soil evaporation component over large areas using coarse spatial resolution relative humidity (RH) from geospatial climate datasets. As a result, the models tend to underperform in dry areas at local scales where moisture status is not well represented by surrounding areas. Earth observation sensors that monitor large-scale global dynamics (e.g., MODIS) afford comparable spatial coverage and temporal frequency, but at a higher spatial resolution than geospatial climate datasets. In this study, we compared soil evaporation parameterized with optical and thermal indices derived from MODIS to RH-based soil evaporation as implemented in the Priestley Taylor-Jet Propulsion Laboratory (PT-JPL) model. We evaluated the parameterizations by subtracting PT-JPL transpiration from observation-based flux tower evapotranspiration in agricultural fields across the contiguous United States. We compared the apparent thermal inertia (ATI) index, land surface water index (LSWI), normalized difference water index (NDWI), and a new index derived from red and shortwave infrared bands (soil moisture divergence index [SMDI]). Relationships were significant at the 95% confidence band. LSWI and SMDI explained 18–33% of variance in 8-day soil evaporation. This led to a 3–11% increase in explained ET variance. LSWI and SMDI tended to perform better at the irrigated sites than RH. LSWI and SMDI led to markedly better performance over other indices at a seasonal time step. L-band microwave backscatter can penetrate clouds and can distinguish soil from canopy moisture content. We are presently fusing red-SWIR-RADAR to improve soil evaporation estimation.
Fil: Marshall, Michael. University of Twente. Faculty of Geo‐information Science and Earth Observation. Department of Natural Resources; Países Bajos
Fil: Tu, Kevin. Corteva Agriscience; Estados Unidos
Fil: Andreo, Verónica Carolina. Comision Nacional de Actividades Espaciales. Instituto de Altos Estudios Espaciales "Mario Gulich"; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba; Argentina
Materia
EVAPOTRANSPIRATION
LAND SURFACE TEMPERATURE
LATENT HEAT
MODIS
PRIESTLEY-TAYLOR
SHORTWAVE INFRARED
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/143384

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spelling On Parameterizing Soil Evaporation in a Direct Remote Sensing Model of ET: PT-JPLMarshall, MichaelTu, KevinAndreo, Verónica CarolinaEVAPOTRANSPIRATIONLAND SURFACE TEMPERATURELATENT HEATMODISPRIESTLEY-TAYLORSHORTWAVE INFRAREDhttps://purl.org/becyt/ford/1.5https://purl.org/becyt/ford/1Remote sensing models that measure evapotranspiration directly from the Penman-Monteith or Priestley-Taylor equations typically estimate the soil evaporation component over large areas using coarse spatial resolution relative humidity (RH) from geospatial climate datasets. As a result, the models tend to underperform in dry areas at local scales where moisture status is not well represented by surrounding areas. Earth observation sensors that monitor large-scale global dynamics (e.g., MODIS) afford comparable spatial coverage and temporal frequency, but at a higher spatial resolution than geospatial climate datasets. In this study, we compared soil evaporation parameterized with optical and thermal indices derived from MODIS to RH-based soil evaporation as implemented in the Priestley Taylor-Jet Propulsion Laboratory (PT-JPL) model. We evaluated the parameterizations by subtracting PT-JPL transpiration from observation-based flux tower evapotranspiration in agricultural fields across the contiguous United States. We compared the apparent thermal inertia (ATI) index, land surface water index (LSWI), normalized difference water index (NDWI), and a new index derived from red and shortwave infrared bands (soil moisture divergence index [SMDI]). Relationships were significant at the 95% confidence band. LSWI and SMDI explained 18–33% of variance in 8-day soil evaporation. This led to a 3–11% increase in explained ET variance. LSWI and SMDI tended to perform better at the irrigated sites than RH. LSWI and SMDI led to markedly better performance over other indices at a seasonal time step. L-band microwave backscatter can penetrate clouds and can distinguish soil from canopy moisture content. We are presently fusing red-SWIR-RADAR to improve soil evaporation estimation.Fil: Marshall, Michael. University of Twente. Faculty of Geo‐information Science and Earth Observation. Department of Natural Resources; Países BajosFil: Tu, Kevin. Corteva Agriscience; Estados UnidosFil: Andreo, Verónica Carolina. Comision Nacional de Actividades Espaciales. Instituto de Altos Estudios Espaciales "Mario Gulich"; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba; ArgentinaAmerican Geophysical Union2020-05info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/143384Marshall, Michael; Tu, Kevin; Andreo, Verónica Carolina; On Parameterizing Soil Evaporation in a Direct Remote Sensing Model of ET: PT-JPL; American Geophysical Union; Water Resources Research; 56; 5; 5-2020; 1-180043-13971944-7973CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2019WR026290info:eu-repo/semantics/altIdentifier/doi/10.1029/2019WR026290info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T10:19:23Zoai:ri.conicet.gov.ar:11336/143384instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 10:19:24.205CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv On Parameterizing Soil Evaporation in a Direct Remote Sensing Model of ET: PT-JPL
title On Parameterizing Soil Evaporation in a Direct Remote Sensing Model of ET: PT-JPL
spellingShingle On Parameterizing Soil Evaporation in a Direct Remote Sensing Model of ET: PT-JPL
Marshall, Michael
EVAPOTRANSPIRATION
LAND SURFACE TEMPERATURE
LATENT HEAT
MODIS
PRIESTLEY-TAYLOR
SHORTWAVE INFRARED
title_short On Parameterizing Soil Evaporation in a Direct Remote Sensing Model of ET: PT-JPL
title_full On Parameterizing Soil Evaporation in a Direct Remote Sensing Model of ET: PT-JPL
title_fullStr On Parameterizing Soil Evaporation in a Direct Remote Sensing Model of ET: PT-JPL
title_full_unstemmed On Parameterizing Soil Evaporation in a Direct Remote Sensing Model of ET: PT-JPL
title_sort On Parameterizing Soil Evaporation in a Direct Remote Sensing Model of ET: PT-JPL
dc.creator.none.fl_str_mv Marshall, Michael
Tu, Kevin
Andreo, Verónica Carolina
author Marshall, Michael
author_facet Marshall, Michael
Tu, Kevin
Andreo, Verónica Carolina
author_role author
author2 Tu, Kevin
Andreo, Verónica Carolina
author2_role author
author
dc.subject.none.fl_str_mv EVAPOTRANSPIRATION
LAND SURFACE TEMPERATURE
LATENT HEAT
MODIS
PRIESTLEY-TAYLOR
SHORTWAVE INFRARED
topic EVAPOTRANSPIRATION
LAND SURFACE TEMPERATURE
LATENT HEAT
MODIS
PRIESTLEY-TAYLOR
SHORTWAVE INFRARED
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.5
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv Remote sensing models that measure evapotranspiration directly from the Penman-Monteith or Priestley-Taylor equations typically estimate the soil evaporation component over large areas using coarse spatial resolution relative humidity (RH) from geospatial climate datasets. As a result, the models tend to underperform in dry areas at local scales where moisture status is not well represented by surrounding areas. Earth observation sensors that monitor large-scale global dynamics (e.g., MODIS) afford comparable spatial coverage and temporal frequency, but at a higher spatial resolution than geospatial climate datasets. In this study, we compared soil evaporation parameterized with optical and thermal indices derived from MODIS to RH-based soil evaporation as implemented in the Priestley Taylor-Jet Propulsion Laboratory (PT-JPL) model. We evaluated the parameterizations by subtracting PT-JPL transpiration from observation-based flux tower evapotranspiration in agricultural fields across the contiguous United States. We compared the apparent thermal inertia (ATI) index, land surface water index (LSWI), normalized difference water index (NDWI), and a new index derived from red and shortwave infrared bands (soil moisture divergence index [SMDI]). Relationships were significant at the 95% confidence band. LSWI and SMDI explained 18–33% of variance in 8-day soil evaporation. This led to a 3–11% increase in explained ET variance. LSWI and SMDI tended to perform better at the irrigated sites than RH. LSWI and SMDI led to markedly better performance over other indices at a seasonal time step. L-band microwave backscatter can penetrate clouds and can distinguish soil from canopy moisture content. We are presently fusing red-SWIR-RADAR to improve soil evaporation estimation.
Fil: Marshall, Michael. University of Twente. Faculty of Geo‐information Science and Earth Observation. Department of Natural Resources; Países Bajos
Fil: Tu, Kevin. Corteva Agriscience; Estados Unidos
Fil: Andreo, Verónica Carolina. Comision Nacional de Actividades Espaciales. Instituto de Altos Estudios Espaciales "Mario Gulich"; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba; Argentina
description Remote sensing models that measure evapotranspiration directly from the Penman-Monteith or Priestley-Taylor equations typically estimate the soil evaporation component over large areas using coarse spatial resolution relative humidity (RH) from geospatial climate datasets. As a result, the models tend to underperform in dry areas at local scales where moisture status is not well represented by surrounding areas. Earth observation sensors that monitor large-scale global dynamics (e.g., MODIS) afford comparable spatial coverage and temporal frequency, but at a higher spatial resolution than geospatial climate datasets. In this study, we compared soil evaporation parameterized with optical and thermal indices derived from MODIS to RH-based soil evaporation as implemented in the Priestley Taylor-Jet Propulsion Laboratory (PT-JPL) model. We evaluated the parameterizations by subtracting PT-JPL transpiration from observation-based flux tower evapotranspiration in agricultural fields across the contiguous United States. We compared the apparent thermal inertia (ATI) index, land surface water index (LSWI), normalized difference water index (NDWI), and a new index derived from red and shortwave infrared bands (soil moisture divergence index [SMDI]). Relationships were significant at the 95% confidence band. LSWI and SMDI explained 18–33% of variance in 8-day soil evaporation. This led to a 3–11% increase in explained ET variance. LSWI and SMDI tended to perform better at the irrigated sites than RH. LSWI and SMDI led to markedly better performance over other indices at a seasonal time step. L-band microwave backscatter can penetrate clouds and can distinguish soil from canopy moisture content. We are presently fusing red-SWIR-RADAR to improve soil evaporation estimation.
publishDate 2020
dc.date.none.fl_str_mv 2020-05
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/143384
Marshall, Michael; Tu, Kevin; Andreo, Verónica Carolina; On Parameterizing Soil Evaporation in a Direct Remote Sensing Model of ET: PT-JPL; American Geophysical Union; Water Resources Research; 56; 5; 5-2020; 1-18
0043-1397
1944-7973
CONICET Digital
CONICET
url http://hdl.handle.net/11336/143384
identifier_str_mv Marshall, Michael; Tu, Kevin; Andreo, Verónica Carolina; On Parameterizing Soil Evaporation in a Direct Remote Sensing Model of ET: PT-JPL; American Geophysical Union; Water Resources Research; 56; 5; 5-2020; 1-18
0043-1397
1944-7973
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2019WR026290
info:eu-repo/semantics/altIdentifier/doi/10.1029/2019WR026290
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv American Geophysical Union
publisher.none.fl_str_mv American Geophysical Union
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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