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Tytuł pozycji:

Evaluating four remote sensing based models to estimate latent heat flux in semi-arid climate for heterogeneous surface coverage of western Algeria

Tytuł:
Evaluating four remote sensing based models to estimate latent heat flux in semi-arid climate for heterogeneous surface coverage of western Algeria
Autorzy:
Oualid, Tewfik A.
Hamimed, Abderahmane
Khaldi, Abdelkader
Powiązania:
https://bibliotekanauki.pl/articles/2174320.pdf
Data publikacji:
2022
Wydawca:
Instytut Technologiczno-Przyrodniczy
Tematy:
Algeria
energy balance
evapotranspiration
Landsat
METRIC
SPARSE
TIM
TSEB
Źródło:
Journal of Water and Land Development; 2022, 55; 259--275
1429-7426
2083-4535
Język:
angielski
Prawa:
CC BY-NC-ND: Creative Commons Uznanie autorstwa - Użycie niekomercyjne - Bez utworów zależnych 3.0 Unported
Dostawca treści:
Biblioteka Nauki
Artykuł
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Optimal estimation of water balance components at the local and regional scales is essential for many applications such as integrated water resources management, hydrogeological modelling and irrigation scheduling. Evapotranspiration is a very important component of the hydrological cycle at the soil surface, particularly in arid and semi-arid lands. Mapping evapotranspiration at high resolution with internalised calibration (METRIC), trapezoid interpolation model (TIM), two-source energy balance (TSEB), and soil-plant-atmosphere and remote sensing evapotranspiration (SPARSE) models were applied using Landsat 8 images for four dates during 2014-2015 and meteorological data. Surface energy maps were then generated. Latent heat flux estimated by four models was then compared and evaluated with those measured by applying the method of Bowen ratio for the various days. In warm periods with high water stress differences and with important surface temperature differences, METRIC proves to be the most robust with the root-mean-square error (RMSE) less than 40 W∙m-2. However, during the periods with no significant surface temperature and soil humidity differences, SPARSE model is superior with the RMSE of 35 W∙m-2. The results of TIM are close to METRIC, since both models are sensitive to the difference in surface temperature. However, SPARSE remains reliable with the RMSE of 55 W∙m-2 unlike TSEB, which has a large deviation from the other models. On the other hand, during the days when the temperature difference is small, SPARSE and TSEB are superior, with a clear advantage of SPARSE serial version, where temperature differences are less important.

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