Estimation Of Evapotranspiration From Satellite-Based Surface Energy Balance Models For Water Management In The Rio Guarico Irrigation System, Venezuela

2006 ◽  
Author(s):  
R. Trezza
Keyword(s):  
Water Management ◽  
Energy Balance ◽  
Surface Energy ◽  
Surface Energy Balance ◽  
Irrigation System ◽  
Energy Balance Models

scholarly journals Estimation of actual evapotranspiration of Mediterranean perennial crops by means of remote-sensing based surface energy balance models

2009 ◽  
Vol 13 (7) ◽  
pp. 1061-1074 ◽  
Author(s):  
M. Minacapilli ◽  
C. Agnese ◽  
F. Blanda ◽  
C. Cammalleri ◽  
G. Ciraolo ◽  
...  
Keyword(s):  
Energy Balance ◽  
Surface Energy ◽  
Water Balance ◽  
Soil Water ◽  
Surface Energy Balance ◽  
Soil Water Balance ◽  
Actual Evapotranspiration ◽  
Balance Model ◽  
Spatially Distributed ◽  
Energy Balance Models

Abstract. Actual evapotranspiration from typical Mediterranean crops has been assessed in a Sicilian study area by using surface energy balance (SEB) and soil-water balance models. Both modelling approaches use remotely sensed data to estimate evapotranspiration fluxes in a spatially distributed way. The first approach exploits visible (VIS), near-infrared (NIR) and thermal (TIR) observations to solve the surface energy balance equation whereas the soil-water balance model uses only VIS-NIR data to detect the spatial variability of crop parameters. Considering that the study area is characterized by typical spatially sparse Mediterranean vegetation, i.e. olive, citrus and vineyards, alternating bare soil and canopy, we focused the attention on the main conceptual differences between one-source and two-sources energy balance models. Two different models have been tested: the widely used one-source SEBAL model, where soil and vegetation are considered as the sole source (mostly appropriate in the case of uniform vegetation coverage) and the two-sources TSEB model, where soil and vegetation components of the surface energy balance are treated separately. Actual evapotranspiration estimates by means of the two surface energy balance models have been compared vs. the outputs of the agro-hydrological SWAP model, which was applied in a spatially distributed way to simulate one-dimensional water flow in the soil-plant-atmosphere continuum. Remote sensing data in the VIS and NIR spectral ranges have been used to infer spatially distributed vegetation parameters needed to set up the upper boundary condition of SWAP. Actual evapotranspiration values obtained from the application of the soil water balance model SWAP have been considered as the reference to be used for energy balance models accuracy assessment. Airborne hyperspectral data acquired during a NERC (Natural Environment Research Council, UK) campaign in 2005 have been used. The results of this investigation seem to prove a slightly better agreement between SWAP and TSEB for some fields of the study area. Further investigations are programmed in order to confirm these indications.

scholarly journals Mapping seasonal glacier melt across the Hindu Kush Himalaya with time series synthetic aperture radar (SAR)

2021 ◽  
Vol 15 (9) ◽  
pp. 4465-4482
Author(s):  
Corey Scher ◽  
Nicholas C. Steiner ◽  
Kyle C. McDonald
Keyword(s):  
Time Series ◽  
Energy Balance ◽  
Surface Energy ◽  
Synthetic Aperture Radar ◽  
Surface Energy Balance ◽  
Synthetic Aperture ◽  
Glacier Melt ◽  
Hindu Kush ◽  
Energy Balance Models ◽  
Aperture Radar

Abstract. Current observational data on Hindu Kush Himalayas (HKH) glaciers are sparse, and characterizations of seasonal melt dynamics are limited. Time series synthetic aperture radar (SAR) imagery enables detection of reach-scale glacier melt characteristics across continents. We analyze C-band Sentinel-1 A/B SAR time series data, comprised of 32 741 Sentinel-1 A/B SAR images, and determine the duration of seasonal glacier melting for 105 432 mapped glaciers (83 102 km2 glacierized area, defined using optical observations) in the HKH across the calendar years 2017–2019. Melt onset and duration are recorded at 90 m spatial resolution and 12 d temporal repeat. All glacier areas within the HKH exhibit some degree of melt. Melt signals persist for over two-thirds of the year at elevations below 4000 m a.s.l. and for nearly half of the calendar year at elevations exceeding 7000 m a.s.l. Retrievals of seasonal melting span all elevation ranges of glacierized area in the HKH region, extending greater than 1 km above the maximum elevation of an interpolated 0 ∘C summer isotherm and at the top of Mount Everest, where in situ data and surface energy balance models indicate that the Khumbu Glacier is melting at surface air temperatures below −10 ∘C. Sentinel-1 melt retrievals reflect broad-scale trends in glacier mass balance across the region, where the duration of melt retrieved in the Karakoram is on average 16 d less than in the eastern Himalaya sub-region. Furthermore, percolation zones are apparent from meltwater retention indicated by delayed refreeze. Time series SAR datasets are suitable to support operational monitoring of glacier surface melt and the development and assessment of surface energy balance models of melt-driven ablation across the global cryosphere.

scholarly journals water: Tools and Functions to Estimate Actual Evapotranspiration Using Land Surface Energy Balance Models in R

The R Journal ◽  
2016 ◽  
Vol 8 (2) ◽  
pp. 352 ◽  
Author(s):  
Guillermo,Federico Olmedo ◽  
Samuel Ortega-Farías ◽  
Daniel,de,la Fuente-Sáiz ◽  
David,Fonseca- Luego ◽  
Fernando Fuentes-Peñailillo
Keyword(s):  
Energy Balance ◽  
Surface Energy ◽  
Land Surface ◽  
Surface Energy Balance ◽  
Actual Evapotranspiration ◽  
Energy Balance Models

scholarly journals What Darkens the Greenland Ice Sheet?

Eos ◽  
2015 ◽  
Vol 96 ◽  
Author(s):  
Marco Tedesco ◽  
Sarah Doherty ◽  
Stephen Warren ◽  
Martyn Tranter ◽  
Julienne Stroeve ◽  
...  
Keyword(s):  
Energy Balance ◽  
Surface Energy ◽  
Observational Data ◽  
Surface Energy Balance ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Data Sets ◽  
Energy Balance Models

Limited observational data sets and incomplete surface energy balance models constrain understanding of the driving processes for Greenland's ice sheet.

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