University of Oulu

The use of remote sensing to fill the gap data in lake water balance

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Author: El Mosleh, Mohamad1
Organizations: 1University of Oulu, Faculty of Technology, Environmental Engineering
Format: ebook
Version: published version
Access: open
Online Access: PDF Full Text (PDF, 1.7 MB)
Pages: 50
Persistent link:
Language: English
Published: Oulu : M. El Mosleh, 2017
Publish Date: 2017-09-06
Thesis type: Master's thesis (tech)
Tutor: Torabi Haghighi, Ali
Reviewer: Torabi Haghighi, Ali
In the arid and semi-arid regions, closed lakes are extensively used to satisfy the high water demands that threats their existence. The Bakhtegan lake is considered as one of the biggest lakes in Iran and has been drying out in the past years due to intensive irrigation in that region. The multiple modifications applied to the Kor river feeding Bakhtegan has affected the lake water intake drastically where the lake dries out completely during the irrigation season and hot summer days. The river inflow data has been missing between the years 1984 and 1997 due to the destruction of the closest gauge stations which was installed above the lake. The aim of this study is to estimate the flow data during this period by combining water balance simulation and remote sensing techniques. Remote sensing has been considered as a very efficient tool in analyzing water features for many water resources engineering applications. Based on the remotely sensed images of Bakhtegan and the water balance equation for the period (1998–2000), we obtained all components of effective parameters of water balance equation (all inflow, e.g., river inflow, rainfall and outflow, e.g., evaporation) and consequently the area-volume depth curve of the lake was developed. The water balance simulation based on the developed area-volume depth curve was validated for the period (2001–2003) that we had real hydrological and climate data. Finally, the gap data was filled by utilizing the water balance simulation based on the results of remote sensing.
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Copyright information: © Mohamad El Mosleh, 2017. This publication is copyrighted. You may download, display and print it for your own personal use. Commercial use is prohibited.