scholarly journals Multi-pixel Calibration of a Distributed Energy Water Balance Model Using Satellite Data of Land Surface Temperature and Eddy Covariance Data

2013 ◽  
Vol 19 ◽  
pp. 285-292 ◽  
Author(s):  
C. Corbari ◽  
G. Ravazzani ◽  
A. Ceppi ◽  
M. Mancini
Keyword(s):  
Water Balance ◽  
Surface Temperature ◽  
Eddy Covariance ◽  
Land Surface Temperature ◽  
Satellite Data ◽  
Land Surface ◽  
Water Balance Model ◽  
Balance Model ◽  
Distributed Energy

scholarly journals Evapotranspiration Estimates at High Spatial and Temporal Resolutions from an Energy–Water Balance Model and Satellite Data in the Capitanata Irrigation Consortium

2020 ◽  
Vol 12 (24) ◽  
pp. 4083
Author(s):  
Chiara Corbari ◽  
Drazen Skokovic Jovanovic ◽  
Luigi Nardella ◽  
Josè Sobrino ◽  
Marco Mancini
Keyword(s):  
Soil Moisture ◽  
Water Balance ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Satellite Data ◽  
Land Surface ◽  
Flash Flood ◽  
Calibration Procedure ◽  
Water Balance Model ◽  
Balance Model

The feasibility of combining remotely sensed land surface temperature data (LST) and an energy–water balance model for improving evapotranspiration estimates over time distributed in space in the Capitanata irrigation consortium is analysed. The energy–water balance FEST-EWB model (flash flood event-based spatially distributed rainfall–runoff transformation—energy–water balance model) computes continuously in time and is distributed in space soil moisture (SM) and evapotranspiration (ET) fluxes solving for a land surface temperature that closes the energy–water balance equations. The comparison between modelled and observed LST was used to calibrate the model soil parametres with a newly developed pixel to pixel calibration procedure. The effects of the calibration procedure were analysed against ground measures of soil moisture and evapotranspiration. The FEST-EWB model was run at 30 m of spatial resolution for the period between 2013 and 2018. Absolute errors of 2.5 °C were obtained for LST estimates against satellite data; while RMSE around 0.06 and 40 Wm−2 are found for ground measured soil moisture and latent heat flux, respectively.

scholarly journals Land surface temperature representativeness in a heterogeneous area through a distributed energy-water balance model and remote sensing data

2010 ◽  
Vol 14 (10) ◽  
pp. 2141-2151 ◽  
Author(s):  
C. Corbari ◽  
J. A. Sobrino ◽  
M. Mancini ◽  
V. Hidalgo
Keyword(s):  
Water Balance ◽  
Surface Temperature ◽  
Spatial Resolution ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Water Balance Model ◽  
Balance Model ◽  
Hydrological Process ◽  
Distributed Hydrological Model ◽  
Data Set

Abstract. Land surface temperature is the link between soil-vegetation-atmosphere fluxes and soil water content through the energy water balance. This paper analyses the representativeness of land surface temperature (LST) for a distributed hydrological water balance model (FEST-EWB) using LST from AHS (airborne hyperspectral scanner), with a spatial resolution between 2–4 m, LST from MODIS, with a spatial resolution of 1000 m, and thermal infrared radiometric ground measurements that are compared with the representative equilibrium temperature that closes the energy balance equation in the distributed hydrological model. Diurnal and nocturnal images are analyzed due to the non stable behaviour of the thermodynamic temperature and to the non linear effects induced by spatial heterogeneity. Spatial autocorrelation and scale of fluctuation of land surface temperature from FEST-EWB and AHS are analysed at different aggregation areas to better understand the scale of representativeness of land surface temperature in a hydrological process. The study site is the agricultural area of Barrax (Spain) that is a heterogeneous area with a patchwork of irrigated and non irrigated vegetated fields and bare soil. The used data set was collected during a field campaign from 10 to 15 July 2005 in the framework of the SEN2FLEX project.

scholarly journals Land surface temperature representativeness in an heterogeneous area through a distributed energy-water balance model and remote sensing data

2010 ◽  
Vol 7 (4) ◽  
pp. 5335-5368 ◽  
Author(s):  
C. Corbari ◽  
J. A. Sobrino ◽  
M. Mancini ◽  
V. Hidalgo
Keyword(s):  
Water Balance ◽  
Surface Temperature ◽  
Spatial Resolution ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Water Balance Model ◽  
Balance Model ◽  
Hydrological Process ◽  
Distributed Hydrological Model ◽  
Data Set

Abstract. Land surface temperature is the link between soil-vegetation-atmosphere fluxes and soil water content through the energy water balance. This paper analyses the representativeness of land surface temperature (LST) for a distributed hydrological water balance model (FEST-EWB) using LST from AHS (airborne hyperspectral scanner), with a spatial resolution between 2–4 m, LST from MODIS, with a spatial resolution of 1000 m, and thermal infrared radiometric ground measurements that are compared with the representative equilibrium temperature that closes the energy balance equation in the distributed hydrological model. Diurnal and nocturnal images are analyzed due to the non stable behaviour of the thermodynamic temperature and to the non linear effects induced by spatial heterogeneity. Spatial autocorrelation and scale of fluctuation of land surface temperature from FEST-EWB and AHS are analysed at different aggregation areas to better understand the scale of representativeness of land surface temperature in an hydrological process. The study site is the agricultural area of Barrax (Spain) that is a heterogeneous area with an alternation of irrigated and non irrigated vegetated field and bare soil. The used data set was collected during a field campaign from 10 to 15 July 2005 in the framework of the SEN2FLEX project.

Evapotranspiration estimates from an energy-water-balance model calibrated on satellite land surface temperature over the Heihe basin

2021 ◽  
Vol 188 ◽  
pp. 104466
Author(s):  
Nicola Paciolla ◽  
Chiara Corbari ◽  
Guangcheng Hu ◽  
Chaolei Zheng ◽  
Massimo Menenti ◽  
...  
Keyword(s):  
Water Balance ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Water Balance Model ◽  
Balance Model

scholarly journals Multi-Satellite Data of Land Surface Temperature, Lakes Area, and Water Level for Hydrological Model Calibration and Validation in the Yangtze River Basin

Water ◽  
2019 ◽  
Vol 11 (12) ◽  
pp. 2621
Author(s):  
Chiara Corbari ◽  
Claire Huber ◽  
Hervè Yesou ◽  
Ying Huang ◽  
Zhongbo Su ◽  
...  
Keyword(s):  
Water Balance ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Yangtze River ◽  
Hydrological Model ◽  
Yangtze River Basin ◽  
Balance Model ◽  
The Yangtze River ◽  
The Yangtze River Basin

This study shows the feasibility of the combined use of multi-satellite data and an energy–water balance model for improving the estimates of water fluxes over time and distributed in space in the Yangtze River basin. In particular, a new methodology is used to constrain an internal model variable of the distributed hydrological model based on the satellite land surface temperature. The hydrological FEST-EWB model (flash flood event-based spatially distributed rainfall–runoff transformation–energy water balance model) with its energy–water balance scheme allows to continuously compute in time and distributed in space soil moisture and evapotranspiration (ET) fluxes thanks to a double link with satellite-derived data as input parameters (e.g., LAI) and as variables for model states’ updates as the land surface temperature (LST). This LST was used to calibrate the model soil parameters instead of using only dedicated ground measurements. The effects of the calibration procedure were evaluated at four available river cross-sections along the Yangtze River, considering also the presence of the Three Gorges Dam. Flow duration curves were also considered to understand the volume storages’ changes. The Poyang and Dongting Lakes dynamics were simulated from FEST-EWB and compared against satellite water extended from MERIS and ASAR data and water levels from LEGOS altimetry data (Topex/Poseidon). The FEST-EWB model was run at 0.009° spatial resolution and three hours of temporal resolutions for the period between 2003 and 2006. Absolute errors on LST estimates of 3 °C were obtained while discharge data were simulated with errors of 10%. Errors on the water area extent of 7% and on the water level of 3% were obtained for the two lakes.

scholarly journals Optimization of the Local Split-Window Algorithm for FY-4A Land Surface Temperature Retrieval

2019 ◽  
Vol 11 (17) ◽  
pp. 2016
Author(s):  
Lijuan Wang ◽  
Ni Guo ◽  
Wei Wang ◽  
Hongchao Zuo
Keyword(s):  
Surface Temperature ◽  
Diurnal Variation ◽  
Land Surface Temperature ◽  
Satellite Data ◽  
Land Surface ◽  
Regional Scale ◽  
Pso Algorithm ◽  
Variation Characteristics ◽  
Split Window Algorithm ◽  
Mean Square Errors

FY-4A is a second generation of geostationary orbiting meteorological satellite, and the successful launch of FY-4A satellite provides a new opportunity to obtain diurnal variation of land surface temperature (LST). In this paper, different underlying surfaces-observed data were applied to evaluate the applicability of the local split-window algorithm for FY-4A, and the local split-window algorithm parameters were optimized by the artificial intelligent particle swarm optimization (PSO) algorithm to improve the accuracy of retrieved LST. Results show that the retrieved LST can efficiently reproduce the diurnal variation characteristics of LST. However, the estimated values deviate hugely from the observed values when the local split-window algorithms are directly used to process the FY-4A satellite data, and the root mean square errors (RMSEs) are approximately 6K. The accuracy of the retrieved LST cannot be effectively improved by merely modifying the emissivity-estimated model or optimizing the algorithm. Based on the measured emissivity, the RMSE of LST retrieved by the optimized local split-window algorithm is reduced to 3.45 K. The local split-window algorithm is a simple and easy retrieval approach that can quickly retrieve LST on a regional scale and promote the application of FY-4A satellite data in related fields.

Plot-scale retrieval of land surface temperature and emissivity estimation

2021 ◽  
Author(s):  
Gitanjali Thakur ◽  
Stan Schymanski ◽  
Kaniska Mallick ◽  
Ivonne Trebs
Keyword(s):  
Land Cover ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Satellite Data ◽  
Land Surface ◽  
Longwave Radiation ◽  
Landscape Scale ◽  
The Earth ◽  
Downwelling Longwave Radiation

<p>The surface energy balance (SEB) is defined as the balance between incoming energy from the sun and outgoing energy from the Earth’s surface. All components of the SEB depend on land surface temperature (LST). Therefore, LST is an important state variable that controls the energy and water exchange between the Earth’s surface and the atmosphere. LST can be estimated radiometrically, based on the infrared radiance emanating from the surface. At the landscape scale, LST is derived from thermal radiation measured using  satellites.  At the plot scale, eddy covariance flux towers commonly record downwelling and upwelling longwave radiation, which can be inverted to retrieve LST  using the grey body equation :<br>             R<sub>lup</sub> = εσ T<sub>s</sub><sup>4</sup> + (1 − ε) R<sub> ldw         </sub>(1)<br>where R<sub>lup</sub> is the upwelling longwave radiation, R<sub>ldw</sub> is the downwelling longwave radiation, ε is the surface emissivity, <em>T<sub>s</sub>  </em>is the surface temperature and σ  is the Stefan-Boltzmann constant. The first term is the temperature-dependent part, while the second represents reflected longwave radiation. Since in the past downwelling longwave radiation was not measured routinely using flux towers, it is an established practice to only use upwelling longwave radiation for the retrieval of plot-scale LST, essentially neglecting the reflected part and shortening Eq. 1 to:<br>               R<sub>lup</sub> = εσ T<sub>s</sub><sup>4 </sup>                       (2)<br>Despite  widespread availability of downwelling longwave radiation measurements, it is still common to use the short equation (Eq. 2) for in-situ LST retrieval. This prompts the question if ignoring the downwelling longwave radiation introduces a bias in LST estimations from tower measurements. Another associated question is how to obtain the correct ε needed for in-situ LST retrievals using tower-based measurements.<br>The current work addresses these two important science questions using observed fluxes at eddy covariance towers for different land cover types. Additionally, uncertainty in retrieved LST and emissivity due to uncertainty in input fluxes was quantified using SOBOL-based uncertainty analysis (SALib). Using landscape-scale emissivity obtained from satellite data (MODIS), we found that the LST  obtained using the complete equation (Eq. 1) is 0.5 to 1.5 K lower than the short equation (Eq. 2). Also, plot-scale emissivity was estimated using observed sensible heat flux and surface-air temperature differences. Plot-scale emissivity obtained using the complete equation was generally between 0.8 to 0.98 while the short equation gave values between 0.9 to 0.98, for all land cover types. Despite additional input data for the complete equation, the uncertainty in plot-scale LST was not greater than if the short equation was used. Landscape-scale daytime LST obtained from satellite data (MODIS TERRA) were strongly correlated with our plot-scale estimates, but on average higher by 0.5 to 9 K, regardless of the equation used. However, for most sites, the correspondence between MODIS TERRA LST and retrieved plot-scale LST estimates increased significantly if plot-scale emissivity was used instead of the landscape-scale emissivity obtained from satellite data.</p>

scholarly journals Near–surface air temperature and snow skin temperature comparison from CREST-SAFE station data with MODIS land surface temperature data

2015 ◽  
Vol 12 (8) ◽  
pp. 7665-7687 ◽  
Author(s):  
C. L. Pérez Díaz ◽  
T. Lakhankar ◽  
P. Romanov ◽  
J. Muñoz ◽  
R. Khanbilvardi ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Skin Temperature ◽  
Air Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Hydrological Cycle ◽  
Critical Role ◽  
Surface Air Temperature ◽  
Balance Model ◽  
Near Surface

Abstract. Land Surface Temperature (LST) is a key variable (commonly studied to understand the hydrological cycle) that helps drive the energy balance and water exchange between the Earth's surface and its atmosphere. One observable constituent of much importance in the land surface water balance model is snow. Snow cover plays a critical role in the regional to global scale hydrological cycle because rain-on-snow with warm air temperatures accelerates rapid snow-melt, which is responsible for the majority of the spring floods. Accurate information on near-surface air temperature (T-air) and snow skin temperature (T-skin) helps us comprehend the energy and water balances in the Earth's hydrological cycle. T-skin is critical in estimating latent and sensible heat fluxes over snow covered areas because incoming and outgoing radiation fluxes from the snow mass and the air temperature above make it different from the average snowpack temperature. This study investigates the correlation between MODerate resolution Imaging Spectroradiometer (MODIS) LST data and observed T-air and T-skin data from NOAA-CREST-Snow Analysis and Field Experiment (CREST-SAFE) for the winters of 2013 and 2014. LST satellite validation is imperative because high-latitude regions are significantly affected by climate warming and there is a need to aid existing meteorological station networks with the spatially continuous measurements provided by satellites. Results indicate that near-surface air temperature correlates better than snow skin temperature with MODIS LST data. Additional findings show that there is a negative trend demonstrating that the air minus snow skin temperature difference is inversely proportional to cloud cover. To a lesser extent, it will be examined whether the surface properties at the site are representative for the LST properties within the instrument field of view.

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