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Mapping evapotranspiration variability over a complex oasis-desert ecosystem based on automated calibration of Landsat 7 ETM+ data in SEBAL

(2019) GISCIENCE & REMOTE SENSING. 56(8). p.1305-1332
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Abstract
Fragmented ecosystems of the desiccated Aral Sea seek answers to the profound local hydrologically- and water-related problems. Particularly, in the Small Aral Sea Basin (SASB), these problems are associated with low precipitation, increased temperature, land use and evapotranspiration (ET) changes. Here, the utility of high-resolution satellite dataset is employed to model the growing season dynamic of near-surface fluxes controlled by the advective effects of desert and oasis ecosystems in the SASB. This study adapted and applied the sensible heat flux calibration mechanism of Surface Energy Balance Algorithm for Land (SEBAL) to 16 clear-sky Landsat 7 ETM+ dataset, following a guided automatic pixels search from surface temperature T-s and Normalized Difference Vegetation Index NDVI (). Results were comprehensively validated with flux components and actual ET (ETa) outputs of Eddy Covariance (EC) and Meteorological Station (KZL) observations located in the desert and oasis, respectively. Compared with the original SEBAL, a noteworthy enhancement of flux estimations was achieved as follows: - desert ecosystem ETa R-2 = 0.94; oasis ecosystem ETa R-2 = 0.98 (P < 0.05). The improvement uncovered the exact land use contributions to ETa variability, with average estimates ranging from 1.24 mm to 6.98 mm . Additionally, instantaneous ET to NDVI (ETins-NDVI) ratio indicated that desert and oasis consumptive water use vary significantly with time of the season. This study indicates the possibility of continuous daily ET monitoring with considerable implications for improving water resources decision support over complex data-scarce drylands.
Keywords
ENERGY BALANCE ALGORITHM, SURFACE, IRRIGATION, MODEL, IMPLEMENTATION, MANAGEMENT, VEGETATION, FLUXES, BASIN, FIELD, evapotranspiration, Landsat 7 ETM+, SEBAL, Small Aral Sea Basin-SASB, oasis-desert ecosystem

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MLA
Ochege, Friday Uchenna, et al. “Mapping Evapotranspiration Variability over a Complex Oasis-Desert Ecosystem Based on Automated Calibration of Landsat 7 ETM+ Data in SEBAL.” GISCIENCE & REMOTE SENSING, vol. 56, no. 8, 2019, pp. 1305–32.
APA
Ochege, F. U., Luo, G., Obeta, M. C., Owusu, G., Duulatov, E., Cao, L., & Nsengiyumva, J. B. (2019). Mapping evapotranspiration variability over a complex oasis-desert ecosystem based on automated calibration of Landsat 7 ETM+ data in SEBAL. GISCIENCE & REMOTE SENSING, 56(8), 1305–1332.
Chicago author-date
Ochege, Friday Uchenna, Geping Luo, Michael Chukwuma Obeta, George Owusu, Eldiiar Duulatov, Liangzhong Cao, and Jean Baptiste Nsengiyumva. 2019. “Mapping Evapotranspiration Variability over a Complex Oasis-Desert Ecosystem Based on Automated Calibration of Landsat 7 ETM+ Data in SEBAL.” GISCIENCE & REMOTE SENSING 56 (8): 1305–32.
Chicago author-date (all authors)
Ochege, Friday Uchenna, Geping Luo, Michael Chukwuma Obeta, George Owusu, Eldiiar Duulatov, Liangzhong Cao, and Jean Baptiste Nsengiyumva. 2019. “Mapping Evapotranspiration Variability over a Complex Oasis-Desert Ecosystem Based on Automated Calibration of Landsat 7 ETM+ Data in SEBAL.” GISCIENCE & REMOTE SENSING 56 (8): 1305–1332.
Vancouver
1.
Ochege FU, Luo G, Obeta MC, Owusu G, Duulatov E, Cao L, et al. Mapping evapotranspiration variability over a complex oasis-desert ecosystem based on automated calibration of Landsat 7 ETM+ data in SEBAL. GISCIENCE & REMOTE SENSING. 2019;56(8):1305–32.
IEEE
[1]
F. U. Ochege et al., “Mapping evapotranspiration variability over a complex oasis-desert ecosystem based on automated calibration of Landsat 7 ETM+ data in SEBAL,” GISCIENCE & REMOTE SENSING, vol. 56, no. 8, pp. 1305–1332, 2019.
@article{8659335,
  abstract     = {Fragmented ecosystems of the desiccated Aral Sea seek answers to the profound local hydrologically- and water-related problems. Particularly, in the Small Aral Sea Basin (SASB), these problems are associated with low precipitation, increased temperature, land use and evapotranspiration (ET) changes. Here, the utility of high-resolution satellite dataset is employed to model the growing season dynamic of near-surface fluxes controlled by the advective effects of desert and oasis ecosystems in the SASB. This study adapted and applied the sensible heat flux calibration mechanism of Surface Energy Balance Algorithm for Land (SEBAL) to 16 clear-sky Landsat 7 ETM+ dataset, following a guided automatic pixels search from surface temperature T-s and Normalized Difference Vegetation Index NDVI (). Results were comprehensively validated with flux components and actual ET (ETa) outputs of Eddy Covariance (EC) and Meteorological Station (KZL) observations located in the desert and oasis, respectively. Compared with the original SEBAL, a noteworthy enhancement of flux estimations was achieved as follows: - desert ecosystem ETa R-2 = 0.94; oasis ecosystem ETa R-2 = 0.98 (P < 0.05). The improvement uncovered the exact land use contributions to ETa variability, with average estimates ranging from 1.24 mm to 6.98 mm . Additionally, instantaneous ET to NDVI (ETins-NDVI) ratio indicated that desert and oasis consumptive water use vary significantly with time of the season. This study indicates the possibility of continuous daily ET monitoring with considerable implications for improving water resources decision support over complex data-scarce drylands.},
  author       = {Ochege, Friday Uchenna and Luo, Geping and Obeta, Michael Chukwuma and Owusu, George and Duulatov, Eldiiar and Cao, Liangzhong and Nsengiyumva, Jean Baptiste},
  issn         = {1548-1603},
  journal      = {GISCIENCE & REMOTE SENSING},
  keywords     = {ENERGY BALANCE ALGORITHM,SURFACE,IRRIGATION,MODEL,IMPLEMENTATION,MANAGEMENT,VEGETATION,FLUXES,BASIN,FIELD,evapotranspiration,Landsat 7 ETM+,SEBAL,Small Aral Sea Basin-SASB,oasis-desert ecosystem},
  language     = {eng},
  number       = {8},
  pages        = {1305--1332},
  title        = {Mapping evapotranspiration variability over a complex oasis-desert ecosystem based on automated calibration of Landsat 7 ETM+ data in SEBAL},
  url          = {http://dx.doi.org/10.1080/15481603.2019.1643531},
  volume       = {56},
  year         = {2019},
}

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