Article
Environmental Sciences
Anna Pelosi, Giovanni Battista Chirico, Pierluigi Furcolo, Paolo Villani
Summary: This study proposes a methodology for assessing mean annual maximum rainfall at sub-hourly scale by combining historical and newer time series data. A linear correlation is found between rainfall maxima with different durations, enabling the use of mechanical station data for sub-hourly assessments.
Article
Meteorology & Atmospheric Sciences
Edouard Singirankabo, Emmanuel Iyamuremye
Summary: This study aims to estimate the frequency and magnitude of intense rainfall events in Kigali. The results indicate that the intensity and frequency of rainfall in Kigali will increase in the future. The study suggests that the generalized Pareto distribution model fits the data well. The findings of this study are crucial for understanding the occurrence of these events and can serve as a tool for decision-making and policy development.
METEOROLOGICAL APPLICATIONS
(2022)
Article
Engineering, Civil
V Agilan, N. Umamahesh, P. P. Mujumdar
Summary: The study aims to quantify the threshold uncertainty in peaks over threshold method and finds that under nonstationary conditions, the choice of threshold leads to higher uncertainty in extreme rainfall return levels.
JOURNAL OF HYDROLOGY
(2021)
Article
Environmental Sciences
Abubakar Haruna, Juliette Blanchet, Anne-Catherine Favre
Summary: Intensity-duration-frequency (IDF) curves are important for water resources engineering. We use all non-zero rainfall intensities and the extended generalized Pareto distribution to model their distribution. We compare three approaches for building IDF curves and find that the data-driven approach is the best model. It can accurately model observed intensities, is reliable and robust, and captures space and time variability of extreme rainfall in Switzerland.
WATER RESOURCES RESEARCH
(2023)
Article
Meteorology & Atmospheric Sciences
M. A. Ben Alaya, F. W. Zwiers, X. Zhang
Summary: The uniform risk engineering practices for structural design require estimates of extreme wind loads based on observational data, which are affected by sampling uncertainty and potential biases. If estimates are biased, reliability could be compromised.
WEATHER AND CLIMATE EXTREMES
(2021)
Article
Computer Science, Interdisciplinary Applications
Senem Tekin, Emrah Altun, Tolga can
Summary: The study introduces a new extreme value model, and through applying it to real data modeling, it is found that the POT-KumGP model produces more accurate results compared to the POT-GP model.
EARTH SCIENCE INFORMATICS
(2021)
Article
Computer Science, Artificial Intelligence
Mi Zhang, Daizong Ding, Xudong Pan, Min Yang
Summary: Time series prediction is widely used in many safety-critical scenarios, but conventional square loss fails to model extreme events. In this study, we propose a unified loss form called Generalized Extreme Value Loss (GEVL) to bridge the misalignment between the estimation and the ground-truth, and introduce three heavy-tailed kernels to enhance the modeling of extreme events.
IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING
(2023)
Article
Geosciences, Multidisciplinary
Paola Mazzoglio, Ilaria Butera, Pierluigi Claps
Summary: In this study, the spatial variability of sub-daily rainfall extremes over Italy is investigated taking into account the influence of local orographic effects. The study uses the Improved Italian - Rainfall Extreme Dataset (I-2-RED) to analyze the orographic effects through a local regression approach. Different criteria for selecting the local sample are examined. The results confirm previous findings and provide material for future investigations on the physical explanation of reverse orographic effects.
GEOMATICS NATURAL HAZARDS & RISK
(2023)
Article
Computer Science, Interdisciplinary Applications
Benjamin D. Youngman
Summary: This article introduces the R package evgam, which provides functions for fitting extreme value distributions including the generalized extreme value and generalized Pareto distributions. The package also supports quantile regression using the asymmetric Laplace distribution, which is useful for estimating high thresholds. The main addition of package evgam is the ability to model extreme value distribution parameters using generalized additive models with objectively estimated smoothness using Laplace's method.
JOURNAL OF STATISTICAL SOFTWARE
(2022)
Article
Engineering, Geological
Xin Liu, Yu Wang
Summary: In the assessment and management of rainfall-induced landslides, the probability of slope failure is often used as an index to measure landslide risk. This study provides analytical solutions to assess the probability of slope failure caused by rainfall events, annual probability of slope failure induced by rainfall, and slope failure probability over multiple years. The proposed method utilizes a bivariate distribution of rainfall intensity and duration and a critical rainfall pattern curve to represent a slope's performance under different rainfall patterns. The method is validated using a cut slope in South Korea, showing consistent results with observed slope failures.
ENGINEERING GEOLOGY
(2023)
Article
Meteorology & Atmospheric Sciences
Marc-Andre Falkensteiner, Harald Schellander, Gregor Ehrensperger, Tobias Hell
Summary: This paper proposes a modification of the MEVD method, called TMEV, for the analysis of non-stationary precipitation extremes. The TMEV method can explicitly account for seasonal differences and identify longterm trends and seasonal variations. Experimental results show that the TMEV method provides similar error characteristics to the simplified MEVD method for estimating quantiles.
WEATHER AND CLIMATE EXTREMES
(2023)
Article
Environmental Sciences
Renato Morbidelli, Carla Saltalippi, Jacopo Dari, Alessia Flammini
Summary: The main finding of this paper is that using rainfall data with coarse temporal resolution can lead to underestimation errors in extreme rainfall estimation and affect the analysis of climate change impacts. It is worth noting that different climate trend analysis methods may produce different results.
Article
Engineering, Chemical
Youssef Kassem, Huseyin Gokcekus, Rifat Gokcekus
Summary: This study aims to identify suitable probability functions for estimating rainfall distribution in the Guzelyurt Region, Northern Cyprus, and evaluate their performance in comparison to commonly used models. Based on statistical analysis and goodness-of-fit tests, the study found that Beta, Log-Pearson 3, and exponential (2P) distributions are the best for studying average rainfall characteristics, while Burr, Wakeby, and Nakagami distributions are the best fit for actual total rainfall data.
DESALINATION AND WATER TREATMENT
(2021)
Article
Environmental Sciences
Tossapol Phoophiwfa, Teerawong Laosuwan, Andrei Volodin, Nipada Papukdee, Sujitta Suraphee, Piyapatr Busababodhin
Summary: This study proposes an adaptive parameter estimation approach for the Generalized Extreme Value distribution (GEVD) using an artificial neural network (ANN), addressing the challenges associated with parameter estimation. By harnessing the power of ANNs, the proposed methodology provides an innovative and effective solution for estimating the parameters of the GEVD, enhancing our understanding of extreme value analysis.
Article
Water Resources
Giuseppe Mascaro, Simon Michael Papalexiou, Daniel B. Wright
Summary: This study advances the understanding and modeling of the space-time correlation structure and marginal distribution of short-duration precipitation. The results show significant seasonal differences in the correlation structure and distribution of precipitation, with summer precipitation exhibiting weak correlation and heavy-tailed distribution, and winter precipitation exhibiting strong correlation and light-tailed distribution. Moreover, the study identifies the anisotropy of winter precipitation at long durations, possibly influenced by the motion of frontal storms.
ADVANCES IN WATER RESOURCES
(2023)
Article
Green & Sustainable Science & Technology
Mohammed K. H. Radwan, Chiu Chuen Onn, Kim Hung Mo, Soon Poh Yap, Ren Jie Chin, Sai Hin Lai
Summary: Coal fly ash and granulated ground blast furnace slag are widely used as supplementary cementitious materials. This study found that incorporating 20-30% fly ash in ternary blends can improve flow characteristics. While partially replacing cement may reduce early-age compressive strength, it can improve later-age strength, with ternary blends containing 20% and 30% fly ash exhibiting the highest compressive strength after 28 days.
ENVIRONMENT DEVELOPMENT AND SUSTAINABILITY
(2022)
Article
Engineering, Multidisciplinary
Ghada Abdalrahman, Sai Hin Lai, Pavitra Kumar, Ali Najah Ahmed, Mohsen Sherif, Ahmed Sefelnasr, Kwok Wing Chau, Ahmed Elshafie
Summary: This study developed a model based on the characteristics parameters of treated wastewater to predict the infiltration rate. The optimal model was found to be the first combination of inputs, including all seven parameters, using the MLP model with a 90% data division. The model achieved high accuracy in predicting the infiltration rate.
ENGINEERING APPLICATIONS OF COMPUTATIONAL FLUID MECHANICS
(2022)
Article
Mathematics
Lloyd Ling, Sai Hin Lai, Zulkifli Yusop, Ren Jie Chin, Joan Lucille Ling
Summary: The curve number (CN) rainfall-runoff model has been found to have limitations in consistently predicting runoff results. This study presents a calibrated model that is statistically significant and does not rely on return period data. The research also highlights the importance of not solely relying on land-use and land cover when selecting CN values.
Article
Meteorology & Atmospheric Sciences
Cia Yik Ng, Wan Zurina Wan Jaafar, Yiwen Mei, Faridah Othman, Sai Hin Lai, Juneng Liew
Summary: This study analyzes the changes of precipitation extremes in Peninsular Malaysia based on long-term rainfall records. The findings show that the intensity and occurrence of extreme precipitation events have increased in response to the rise of global surface temperature. The study also reveals regional and seasonal variations in precipitation extremes in Peninsular Malaysia and their correlation with the El Nino-Southern Oscillation.
INTERNATIONAL JOURNAL OF CLIMATOLOGY
(2022)
Article
Chemistry, Multidisciplinary
Biao He, Sai Hin Lai, Ahmed Salih Mohammed, Mohanad Muayad Sabri Sabri, Dmitrii Vladimirovich Ulrikh
Summary: This study developed a regular random forest model to accurately estimate the environmental impact of blasting. To enhance the model's performance, several techniques were proposed. The results showed that all refined weighted models outperformed the regular model, with the refined weighted RF model using the whale optimization algorithm performing the best. Sensitivity analysis revealed that the powder factor has the most significant impact on the prediction of peak particle velocity.
APPLIED SCIENCES-BASEL
(2022)
Article
Green & Sustainable Science & Technology
Gege Cheng, Sai Hin Lai, Ahmad Safuan A. Rashid, Dmitrii Vladimirovich Ulrikh, Bin Wang
Summary: The current research aims to investigate the effect of parameters on the confinement coefficient, Ks, using machine learning and develop a new computational model to address this issue. Based on previous research, six effective parameters were identified and a supply-demand-based optimization model was developed. The performance of the model depends on main parameters such as market size and iteration. Comparisons with classical models showed that the new SDO-ANFIS model outperformed others. Different relationships between parameters were considered to identify the strongest and weakest parameters for this study.
Article
Plant Sciences
Jen Feng Khor, Lloyd Ling, Zulkifli Yusop, Ren Jie Chin, Sai Hin Lai, Ban Hoe Kwan, Danny Wee Kiat Ng
Summary: Ageing oil palm crops in Malaysia have a significant negative impact on the oil palm yield, leading to lower production and increased harvesting costs. Despite the recovery of the oil palm yield after the 1997/98 El Nino event, it failed to recover after the recent 2015/16 El Nino. This is due to the accumulation of aged oil palm plantations in Malaysia, resulting in increasing financial losses. The study shows that the oil palm yield downtrend pattern is consistent regardless of El Nino events for the most recent 15 years (2005 to 2019).
Article
Mathematics
Danial Jahed Armaghani, Biao He, Edy Tonnizam Mohamad, Y. X. Zhang, Sai Hin Lai, Fei Ye
Summary: This study proposes two neuro-based metaheuristic models, neuro-imperialism and neuro-swarm, to estimate the peak particle velocity (PPV) caused by blasting. Through extensive observation and data collection, a detailed modeling procedure was conducted to estimate PPV values using both empirical methods and intelligence techniques. The neuro-swarm model outperforms the others in terms of accuracy.
Review
Engineering, Civil
Hong Kang Ji, Majid Mirzaei, Sai Hin Lai, Adnan Dehghani, Amin Dehghani, Tessa Maurer
Summary: Conceptual rainfall-runoff (CRR) models are widely used in climate change impact studies, but their transferability in a climate variability context has not been systematically assessed. This paper examines the transferability of CRR models and proposes a strategy to diagnose model transferability for assessing their prediction ability under various climate conditions.
JOURNAL OF HYDROLOGY
(2023)
Article
Construction & Building Technology
Biao He, Danial Jahed Armaghani, Sai Hin Lai
Summary: Overbreak, caused by tunnel blasting, can lead to delays and increased costs in construction. It is crucial to develop a model that accurately predicts overbreak. In this study, the random forest model was optimized using the grey wolf, whale optimization, and tunicate swarm algorithms to predict overbreak based on seven input factors. The results showed that the RF-TSA model had the highest accuracy in tackling overbreak issues.
TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY
(2023)
Article
Chemistry, Multidisciplinary
Seng Choon Toh, Sai Hin Lai, Majid Mirzaei, Eugene Zhen Xiang Soo, Fang Yenn Teo
Summary: This study introduces a systematic methodology for comparing rainfall datasets from IMERG satellite and rain gauges. Automated shell scripts were developed for data downloading and storage, while PHP programs were built for data visualization. LSTM with ADAM optimizer trained against MSE loss was used to improve daily IMERG estimations. The approach increases the accuracy of satellite estimations, reduces bias, MAE, RMSE, and improves KGE. It establishes a comprehensive data processing and analysis pipeline for diverse datasets and regions.
APPLIED SCIENCES-BASEL
(2023)
Article
Computer Science, Interdisciplinary Applications
Woon Yang Tan, Sai Hin Lai, Kumar Pavitra, Fang Yenn Teo, Ahmed El-Shafie
Summary: Water security and urban flooding are major sustainability concerns, and this study introduces a novel method of using rates of change in artificial intelligence models for predicting floods. The LSTM model outperformed the MLP model and showed significant improvement in forecast accuracy.
JOURNAL OF HYDROINFORMATICS
(2023)
Article
Green & Sustainable Science & Technology
Chia Yu Huat, Danial Jahed Armaghani, Sai Hin Lai, Haleh Rasekh, Xuzhen He
Summary: Mechanised tunnelling is widely used for twin tunnel construction in urban areas, but surface settlement caused by the tunnelling activities is a common challenge. Existing methods for determining surface settlement are often constrained by soil types and are time-consuming, and they often omit crucial parameters such as tunnel operational factors. Therefore, this paper employs 3D numerical analysis to simulate tunnelling-induced surface settlement, taking into account various factors and incorporating data from in-situ and laboratory tests. The obtained results closely match field measurements, and the approach allows for customizable mitigation strategies. Overall, this paper is highly important in improving the planning and construction of sustainable tunnels. Evaluation: 9/10.
Review
Engineering, Civil
Mujahid Ali, Sai Hin Lai
Summary: In rock design projects, mechanical properties such as unconfined compressive strength (UCS) and deformation (E) are frequently used. Due to the challenges of direct measurement, researchers often rely on indirect investigations using rock index tests. These properties play an essential role in modern design methods involving numerical modeling techniques. The current study compares laboratory tests, statistical analysis, and intelligent techniques for estimating UCS and E, and highlights the importance of considering variations in rock types and applying modern techniques to improve accuracy.
Article
Engineering, Environmental
Dehua Zhao, Wai Yan Cheah, Sai Hin Lai, Eng-Poh Ng, Kuan Shiong Khoo, Pau Loke Show, Tau Chuan Ling
Summary: Heavy metals in industrial wastewater are hazardous and can be enriched in the food chain, leading to serious global environmental problems. Biosorption, especially when microalgae and bacteria are combined, is an effective and affordable method for treating heavy metal wastewater. This review discusses the advantages, mechanisms, and potential applications of microalgae-bacteria consortia as biosorbents, aiming to promote the development of more effective ways for bioremediation of heavy metals from wastewater.
JOURNAL OF ENVIRONMENTAL CHEMICAL ENGINEERING
(2023)
