气候变化领域集成服务门户(CCPortal): An evapotranspiration model self-calibrated from remotely sensed surface soil moisture; land surface temperature and vegetation cover fraction: Application to disaggregated SMOS and MODIS data

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DOI	10.5194/hess-24-1781-2020
	An evapotranspiration model self-calibrated from remotely sensed surface soil moisture; land surface temperature and vegetation cover fraction: Application to disaggregated SMOS and MODIS data
	Ait Hssaine B.; Merlin O.; Ezzahar J.; Ojha N.; Er-Raki S.; Khabba S.
发表日期	2020
ISSN	1027-5606
起始页码	1781
结束页码	1803
卷号	24 期号:4
英文摘要	Thermal-based two-source energy balance modeling is essential to estimate the land evapotranspiration (ET) in a wide range of spatial and temporal scales. However, the use of thermal-derived land surface temperature (LST) is not sufficient to simultaneously constrain both soil and vegetation flux components. Therefore, assumptions (about either soil or vegetation fluxes) are commonly required. To avoid such assumptions, an energy balance model, TSEB-SM, was recently developed by Ait Hssaine et al. (2018b) in order to consider the microwave-derived near-surface soil moisture (SM), in addition to the thermal-derived LST and vegetation cover fraction (fc) normally used. While TSEB-SM has been successfully tested using in situ measurements, this paper represents its first evaluation in real life using 1 km resolution satellite data, comprised of MODIS (MODerate resolution Imaging Spectroradiometer) for LST and fc data and 1 km resolution SM data disaggregated from SMOS (Soil Moisture and Ocean Salinity) observations. The approach is applied during a 4-year period (2014-2018) over a rainfed wheat field in the Tensift basin, central Morocco. The field used was seeded for the 2014-2015 (S1), 2016-2017 (S2) and 2017-2018 (S3) agricultural seasons, while it remained unploughed (as bare soil) during the 2015-2016 (B1) agricultural season. The classical TSEB model, which is driven only by LST and fc data, significantly overestimates latent heat fluxes (LE) and underestimates sensible heat fluxes (H) for the four seasons. The overall mean bias values are 119, 94, 128 and 181 W m-2 for LE and-104,-71,-128 and-181 W m-2 for H, for S1, S2, S3 and B1, respectively. Meanwhile, when using TSEB-SM (SM and LST combined data), these errors are significantly reduced, resulting in mean bias values estimated as 39, 4, 7 and 62 W m-2 for LE and-10, 24, 7, and-59 W m-2 for H, for S1, S2, S3 and B1, respectively. Consequently, this finding confirms again the robustness of the TSEB-SM in estimating latent/sensible heat fluxes at a large scale by using readily available satellite data. In addition, the TSEB-SM approach has the original feature to allow for calibration of its main parameters (soil resistance and Priestley-Taylor coefficient) from satellite data uniquely, without relying either on in situ measurements or on a priori parameter values. © Author(s) 2020.
语种	英语
scopus关键词	Agricultural robots; Agriculture; Atmospheric temperature; Energy balance; Evapotranspiration; Heat flux; Radiometers; Satellites; Soil moisture; Soil surveys; Surface measurement; Surface properties; Vegetation; Energy balance models; Evapotranspiration modeling; In-situ measurement; Moderate resolution imaging spectroradiometer; Remotely sensed surface soil moistures; Soil Moisture and Ocean Salinity (SMOS); Spatial and temporal scale; Two-source energy balance model; Land surface temperature; calibration; energy balance; evapotranspiration; land surface; latent heat flux; MODIS; satellite data; sensible heat flux; SMOS; soil moisture; surface temperature; vegetation cover; Morocco; Triticum aestivum
来源期刊	Hydrology and Earth System Sciences
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/159442
作者单位	Ait Hssaine, B., CRSA, Centre for Remote Sensing Applications, University Mohammed VI Plytechnic (UM6P), Ben Guerir, Morocco, CESBIO, Université de Toulouse, IRD/CNRS/UPS/CNES, Toulouse, France, LMFE, Département de Physique, Faculté des Sciences Semlalia, Université Cadi Ayyad, Marrakech, Morocco; Merlin, O., CESBIO, Université de Toulouse, IRD/CNRS/UPS/CNES, Toulouse, France; Ezzahar, J., CRSA, Centre for Remote Sensing Applications, University Mohammed VI Plytechnic (UM6P), Ben Guerir, Morocco, Département GIRT/Laboratoire MISC, Ecole Nationale des Sciences Appliquées, Université Cadi Ayyad, Safi, Morocco; Ojha, N., CESBIO, Université de Toulouse, IRD/CNRS/UPS/CNES, Toulouse, France; Er-Raki, S., CRSA, Centre for Remote Sensing Applications, University Mohammed VI Plytechnic (UM6P), Ben Guerir, Morocco, LP2M2E, Département de Physique Appliquée, Faculté des Sciences et Techniques, Université Cadi Ayyad, Marrakech, Morocco; Khabba, S., CRSA, Centre for Remote Sensing Applications, University Mohammed VI...
推荐引用方式 GB/T 7714	Ait Hssaine B.,Merlin O.,Ezzahar J.,et al. An evapotranspiration model self-calibrated from remotely sensed surface soil moisture; land surface temperature and vegetation cover fraction: Application to disaggregated SMOS and MODIS data[J],2020,24(4).
APA	Ait Hssaine B.,Merlin O.,Ezzahar J.,Ojha N.,Er-Raki S.,&Khabba S..(2020).An evapotranspiration model self-calibrated from remotely sensed surface soil moisture; land surface temperature and vegetation cover fraction: Application to disaggregated SMOS and MODIS data.Hydrology and Earth System Sciences,24(4).
MLA	Ait Hssaine B.,et al."An evapotranspiration model self-calibrated from remotely sensed surface soil moisture; land surface temperature and vegetation cover fraction: Application to disaggregated SMOS and MODIS data".Hydrology and Earth System Sciences 24.4(2020).