DOI: 10.5194/hess-19-4653-2015
Scopus记录号: 2-s2.0-84948450491
论文题名: The SPARSE model for the prediction of water stress and evapotranspiration components from thermal infra-red data and its evaluation over irrigated and rainfed wheat
作者: Boulet G ; , Mougenot B ; , Lhomme J ; -P ; , Fanise P ; , Lili-Chabaane Z ; , Olioso A ; , Bahir M ; , Rivalland V ; , Jarlan L ; , Merlin O ; , Coudert B ; , Er-Raki S ; , Lagouarde J ; -P
刊名: Hydrology and Earth System Sciences
ISSN: 10275606
出版年: 2015
卷: 19, 期: 11 起始页码: 4653
结束页码: 4672
语种: 英语
Scopus关键词: Atmospheric temperature
; Electric resistance
; Energy balance
; Evaporation
; Mean square error
; Moisture
; Plants (botany)
; Remote sensing
; Soil moisture
; Soil testing
; Soils
; Surface properties
; Vegetation
; Energy balance models
; Parallel resistance
; Remote sensing data
; Retrieval performance
; Root mean square errors
; Series resistances
; Surface temperatures
; Two-source energy balance model
; Evapotranspiration
; data assimilation
; energy balance
; evapotranspiration
; infrared imagery
; irrigation system
; plant water relations
; rainfed agriculture
; remote sensing
; soil moisture
; spatial distribution
; surface temperature
; water stress
; wheat
; Triticum aestivum
英文摘要: Evapotranspiration is an important component of the water cycle, especially in semi-arid lands. A way to quantify the spatial distribution of evapotranspiration and water stress from remote-sensing data is to exploit the available surface temperature as a signature of the surface energy balance. Remotely sensed energy balance models enable one to estimate stress levels and, in turn, the water status of continental surfaces. Dual-source models are particularly useful since they allow derivation of a rough estimate of the water stress of the vegetation instead of that of a soil-vegetation composite. They either assume that the soil and the vegetation interact almost independently with the atmosphere (patch approach corresponding to a parallel resistance scheme) or are tightly coupled (layer approach corresponding to a series resistance scheme). The water status of both sources is solved simultaneously from a single surface temperature observation based on a realistic underlying assumption which states that, in most cases, the vegetation is unstressed, and that if the vegetation is stressed, evaporation is negligible. In the latter case, if the vegetation stress is not properly accounted for, the resulting evaporation will decrease to unrealistic levels (negative fluxes) in order to maintain the same total surface temperature. This work assesses the retrieval performances of total and component evapotranspiration as well as surface and plant water stress levels by (1) proposing a new dual-source model named Soil Plant Atmosphere and Remote Sensing Evapotranspiration (SPARSE) in two versions (parallel and series resistance networks) based on the TSEB (Two-Source Energy Balance model, Norman et al., 1995) model rationale as well as state-of-the-art formulations of turbulent and radiative exchange, (2) challenging the limits of the underlying hypothesis for those two versions through a synthetic retrieval test and (3) testing the water stress retrievals (vegetation water stress and moisture-limited soil evaporation) against in situ data over contrasted test sites (irrigated and rainfed wheat). We demonstrated with those two data sets that the SPARSE series model is more robust to component stress retrieval for this cover type, that its performance increases by using bounding relationships based on potential conditions (root mean square error lowered by up to 11 W mg-2 from values of the order of 50-80 W mg-2), and that soil evaporation retrieval is generally consistent with an independent estimate from observed soil moisture evolution. © Author(s) 2015. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/78378
Appears in Collections: 气候变化事实与影响
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作者单位: CESBIO, UMR 5126 UPS, CNRS, CNES, IRD, Toulouse, France; Département Génie Rural des Eaux et Forêts, Institut National Agronomique de Tunisie, Université de Carthage, Tunis, Tunisia; IRD, UMR LISAH, Montpellier, France; INRA, EMMAH - UMR1114, Avignon, France; UAPV, EMMAH - UMR1114, Avignon, France; LP2M2E, FST, Université Cadi Ayyad, Marrakech, Morocco; INRA, UMR 1391 ISPA, Villenave d'Ornon, France
Recommended Citation:
Boulet G,, Mougenot B,, Lhomme J,et al. The SPARSE model for the prediction of water stress and evapotranspiration components from thermal infra-red data and its evaluation over irrigated and rainfed wheat[J]. Hydrology and Earth System Sciences,2015-01-01,19(11)