06. İYTE Araştırma Merkezleri / IZTECH Research Centers

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Browsing 06. İYTE Araştırma Merkezleri / IZTECH Research Centers by Department "İzmir Institute of Technology. International Water Resources"

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    Book Part
    Citation - Scopus: 2
    High Radiogenic Granites of Western Anatolia for Egs: a Review
    (CRC Press, 2023) Chandrasekharam, Dornadula; Baba, Alper; Ayzit, Tolga; 03.03. Department of Civil Engineering; 03. Faculty of Engineering; 01. Izmir Institute of Technology
    Turkey has made remarkable progress in the hydrothermal sector by promoting both electricity generation and direct application. In terms of power generation, this country is the fourth top country in the world. Nearly 1 billion kWh of energy is being utilized to keep 150,000 homes warm in the winter. In addition, Turkey has huge amounts of uptapped energy in its high radiogenic granites in western Anatolia, spread over a cumulative area of 6,910 km2. The radioactive heat generated by these granites varies from 5 to 13 µW/m3. These granite plutons are located over a region with high heat flow values (120 mW/m2) and the Curie temperature isotherm in this region is located at a depth varying from 6 to 12 km. The heat flow values here are 50% higher than the world average. This thermal regime concurs well with the wet granite melting curve at a heat flow of 85 mW/m2. The entire thermal regime indicates a visco-elastic lower crustal layer in this region. Thus, these granites provide excellent sites for initiating Enhanced Geothermal Systems projects in Turkey. Earlier EGS projects in France and Australia gave power estimates of 79×106 kWh of electricity from 1km3 of such granite. With ongoing development in drilling technology, the classical concept of creating a fracture network is being replaced with loop technology that reduces minor seismic risks and also the cost of power. The most important additional advantage Turkey has is the high-temperature regime at shallow depth, unlike other countries where the granites are located at depths >5km. These factors cause the cost of power to fall below 6 euro cents per kWh. Besides the power and heat, the greatest advantage is the reduction in emissions and achieving UN sustainable development goals. A conservative estimate shows that these radiogenic granites of western Anatolia are capable of generating a minimum of 546×109 kWh of power. Energy from these granites can be utilized to generate freshwater using the desalination method. Earlier studies indicate that to produce 1 m3 of desalinated water, ~16 kWh of electrical energy are needed. The cost of fresh water generated using geothermal energy sources will be <1.5 euros per 1m3. Turkey can utilize the energy from granite for water and food security in the future. © 2024 selection and editorial matter, Dornadula Chandrasekharam and Alper Baba.
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    Article
    Citation - WoS: 6
    Citation - Scopus: 6
    A Novel Land Surface Temperature Reconstruction Method and Its Application for Downscaling Surface Soil Moisture With Machine Learning
    (Elsevier, 2024) Güngör, Şahin; Gündüz, Orhan; 03.10. Department of Mechanical Engineering; 03.07. Department of Environmental Engineering; 03. Faculty of Engineering; 01. Izmir Institute of Technology
    Downscaling of soil moisture data is important for high resolution hydrological modeling. Most downscaling studies in the literature have used spatially discontinuous land surface temperature (LST) maps as the main auxiliary parameter, which limits the creation of continuous soil moisture maps. The number of studies on soil moisture downscaling with machine learning that use gapless LST maps is limited. With this motivation, a hybrid reconstruction method has been proposed in this study to practically obtain continuous LST maps, which are then used to produce high resolution surface soil moisture (SSM) datasets. The proposed method is shown to have high mean performance with R2 and RMSE values of 0.94 and 1.84°K, respectively, for the period between 2019 and 2022. The developed reconstructed LST maps were then used to downscale original 9 km spatial resolution soil moisture datasets of SMAP L3 and SMAP L4 with Random Forest (RF) machine learning algorithm. The RF model were run with four different rainfall datasets, and the MSWEP rainfall dataset was found to produce the best results. The use of antecedent rainfall values as input variables in machine learning models has been shown to improve the performance of the models R2 0.76 to 0.93. The accuracy of the downscaled data was later evaluated for Western Anatolia Basins (WAB) in Türkiye with 31 in-situ stations. The downscaled SMAP L4 had good average statistical indicators R (0.815 ± 0.1), RMSE (0.09 ± 0.047 cm3/cm3), and ubRMSE (0.058 ± 0.025 cm3/cm3). Downscaled SMAP L3 was also validated with in-situ observations with satisfactory R (0.79 ± 0.074), RMSE (0.09 ± 0.043 cm3/cm3), and ubRMSE (0.06 ± 0.026 cm3/cm3) statistics. Furthermore, the performance of the downscaled SMAP L3 was also cross validated with SMAP + Sentinel 1 (L2) dataset between 2019 and 2022. The mean statistics of R (0.761 ± 0.11) and Root Mean Squared Difference (RMSD) (0.05 ± 0.014 cm3/cm3) between downscaled SMAP L3 and L2 data revealed that the new reconstruction method of LST used in the RF model for downscaling of soil moisture performed well to obtain high resolution soil moisture datasets. The proposed technique also overcame the difficulties associated with coastal regions where data was masked for quality considerations, by not only enhancing overall spatial resolution but also filling these data gaps and giving a complete SSM coverage. © 2024 Elsevier B.V.
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    Article
    Citation - WoS: 30
    Citation - Scopus: 35
    Statistical Downscaling of Grace Twsa Estimates To a 1-Km Spatial Resolution for a Local-Scale Surveillance of Flooding Potential
    (Elsevier, 2023) Khorrami, Behnam; Pirasteh, Saied; Ali, Shoaib; Şahin, Onur Güngör; Vaheddoost, Babak; 01. Izmir Institute of Technology
    The Gravity Recovery and Climate Experiment (GRACE) paved the way for large-scale monitoring of the hydrological extremes. However, local scale analysis is aslo challenging due to the coarse resolution of the GRACE estimates. The feasibility of the downscaled GRACE data for the flood monitoring in the Kizilirmak Basin (KB) in Turkiye is investigated in this study by integrating the GRACE and hydrological model outputs of a random forest approach. Results suggest that the TWSA, over the Asagi Kizilirmak Basin (AKB), is ascending with an annual rate of + 3.51mm/yr; while the Orta Kizilirmak Basin (OKB), Yukari Kizilirmak Basin (YKB), Delice Basin (DB), Develi Kapali Basin (DKB), and Seyfe Kapali Basin (SKB) showed descending trend respectively as -1.15mm/yr, -1.58mm/yr, -1.14mm/yr, -2.34mm/yr, and -1.31mm/yr. The hydrological status of the basin showed that in 2003, 2005, 2010-2013, and 2015-2016 periods the study area was prone to the inundation. Hence, by validating the Flood Potential Index (FPI) rates acquired from the downscaled GRACE data, it was shown that the best correlation coefficient (0.73) between FPI and streamflow (Q) is associated with the SKB. It is also concluded that the downscaled TWSA associated with the fine-resolution models depicts acceptable accuracy in determination of the flood potential at local scales.