Prediction of spatial ET-fluxes using remote sensing and field data of selected areas in the Eastern Part of Abu Dhabi, United Arab Emirates
Fares M. Howari A B , Ahmed Murad A and Hassan Garamoon AA Geology Department, Faculty of Science, UAE University Al-Ain, PO Box 17555, United Arab Emirates.
B Corresponding author. Email: fhowari@uaeu.ac.ae
Australian Journal of Soil Research 44(8) 759-768 https://doi.org/10.1071/SR06052
Submitted: 29 April 2006 Accepted: 2 October 2006 Published: 29 November 2006
Abstract
Evapotranspiration (ET) is a major source of water depletion in arid and semi-arid environments; and it is a poorly quantified variable in the hydrological cycle. Remote sensing has the potential application to quantify this variable especially at large scale. The present study reports methodology useful to determine whether derived variables from remotely sensed data, such as vegetation and soil brightness indices, could be used to predict ET. To achieve this goal, various regression analyses were conducted between data derived from satellites, field meteorological stations, and ET values. Selected sub-scenes of Landsat Enhanced Thematic Mapper images free of cloud were used to derive Normalized Difference Vegetation Index (NDVI) and Soil Brightness Index using ER-Mapper and JMP software packages. From the obtained relationship between NDVI and ET, it was observed that ET increases sharply with increase in NDVI. The predicted ET results obtained from the multiple regression functions of field ET, NDVI, solar radiation, wind velocity, and/or temperature are comparable with the ET values obtained by Penman-Monteith method. The results showed that a remotely sensed vegetation index could be used, indirectly, to determine ET values. However, there is still considerable work to be done before simple and full automated extraction of ET from the reported methods can be achieved for large-scale applications.
Additional keywords: soil, evapotranspiration, NDVI, SBI, UAE.
Acknowledgment
This work was financially supported by the Research Affairs at the UAE University under a contract no. 01-05-2-11/05.
Bastiaanssen WGM,
Menenti M,
Feddes RA, Holtslag AAM
(1998) A remote sensing surface energy balance algorithm for land (SEBAL) 1. Formulation. Journal of Hydrology 212–213, 198–212.
| Crossref | GoogleScholarGoogle Scholar |
Beyazgül M,
Kayarn Y, Engelsman F
(2000) Estimation methods for crop water requirements in the Gediz basin of Western Turkey. Journal of Hydrology 229, 19–26.
| Crossref | GoogleScholarGoogle Scholar |
Carlson TN,
Capehart WJ, Gillies RR
(1995) A new look at the simplified method for remote sensing of daily evapotranspiration. Remote Sensing of Environment 54, 161–167.
| Crossref | GoogleScholarGoogle Scholar |
Gardner BR, Blad BL
(1986) Evaluation of spectral reflectance models to estimate corn leaf area while minimizing the influence of soil background effects. Remote Sensing of Environment 20, 183–193.
| Crossref |
Hargreaves GH, Samani ZA
(1982a) Estimating potential evapotranspiration. Technical Note. Journal of Irrigation and Drainage Engineering, ASCE 108, 225–230.
Hargreaves GH, Samani ZA
(1982b) Reference crop evapotranspiration from temperature. Applied Engineering in Agriculture 1, 96–99.
Kustas P,
Norman J,
Anderson MC, French AN
(2003) Estimating subpixel surface temperatures and energy fluxes from the vegetation index radiometric temperature relationship. Remote Sensing of Environment 85, 429–440.
| Crossref | GoogleScholarGoogle Scholar |
Kustas WP,
Perry EM,
Doraiswamy PC, Moran MS
(1994) Using satellite remote sensing to extrapolate evapotranspiration estimates in time and space over a semiarid rangeland basin. Remote Sensing of Environment 49, 275–286.
| Crossref | GoogleScholarGoogle Scholar |
Mo X,
Liu S,
Lin Z, Zhao W
(2004) Simulating temporal and spatial variation of evapotranspiration over the Lushi basin. Journal of Hydrology 285, 125–142.
| Crossref | GoogleScholarGoogle Scholar |
Moran MS, Jackson RD
(1991) Assessing the spatial distribution of evapotranspiration using remotely sensed inputs. Journal of Environmental Quality 20, 725–737.
Moran MS,
Rahman AF,
Washbume JC,
Goodrich DC,
Weltz MA, Kustas WP
(1996) Combining the Penman-Monteith equation with measurements of surface temperature and reflectance to map regional evaporation rates. Agricultural and Forest Meteorology 80, 87–109.
| Crossref | GoogleScholarGoogle Scholar |
Turner DP,
Cohen WB,
Kennedy RE,
Fassnacht KS, Briggs JM
(1999) Relationships between leaf area index and Landsat TM spectral vegetation indices across three temperate zone sites. Remote Sensing of Environment 70, 52–68.
| Crossref | GoogleScholarGoogle Scholar |
Zhang L,
Lemeur R, Goutorbe JP
(1995) A one-layer resistance model for estimating regional evapotranspiration using remote sensing data. Agricultural and Forest Meteorology 77, 241–261.
| Crossref | GoogleScholarGoogle Scholar |