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Biblioteca (s) : |
INIA Las Brujas. |
Fecha : |
15/08/2023 |
Actualizado : |
16/08/2023 |
Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
Autor : |
GALLEGO, F.; CAMBA SANS, G.; DI BELLA, C.M.; TISCORNIA, G.; PARUELO, J. |
Afiliación : |
F. GALLEGO, Instituto de Ecología y Ciencias Ambientales, Facultad de Ciencias, Universidad de la República, Iguá 4225, Montevideo, Uruguay; G. CAMBA SANS, Departamento de Métodos Cuantitativos y Sistemas de Información. Facultad de Agronomía. Universidad de Buenos, Av. San Martín 4453, Buenos Aires, Argentina; C.M. DI BELLA, Departamento de Métodos Cuantitativos y Sistemas de Información. Facultad de Agronomía. Universidad de Buenos, Av. San Martín 4453, Buenos Aires, Argentina; IFEVA-CONICET, Av. San Martín 4453, Buenos Aires, Argentina; GUADALUPE TISCORNIA TOSAR, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; JOSÉ PARUELO, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; Inst. Ecología y Ciencias Ambientales, Fac. Ciencias, Univ. de la República, Mdeo; Dpto. Métodos Cuantitativos y Sistemas Inf., Fac. Agronomía. Univ. Bs.As, Bs.As., Argentina; IFEVA-CONICET. |
Título : |
Performance of real evapotranspiration products and water yield estimations in Uruguay. |
Fecha de publicación : |
2023 |
Fuente / Imprenta : |
Remote Sensing Applications: Society and Environment. 2023, Volume 32, 101043. https://doi.org/10.1016/j.rsase.2023.101043 |
ISSN : |
2352-9385 (online). |
DOI : |
10.1016/j.rsase.2023.101043 |
Idioma : |
Inglés |
Notas : |
Article history: Received 2 March 2023; Received in revised form 5 July 2023; Accepted 7 August 2023; Available online 9 August 2023. -- Corresponding author. Iguá 4225, Montevideo, CP:11400, Uruguay. E-mail addresses: fgallego@fcien.edu.uy (F. Gallego), camba@agro.uba.ar (G. Camba Sans), carlos.m.dibella@gmail.com (C.M. Di Bella), gtiscornia@inia.org.uy (G. Tiscornia), jparuelo@inia.org.uy (J.M. Paruelo). -- Funding: This research was funded by the FMV - ANII project (FMV_3_2020_1_162279) and INIA. -- Supplementary data: Supplementary data to this article can be found online at https://doi.org/10.1016/j.rsase.2023.101043 -- |
Contenido : |
Real evapotranspiration (ETR) is a key variable in socio-ecological systems since it is related to the food supply, climate regulation, among others. Additionally, ETR plays a significant role in determining water yield (WY) at the catchment level, which directly impacts water availability for consumption and irrigation. Therefore, it is essential to quantify ETR and WY fluctuations in response to various human pressures to enable comprehensive water planning. In recent decades, remote sensing has become increasingly employed worldwide for hydrological monitoring and estimating ETR. In Uruguay, several approaches have been attempted to quantify ETR. However, there is still a lack of assessments concerning the performance of different products, particularly those using remote sensing. The main objectives of this article were twofold: a) to evaluate the performance of various spatial explicit approaches for estimating real ETR and b) to estimate and analyse the variability in WY derived from the different ETR products for three climatically contrasting years. To achieve these objectives, we utilized four remote sensing ETR products: the Penman?Monteith?Leuning model (PMLv2), the MODIS product, the Simplified Jackson Model based on Landsat images and INTA-SEPA model based on NOAA-AVHRR images. We also employed two water balance models at two scales: national (derived from the National Institute for Agricultural Research of Uruguay, INIA) and micro-watershed level. Our results indicate that MODIS and PMLv2 remote sensing products exhibited better performances compared to the other approaches. These products provided the highest spatial (500 m) and temporal (8 days) resolution, effectively capturing seasonal differences between land-covers. Moreover, they showed positive and strong correlations with annual precipitation and productivity. The discrepancies observed between products have direct implications on the estimation of WY, not only in terms of quantity but also in terms of spatial patterns. Future studies should explore the application of MODIS and PMLv2 ETR estimations for understanding hydrological and ecological processes, conducting climate change research, detecting and mitigating agricultural drought, and managing water resources effectively. © 2023 Elsevier B.V. All rights reserved. MenosReal evapotranspiration (ETR) is a key variable in socio-ecological systems since it is related to the food supply, climate regulation, among others. Additionally, ETR plays a significant role in determining water yield (WY) at the catchment level, which directly impacts water availability for consumption and irrigation. Therefore, it is essential to quantify ETR and WY fluctuations in response to various human pressures to enable comprehensive water planning. In recent decades, remote sensing has become increasingly employed worldwide for hydrological monitoring and estimating ETR. In Uruguay, several approaches have been attempted to quantify ETR. However, there is still a lack of assessments concerning the performance of different products, particularly those using remote sensing. The main objectives of this article were twofold: a) to evaluate the performance of various spatial explicit approaches for estimating real ETR and b) to estimate and analyse the variability in WY derived from the different ETR products for three climatically contrasting years. To achieve these objectives, we utilized four remote sensing ETR products: the Penman?Monteith?Leuning model (PMLv2), the MODIS product, the Simplified Jackson Model based on Landsat images and INTA-SEPA model based on NOAA-AVHRR images. We also employed two water balance models at two scales: national (derived from the National Institute for Agricultural Research of Uruguay, INIA) and micro-watershed level. Our results i... Presentar Todo |
Palabras claves : |
Land-cover; NDVI; Precipitation; Remote sensing; Water balance. |
Asunto categoría : |
-- |
Marc : |
LEADER 03781naa a2200265 a 4500 001 1064286 005 2023-08-16 008 2023 bl uuuu u00u1 u #d 022 $a2352-9385 (online). 024 7 $a10.1016/j.rsase.2023.101043$2DOI 100 1 $aGALLEGO, F. 245 $aPerformance of real evapotranspiration products and water yield estimations in Uruguay.$h[electronic resource] 260 $c2023 500 $aArticle history: Received 2 March 2023; Received in revised form 5 July 2023; Accepted 7 August 2023; Available online 9 August 2023. -- Corresponding author. Iguá 4225, Montevideo, CP:11400, Uruguay. E-mail addresses: fgallego@fcien.edu.uy (F. Gallego), camba@agro.uba.ar (G. Camba Sans), carlos.m.dibella@gmail.com (C.M. Di Bella), gtiscornia@inia.org.uy (G. Tiscornia), jparuelo@inia.org.uy (J.M. Paruelo). -- Funding: This research was funded by the FMV - ANII project (FMV_3_2020_1_162279) and INIA. -- Supplementary data: Supplementary data to this article can be found online at https://doi.org/10.1016/j.rsase.2023.101043 -- 520 $aReal evapotranspiration (ETR) is a key variable in socio-ecological systems since it is related to the food supply, climate regulation, among others. Additionally, ETR plays a significant role in determining water yield (WY) at the catchment level, which directly impacts water availability for consumption and irrigation. Therefore, it is essential to quantify ETR and WY fluctuations in response to various human pressures to enable comprehensive water planning. In recent decades, remote sensing has become increasingly employed worldwide for hydrological monitoring and estimating ETR. In Uruguay, several approaches have been attempted to quantify ETR. However, there is still a lack of assessments concerning the performance of different products, particularly those using remote sensing. The main objectives of this article were twofold: a) to evaluate the performance of various spatial explicit approaches for estimating real ETR and b) to estimate and analyse the variability in WY derived from the different ETR products for three climatically contrasting years. To achieve these objectives, we utilized four remote sensing ETR products: the Penman?Monteith?Leuning model (PMLv2), the MODIS product, the Simplified Jackson Model based on Landsat images and INTA-SEPA model based on NOAA-AVHRR images. We also employed two water balance models at two scales: national (derived from the National Institute for Agricultural Research of Uruguay, INIA) and micro-watershed level. Our results indicate that MODIS and PMLv2 remote sensing products exhibited better performances compared to the other approaches. These products provided the highest spatial (500 m) and temporal (8 days) resolution, effectively capturing seasonal differences between land-covers. Moreover, they showed positive and strong correlations with annual precipitation and productivity. The discrepancies observed between products have direct implications on the estimation of WY, not only in terms of quantity but also in terms of spatial patterns. Future studies should explore the application of MODIS and PMLv2 ETR estimations for understanding hydrological and ecological processes, conducting climate change research, detecting and mitigating agricultural drought, and managing water resources effectively. © 2023 Elsevier B.V. All rights reserved. 653 $aLand-cover 653 $aNDVI 653 $aPrecipitation 653 $aRemote sensing 653 $aWater balance 700 1 $aCAMBA SANS, G. 700 1 $aDI BELLA, C.M. 700 1 $aTISCORNIA, G. 700 1 $aPARUELO, J. 773 $tRemote Sensing Applications: Society and Environment. 2023, Volume 32, 101043. https://doi.org/10.1016/j.rsase.2023.101043
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INIA Las Brujas (LB) |
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Registro completo
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Biblioteca (s) : |
INIA Las Brujas. |
Fecha actual : |
17/02/2020 |
Actualizado : |
17/02/2020 |
Tipo de producción científica : |
Informes Agroclimáticos |
Autor : |
GIMÉNEZ, A.; CAL, A.; TISCORNIA, G.; SCHIAVI, C. |
Afiliación : |
AGUSTIN EDUARDO GIMÉNEZ FUREST, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; ADRIAN TABARE CAL ALVAREZ, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; GUADALUPE TISCORNIA TOSAR, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; CARLOS IGNACIO SCHIAVI RAMPELBERG, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay. |
Título : |
Informe agroclimático 2020- Situación a Enero. |
Fecha de publicación : |
2020 |
Fuente / Imprenta : |
Montevideo (Uruguay): INIA, 2020. |
Páginas : |
4 p. |
Serie : |
(Informe Agroclimático; Año 15, No.1) |
Idioma : |
Español |
Palabras claves : |
AGROCLIMA; AGROCLIMATOLOGÍA; BOLETIN AGROCLIMÁTICO; CARACTERIZACIÓN AGROCLIMÁTICA; DIRECCION VIENTO; ESTACIONES AGROMETEOROLOGICAS; ESTACIONES AUTOMATICAS; ESTACIONES INIA; ESTADO DEL TIEMPO; ESTRÉS HÍDRICO; GRAFICAS AGROCLIMATICOS; GRAS; HELIOFANOGRAFO; INFORMACION SATELITAL; INFORME AGROCLIMÁTICO 2020; INUNDACIONES; LLUVIAS DIARIAS; MAXIMA; MEDIA; MINIMA; PANEL SOLAR; PERSPECTIVAS CLIMATICAS; PLUVIOMETRO; PRECIPITACION NACIONAL; PREVENCION HELADAS; PRONOSTICO; SENSOR; SIMETRICO; TANQUE A; TERMOCUPLAS; TERMOHIDROGRAFO; VARIABLES AGROCLIMATICAS; VELETA. |
Thesagro : |
AGROCLIMATOLOGIA; CAMBIO CLIMATICO; CLIMA; CLIMATOLOGIA; ESTACIONES METEOROLOGICAS; ESTRES HIDRICO; EVAPORACION; EVAPOTRANSPIRACION; HUMEDAD; HUMEDAD RELATIVA; LLUVIA; METEOROLOGIA; PERSPECTIVAS; PLUVIOMETROS; PRONOSTICO DEL TIEMPO; SENSORES; SISTEMAS; SISTEMAS DE INFORMACION; SUELO; TEMPERATURA; TERMOMETROS. |
Asunto categoría : |
P40 Meteorología y climatología |
URL : |
http://www.inia.uy/Publicaciones/Documentos%20compartidos/Informe%20agroclimatico%20INIA-GRAS%20Enero%20de%202020.pdf
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Marc : |
LEADER 02135nam a2200805 a 4500 001 1060815 005 2020-02-17 008 2020 bl uuuu u0uu1 u #d 100 1 $aGIMÉNEZ, A. 245 $aInforme agroclimático 2020- Situación a Enero.$h[electronic resource] 260 $aMontevideo (Uruguay): INIA$c2020 300 $a4 p. 490 $a(Informe Agroclimático; Año 15, No.1) 650 $aAGROCLIMATOLOGIA 650 $aCAMBIO CLIMATICO 650 $aCLIMA 650 $aCLIMATOLOGIA 650 $aESTACIONES METEOROLOGICAS 650 $aESTRES HIDRICO 650 $aEVAPORACION 650 $aEVAPOTRANSPIRACION 650 $aHUMEDAD 650 $aHUMEDAD RELATIVA 650 $aLLUVIA 650 $aMETEOROLOGIA 650 $aPERSPECTIVAS 650 $aPLUVIOMETROS 650 $aPRONOSTICO DEL TIEMPO 650 $aSENSORES 650 $aSISTEMAS 650 $aSISTEMAS DE INFORMACION 650 $aSUELO 650 $aTEMPERATURA 650 $aTERMOMETROS 653 $aAGROCLIMA 653 $aAGROCLIMATOLOGÍA 653 $aBOLETIN AGROCLIMÁTICO 653 $aCARACTERIZACIÓN AGROCLIMÁTICA 653 $aDIRECCION VIENTO 653 $aESTACIONES AGROMETEOROLOGICAS 653 $aESTACIONES AUTOMATICAS 653 $aESTACIONES INIA 653 $aESTADO DEL TIEMPO 653 $aESTRÉS HÍDRICO 653 $aGRAFICAS AGROCLIMATICOS 653 $aGRAS 653 $aHELIOFANOGRAFO 653 $aINFORMACION SATELITAL 653 $aINFORME AGROCLIMÁTICO 2020 653 $aINUNDACIONES 653 $aLLUVIAS DIARIAS 653 $aMAXIMA 653 $aMEDIA 653 $aMINIMA 653 $aPANEL SOLAR 653 $aPERSPECTIVAS CLIMATICAS 653 $aPLUVIOMETRO 653 $aPRECIPITACION NACIONAL 653 $aPREVENCION HELADAS 653 $aPRONOSTICO 653 $aSENSOR 653 $aSIMETRICO 653 $aTANQUE A 653 $aTERMOCUPLAS 653 $aTERMOHIDROGRAFO 653 $aVARIABLES AGROCLIMATICAS 653 $aVELETA 700 1 $aCAL, A. 700 1 $aTISCORNIA, G. 700 1 $aSCHIAVI, C.
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