scholarly journals Evapotranspiration estimation of Urmia Lake Basin using GCOM-C thermal imagery

2021 ◽  
Vol 958 (1) ◽  
pp. 012010
Author(s):  
M Tasumi ◽  
M Moriyama

Abstract Basin-scale monthly and annual evapotranspiration (ET) is estimated for Urmia Lake Basin by applying the Global Change Observation Mission for Climate (GCOM-C) global ETindex estimation algorithm to thermal imagery observed by the GCOM-C satellite. In total, 297 satellite images acquired during 2018-2019 were used in this study. ET estimation accuracy was examined for an area dominated by apple fields using traditional surface irrigation. The estimated ET was 15% lower than the standard crop ET, which was computed using a procedure suggested by the Food and Agriculture Organization of the United Nations on a monthly timescale, and was 8% lower on an annual timescale. Comparison of estimated ET with a satellite-based ET map derived by using the Mapping EvapoTranspiration at high Resolution with Internalized Calibration (METRIC) model showed a similar difference. The 8%–15% differences among the different sources of ET were small, given that a similar or wider range of uncertainty is frequently available even in ground-based ET measurements. Comparison between the estimated ET and the MODIS ET Product (MOD16) revealed a greater difference in the evaluated area of the apple fields. Given the climatic ET demands and the irrigation practices of the area, ET estimation accuracy is more likely to be higher using the dataset derived from this study than using MOD16. The GCOM-C satellite started routine surface observations in January 2018. Its contribution to agricultural water management, such as by estimating ET as presented in this study, will increase as the amount of historical data stored continues to accumulate.

2019 ◽  
Vol 83 (4) ◽  
pp. 993-1002 ◽  
Author(s):  
Mohaddese Effati ◽  
Hossien‐Ali Bahrami ◽  
Mohammad Gohardoust ◽  
Ebrahim Babaeian ◽  
Markus Tuller

2020 ◽  
Vol 13 (4) ◽  
Author(s):  
Fatemeh Bashirian ◽  
Dariush Rahimi ◽  
Saeed Movahedi ◽  
Reza Zakerinejad

2017 ◽  
Vol 38 (5) ◽  
pp. 2298-2313 ◽  
Author(s):  
Zohreh Dehghan ◽  
Seyed Saeid Eslamian ◽  
Reza Modarres

Author(s):  
Yusuf Alizade Govarchin Ghale ◽  
Metin Baykara ◽  
Alper Unal

Abstract. Urmia Lake located in the north-west of Iran, is one of the largest hyper-saline lakes in the world. In recent years, most of the Urmia Lake have been rendered to unusable lands. Drought and rapid increase in agricultural activities are the most important reasons behind the shrinkage of the Lake. This kind of exploitation with the added salinity from irrigation occurring over time has caused increased soil salinity in the basin leading up to desertification. Soil salinity research are crucial to understand underlying causes and consequences of the drying Urmia Lake. In this study, we use remote sensing technology and image processing techniques to detect spatio-temporal variability of salt body, salt affected lands, and development of irrigated lands to estimate the extend of salinization in terms of spectral response of satellite images for the Urmia Lake Basin from 1975 to 2016. The results of this study indicate that salt and salty soil areas has increased dramatically from 1995 to 2014 and more than 5000 km2 of Urmia Lake's water surface area was converted to salt or salty soil bodies during recent years. Salinization and desertification progress are not limited to just dried bottom of the Urmia Lake. Although the area of irrigated lands has increased more than two times during the studied period, soil salinity has increased in regions close to Urmia Lake too. This desertification in the basin have potential to be the source of dust storms, which have adverse effects on people's life and climate as well.


2021 ◽  
Vol 12 ◽  
pp. 100513
Author(s):  
Maryam Mosaffa ◽  
Sara Nazif ◽  
Youssef Khalaj Amirhosseini ◽  
Werner Balderer ◽  
Hadi Mahmoodi Meiman

2009 ◽  
Vol 47 (1) ◽  
pp. 117-120 ◽  
Author(s):  
Alireza Asem ◽  
Behrooz Atashbar ◽  
Nasrullah Rastegar-Pouyani ◽  
Naser Agh

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