Land data assimilation with satellite measurements for the estimation of surface energy balance components and surface control on evaporation

Boni, Giorgio; Entekhabi, Dara; Castelli, Fabio

doi:10.1029/2001wr900020

Cited by 100 publications

(62 citation statements)

References 14 publications

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“…Existing DA schemes were developed mainly for numerical weather prediction, where the most commonly used techniques are optimal interpolation and variational minimisation (Daley, 1991). Spurred by the success of DA in other fields and by a few early hydrological investigations (e.g., Entekhabi et al, 1994;Milly, 1986) DA has attracted a lot of attention in hydrology in recent years (Wigneron et al, 1999;Hoeben and Troch, 2000;Houser et al, 2000;Boni et al, 2001;Walker et al, 2001;Francois et al, 2003, Schuurmans et al, 2003. These papers have mostly focused on the assimilation of surface soil moisture data into land surface models.…”

Section: Introductionmentioning

confidence: 99%

Assimilating scatterometer soil moisture data into conceptual hydrologic models at the regional scale

Parajka

Naeimi

Blöschl

et al. 2006

Hydrol. Earth Syst. Sci.

143

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Abstract. This paper examines the potential of scatterometer data from ERS satellites for improving hydrological simulations in both gauged and ungauged catchments. We compare the soil moisture dynamics simulated by a semidistributed hydrologic model in 320 Austrian catchments with the soil moisture dynamics inferred from the satellite data. The most apparent differences occur in the Alpine areas. Assimilating the scatterometer data into the hydrologic model during the calibration phase improves the relationship between the two soil moisture estimates without any significant decrease in runoff model efficiency. For the case of ungauged catchments, assimilating scatterometer data does not improve the daily runoff simulations but does provide more consistent soil moisture estimates. If the main interest is in obtaining estimates of catchment soil moisture, reconciling the two sources of soil moisture information seems to be of value because of the different error structures.

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Section: Introductionmentioning

confidence: 99%

Assimilating scatterometer soil moisture data into conceptual hydrologic models at the regional scale

Parajka

Naeimi

Blöschl

et al. 2006

Hydrol. Earth Syst. Sci.

143

View full text Add to dashboard Cite

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“…Comprehensive reviews of the historical development and accuracies of in situ and satellite-based LE estimation methods are provided elsewhere [3,5,22]. These LE methods mainly include the simplified empirical (SE) method [2,23,24], surface energy balance (SEB) based single-and dual-source models [11,25,26], Penman-Monteith (PM) equation [8,[14][15][16]27], and data assimilation (DA) techniques [28][29][30]. Although great progress has been made on remotely sensed estimation of LE at a regional scale with these models, there are still challenges and limitations that have not yet been solved properly.…”

Section: Introductionmentioning

confidence: 99%

Validation and Application of the Modified Satellite-Based Priestley-Taylor Algorithm for Mapping Terrestrial Evapotranspiration

et al. 2014

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Satellite-based vegetation indices (VIs) and Apparent Thermal Inertia (ATI) derived from temperature change provide valuable information for estimating evapotranspiration (LE) and detecting the onset and severity of drought. The modified satellite-based Priestley-Taylor (MS-PT) algorithm that we developed earlier, coupling both VI and ATI, is validated based on observed data from 40 flux towers distributed across the world on all continents. with the Priestley-Taylor-based LE (PT-JPL) algorithm, the MS-PT algorithm improves the LE estimates at most flux tower sites. Importantly, the MS-PT algorithm is also satisfactory in reproducing the inter-annual variability at flux tower sites with at least five years of data. The R 2 between measured and predicted annual LE anomalies is 0.42 (p = 0.02). The MS-PT algorithm is then applied to detect the variations of long-term terrestrial LE over Three-North Shelter Forest Region of China and to monitor global land surface drought. The MS-PT algorithm described here demonstrates the ability to map regional terrestrial LE and identify global soil moisture stress, without requiring precipitation information.

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“…Examples of model hybridization include combining land surface temperature derived from remote sensing data with a soil vegetation atmosphere transfer model in Olioso et al (1999) and an indirect, remote-based model in Boni et al (2001). Evapotranspiration estimates in (Chen et al, 1996).…”

Section: Introductionmentioning

confidence: 99%

Improving operational land surface model canopy evapotranspiration in Africa using a direct remote sensing approach

Marshall

Funk

et al. 2013

Hydrol. Earth Syst. Sci.

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Abstract. Climate change is expected to have the greatest impact on the world's economically poor. In the Sahel, a climatically sensitive region where rain-fed agriculture is the primary livelihood, expected decreases in water supply will increase food insecurity. Studies on climate change and the intensification of the water cycle in sub-Saharan Africa are few. This is due in part to poor calibration of modeled evapotranspiration (ET), a key input in continental-scale hydrologic models. In this study, a remote sensing model of transpiration (the primary component of ET), driven by a time series of vegetation indices, was used to substitute transpiration from the Global Land Data Assimilation System realization of the National Centers for Environmental Prediction, Oregon State University, Air Force, and Hydrology Research Laboratory at National Weather Service Land Surface Model (GNOAH) to improve total ET model estimates for monitoring purposes in sub-Saharan Africa. The performance of the hybrid model was compared against GNOAH ET and the remote sensing method using eight eddy flux towers representing major biomes of sub-Saharan Africa. The greatest improvements in model performance were at humid sites with dense vegetation, while performance at semi-arid sites was poor, but better than the models before hybridization. The reduction in errors using the hybrid model can be attributed to the integration of a simple canopy scheme that depends primarily on low bias surface climate reanalysis data and is driven primarily by a time series of vegetation indices.

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Land data assimilation with satellite measurements for the estimation of surface energy balance components and surface control on evaporation

Cited by 100 publications

References 14 publications

Assimilating scatterometer soil moisture data into conceptual hydrologic models at the regional scale

Assimilating scatterometer soil moisture data into conceptual hydrologic models at the regional scale

Validation and Application of the Modified Satellite-Based Priestley-Taylor Algorithm for Mapping Terrestrial Evapotranspiration

Improving operational land surface model canopy evapotranspiration in Africa using a direct remote sensing approach

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