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 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.

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 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 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.

Scale analysis of evapotranspiration estimates from an energy-water balance model and remotely sensed LST

2021 ◽  
Author(s):  
Nicola Paciolla ◽  
Chiara Corbari ◽  
Giuseppe Ciraolo ◽  
Antonino Maltese ◽  
Marco Mancini
Keyword(s):  
Energy Balance ◽  
High Resolution ◽  
Water Balance ◽  
Surface Temperature ◽  
Remotely Sensed ◽  
Water Balance Model ◽  
Balance Model ◽  
Source Surface ◽  
Scale Analysis ◽  
Energy Fluxes

<p>Remote Sensing (RS) information has progressively found, in recent years, more and more applications in hydrological modelling as a valuable tool for easy and frequent collection of geophysical data. However, this kind of data should be handled carefully, minding its characteristics, spatial resolution and the heterogeneity of the target area.</p><p>In this work, a scale analysis on evapotranspiration estimates over heterogeneous crops is performed combining a distributed energy-water balance model (FEST-EWB) and high-resolution remotely-sensed Land Surface Temperature (LST) and vegetation data.</p><p>The FEST-EWB model is calibrated on measured LST, based on a procedure where every single pixel is modified independently one from the other; hence in each pixel of the analysed domain the minimum of the pixel difference between modelled RET and satellite observed LST is searched over the period of calibration.</p><p>The case study is a Sicilian vineyard, with test dates in the summer of 2008. Meteorological and energy fluxes data are available from an eddy-covariance station, while LST and vegetation data are obtained from low-altitude flights at the high resolution of 1.7 metres.</p><p>After a preliminary calibration on LST data and validation on energy fluxes, the scale analysis is performed in two ways: model input aggregation and model output aggregation. Four coarser scales are selected in reference to some common satellite products resolution: 10.2 m (in reference to Sentinel’s 10 m), 30.6 m (Landsat, 30 m), 244.8 m (MODIS visible, 250 m) and 734.4 m (MODIS, 1000 m). First, modelled surface temperature and evapotranspiration are aggregated to each scale by progressive averaging. Then, model inputs are upscaled to the same spatial resolutions and the model is calibrated anew, obtaining independent results directly at the target scale.</p><p>The results of the two procedures are found to be quite similar, testifying to the capacity of the model to provide accurate products for a heterogeneous area even at low resolutions. The robustness of the analysis is strengthened by a further comparison with two well-established energy-balance algorithms: the one source Surface Energy Balance Algorithm for Land (SEBAL) and the Two-Source Energy Balance (TSEB) model.</p>

Implementation of Snowpack Treatment in the CPC Water Balance Model and Its Impact on Drought Assessment

2021 ◽  
Author(s):  
Jorge Arevalo ◽  
Josh Welty ◽  
Yun Fan ◽  
Xubin Zeng
Keyword(s):  
Water Balance ◽  
Land Surface ◽  
Snow Water Equivalent ◽  
Water Balance Model ◽  
Balance Model ◽  
Drought Indices ◽  
Leaky Bucket ◽  
Drought Assessment ◽  
Temperature And Precipitation ◽  
Drought Conditions

AbstractDroughts are a worldwide concern, thus assessment efforts are conducted by many centers around the world, mainly through simple drought indices which usually neglect important hydrometeorological processes or require variables available only from complex Land Surface Models (LSMs). The U.S. Climate Prediction Center (CPC) uses the Leaky Bucket (LB) water-balance model to post-process temperature and precipitation, providing soil moisture (SM) anomalies to assess drought conditions. However, despite its crucial role in the water cycle, snowpack has been neglected by LB and most drought indices.Taking advantage of the high-quality snow water equivalent (SWE) data from the University of Arizona (UA), a single-layer snow scheme, forced by daily temperature and precipitation only, is developed for LB implementation and tested with two independent forcing datasets. Compared against the UA and SNOTEL SWE data over CONUS, LB outperforms a sophisticated LSM (Noah/NLDAS-2), with the median LB vs SNOTEL correlation (RMSE) about 40% (26%) higher (lower) than that from Noah/NLDAS-2, with only slight differences due to different forcing datasets.The changes in the temporal variability of SM due to the snowpack treatment lead to improved temporal and spatial distribution of drought conditions in the LB simulations compared to the reference U.S. Drought Monitor maps, highlighting the importance of snowpack inclusion in drought assessment. The simplicity but reasonable reliability of the LB with snowpack treatment makes it suitable for drought monitoring and forecasting in both snow-covered and snow-free areas, while only requiring precipitation and temperature data (markedly less than other water-balance-based indices).

scholarly journals Calibration and Validation of a Distributed Energy–Water Balance Model Using Satellite Data of Land Surface Temperature and Ground Discharge Measurements

2014 ◽  
Vol 15 (1) ◽  
pp. 376-392 ◽  
Author(s):  
Chiara Corbari ◽  
Marco Mancini
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Equilibrium Temperature ◽  
Temperature Data ◽  
Balance Model ◽  
Spatially Distributed ◽  
Vegetation Parameters ◽  
Discharge Measurements ◽  
Surface Temperature Data

Abstract Distributed hydrological models of energy and mass balance need as inputs many soil and vegetation parameters, which are usually difficult to define. This paper will try to approach this problem by performing a pixel to pixel calibration procedure of soil hydraulic and vegetation parameters based on satellite land surface temperature data as a complementary method to the traditional calibration with ground discharge measurements at river control cross sections. These analyses are performed for the upper Po River basin (Italy) closed at the river cross section of Ponte della Becca with a total catchment area of about 38 000 km2, for a calibration period from 2000 to 2003, and a validation period from 2004 to 2010. Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature data and a distributed hydrological model, Flash-Flood Event-Based Spatially Distributed Rainfall-Runoff Transformation Energy Water Balance model (FEST-EWB), that solves the system of energy and mass balance equations as a function of the representative equilibrium temperature will be used. This equilibrium surface temperature is comparable to the land surface temperature as retrieved from operational remote sensing data. Results suggest that a combined calibration based on satellite land surface temperature and ground discharge is needed to correctly reproduce volume discharge and also spatially distributed maps of representative equilibrium temperature and evapotranspiration. Improvements of about 10 mm/8 days are obtained on evapotranspiration from the model calibrated with Q and land surface temperature (LST) respect to the calibration based only on discharge.

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