Article
Environmental Sciences
Roya Sahraei, Yousef Kanani-Sadat, Saeid Homayouni, Abdolreza Safari, Khalid Oubennaceur, Karem Chokmani
Summary: This study proposes a novel hybrid MCDM framework to assess flood susceptibility in large ungauged watersheds, tackling issues of data scarcity and uncertainty in expert opinions. Comparing with different approaches, the proposed method outperforms in terms of statistical measures. By overlaying classified maps with historical flood events locations, it is found that 85.96% of flooded areas are classified as high and very high.
JOURNAL OF FLOOD RISK MANAGEMENT
(2022)
Article
Environmental Sciences
A. Balogun, S. Quan, B. Pradhan, U. Dano, S. Yekeen
Summary: This study proposes an integrated GIS-FANP flood susceptibility model to assess the impacts of flood on residential property prices. Validating the model on Kelantan, Malaysia showed a high accuracy, with a weak positive correlation between highly susceptible flood class and housing locations vs market prices.
JOURNAL OF ENVIRONMENTAL INFORMATICS
(2021)
Article
Environmental Sciences
Ali Azareh, Elham Rafiei Sardooi, Bahram Choubin, Saeed Barkhori, Ali Shahdadi, Jan Adamowski, Shahaboddin Shamshirband
Summary: This study developed an integrated framework for flood susceptibility assessment in the Haraz watershed in Iran, using data to select flood-influencing indices and employing DEMATEL, ANP, and FVF methods for evaluation. The results indicated that sub-watershed C1 was highly susceptible to flooding and in need of flood management.
GEOCARTO INTERNATIONAL
(2021)
Article
Environmental Studies
Francis Miranda, Anna Beatriz Franco, Osvaldo Rezende, Bruno B. F. da Costa, Mohammad Najjar, Assed N. Haddad, Marcelo Miguez
Summary: The identification and classification of flood-prone areas is crucial for flood risk management. A new index-based approach called PhySFI is introduced in this study, which is capable of qualitatively assessing flood-prone areas using physical parameters. This index was developed and validated in Rio de Janeiro, and has proven to be a powerful tool for assessing flood-prone areas in coastal cities.
Article
Computer Science, Interdisciplinary Applications
Huai-Wei Lo, James J. H. Liou
Summary: This article discusses a research paper by Nilashi et al. (2019) on factors influencing medical tourism adoption in Malaysia, highlighting errors and misguided use of fuzzy TOPSIS in their study.
COMPUTERS & INDUSTRIAL ENGINEERING
(2021)
Article
Computer Science, Artificial Intelligence
Melike Erdogan, Ihsan Kaya, Ali Karasan, Murat Colak
Summary: This paper proposes a study using a multi-criteria decision-making method to evaluate alternative solutions of autonomous vehicle driving systems, taking into account risk criteria. The results of the study indicate that "Software Specifications" and "Reliability" are the most important main and sub-criteria.
APPLIED SOFT COMPUTING
(2021)
Article
Engineering, Civil
Kuldeep Kavta, Arkopal K. Goswami
Summary: The study introduces a novel Multi-Criteria Decision Making approach to select appropriate TDM measures, specifically focusing on the case study of Ahmedabad's old city. By employing multiple methods like DEMATEL, ANP, and VIKOR, the research presents a methodological framework for policymakers to select TDM packages in advance.
Article
Mathematics
Jung-Fa Tsai, Chin-Po Wang, Ming-Hua Lin, Shih-Wei Huang
Summary: This study investigates key factors for supplier selection in Taiwan's TFT-LCD industry, focusing on technological abilities and resilience criteria, and utilizing a combination of DEMATEL and ANP methods for analysis. The results reveal that technological abilities and resilience criteria hold significant importance in supplier selection.
Article
Green & Sustainable Science & Technology
Changlu Zhang, Liqian Tang, Jian Zhang
Summary: This study identifies critical indicators in the performance evaluation of green supply chains (GSC) and provides suggestions for improvement. The research framework was determined using the Delphi method and the fuzzy DEMATEL-based ANP model. The critical indicators include the return rate of net assets, the growth rate of profit, the rate of service satisfaction, market share, production flexibility, and the green consensus.
Article
Mathematics
Hsu-Lin Chen, Yi-Chung Hu, Ming-Yen Lee
Summary: Subsidiaries typically begin as a company division and as the company expands, the heads of these divisions gain more authority and play an important role in the company's future operational planning.
Article
Economics
Nistha Dubey, Ajinkya Tanksale
Summary: This study examines challenges and barriers faced by food banks in India, with a focus on policy, finance, infrastructure, human resources, planning coordination, knowledge, and uncertainty. Lack of planning and coordination was identified as the most significant barrier hindering the growth of food banks in India.
SOCIO-ECONOMIC PLANNING SCIENCES
(2022)
Article
Green & Sustainable Science & Technology
Idris Bello Yamusa, Mohd Suhaili Ismail, Abdulwaheed Tella
Summary: This study examines the susceptibility of landslides in a specific area of Malaysia and generates a landslide susceptibility map using multi-criteria decision-making models and GIS technology. The results indicate that the area has a moderate to very high landslide risk, emphasizing the importance of proper intervention in future construction or renovation projects.
Article
Environmental Sciences
Murugesan Bagyaraj, Venkatramanan Senapathi, Sang Yong Chung, Gnanachandrasamy Gopalakrishnan, Yong Xiao, Sivakumar Karthikeyan, Ata Allah Nadiri, Rahim Barzegar
Summary: This study employed the GIS-MCDA model, combining remote sensing, GIS, and analytical hierarchy technique, to identify flood-prone zones and determine the weights of various factors affecting flood risk in Chennai. The results indicated that regions close to rivers, with low elevation, slope, and high runoff density, were more susceptible to flooding. The flood susceptibility map generated by the GIS-MCDA accurately depicted the flood-prone regions in the study area.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2023)
Article
Green & Sustainable Science & Technology
Girish Kumar, Ajith Tom James, Gourav Kumar, Romesh Rajput, Sunny Choudhary
Summary: This paper analyzes the influence of elements and indicators on the sustainability of machine tools. A new hybrid model is developed to determine the priorities of the indicators. The results classify the indicators and provide insights for improving machine sustainability.
ENVIRONMENT DEVELOPMENT AND SUSTAINABILITY
(2023)
Article
Construction & Building Technology
Hai-Min Lyu, Zhen-Yu Yin
Summary: This study introduces an improved multi criteria decision making (MCDM) approach to assess multi-hazard risks in Hong Kong using fuzzy analytical hierarchy process (FAHP) with interval numbers. This approach, incorporating AHP, interval-FAHP, and analytical network process (ANP) into a GIS, shows that more than 15%, 17%, and 18% of areas in Hong Kong are at high risk of floods, muddy-water flows, and landslides, respectively. The comparison suggests that the interval-FAHP-GIS method outperforms AHP-GIS and ANP-GIS in identifying high-risk areas, thanks to its use of interval fuzzy numbers to reflect the importance of assessment factors.
SUSTAINABLE CITIES AND SOCIETY
(2023)
Article
Energy & Fuels
Mercedeh Taheri, Abdolmajid Mohammadian, Fatemeh Ganji, Mostafa Bigdeli, Mohsen Nasseri
Summary: This review provides a clear and comprehensive classification of energy-based approaches considering the role of land surface temperature (LST) in solving the energy budget. Three general approaches using LSTs derived from climate and land surface models, satellite-based data, and energy balance closure are presented. The concepts, inputs, and assumptions of energy-based LSMs and SEB algorithms are discussed in detail, along with the limitations and challenges of these approaches.
Article
Engineering, Marine
Mohsen Abyani, Mohammad Reza Bahaari, Mohamad Zarrin, Mohsen Nasseri
Summary: This paper predicts the failure pressure of corroded offshore pipelines using different machine learning techniques. An efficient finite element based algorithm is developed to numerically estimate the failure pressure, and reliable machine learning methods are used due to the high computational effort. Gaussian Process Regression (GPR) and MultiLayer Perceptron (MLP) models show the best performance among all the chosen models. It was also found that the Maximum Von-Mises Stress (MVMS) of the pipeline increases with water depth at low internal pressure levels, while increasing water depth leads to a reduction in MVMS values at high internal pressure levels.
Article
Meteorology & Atmospheric Sciences
Omid Zandi, Banafsheh Zahraie, Mohsen Nasseri, Ali Behrangi
Summary: This study applied a stacked generalization ensemble approach to generate high-resolution precipitation estimates and compared its performance with an optimized local weighted linear regression (LWLR) algorithm. The results showed that the stacking model outperformed LWLR and had a better extrapolation ability in high elevations.
ATMOSPHERIC RESEARCH
(2022)
Article
Geosciences, Multidisciplinary
Mercedeh Taheri, Milad Shamsi Anboohi, Rahimeh Mousavi, Mohsen Nasseri
Summary: This study investigates the performance of multi-source Global Gridded Snow Products (GGSPs) in hydrological modeling using multi-stage calibration strategies. The results show that using GGSPs as complementary information can improve the accuracy of the modeling compared to traditional calibration methods.
FRONTIERS OF EARTH SCIENCE
(2023)
Article
Environmental Sciences
Amir Reza Azarnivand, Masoud Sadrinasab, Mohsen Nasseri
Summary: Climate change affects global atmospheric circulation patterns and intensifies extreme weather events. This study investigates the impact of climate change and meteorological variables on water circulation patterns in the Persian Gulf, leading to changes in salinity, temperature, and density of water mass. The findings project significant alterations in physical properties, which can have detrimental effects on the aquatic ecosystem in the Gulf. The study highlights the importance of developing adaptation management plans in line with sustainable development goals.
ESTUARIES AND COASTS
(2023)
Article
Water Resources
Mercedeh Taheri, Milad Shamsi Anboohi, Mohsen Nasseri, Abdolmajid Mohammadian
Summary: This study developed a water balance model to estimate evapotranspiration and established a correct dynamic relationship between evapotranspiration and soil moisture using physical concepts. The evaluation results showed that the model had better performance in simulating streamflow and groundwater level, with higher accuracy compared to alternative models, and the estimated spatiotemporal distribution of evapotranspiration agreed well with climatic-vegetation conditions.
HYDROLOGICAL SCIENCES JOURNAL
(2023)
Article
Meteorology & Atmospheric Sciences
Omid Zandi, Mohsen Nasseri, Banafsheh Zahraie
Summary: This article investigates the potential of using large-scale precipitation products and land surface characteristics to improve the accuracy of an elevation-based spatial non-stationary regression method. A two-step approach of downscaling and merging is proposed and assessed in an orographically complex region in Iran. The results show that the proposed framework improves the accuracy of precipitation predictions and has better extrapolation ability and robustness compared to the benchmark model.
INTERNATIONAL JOURNAL OF CLIMATOLOGY
(2023)
Article
Geochemistry & Geophysics
Rahimeh Mousavi, Mohsen Nasseri, Saeed Abbasi, Mercedeh Taheri, Milad Shamsi Anboohi
Summary: This study investigates the impact of precipitation and evapotranspiration (ET) products on hydrological model performance, specifically water balance in two basins in Iran. The results show that using large-scale products as model inputs in mountainous and highland watersheds, where ground measurements are not possible, can effectively maintain model performance. Simultaneously calibrating ET and streamflow, the use of ET products improves ET simulation but decreases the accuracy of streamflow simulation.
Article
Computer Science, Interdisciplinary Applications
Rahimeh Mousavi, Mohsen Nasseri, Saeed Abbasi
Summary: The study proposes a statistical blending method that combines five large-scale and satellite precipitation and evapotranspiration products in three modeling scenarios. The blending procedures, organized using a conceptual water balance model, improve the performance of the model and show conformity with the observed precipitation patterns and behavior in the study area.
JOURNAL OF HYDROINFORMATICS
(2023)
Article
Meteorology & Atmospheric Sciences
Hesam Barkhordari, Mohsen Nasseri, Hamidreza Rezazadeh
Summary: Previous studies have shown that global gridded hydroclimatic products lack precision and consistency. This study evaluates the efficiency of eight streamflow datasets in two large-scale watersheds with different climate conditions. Two tuning procedures are used to correct the products, resulting in improved accuracy in terms of statistical metrics and streamflow simulation.
THEORETICAL AND APPLIED CLIMATOLOGY
(2023)
Article
Computer Science, Interdisciplinary Applications
Neda Dolatabadi, Mohsen Nasseri, Banafsheh Zahraie
Summary: Radar satellite imagery is widely used for accurate estimation of soil moisture. This study investigated the contribution of vegetation canopy to the accuracy of retrieved soil moisture and used the Integral Equation Model (IEM) coupled with the Water Cloud Model (WCM) to estimate surface soil moisture. Data-driven models (Support Vector Machine and Regression Tree) were used to obtain soil moisture estimates at measurement stations based on radar signal and vegetation indices. The Regression Tree model showed the best performance and was used to calculate regionalized estimates for the watershed. The results demonstrated the feasibility of using data-driven models for regionalized soil moisture measurements.
EARTH SCIENCE INFORMATICS
(2023)
Article
Geochemistry & Geophysics
Maryam Khodadadi, Tarokh Maleki Roozbahani, Mercedeh Taheri, Fatemeh Ganji, Mohsen Nasseri
Summary: This study explores the relationship between groundwater withdrawal and the uncertainty effects of actual evapotranspiration (ET) by incorporating the uncertainty of calculated ET values into a comprehensive interval-based water balance model. The study area is the Ghorveh-Dehgolan basin in Northern Iran. The proposed approach improves the statistical metrics of the model responses and decreases the uncertainty level tied to simulated streamflow and groundwater levels.
Article
Environmental Sciences
Yasaman Mohammadi, Omid Zandi, Mohsen Nasseri, Yousef Rashidi
Summary: The aim of this paper is to use machine learning models (Random Forest and Gaussian Process Regression) to characterize the spatiotemporal patterns of daily PM10 in Tehran, Iran, for policy-makers. The performance of these models was compared to a benchmark interpolator called Inverse Distance Weighting using statistical metrics. The results showed that the machine learning models performed well in spring and summer, while Inverse Distance Weighting and machine learning models performed better in winter and autumn, respectively. Additionally, the results of the Correlated Triple Collocation analysis suggested that machine learning techniques provided a more accurate spatial distribution. Overall, the Inverse Distance Weighting method may not provide a realistic estimation of pollutant levels in the study region.
Article
Engineering, Environmental
Arash Ghomlaghi, Mohsen Nasseri, Bardia Bayat
Summary: Precipitation is crucial for hydroclimatic studies, and accurate measurement is essential. While satellite data is available, gauge measurements remain the most reliable. Current research focuses on redesigning rain gauge networks globally, but few have explored the potential of using global gridded precipitation products for network optimization.
STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT
(2023)
Article
Environmental Sciences
Mohammad Masoud Mohammadpour Khoie, Mohsen Nasseri, Mohammad Ali Banihashemi
Summary: This study examines the impacts of human activities and climate change on streamflow and sediment transport in the Gorganroud watershed in northern Iran. The results suggest that changes in land use have contributed more than 60% to the changes in streamflow and sediment regime, with the increase in orchard land use being the primary driver.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2023)
Article
Engineering, Civil
Arfan Arshad, Ali Mirchi, Javier Vilcaez, Muhammad Umar Akbar, Kaveh Madani
Summary: High-resolution, continuous groundwater data is crucial for adaptive aquifer management. This study presents a predictive modeling framework that incorporates covariates and existing observations to estimate groundwater level changes. The framework outperforms other methods and provides reliable estimates for unmonitored sites. The study also examines groundwater level changes in different regions and highlights the importance of effective aquifer management.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Lihua Chen, Jie Deng, Wenzhe Yang, Hang Chen
Summary: A new grid-based distributed karst hydrological model (GDKHM) is developed to simulate streamflow in the flood-prone karst area of Southwest China. The results show that the GDKHM performs well in predicting floods and capturing the spatial variability of karst system.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Faruk Gurbuz, Avinash Mudireddy, Ricardo Mantilla, Shaoping Xiao
Summary: Machine learning algorithms have shown better performance in streamflow prediction compared to traditional hydrological models. In this study, researchers proposed a methodology to test and benchmark ML algorithms using artificial data generated by physically-based hydrological models. They found that deep learning algorithms can correctly identify the relationship between streamflow and rainfall in certain conditions, but fail to outperform traditional prediction methods in other scenarios.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Yadong Ji, Jianyu Fu, Bingjun Liu, Zeqin Huang, Xuejin Tan
Summary: This study distinguishes the uncertainty in drought projection into scenario uncertainty, model uncertainty, and internal variability uncertainty. The results show that the estimation of total uncertainty reaches a minimum in the mid-21st century and that model uncertainty is dominant in tropical regions.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Z. R. van Leeuwen, M. J. Klaar, M. W. Smith, L. E. Brown
Summary: This study quantifies the effectiveness of leaky dams in reducing flood peak magnitude using a transfer function noise modelling approach. The results show that leaky dams have a significant but highly variable impact on flood peak magnitude, and managing expectations should consider event size and type.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Zeda Yin, Yasaman Saadati, M. Hadi Amini, Linlong Bian, Beichao Hu
Summary: Combined sewer overflows pose significant threats to public health and the environment, and various strategies have been proposed to mitigate their adverse effects. Smart control strategies have gained traction due to their cost-effectiveness but face challenges in balancing precision and computational efficiency. To address this, we propose exploring machine learning models and the inversion of neural networks for more efficient CSO prediction and optimization.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Qimou Zhang, Jiacong Huang, Jing Zhang, Rui Qian, Zhen Cui, Junfeng Gao
Summary: This study developed a N-cycling model for lowland rural rivers covered by macrophytes and investigated the N imports, exports, and response to sediment dredging. The findings showed a considerable N retention ability in the study river, with significant N imports from connected rivers and surrounding polders. Sediment dredging increased particulate nitrogen resuspension and settling rates, while decreasing ammonia nitrogen release, denitrification, and macrophyte uptake rates.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Xue Li, Yingyin Zhou, Jian Sha, Man Zhang, Zhong-Liang Wang
Summary: High-resolution climate data is crucial for predicting regional climate and water environment changes. In this study, a two-step downscaling method was developed to enhance the spatial resolution of GCM data and improve the accuracy for small basins. The method combined medium-resolution climate data with high-resolution topographic data to capture spatial and temporal details. The downscaled climate data were then used to simulate the impacts of climate change on hydrology and water quality in a small basin. The results demonstrated the effectiveness of the downscaling method for spatially differentiated simulations.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Tongqing Shen, Peng Jiang, Jiahui Zhao, Xuegao Chen, Hui Lin, Bin Yang, Changhai Tan, Ying Zhang, Xinting Fu, Zhongbo Yu
Summary: This study evaluates the long-term interannual dynamics of permafrost distribution and active layer thickness on the Tibetan Plateau, and predicts future degradation trends. The results show that permafrost area has been decreasing and active layer thickness has been increasing, with an accelerated degradation observed in recent decades. This has significant implications for local water cycle processes, water ecology, and water security.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Chi Zhang, Xu Zhang, Qiuhong Tang, Deliang Chen, Jinchuan Huang, Shaohong Wu, Yubo Liu
Summary: Precipitation over the Tibetan Plateau is influenced by systems such as the Asian monsoons, the westerlies, and local circulations. The Indian monsoon, the westerlies, and local circulations are the main systems affecting precipitation over the entire Tibetan Plateau. The East Asian summer monsoon primarily affects the eastern Tibetan Plateau. The Indian monsoon has the greatest influence on precipitation in the southern and central grid cells, while the westerlies have the greatest influence on precipitation in the northern and western grid cells. Local circulations have the strongest influence on the central and eastern grid cells.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Manuel Almeida, Antonio Rodrigues, Pedro Coelho
Summary: This study aimed to improve the accuracy of Total Phosphorus export coefficient models, which are essential for water management. Four different models were applied to 27 agroforestry watersheds in the Mediterranean region. The modeling approach showed significant improvements in predicting the Total Phosphorus diffuse loads.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Yutao Wang, Haojie Yin, Ziyi Wang, Yi Li, Pingping Wang, Longfei Wang
Summary: This study investigated the distribution and transformation of dissolved organic nitrogen (DON) in riverbed sediments impacted by effluent discharge. The authors found that the spectral characteristics of dissolved organic matter (DOM) in surface water and sediment porewater could be used to predict DON variations in riverbed sediments. Random forest and extreme gradient boosting machine learning methods were employed to provide accurate predictions of DON content and properties at different depths. These findings have important implications for wastewater discharge management and river health.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Saba Mirza Alipour, Kolbjorn Engeland, Joao Leal
Summary: This study assesses the uncertainty associated with 100-year flood maps under different scenarios using Monte Carlo simulations. The findings highlight the importance of employing probabilistic approaches for accurate and secure flood maps, with the selection of probability distribution being the primary source of uncertainty in precipitation.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Janine A. de Wit, Marjolein H. J. van Huijgevoort, Jos C. van Dam, Ge A. P. H. van den Eertwegh, Dion van Deijl, Coen J. Ritsema, Ruud P. Bartholomeus
Summary: The study focuses on the hydrological consequences of controlled drainage with subirrigation (CD-SI) on groundwater level, soil moisture content, and soil water potential. The simulations show that CD-SI can improve hydrological conditions for crop growth, but the success depends on subtle differences in geohydrologic characteristics.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Constantin Seidl, Sarah Ann Wheeler, Declan Page
Summary: Water availability and quality issues will become increasingly important in the future due to climate change impacts. Managed Aquifer Recharge (MAR) is an effective water management tool, but often overlooked. This study analyzes global MAR applications and identifies the key factors for success, providing valuable insights for future design and application.
JOURNAL OF HYDROLOGY
(2024)