Yurui Fan

Yurui Fan
University of Regina · Faculty of Engineering and Applied Science

Doctor of Philosophy

About

119
Publications
12,310
Reads
How we measure 'reads'
A 'read' is counted each time someone views a publication summary (such as the title, abstract, and list of authors), clicks on a figure, or views or downloads the full-text. Learn more
3,351
Citations
Introduction
Skills and Expertise

Publications

Publications (119)
Article
Full-text available
In this study, we attempt to quantify the potential impacts of two global warming levels (i.e., 1.5 °C and 2.0 °C) on extreme temperature indices across China. The CMIP6 dataset is first evaluated against the CN05.1 observation for the historical period of 1995–2014. Then, future spatiotemporal patterns of changes in extreme temperature at two glob...
Article
Full-text available
In recent years, concurrent climate extreme conditions (i.e., hot‐dry, cold‐dry, hot‐wet, and cold‐wet) have led to various unprecedented natural disasters (e.g., floods, landslide, wildfire, droughts, etc.), causing significant damages to human societies and ecosystems. This is especially true for China where many unprecedented natural disasters h...
Article
Full-text available
In this study, a climate-streamflow modeling framework (CSF) is advanced to generate future climate projections and assess climate change impacts on water. The proposed CSF incorporates global climate models (GCMs), meteorological factors downscaled by the providing regional climate impacts for studies (PRECIS), and stepwise-clustered hydrological...
Article
In this study, a factorial inexact copula stochastic programming (FICSP) method is developed for planning the regional-scale water-energy-food nexus (WEFN) system. The FICSP cannot only deal with uncertainties expressed as interval and random parameters, but also handle the interdependence among correlated random variables. Moreover, the multilevel...
Article
Full-text available
The very nature of weather forecasts and verifications and the way they are used make it impossible for one single or absolute standard of evaluation. However, little research has been conducted on verifying deterministic multi‐category forecasts, which is based on the attribute of uncertainty. The authors propose a new approach using two mutual in...
Article
Full-text available
Background Hydrological extremes such as floods generally have multidimensional attributes with complex dependence structures. This leads to the urgent demand of hydrological risk analysis within a multivariate context. In this study, the bivariate hydrologic risk framework is proposed based on the bivariate copula method. In the proposed risk anal...
Article
Long-term hydrological projections can vary substantially depending on the combination of meteorological forcing dataset, hydrologic model (HM), emissions scenario, and natural climate variability. Identifying dominant sources of model spread in an ensemble of hydrologic projections is critically important for developing reliable hydrological proje...
Article
In this study, an iterative factorial data assimilation (IFDA) framework is developed to holistically characterize the individual and interactive effects of various uncertain factors on hydrological data assimilation (DA). The IFDA framework is flexible and is able to reveal the impacts for different numbers of factors under consideration. An itera...
Article
In this study, a particle copula Metropolis-Hastings (PCMH) approach was developed for reliable uncertainty quantification of hydrological predictions. The proposed PCMH approach employs a mixed particle evolution scheme, which integrates the Gaussian perturbation and copula-based dependent sampling methods. The Metropolis ratio is then employed to...
Preprint
Full-text available
In this study, a climate-streamflow modeling framework (CSF) is advanced to generate future climate projections and assess climate change impacts on water. The proposed CSF incorporates global climate models (GCMs), meteorological factors downscaled by the providing regional climate impacts for studies (PRECIS), and stepwise-clustered hydrological...
Article
Water, energy and food security are the prerequisites for coping with intensified climate change, and also the guarantee for sustaining socio-economic development. This study aims to establish a “Pressure-State-Response” (PSR) model to evaluate the water-energy-food (WEF) system security and clarify the main factors affecting WEF development, syste...
Article
A disaggregated multi-level factorial hydrologic data assimilation model (FHDA) is proposed for exploring not only the direct effects from individual uncertainties but also, more importantly, the composite ones from multi-layer and multi-parameter interactions among multiple uncertainties in hydrologic data assimilation systems. Based on a disaggre...
Article
In this study, an inexact fractional programming method is employed for planning the regional-scale water-energy-food nexus (WEFN) system. The IFP cannot only deal with uncertainties expressed as interval parameters, but also handle conflicts among multiple decision stakeholders. The IFP approach is then applied to planning the WEFN system of Henan...
Article
Full-text available
This study analyzed the multivariate flood risk for the river Thames at Kingston based on historical flood data from the National River Flow Archive (NRFA) website. The bivariate risk analysis framework was prepared from the joint return periods of the peak flow (m3/s) and 3-day annual maximum flow (m3/s) flood pair. A total of 137 samples of flood...
Article
Full-text available
In this study, an iterative factorial multimodel Bayesian copula (IFMBC) framework was developed for revealing uncertainties in risk inferences of compound extremes under the consideration of diverse model structures and parameter sets. Particularly, an iterative factorial analysis (IFA) method would be advanced in IFMBC to track the dominant contr...
Code
Main R code for “Development of a disaggregated multi-level factorial hydrologic data assimilation model ”
Article
Management of water-food-energy nexus (WEFN) is of great importance to achieve the Sustainable Development Goals. The development of WEFN management strategies is challenged by extensive uncertainties in different system components. Also, agricultural activities would contribute a large portion of the total GHG emissions in many countries, which ar...
Article
Synergetic development of water, energy and food is prerequisite for coping with issues of increment of global population, deterioration of ecological environment and aggravation of climate change. This study aims to develop a scenario-based type-2 fuzzy interval programming (STFIP) approach for planning agricultural water, energy and food (WEF) as...
Article
In this study, a factorial multimodel Bayesian copula (FMBC) method is proposed to investigate various uncertainties in the copula-based multivariate risk models and further track the major contributors to the imprecise predictions for different risk indices. In FMBC, the copula models with different marginals and dependence structures will be firs...
Article
An integrated PCA-SCA-ANOVA framework (abbreviated as PSAF) is advanced to analyze the impacts of multiple factors on water-flow variation. PSAF incorporates techniques of principle component analysis (PCA), stepwise-cluster analysis (SCA), and analysis of variance (ANOVA) within a general framework. PSAF cannot only quantify the sensitivity of wat...
Article
This study introduced a clustered polynomial chaos expansion (CPCE) model to reveal random propagation and dynamic sensitivity of uncertainty parameters in hydrologic prediction. In the CPCE model, the random characteristics of the streamflow simulations resulting from parameter uncertainties are characterized through the polynomial chaotic expansi...
Article
Extensive uncertainties exist in hydroclimatic risk analysis. Especially in multivariate hydrologic risk inferences, uncertainties in individual hydroclimatic extremes such as floods and their dependence structure may lead to bias and uncertainty in future hydrologic risk predictions. In this study, a parameter uncertainty and sensitivity evaluatio...
Article
A vine copula‐based ensemble downscaling (VCED) framework is proposed to jointly downscale the projected precipitation from multiple regional climate models (RCMs). This approach can effectively reduce the biases inherent to precipitation projections from different RCMs and thus provide more reliable ensemble projections. The proposed approach was...
Article
Nuclear power has the potential to provide a clean solution to relieve environmental pressures caused by increasing fossil fuel consumption. As an emerging technology, small modular reactors (SMRs) are developed to tackle global needs for providing safe, clean, and economic energy. The identification of suitable sites for SMRs, which is a multiface...
Data
Data for multivariate flood risk analysis
Data
Flood data at Zhangjiashan station of Jing River basin
Article
Full-text available
Extensive uncertainties exist in hydrologic risk analysis. Particularly for interdependent hydrometeorological extremes, the random features in individual variables and their dependence structures may lead to bias and uncertainty in future risk inferences. In this study, an iterative factorial copula (IFC) approach is proposed to quantify parameter...
Article
Full-text available
Sensitivity analysis is an important component for modelling water resource and environmental processes. Analysis of Variance (ANOVA), has been widely used for global sensitivity analysis for various models. However, the applicability of ANOVA is restricted by this biased variance estimator. To address this issue, the subsampling based ANOVA method...
Article
This study aims to develop a multi-preference based interval fuzzy-credibility constrained programming (MIFCP) approach for planning the regional-scale water-resources management system (RWMS) of Henan Province, China. This is the first attempt at planning RWMS through combining interval parameter programming (IPP), fuzzy-credibility constrained pr...
Article
Full-text available
Extreme precipitation can seriously affect the ecological environment, agriculture, human safety, and property resilience. A full-scale and scientific assessment in extreme precipitation characteristics is necessary for water resources management and providing decision-making support to mitigate the potential losses brought by extreme precipitation...
Article
Water and energy are closely linked and restrict each other, which has become major restraints to urban development associated with constricted water resources availability, increased electricity demand and limited environmental capacity. In this study, a copula-based fuzzy interval-random programming method is proposed through integration of copul...
Article
Noise pollution has been considered as a major challenge for the life of quality and engineering practices for environmental noise control for urban communities is of great importance. In this study, a series of experimental investigations are conducted to investigate the effects of a vacuum on the sound reduction and acoustic properties of porous...
Article
In this study, an interval joint-probabilistic stochastic flexible programming method is proposed by integrating interval joint-probabilistic stochastic programming and flexible programming into one framework. It can not only be effective for handling interval-fuzzy information associated with flexible constraints, but also be efficient for reflect...
Article
The management of water resources system and energy system belongs to different decision-making departments, and there is a certain hierarchical relationship between them. Optimizing the configuration of regional-scale water and energy systems from a global perspective, and considering the correlations between water resources shortage risk and ener...
Article
In this study, a factorial Bayesian copula (FBC) method is proposed to quantify parameter uncertainties in copula-based models and then reveal their impacts on hydrologic risk inferences within a multivariate context. In detail, Bayesian inference and factorial analysis are integrated into copula-based multivariate risk models to (1) quantify param...
Article
Full-text available
The unique characteristics of topography, landforms, and climate in the Loess Plateau make it especially important to investigate its extreme precipitation characteristics. Daily precipitation data of Loess Plateau covering a period of 1959–2017 are applied to evaluate the probability features of five precipitation indicators: the amount of extreme...
Article
Full-text available
In this study, a nested ensemble filtering (NEF) approach is advanced for uncertainty parameter estimation and uncertainty quantification of a traffic noise model. As an extension of the ensemble Kalman filter (EnKF) and particle filter methods, the proposed NEF method improves upon the ensemble Kalman filter (EnKF) method by incorporating the samp...
Preprint
Full-text available
Extensive uncertainties exist in hydrologic risk analysis. Particularly for interdependent hydrometeorological extremes, the random features in individual variables and their dependence structures may lead to bias and uncertainty in future risk inferences. In this study, a full-subsampling factorial copula (FSFC) approach is proposed to quantify pa...
Article
Full-text available
A fuzzy random conditional value-at-risk-based linear programming (FCVLP) model was proposed in this study for dealing with municipal solid waste (MSW) management problems under uncertainty. FCVLP improves upon the existing fuzzy linear programming and fuzzy random conditional value-at-risk methods by allowing analysis of the risks of violating con...
Article
Full-text available
Drought is one of the most widespread and destructive hazards over the Loess Plateau (LP) of China. Due to climate change, extremely high temperature accompanied with drought (expressed as hot drought) may lead to intensive losses of both properties and human deaths in future. A hot drought probabilistic recognition system is developed to investiga...
Article
Full-text available
In the bivariate hydrologic correlation analysis framework, the correlation analysis between rainfall and runoff in Xiangxi River is constructed using Archimedean Copula method. Results show that: (1) the monthly rainfall and runoff in Xiangxi River water shed has a relatively strong positive correlation based on Kendall and Spearman's rank correla...
Article
Full-text available
Frequency analysis of streamflow is critical for water-resources system planning, water conservancy projects and the mitigation of hydrological extremes events. In this study, a maximum entropy-Archimedean copula-based Bayesian network (MECBN) method has been proposed for frequency analysis of monthly streamflow in the Kaidu River Basin, which inte...
Article
In this study, the Providing Regional Climates for Impacts Studies (PRECIS) and the Regional ClimateModel (RegCM) system as well as theVariable InfiltrationCapacity (VIC)macroscale hydrologicmodel were integrated into a general framework to investigate impacts of future climates on the hydrologic regime of the Athabasca River basin. Regional climat...
Article
Extensive uncertainties exist in many resources and environmental management problems, which can be interrelated and thus amplify the complexity and nonlinearity of study systems. The interactions from dependent random variables pose significant impacts on the potential management strategies. In this study, an inexact copula-based stochastic progra...
Article
Full-text available
In this study, a coupled dynamical-copula downscaling approach was developed through integrating the Providing Regional Climates for Impacts Studies (PRECIS) modeling system and the copula method. This approach helps to reflect detailed features at local scales based on dynamical downscaling, while also effectively simulating the interactions betwe...
Article
Full-text available
In this research, a multistagedistribution-generation planning (MDGP) model is developed for clean power generation in the regional distributed generation (DG) power system under multiple uncertainties. The developed model has been applied for sustainable energy system management at Urumqi, China. Various scenarios are designed to reflect variation...
Article
In this study, a generalized fuzzy chance constrained programming method is developed for the energy system planning in Guangzhou under multiple uncertainties. Through integrating the generalized fuzzy programming and chance-constrained programming into an inexact optimization framework, this method can handle uncertainties expressed as probability...
Article
Full-text available
This study develops a multivariate eco-hydrological risk-assessment framework based on the multivariate copula method in order to evaluate the occurrence of extreme eco-hydrological events for the Xiangxi River within the Three Gorges Reservoir (TGR) area in China. Parameter uncertainties in marginal distributions and dependence structure are quant...
Article
Full-text available
In this study, an integrated simulation, inference and optimization approach with two-stage health risk assessment (i.e., ISIO-THRA) is developed for supporting groundwater remediation for a petroleum-contaminated site in western Canada. Both environmental standards and health risk are considered as the constraints in the ISIO-THRA model. The healt...
Article
Full-text available
Apparent changes in the temperature patterns in recent years brought many challenges to the province of Ontario, Canada. As the need for adapting to climate change challenges increases, the development of reliable climate projections becomes a crucial task. In this study, a regional climate modeling system, Providing Regional Climates for Impacts S...
Article
In this study, a copula-based stochastic fuzzy-credibility programming (CSFP) method is developed for planning regional-scale electric power systems (REPS). CSFP cannot only deal with multiple uncertainties presented as random variables, fuzzy sets, interval values as well as their combinations, but also reflect uncertain interactions among multipl...
Article
In this study, a copula-based flexible-stochastic programming (CFSP) method is developed for planning regional energy system (RES). CFSP can deal with multiple uncertainties expressed as interval values, random variables and fuzzy sets as well as their combinations employed to objective function and soft constraints. It can also reflect uncertain i...
Article
Full-text available
Water resources systems are associated with a variety of complexities and uncertainties due to socio-economic and hydro-environmental impacts. Such complexities and uncertainties lead to challenges in evaluating the water resources management alternatives and the associated risks. In this study, the factorial analysis and fuzzy random value-at-risk...
Article
An integrated simulation-optimization (ISO) approach is developed for assessing climate change impacts on water resources. In the ISO, uncertainties presented as both interval numbers and probability distributions can be reflected. Moreover, ISO permits in-depth analyses of various policy scenarios that are associated with different levels of econo...
Article
In this study, a Bayesian-based multilevel factorial analysis (BMFA) method is developed to assess parameter uncertainties and their effects on hydrological model responses. In BMFA, Differential Evolution Adaptive Metropolis (DREAM) algorithm is employed to approximate the posterior distributions of model parameters with Bayesian inference; factor...
Article
The ensemble Kalman filter (EnKF) is recognized as a powerful data assimilation technique that generates an ensemble of model variables through stochastic perturbations of forcing data and observations. However, relatively little guidance exists with regard to the proper specification of the magnitude of the perturbation and the ensemble size, posi...
Article
Full-text available
In this study, an entropy-copula method is proposed for modelling dependence between traffic volume and traffic noise on the Trans-Canada Highway (#1 highway of Canada) in the City of Regina based on a series of field experiment measurements. The proposed entropy-copula method combines the maximum entropy and copula methods into a general framework...
Article
In this study, a copula-based particle filter (CopPF) approach was developed for sequential hydrological data assimilation by considering parameter correlation structures. In CopPF, multivariate copulas are proposed to reflect parameter interdependence before the resampling procedure with new particles then being sampled from the obtained copulas....
Article
Full-text available
In this study, a semi-infinite interval-stochastic risk management (SIRM) model is developed for river water pollution control, where various policy scenarios are explored in response to economic penalties due to randomness and functional intervals. SIRM can also control the variability of the recourse cost as well as capture the notion of risk in...
Article
This study improved hydrologic data assimilation through integrating the capabilities of particle filter (PF) and ensemble Kalman filter (EnKF) methods, leading to two integrated data assimilation schemes: the coupled EnKF and PF (CEnPF) and parallelized EnKF and PF (PEnPF) approaches. The applicability and usefulness of CEnPF and PEnPF were demons...
Article
An interval-based two-stage risk analysis (ITRA) method is developed for planning water resource systems associated with uncertainties presented in terms of probability distributions and interval values. Risk measures are employed to assess the impacts of degrees of the preference of decision makers on the tradeoff between system benefits and expec...
Article
This study developed a copula-based fuzzy chance-constrained programming (CFCCP) model and applied it to electric power generation systems planning under multiple uncertainties. The CFCCP model was formulated by incorporating existing joint-probabilistic constrained programming and generalized fuzzy linear programming techniques within a general mi...
Article
Full-text available
In this study, bivariate hydrologic risk analysis was conducted based on the daily streamflow discharge at the Xianyang station on the Wei River. This bivariate hydrologic risk analysis was conducted based on copula methods, in which the bivariate hydrologic frequency was firstly quantified through copulas, and the bivariate hydrologic risk analysi...
Article
Nuclear power accidents are one of the most dangerous disasters posing a lethal threat to human health and have detrimental effects lasting for decades. Therefore, emergency evacuation is important to minimize injuries and prevent lethal consequences resulting from a nuclear power accident. An inexact fuzzy stochastic chance constrained programming...
Article
In this study, a hybrid sequential data assimilation and probabilistic collocation (HSDAPC) approach is proposed for analyzing uncertainty propagation and parameter sensitivity of hydrologic models. In HSDAPC, the posterior probability distributions of model parameters are first estimated through a particle filter method based on streamflow dischar...
Article
In this study, a PCA-based cluster quantile regression (PCA-CQR) framework was proposed through integrating principal component analysis and quantile regression approaches into a stepwise cluster analysis framework. In detail, the principal component analysis was adopted to overcome the multicollinearity among the explanatory variables, while the q...
Article
Full-text available
In this study, a stepwise cluster forecasting (SCF) framework is proposed for probabilistic prediction for monthly streamflow through integrating stepwise cluster analysis and quantile regression methods. The developed SCF method can capture discrete and nonlinear relationships between explanatory and response variables. A cluster tree was generate...
Article
The effectiveness of diatomite as the low-cost sorbent in the removal of polycyclic aromatic hydrocarbons (PAHs) from water was investigated. The effects of ionic strength, pH, dissolved organic matter, and temperature on sorption of phenanthrene (PHE) to two types of diatomite clay (DM 545 and DM 577) were systematically studied. The maximal infor...
Article
A nonlinear fractional programming approach is provided for addressing the environmental–economic power dispatch problems in the thermal power dispatch systems. The objective of this study is to simultaneously minimize the total fuel cost and total emissions of the power dispatch systems, which is realized by two simultaneous models with nonlinear...
Article
Over the recent years, climate change impacts have been increasingly studied at the watershed scale. However, the impact assessment is strongly dependent upon the performance of the climatic and hydrological models. This study developed a two-step method to assess climate change impacts on water resources based on the Providing Regional Climates fo...
Article
In this study, an interactive two-stage fuzzy stochastic programming (ITFSP) method is developed for supporting crop planning and water resource allocation under uncertainty. ITFSP can effectively address uncertainties expressed as probability distributions and fuzzy-boundary intervals. It can also be utilized for in-depth analyzing different polic...
Article
An interval type-2 fuzzy fractional programming (IT2FFP) method is developed for planning the renewable energy in electric power system for supporting sustainable development under uncertainty. IT2FFP can tackle output/input ratio problems where complex uncertainties are expressed as type-2 fuzzy intervals (T2FI) with uncertain membership functions...
Article
The present study proposes a copula-based chance-constrained waste management planning method. The method can effectively reflect the interactions between random parameters of the waste management planning systems, and thus help analyze the influences of their interactions on the entire systems. In particular, a joint distribution function is estab...