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| 1. |  | LARZÁBAL, J.; YAMANAKA, N.; CERETTA, S.; RODRIGUEZ, M.; STEWART, S. Introgression of Asian soybean rust resistant genes into elite soybean lines from Uruguay. International Journal of Pest Management, 2022, vol. 68, issue 4: "Uruguayan Society of Phytopathology (SUFIT): Plant protection for a sustainable agriculture", p.319-327. doi: https://doi.org/10.1080/09670874.2022.2118894 Article history: Received 03 May 2022, Accepted 23 August 2022, Published online: 11 November 2022. Corresponding author: Silvina Stewart, Instituto Nacional de Investigación Agropecuaria (INIA), Programa Nacional de Cultivos de Secano,...| Biblioteca(s): INIA Las Brujas. |
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 | Acceso al texto completo restringido a Biblioteca INIA Las Brujas. Por información adicional contacte bibliolb@inia.org.uy. |
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Registro completo
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Biblioteca (s) : |
INIA Las Brujas. |
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Fecha actual : |
15/08/2023 |
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Actualizado : |
16/08/2023 |
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Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
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Circulación / Nivel : |
Internacional - -- |
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Autor : |
GALLEGO, F.; CAMBA SANS, G.; DI BELLA, C.M.; TISCORNIA, G.; PARUELO, J. |
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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. |
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Título : |
Performance of real evapotranspiration products and water yield estimations in Uruguay. |
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Fecha de publicación : |
2023 |
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Fuente / Imprenta : |
Remote Sensing Applications: Society and Environment. 2023, Volume 32, 101043. https://doi.org/10.1016/j.rsase.2023.101043 |
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ISSN : |
2352-9385 (online). |
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DOI : |
10.1016/j.rsase.2023.101043 |
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Idioma : |
Inglés |
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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 -- |
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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 |
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Palabras claves : |
Land-cover; NDVI; Precipitation; Remote sensing; Water balance. |
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Asunto categoría : |
-- |
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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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