MAPPING DAM LAKE EVAPORATION USING SEBAL EVAPOTRANSPIRATION MODEL CASE STUDY: AMIR KABIR DAM

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ZAMANI SAEEDE; RAHIMZADEGAN MAJID

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Journal: GEOGRAPHICAL DATA Year:2018 | Volume:27 | Issue:106 Page(s): 7-8

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Information Journal Paper

Title

MAPPING DAM LAKE EVAPORATION USING SEBAL EVAPOTRANSPIRATION MODEL CASE STUDY: AMIR KABIR DAM

Author(s)

ZAMANI SAEEDE | RAHIMZADEGAN MAJID | Issue Writer Certificate

Keywords

SEBAL ALGORITHMQ1

EVAPOTRANSPIRATIONQ1

SATELLITE IMAGESQ2

LAKE DAMQ1

MAPPINGQ2

Abstract

Introduction Evaporation from the lakes behind the dams and freshwater lakes is one of the most important parameters in water resource losses. Therefore, zoning evaporation is very important in water resources management. There are various methods for measuring and estimating EVAPOTRANSPIRATION (ET) that are used according to their accuracy and cost.These models include using evaporation pan and using meteorological models such as Bowen ratio and eddy correlation methods. Nowadays, modern methods such as utilizing satellite remote sensing images are developed to estimate EVAPOTRANSPIRATION in different regions. Surface Energy Balance Algorithm for Land (SEBAL) is one of these algorithms which is highly regarded. SEBAL estimates ET as a residual in energy flux in the surface of land. This is done by calculating the difference in the soil heat flux and the sensible heat flux from the net radiation....

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APA: Copy

ZAMANI, SAEEDE, & RAHIMZADEGAN, MAJID. (2018). MAPPING DAM LAKE EVAPORATION USING SEBAL EVAPOTRANSPIRATION MODEL CASE STUDY: AMIR KABIR DAM. GEOGRAPHICAL DATA, 27(106 ), 7-8. SID. https://sid.ir/paper/360420/en

Vancouver: Copy

ZAMANI SAEEDE, RAHIMZADEGAN MAJID. MAPPING DAM LAKE EVAPORATION USING SEBAL EVAPOTRANSPIRATION MODEL CASE STUDY: AMIR KABIR DAM. GEOGRAPHICAL DATA[Internet]. 2018;27(106 ):7-8. Available from: https://sid.ir/paper/360420/en

IEEE: Copy

SAEEDE ZAMANI, and MAJID RAHIMZADEGAN, “MAPPING DAM LAKE EVAPORATION USING SEBAL EVAPOTRANSPIRATION MODEL CASE STUDY: AMIR KABIR DAM,” GEOGRAPHICAL DATA, vol. 27, no. 106 , pp. 7–8, 2018, [Online]. Available: https://sid.ir/paper/360420/en

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