Environmental Engineering / Çevre Mühendisliği
Permanent URI for this collectionhttps://hdl.handle.net/11147/4321
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Article Citation - WoS: 6Citation - Scopus: 6A Novel Land Surface Temperature Reconstruction Method and Its Application for Downscaling Surface Soil Moisture With Machine Learning(Elsevier, 2024) Güngör, Şahin; Gündüz, OrhanDownscaling 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.Article Citation - WoS: 19Citation - Scopus: 18An Appraisal of the Local-Scale Spatio-Temporal Variations of Drought Based on the Integrated Grace/Grace-fo Observations and Fine-Resolution Fldas Model(Wiley, 2023) Khorrami, Behnam; Ali, Shoaib; Gündüz, OrhanThe gravity recovery and climate experiment (GRACE) observations have so far been utilized to detect and trace the variations of hydrological extremes worldwide. However, applying the coarse resolution GRACE estimates for local-scale analysis remains a big challenge. In this study, a new version of the fine resolution (1 km) Famine early warning systems network Land Data Assimilation System (FLDAS) model data was integrated into a machine learning model along with the GRACE data to evaluate the subbasin-scale variations of water storage, and drought. With a correlation of 0.99 and a root mean square error (RMSE) of 3.93mm of its results, the downscaling model turned out to be very successful in modelling the finer resolution variations of TWSA. The water storage deficit (WSD) and Water Storage Deficit Index (WSDI) were used to determine the episodes and severity of drought events. Accordingly, two severe droughts (January 2008 to March 2009 and September 2019 to December 2020) were discerned in the Kizilirmak Basin (KB) located in Central Turkiye. The characterization of droughts was evaluated based on WSDI, scPDSI, and model-based drought indices of the soil moisture storage percentile (SMSP) and groundwater storage percentile (GWSP). The results indicated discrepancies in the drought classes based on different indices. However, the WSDI turned out to be more correlated with GWSP, suggesting its high ability to monitor groundwater droughts as well.Conference Object 3d Modeling of a Historical Mine Waste Site Using Uav Images: Estimation of Stockpile Volumes(Springer, 2023) Önal, Okan; Gündüz, OrhanIn recent decades, the use of Unmanned Aerial Vehicles (UAV) for land surveying became very popular because of their simplicity and low cost. Aerial images of the site can be used for the reconstruction of the site’s 3D digital model. Once proper calibrations are made, these digital models can be used for several purposes including stockpile volume estimation, stability analyses, forensic engineering and archiving, etc. In this study, the 3D model of an abandoned historical mine waste disposal site located in Balıkesir-Turkey was reconstructed for the estimation of the waste stockpile volumes. The historical mine site is a facility that was abandoned more than 80 years ago. Mine wastes of different quality were disposed of in and around the site along the hydrologically intermittent creek that passes through the site. No engineered precautions were taken at the site to reduce the environmental impacts and all waste piles were exposed to the natural eroding effect of precipitation and wind. The total amount of the waste volume is not known accurately, which prevents researchers to quantify the potential impacts associated with different waste stockpiles. Thus, a 3D digital model of the site was created by using UAV data obtained from a quadcopter and later processed to obtain a digital topography of the site with an improved accuracy value of ± 2 cm. The stockpiles were later analyzed with geographic information systems to characterize the magnitude of mine wastes and to propose alternative engineering solutions for environmental mitigation. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2023.Article Citation - WoS: 21Citation - Scopus: 21Remote Sensing-Based Monitoring and Evaluation of the Basin-Wise Dynamics of Terrestrial Water and Groundwater Storage Fluctuations(Springer, 2023) Khorrami, Behnam; Gündüz, OrhanThe recent dynamics of terrestrial water storage (TWS) and groundwater storage (GWS) fluctuations were investigated based on the Gravity Recovery And Climate Experiment (GRACE) observations over 25 basins of Türkiye. Coarse-resolution GRACE estimates were downscaled based on the Random Forest algorithm. The impacts of precipitation (P) and evapotranspiration (ET) on the variations of water storage were also assessed. The findings demonstrated good performance for the RF model in simulating finer resolution estimates of TWS. The results indicated a diminishing trend of TWS and its hydrologic components over all the basins from 2003 to 2020. The Doğu Akdeniz Basin with the annually decreasing TWS and GWS of 1.15cm/yr and 1.10cm/yr was the most critical basin of Türkiye. The least storage loss was observed in the Batı Karadeniz Basin with the annual TWS and GWS loss of 0.38cm/yr and 0.45cm/yr , respectively. Based on the results, Türkiye has lost, on average, an estimated 5.16km3/yr and 4.09km3/yr of its TWS and GWS, respectively, which are equivalent to the total storage loss of 92.88km3 and 73.62km3 of TWS and GWS during the last 18 years. The results also indicated that P and ET interact differently with the variations of TWS and GWS. The net water flux was revealed to be partially correlated with the total water storage fluctuations, suggesting the governing role of other deriving forces particularly the anthropogenic factors in the spatiotemporal variations of Türkiye’s water storage; therefore, a sector-specific analysis of the water storage variations is crucial for the country, particularly by concentrating more on the dynamics of GWS. Graphical Abstract: [Figure not available: see fulltext.]. © 2023, The Author(s), under exclusive licence to Springer Nature Switzerland AG.Article Citation - WoS: 16Citation - Scopus: 20Development of an Emission Estimation Method With Satellite Observations for Significant Forest Fires and Comparison With Global Fire Emission Inventories: Application To Catastrophic Fires of Summer 2021 Over the Eastern Mediterranean(Elsevier, 2023) Bilgiç, Efem; Tuna Tuygun, Gizem; Gündüz, OrhanIn the past few decades, forest fires have increased in number and severity, especially in the Mediterranean regions of Turkiye and Greece, where significant fires caused damage to thousands of hectares of land as well as wildlife. The main objective of the present study is to develop an emission estimation method with satellite-based burned area data from significant forest fire events in the Eastern Mediterranean in July-August 2021. In the first stage of this study, pre-fire and post-fire images of the study area acquired by the Sentinel-2 satellite were processed to calculate the normalized burn rate difference index (dNBR). Then, CORINE Land Cover (CLC) data were used for detecting land cover classes in the burned areas. Atmospheric emissions of NOx, CO, SO2, total suspended particulate matter (TSP), particulate matter with diameters that are equal to or smaller than 2.5 & mu;m (PM2.5), and black carbon (BC) were estimated using the EMEP/EEA Tier 2 -technology-specific approach method, in which burned area maps were retrieved using Sentinel-2 imageries and later combined with land cover type and burning efficiency to estimate the quantity of burning biomass emissions. Emission factors were then used to estimate the fires' trace gas and aerosol emissions. The results showed that the highest burned areas were found in the western Mediterranean region in Turkiye and Central Greece (⁓50,000 ha). The atmospheric emissions from these fires were calculated to be similar in both countries. Furthermore, emission amounts were compared with three different global fire emission inventories including GFAS, GFED, and FINN. The emissions obtained from the GFAS database were the highest emissions of the four emission estimation approaches and our estimated emissions were close to the GFAS. Emissions calculated from the other two databases (FINN and GFED) mostly provided underestimated emissions. The emission uncertainties in this study mainly originated from assumptions regarding the inclusion of burned area efficiency in emission calculations, the landcover dataset, and the emission factors used. Overall, this study is considered a new approach to emission calculations using Sentinel-2 data. This research provides further insight into the use of Sentinel-2 data in emission calculation applications at the local to regional scales.Article Citation - WoS: 40Citation - Scopus: 38Investigating the Local-Scale Fluctuations of Groundwater Storage by Using Downscaled Grace/Grace-fo Jpl Mascon Product Based on Machine Learning (ml) Algorithm(Springer, 2023) Khorrami, Behnam; Ali, Shoaib; Gündüz, OrhanGroundwater storage is of grave significance for humanity by sustaining the required water for agricultural irrigation, industry, and domestic use. Notwithstanding the impressive contribution of the state-of-the-art Gravity Recovery and Climate Experiment (GRACE) to detecting the groundwater storage anomaly (GWSA), its feasibility for the characterization of GWSA variation hotspots over small scales is still a major challenge due to its coarse resolution. In this study, a spatial water balance approach is proposed to enhance the spatial depiction of groundwater storage and depletion changes that can detect the hotspots of GWSA variation. In this study, Random Forest Machine Learning (RFML) model was utilized to simulate fine-resolution (10 km) groundwater storage based on the coarse resolution (50 km) of GRACE observations. To this end, parameters including soil moisture, snow water, evapotranspiration, precipitation, surface runoff, surface elevation, and GRACE data were integrated into the RFML model. The results show that with a correlation of above 0.98, the RFML model is very successful in simulating the fine-resolution groundwater storage over the Western Anatolian Basin (WAB), Turkiye. The results indicate an estimated annual depletion rate of 0.14 km(3)/year for the groundwater storage of the WAB, which is equivalent to about 2.57 km(3) of total groundwater depletion from 2003 to 2020. The findings also suggest that the downscaled GWSA is in harmony with the original GWSA in terms of temporal variations. The validation of the results demonstrates that the correlation is increased from 0.56 (for the GRACE-derived GWSA) to 0.60 (for the downscaled GWSA) over the WAB.Article Citation - WoS: 31Citation - Scopus: 34Model-Coupled Grace-Based Analysis of Hydrological Dynamics of Drying Lake Urmia and Its Basin(Wiley, 2023) Khorrami, Behnam; Ali, Shoaib; Şahin, Onur Güngör; Gündüz, OrhanLake Urmia basin (LUB), in northwestern Iran, is under the influence of extreme degradation due to a number of natural and anthropogenic factors. The existence of the Lake is critical for the microclimate of the region as well as the quality of human life and wildlife, which necessitates an up-to-date and holistic analysis of its hydrological dynamics. In this premise, satellite-based terrestrial water storage (TWS) received from the Gravity Recovery and Climate Experiment (GRACE) mission was coupled with hydrometeorological modelling and assessment tools to analyse the hydrological status of the lake and its basin. As a new gap-filling approach, the Seasonal-Trend decomposition using Locally estimated scatterplot smoothing (LOESS) (STL) decomposition technique was proposed in this study to reconstruct the missing TWS data. Integrating satellite precipitation data with the Catchment Land Surface Model (CLSM) and WaterGAP model outputs, the hydrological status of the lake was investigated. The STL-based TWS turned out to concord well with the simulated TWS from the CLSM indicating the acceptable performance of the proposed technique. The findings revealed that the LUB had undergone an alarming hydrological situation from 2003 to 2021 with a total loss of 10 and 7.56km3 from its TWS and groundwater storage (GWS), respectively. The water level time series also indicated that the water level of the lake had diminished with an annual rate of -70 +/- 21cm/year corresponding to a total water level depletion of about 13.35 +/- 3.9m during the 2003-2021 period. The GRACE-derived TWS and GWS also agreed well with the CLSM simulations. Assessment of the extreme events of the LUB suggested that the basin suffered from a severe dry event in 2008 resulting in the depletion of its water storage and water level. It was also found that from 2003 onward, a critical hydrological setting had dominated the LUB with a negative hydrological balance of -0.96km3.Article Citation - WoS: 11Citation - Scopus: 13A Systematic Assessment of Flooding Potential in a Semi-Arid Watershed Using Grace Gravity Estimates and Large-Scale Hydrological Modeling(Taylor & Francis, 2022) Khorrami, Behnam; Fıstıkoğlu, Okan; Gündüz, OrhanThe emergence of the Gravity Recovery And Climate Experiment (GRACE) paved the way for remote tracking of hydrological water cycle components at large scales. With the main motivation of evaluating the feasibility of the coarse resolution GRACE data for small-scale analysis, the GRACE data and large-scale hydrological models were utilized in an integrated manner to monitor the variations of the flood potential index (FPI) over the Western Anatolian Basin (WAB). The results show an ascending trend for monthly and annual FPI over the WAB. The results also suggest that the monthly FPI in 2015, 2003, 2009, and 2016 was the highest, from which the highest potentiality of flood appertains to 2015/07 with an FPI of 0.92. The lowest and highest annual FPI is 0.26 (in 2007) and 0.76 (in 2015), respectively. The validation of the results indicates that variations of FPI coincide with that of the flood incidents, stream discharge, Standardized Precipitation Index (SPI), and the simulated flood risk. The findings accentuate the high feasibility of the GRACE JPL Mascons for better surveillance of floods over local scale areas. Highlights The coarse resolution GRACE JPL mascon functions very well in tracing the spatio-temporal characteristics of flood incidents over local scales. There is an ascending trend in the variations of flood potential over the Western Anatolia Basin (WAB). The WAB has experienced its lowest and highest possibility of flooding in 2007 and 2015 with an average FPI of 0.26 and 0.76, respectively. The variations of the flood potential index (FPI) coincides with that of the reported flood incidents, stream discharge, Standardized Precipitation Index (SPI), and the simulated flood risk.Article Citation - WoS: 36Citation - Scopus: 38Detection and Analysis of Drought Over Turkey With Remote Sensing and Model-Based Drought Indices(Taylor & Francis, 2022) Khorrami, Behnam; Gündüz, OrhanUnder the severe impacts of climate change, drought has become one of the most undesirable and complex natural phenomena with critical consequences for the environment, economy and society. The orthodox drought monitoring approaches use observations of meteorological stations, which are typically restricted in time and space. Remote sensing, conversely, provides continuous global coverage of a variety of hydro-meteorological variables that are influential in drought, and data extracted from remote sensing and modeling missions are now considered more practical and alluring for researchers. In this study, we applied a combination of field data, remotely sensed data and modeled data to detect and quantitatively analyze drought phenomena. To achieve this objective, we utilized Terrestrial Water Storage Anomalies (TWSA) estimations from GRACE mission, Normalized Difference Vegetation Index (NDVI) from MODIS mission, Surface Runoff (R) and Evapotranspiration from ERA5 reanalysis datasets and Soil Moisture (SM) from GLDAS data model to evaluate their feasibility in detecting recent droughts over Turkey. We validated the accuracy of several remote sensing-based indices (GRACE Drought Severity Index, Water Storage Deficit Index [WSDI], Soil Moisture Index, Standardized Runoff Index and NDVI) with the traditional indices (SPI and SPEI) calculated from in situ observations of precipitation. The results revealed that the GRACE-based WSDI gave the best performance with high correlations with the SPI index both temporally and spatially over Turkey. We also found that monthly and annual time series of WSDI agreed well with the SPI index with correlations of 0.69 and 0.73, respectively. The results of drought analysis also indicated that WSDI could be used as a proxy to standard meteorological drought indices over Turkey as it performed well to detect and characterize the recent droughts of Turkey based on its comparisons to SPI results.Article Citation - WoS: 4Citation - Scopus: 5Radiological Modeling of the Impacts of the Chernobyl Nuclear Power Plant Accident on Turkey and Southwest Asia(Elsevier, 2022) Bilgiç, Efem; Gündüz, OrhanMany studies investigated the impacts of the Chernobyl Nuclear Power Plant accident on Europe. However, majority of these have spatially excluded the highly populated southeast region of Chernobyl, including countries such as Turkey, Armenia, Georgia and Iran. In this study, a comprehensive environmental and radiological analysis were conducted particularly for this region. For this purpose, atmospheric dispersion and ground deposition of radionuclides were estimated using a Lagrangian particle dispersion model, FLEXPART. Totally, six simulations were conducted and model results were validated with measurements from Europe and Turkey. Furthermore, total effective dose equivalent (TEDE) values were estimated for adults and infants using the most current dose conversion factors of ICRP. Highest deposition of 137Cs were found in around Eastern Black Sea areas (10–40 kBq/m2). Similar values were found in some locations of Armenia and Azerbaijan under some scenarios, but country averages of 137Cs deposition were lower than 10 kBq/m2 for both countries. No significant depositions were found in southwest Iran, but relatively higher depositions (2–10 kBq/m2) of 137Cs were estimated along the Turkish border. Although there were slightly higher values in northern areas of Syria, Iraq, Lebanon and Cyprus, 137Cs depositions were mostly less than 2 kBq/m2. The 1-year TEDE value was calculated less than 1 mSv throughout the model domain except for some regions of eastern Black Sea. Highest values in lifetime dose values were calculated along the Black Sea coasts of Turkey and Georgia. Overall, infants were affected more from ionizing radiation compared to adults in this region.