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Development of a Three-Dimensional Numerical Hydrodynamic Model of Lake Urmia Using Satellite Data Integration, Field Data, and Data Assimilation

Jamaat, Amir Moez | 2023

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 56457 (09)
  4. University: Sharif University of Technology
  5. Department: Civil Engineering
  6. Advisor(s): Safaie Nematabadi, Ammar
  7. Abstract:
  8. The aim of this research is to use data assimilation in hydrodynamic modeling of Lake Urmia, which is known as one of the world's hypersaline lakes. In other words, it is the first time that the development of a numerical model for Lake Urmia has been accompanied by data assimilation. In recent years, Lake Urmia has experienced unfavorable climatic conditions, resulting in a decline of over 8 meters in its water level over the past 20 years. Hydrodynamic analysis of the lake can play a crucial role in major management decisions for restoration of the lake ecosystem. In this project, the three-dimensional FVCOM model was used to perform numerical modeling, and efforts were made to improve simulated results through data assimilation. Salinity and temperature of the lake were extracted using field data collection and optical satellite images. Machine learning algorithms were employed to model the mentioned variables. Additionally, altimetry modeling of Lake Urmia was carried out using satellite altimetry data, and the changes in water level in the southern and northern regions were compared with the results of the hydrodynamic model. The results of this research demonstrate that the combination of satellite data with data assimilation techniques enhances the accuracy of hydrodynamic modeling in lake environments, and the integration of remote sensing data significantly impacts the data assimilation process. In other words, data assimilation reduces mean errors in salinity and water temperature predictions to about 7 p.s.u and 0.36 oC, respectively, which would otherwise be accompanied by substantial errors without data assimilation. Moreover, the model had a good performance in predicting the water level of the lake with only 0.1 centimeter error. Particularly, hydrodynamic modeling accompanied by data assimilation and lake monitoring through remote sensing allows water resource managers to make informed decisions regarding the management of sensitive water basins like Lake Urmia. This information leads to optimizing the utilization of lake waters, planning optimal irrigation for fields, regulating water release timing, and implementing actions for the rejuvenation and protection of water resources in the region. The provided results in this study are more reliable and accurate compared to those obtained in the previous studies, which will be beneficial for sustainable lake management, closer to water resource managers and decision-makers
  9. Keywords:
  10. Finite Volume Ocean Comuntty Model (FVCOM) ; Remote Sensing ; Urumieh Lake ; Data Assimilation ; Hydrodynamic Modeling ; Satellite Data

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