Browsing by Author "Vaheddoost, Babak"

Now showing 1 - 20 of 23

Citation - WoS: 9
Citation - Scopus: 11
A Joint Evaluation of Streamflow Drought and Standard Precipitation Indices in Aegean Region- Turkey
(SPRINGER BASEL AG, 2023-11-23) Ayse Gulmez; Denizhan Mersin; Babak Vaheddoost; Mir Jafar Sadegh Safari; Gokmen Tayfur; Tayfur, Gokmen; Vaheddoost, Babak; Safari, Mir Jafar Sadegh; Mersin, Denizhan; Gulmez, Ayse
Water is an invaluable substance that ensures the life cycle and causes hydrologic events worldwide. Water deficit also known as drought is a naturally occurring disaster that affects the hydrometeorologic and/or climatic responses in time and space. In this study the meteorologic and hydrologic droughts in Buyuk Menderes Kucuk Menderes and Gediz basins in Turkey are investigated. The streamflow drought index (SDI) and standard precipitation index (SPI) are used considering different time windows. To achieve this the monthly streamflow at Cicekli-Nif Besdegirmenler-Dandalas Bebekler-Rahmanlar and Kocarli-Koprubasi hydrometric stations together with monthly precipitation at 14 meteorologic stations during 1973-2020 (47 years) are used. The SDI and SPI with 1 3 6 and 12 months moving average are then used to express the association between the meteorologic and hydrologic droughts in the basin. Results showed that the SDI depicts no abnormal situations while the SPI rates in the 1980s and 2010s indicated severe droughts. It was concluded that the inner parts of the basins are prone to frequent droughts and there is a concordance between SPI and SDI patterns at the basin level. However minor discrepancies between SPI and SDI do exist and probably originated from temporal delays and water abstraction.
Citation - WoS: 2
Citation - Scopus: 3
A stochastic approach for the assessment of suspended sediment concentration at the Upper Rhone River basin- Switzerland
(SPRINGER HEIDELBERG, 2022-02-03) Babak Vaheddoost; Saeed Vazifehkhah; Mir Jafar Sadegh Safari; Vaheddoost, Babak; Vazifehkhah, Saeed; Safari, Mir Jafar Sadegh
This study addresses the link between suspended sediment concentration precipitation streamflow and direct runoff components. This is important since suspended sediment concentration in the streamflow has invaluable importance in the management of the river basin. For this the daily streamflow time series in five consecutive stations at Upper Rhone River Basin a relatively large basin in the Alpine region of Switzerland daily precipitation at one station and the twice a week suspended sediment concentration records at the most downstream station between January 1981 and October 2020 are used. Initially the base flow and the direct runoff associated with streamflow time series are obtained using the sliding interval method. Elasticity analyses between streamflow and suspended sediment concentration together with correlation autocorrelation partial autocorrelation stationarity and homogeneity are examined by the Augmented Dickey-Fuller and Pettitt's tests respectively. Then various stochastic scenarios are generated using the autoregressive moving average exogenous method (ARMAX). It is concluded that the precipitation and direct runoff have fewer effects on the suspended sediment concentration at downstream of the river. Hence the cumulative effect of the glacier or snowmelt and channel erosion may exceed the effect of rain blown washouts on the suspended sediment concentration at the Port du Scex station. It is found that the ARMAX model results are satisfactory and can be suggested for further application.
Citation - WoS: 12
Citation - Scopus: 16
Application of Signal Processing in Tracking Meteorological Drought in a Mountainous Region
(SPRINGER BASEL AG, 2021-05) Babak Vaheddoost; Mir Jafar Sadegh Safari; Vaheddoost, Babak; Safari, Mir Jafar Sadegh
This study addresses the application of signal processing in the evaluation of meteorological drought associated with monthly precipitation time series. Several drought indices and a Haar wavelet decomposition (WD) with ten components are implemented in the evaluation of the monthly precipitation of a mountainous region called Mount Uludag in Turkey. Monthly precipitation time series in three meteorological stations at the summit and foothills are used. The Standardized Precipitation Index (SPI) is used at monthly annual and 12- and 48-month moving average time frames as the benchmark to investigate the drought patterns. The results obtained by the WD and SPI are then confirmed using the Z-score index (ZSI) at monthly and annual scales together with the modified China Z-index (MCZI) and rainfall anomaly index (RAI) at a monthly scale. Changes in the moments of the distribution correlation analysis mutual information and power spectrum are applied to investigate the nature of the relationship between the sequences of precipitation events in time and space. The temporal correlation analysis together with the mutual information showed that the system has a short-term memory with strong seasonality. Similarly the power spectra depicted major seasonality at 1 3 5 6 12 22 and 60 months in the precipitation time series. It is concluded that the recent drought events have an infrequent nature which altered the sinusoidal patterns of the large-scale events. The SPI-48 and the WD showed that declines are strongly related to the large-scale cycles but the decline patterns are more related to the station located at the mountain summit.
Assessment of Drought in Izmir District Using Standardized Precipitation Index
(Springer Nature, 2025) Tayfur, Gokmen; Vaheddoost, Babak; Safari, Mir Jafar Sadegh; Mersin, Denizhan; Gulmez, Ayse
Assessment of Drought in Izmir District Using Standardized Precipitation Index
(Springer Nature, 2025) Tayfur, Gokmen; Vaheddoost, Babak; Safari, Mir Jafar Sadegh; Mersin, Denizhan; Gulmez, Ayse
Citation - Scopus: 1
Comparability Analyses of Three Meteorological Drought Indices in Turkey
(CRC Press, 2023-07-24) Babak Vaheddoost; Mir Jafar Sadegh Safari; Vaheddoost, Babak; Safari, Mir Jafar Sadegh
The following chapter investigates the role of precipitation in the evaluation of meteorological drought in a mountainous region. For this Mount Uludag in Turkey was taken as the case of study. Three meteorological stations with quite long precipitation records were used. Monthly precipitation time series between January 1980 and October 2018 at the Keles and Osmangazi stations in the northern and southern hillsides together with the Uludag station near the summit were used in the analysis. Afterward the patterns in the data run frequency changes and temporal events related to the time series were evaluated using precipitation anomaly z-index autocorrelation mutual information and power spectrum. It was concluded that there is a strong seasonality in the data at every 6 and 12 months whereas the temporal persistence is quite low and decays after the second time lag. In the next stage three drought indices namely the Standardized Precipitation Index (SPI) Deciles Index (DI) and percent of normal (PN) were calculated at monthly seasonal and annual scales for each station. Finally a model based on the spatial temporal and spatiotemporal properties of the precipitation time series was developed using the multivariate adaptive regression splines (MARS) model. It was concluded that the spatial scenario is the best predictive model in the assessment of precipitation and drought and the SPI is the best one-parameter meteorological drought index for use in drought studies. © 2023 Elsevier B.V. All rights reserved.
Citation - WoS: 2
Citation - Scopus: 2
Data Reconstruction for Groundwater Wells Proximal to Lakes: A Quantitative Assessment for Hydrological Data Imputation
(Multidisciplinary Digital Publishing Institute (MDPI), 2025-03-01) Murat Can; Babak Vaheddoost; Mir Jafar Sadegh Safari; Vaheddoost, Babak; Safari, Mir Jafar Sadegh; Can, Murat
The reconstruction of missing groundwater level data is of great importance in hydrogeological and environmental studies. This study provides a comprehensive and sequential approach for the reconstruction of groundwater level data near Lake Uluabat in Bursa Turkey. This study addresses missing data reconstruction for both past and future events using the Gradient Boosting Regression (GBR) model. The reconstruction process is evaluated through model calibration metrics and changes in the statistical properties of the observed and reconstructed time series. To achieve this goal the groundwater time series from two observational wells and lake water levels during the January 2004 to September 2019 period are used. The lake water level the definition of the four seasons via the application of three dummy variables and time are used as inputs in the prediction of groundwater levels in observation wells. The optimal GBR model calibration is achieved by training the dataset selected based on data gaps in the time series while test-past and test-future datasets are used for model validation. Afterward the GBR models are used in reconstructing the missing data both in the pre- and post-training data sets and the performance of the models are evaluated via the Nash–Sutcliffe efficiency (NSE) Root Mean Square Percentage Error (RMSPE) and Performance Index (PI). The statistical properties of the time series including the probability distribution maxima minima quartiles (Q1–Q3) standard error (SE) coefficient of variation (CV) entropy (H) and error propagation are also measured. It was concluded that GBR provides a good base for missing data reconstruction (the best performance was as high as NSE: 0.99 RMSPE: 0.36 and PI: 1.002). In particular the standard error and the entropy of the system in one case respectively experienced a 53% and 35% rise which was found to be tolerable and negligible. © 2025 Elsevier B.V. All rights reserved.
Citation - WoS: 12
Citation - Scopus: 14
Discharge coefficient for vertical sluice gate under submerged condition using contraction and energy loss coefficients
(Elsevier Ltd, 2021-08) Babak Vaheddoost; Mir Jafar Sadegh Safari; Rasoul Ilkhanipour Zeynali; Zeynali, Rasoul Ilkhanipour; Vaheddoost, Babak; Ilkhanipour Zeynali, Rasoul; Safari, Mir Jafar Sadegh
A novel method is suggested for the determination of flow discharge in vertical sluice gates with considerably small bias. First in order to derive an equation for the discharge coefficient energy-momentum equations are implemented to define the physical realization of the phenomenon. Afterward the discharge coefficient is presented in terms of contraction and energy loss coefficients. Subsequently discharge coefficient contraction and energy loss coefficients were determined through an implicit optimization technique on the data. Data analysis illustrated that there is a meaningful power relationship between the contraction and energy loss coefficients. Thereafter dimensional analysis is performed and an explicit best-fit regression equation is developed for defining the energy loss coefficient. The obtained equations for contraction and energy loss coefficients were then used in the computation of the discharge coefficient and determination of the flow discharge in the vertical sluice gate. The performance of the developed approach is validated against the selected benchmarks existing in the literature. © 2021 Elsevier B.V. All rights reserved.
Drought Dynamics
(Elsevier, 2026) Vaheddoost, Babak; Safari, Mir Jafar Sadegh
Citation - WoS: 17
Citation - Scopus: 22
Enhancing Meteorological Drought Modeling Accuracy Using Hybrid Boost Regression Models: A Case Study from the Aegean Region Türkiye
(Multidisciplinary Digital Publishing Institute (MDPI), 2023-07-26) Enes Gul; Efthimia Staiou; Mir Jafar Sadegh Safari; Babak Vaheddoost; Vaheddoost, Babak; Safari, Mir Jafar Sadegh; Gul, Enes; Staiou, Efthymia
The impact of climate change has led to significant changes in hydroclimatic patterns and continuous stress on water resources through frequent wet and dry spells. Hence understanding and effectively addressing the escalating impact of climate change on hydroclimatic patterns especially in the context of meteorological drought necessitates precise modeling of these phenomena. This study focuses on assessing the accuracy of drought modeling using the well-established Standard Precipitation Index (SPI) in the Aegean region of Türkiye. The study utilizes monthly precipitation data from six stations in Cesme Kusadasi Manisa Seferihisar Selcuk and Izmir at Kucuk Menderes Basin covering the period from 1973 to 2020. The dataset is divided into three sets training (60%) validation (20%) and testing (20%) sets. The study aims to determine the SPI-3 SPI-6 and SPI-12 using a multi-station prediction technique. Three boosting regression models (BRMs) namely Extreme Gradient Boosting (XgBoost) Adaptive Boosting (AdaBoost) and Gradient Boosting (GradBoost) were employed and optimized with the help of the Weighted Mean of Vectors (INFO) technique. Model performances were then evaluated with the Root Mean Square Error (RMSE) Mean Absolute Error (MAE) Mean Absolute Percentage Error (MAPE) Coefficient of Determination (R2) and the Willmott Index (WI). Results demonstrated a distinct superiority of the XgBoost model over AdaBoost and GradBoost in terms of accuracy. During the test phase the XgBoost model achieved RMSEs of 0.496 0.429 and 0.389 for SPI-3 SPI-6 and SPI-12 respectively. The WIs were 0.899 0.901 and 0.825 for SPI-3 SPI-6 and SPI-12 respectively. These are considerably lower than the corresponding values obtained by the other models. Yet the comparative statistical analysis further underscores the effectiveness of XgBoost in modeling extended periods of drought in the Aegean region of Türkiye. © 2023 Elsevier B.V. All rights reserved.
Citation - WoS: 10
Citation - Scopus: 11
Estimation of flow duration and mass flow curves in ungauged tributary streams
(Elsevier Ltd, 2023-07) Babak Vaheddoost; Mustafa Utku Yilmaz; Mir Jafar Sadegh Safari; Vaheddoost, Babak; Yilmaz, Mustafa Utku; Safari, Mir Jafar Sadegh
The mastery in forecasting the streamflow rates is of great importance in the design planning and resilience against droughts. Likewise the application of flow duration and mass flow curves in the design of the reservoir capacity energy generation water allocation etc. especially at the tributary reaches is a great challenge mostly due to the lack of information and data records. In this study we have developed a methodology to obtain the flow duration curve (FDC) and mass flow curve (MFC) in tributary stream stations with the help of estimated streamflow rates. The procedure suggests using two alternative approaches in the selection of the reference station on the mainstream. The streamflow in the reference station is decomposed into direct runoff (DR) and base flow (BF) using one-parameter digital filter method. Together with the precipitation records in the tributary station the DR and BF on the reference station are then used to estimate the FDC and MFC. The multivariate adaptive regression spline (MARS) and random forest (RF) methods are used to alternate each other and the residual of the models are simulated using the autoregressive conditionally heteroscedastic (ARCH) approach to develop the hybrid MARS-ARCH and RF-ARCH models. A data set related to Coruh River Basin in Turkey is used to confirm the methodology while results with R2 ≥ 0.92 reasonable bias and relative error in the estimation of the expected FDC and MFC rates indicated the robustness of the suggested methodology. © 2023 Elsevier B.V. All rights reserved.
Evaluating the Impact of Subsurface Hydraulic Barriers on Qanat Flow Rates Using Quantile Regression Forest
(Nature Portfolio, 2025-11-22) Vaheddoost, Babak; Can, Murat; Safari, Mir Jafar Sadegh
Qanats, as hydraulic innovations, enabled the sustainable extraction and distribution of groundwater for irrigation and domestic use during history. This study presents a data-driven modeling framework that implements Quantile Regression Forest (QRF), Random Forest (RF), and Support Vector Regression (SVR) to predict Qanat discharge under altered subsurface conditions. Using field data from the Dirsak Qanat in northern Iran, a traditional drainage system recently enhanced by the construction of a subsurface dam (SD), we investigate the dam's effect on discharge potential. The modeling framework incorporates determination of multiple hydro-meteorological inputs including precipitation, temperature, evaporation, humidity, runoff depth, infiltration depth and groundwater levels observed at three monitoring wells. A binary (dummy) variable was also introduced to represent the presence or absence of the SD, thereby capturing the associated changes in boundary conditions. The analysis further revealed that the SD and evaporation are the most influential factors, highlighting the combined effects of anthropogenic modifications and climatic variations on the discharge behavior of the Qanats. It was also concluded that the QRF model with a Nash-Sutcliffe Efficiency (NSE) of 0.818, demonstrate strong predictive capability in capturing complex and non-linear hydrological interactions.
Evaluating the Impact of Subsurface Hydraulic Barriers on Qanat Flow Rates Using Quantile Regression Forest
(Nature Portfolio, 2025-11-22) Vaheddoost, Babak; Can, Murat; Safari, Mir Jafar Sadegh
Qanats, as hydraulic innovations, enabled the sustainable extraction and distribution of groundwater for irrigation and domestic use during history. This study presents a data-driven modeling framework that implements Quantile Regression Forest (QRF), Random Forest (RF), and Support Vector Regression (SVR) to predict Qanat discharge under altered subsurface conditions. Using field data from the Dirsak Qanat in northern Iran, a traditional drainage system recently enhanced by the construction of a subsurface dam (SD), we investigate the dam's effect on discharge potential. The modeling framework incorporates determination of multiple hydro-meteorological inputs including precipitation, temperature, evaporation, humidity, runoff depth, infiltration depth and groundwater levels observed at three monitoring wells. A binary (dummy) variable was also introduced to represent the presence or absence of the SD, thereby capturing the associated changes in boundary conditions. The analysis further revealed that the SD and evaporation are the most influential factors, highlighting the combined effects of anthropogenic modifications and climatic variations on the discharge behavior of the Qanats. It was also concluded that the QRF model with a Nash-Sutcliffe Efficiency (NSE) of 0.818, demonstrate strong predictive capability in capturing complex and non-linear hydrological interactions.
Citation - WoS: 2
Evaluation of Streamflow Drought Index in Aegean Region- Turkey
(SPRINGER INTERNATIONAL PUBLISHING AG, 2022) Ayse Gulmez; Denizhan Mersin; Babak Vaheddoost; Mir Jafar Sadegh Safari; Vaheddoost, Babak; Safari, Mir Jafar Sadegh; Mersin, Denizhan; Gulmez, Ayse; H Gokcekus; Y Kassem
Water is an invaluable substance of which ensures the life cycle and hydrological events across the world. In this respect water deficit also known as drought is a natural disaster related to water scarcity in time and space. Although there is no solid definition for the phenomenon the outcome of repeated wet and dry spells cause in economic social and political problems at regional country-wide and world-wide scale. In this study drought associated with the streamflow in the Aegean region which has an important economic historical and wsocio-cultural role in the western Turkey is investigated through the well-known streamflow drought index (SDI). Therefore average discharge in the Cicekli-Nif Besdegirmenler-Dandalas Bebekler-Rahmanlar and Kocarli-Koprubasi station respectively related to on Gediz Buyuk Menderes and Kucuk Menderes basins were used. Then SDI with 1 3 612 months moving average are acquired to express the drought severity associated with the streamflow in the basins. Results showed that the SDI values in all of stations together with the 1 3 6 and 12-month moving averages depicts similar results and no abnormal situation exist during the study period.
Flow and turbulence characteristics of bed load sediment transport for self-cleansing without deposition
(John Wiley and Sons Ltd, 2025-07) Mehrnoush Kohandel Gargari; Ilayda Keskin; Mir Jafar Sadegh Safari; Babak Vaheddoost; Vaheddoost, Babak; Safari, Mir Jafar Sadegh; Keskin, Ilayda; Kohandel Gargari, Mehrnoush
Investigating the structure of flow turbulence and bed load sediment transport is crucial as it provides insights into the functioning of aquatic environments where such variations can lead to changes in ecosystem dynamics. This study focuses on the impact of sediments on the hydraulic characteristics of flow at self-cleansing without deposition conditions of sediment transport. The self-cleansing without deposition is not only a mode of sediment transport in alluvial channels but it also serves as a criterion for the design of lined channels. Among the various design concepts for lined open channels such as sewers and drainage channels self-cleansing without deposition condition is implemented as the most conservative and reliable approach. However most of the conducted experimental studies on self-cleansing without deposition have focused on measuring the basic flow and sediment characteristics for modelling purposes and neglected the effect of bed load sediment size flow discharge and channel bed slope on turbulence characteristics. This study addresses this gap by examining the impact of bed load sediment size bed slope and discharge on turbulence characteristics through a series of experiments conducted in a 12.5 m flume with a rectangular cross-section equipped with an automatic control system (ACS) at the Hydraulic Laboratory of Yaşar University. The channel bed slope sediment discharge flow discharge and depth were adjusted and measured using ACS. Discharge and flow depth were measured using an ultrasonic flow-meter and depth sensors respectively. Flow characteristics were measured using a Vectrino profiler device. The study reveals that bed load sediment transport reduces streamwise velocity especially for coarse particles. Additionally at a constant bed slope velocity differences remain small at lower discharges but become more significant as discharge increases. Turbulence intensity rises with bed load motion more in the streamwise direction than vertically. At a constant bed slope increasing discharge enhances turbulence but the effect is more pronounced at lower slopes and less significant at steeper slopes. Reynolds shear stress increases with particle size and steeper slopes indicating greater shear production. These observations suggest critical implications for the design and optimization of open-channel systems emphasizing the need for detailed consideration of particle sizes and bed conditions in engineering practices. © 2025 Elsevier B.V. All rights reserved.
Citation - Scopus: 1
Meteorological Drought Assessment in Mountainous Regions Based on Outputs of General Circulation Models
(CRC Press, 2023-07-24) Mustafa Nuri Balov; Babak Vaheddoost; Mir Jafar Sadegh Safari; Balov, Mustafa Nuri; Vaheddoost, Babak; Safari, Mir Jafar Sadegh
The availability of water among the different parts of the hydrological cycle has a significant impact on the environment and ecological balance as well as on the food industry and tourism. Drought which can be considered as the shortage of available water in time and/or space has become more frequent and intense in recent years. From the ecological point of view studying the effect of climatic variables on the quantity and quality of flora and fauna needs multidisciplinary comprehensive research and measurements. However the various impacts of extreme climatic events such as droughts on the economy health and welfare of society are highly interconnected with the environmental and ecological considerations of the climate system. © 2023 Elsevier B.V. All rights reserved.
Citation - Scopus: 1
Non-Linear Output Structure Learning: A Novel Multi-Target Technique for Multi-Station and Multi-Index Drought Modelling
(WILEY, 2025-08-28) Mir Jafar Sadegh Safari; Shervin Rahimzadeh Arashloo; Babak Vaheddoost; Rahimzadeh Arashloo, Shervin; Vaheddoost, Babak; Safari, Mir Jafar Sadegh; Arashloo, Shervin Rahimzadeh
Exiting artificial intelligence-based drought models estimate a single drought index in a single station. This study advances drought modelling by proposing Non-linear Output Structure Learning (NOSL) for simultaneously estimating two drought indices at eight stations. A multi-target drought model provides insights for a better understanding of the meteorological and hydrological impacts of drought. Hydro-meteorological data including precipitation evaporation and streamflow are used for a joint estimation of Streamflow Drought Index (SDI) and Standardized Precipitation Evapotranspiration Index (SPEI). The efficacy of the NOSL algorithm is examined against single-target Kernel Ridge Regression (KRR) and Fast Multi-output Relevance Vector Regression (FMRVR) models. The data during October 1981 to September 2015 at a monthly scale (408 Months) from eight different stations in Buyuk Menderes Basin (BMB) located (BMB) in Western T & uuml,rkiye are used in this study. The effects of 1- 3- and 6-month Moving Average (MA) are also considered for drought estimation. Results show that NOSL can effectively estimate the SPEI and SDI indices and outperforms KRR and FMRVR benchmarks. The effectiveness of the NOSL technique can be linked to a structural modelling mechanism based on vector-valued functions where the dependencies among output variables are captured utilising a non-linear function for enhanced performance. The developed multi-target drought model based on the NOSL technique not only helps in incorporating multiple variables in the model for a better estimation but it enhances our understanding of various aspects of droughts and building adaptive strategies and resilience map counter to drought hazard.
Citation - WoS: 2
Citation - Scopus: 2
Projected Drought Intensification in the Büyük Menderes Basin Under CMIP6 Climate Scenarios
(Multidisciplinary Digital Publishing Institute (MDPI), 2025-02-26) Farzad Rotbeei; Mustafa Nuri Balov; Mir Jafar Sadegh Safari; Babak Vaheddoost; Vaheddoost, Babak; Rotbeei, Farzad; Safari, Mir Jafar Sadegh; Nuri Balov, Mustafa
The amplitude and interval of drought events are expected to enhance in upcoming years resulting from global warming and climate alterations. Understanding future drought events’ potential impacts is important for effective regional adaptation and mitigation approaches. The main goal of this research is to study the impacts of climate change on drought in the Büyük Menderes Basin located in the Aegean region of western Türkiye by using the outcomes of three general circulation models (GCMs) from CMIP6 considering two different emission scenarios (SSP2-4.5 and SSP5-8.5). Following a bias correction using a linear scaling method daily precipitation and temperature projections are used to compute the Standardized Precipitation Evapotranspiration Index (SPEI). The effectiveness of the GCMs in projecting precipitation and temperature is evaluated using observational data from the reference period (1985–2014). Future drought conditions are then assessed based on drought indices for three periods: 2015–2040 (near future) 2041–2070 (mid-term future) and 2071–2100 (late future). Consequently the number of dry months is projected and expected to elevate informed by SSP2-4.5 and SSP5-8.5 scenarios during the late-century timeframe (2071–2100) in comparison to the baseline period (1985–2014). The findings of this study offer an important understanding for crafting adaptation strategies aimed at reducing future drought impacts in the Büyük Menderes Basin in the face of changing climate conditions. © 2025 Elsevier B.V. All rights reserved.
Sediment Yield and Discharge in the Changing Climatic Scenario
(CRC Press, 2024-07-08) Eslamian, Saeid; Vaheddoost, Babak; Safari, Mir Jafar Sadegh
Sediment Yield and Discharge in the Changing Climatic Scenario
(CRC Press, 2024-07-08) Eslamian, Saeid; Vaheddoost, Babak; Safari, Mir Jafar Sadegh