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This study investigated the temporal rainfall pattern in order to facilitate rainfall design, which normally requires a good understanding of the temporal patterns of rainstorm events. The analysis employed a storm-event-based approach using the concept of inter-event time definition (IETD) and rainfall depth/duration/intensity thresholds. The 5-min rainfall data at three raingauge stations were analysed to determine representative quartiles of a design storm in a tropical city. The temporal characteristics of the design storm could be determined from the rainfall depth ratios of consecutive peak rainfalls for each interval of storm duration, and time to the first peak rainfall depending on each quartile’s rainstorm events. The determination of the quantile distribution of tropical rainfall could help improve the representativeness of design rainfall and facilitate rainfall–runoff modelling for urban flood control in a tropical region. Ministry of Education (MOE) This work was partly supported by Academic Research Fund Tier 1 from the Ministry of Education (MOE), Singapore (2019-T1-001-160), and partly by the Chung-Ang University Research Grants in 2019.

To improve the convergence of multiple-site weather generators (SWGs) based on the brute force algorithm (MBFA), a genetic algorithm (GA) is proposed to search the overall optimal correlati...

This review article discusses the climate, water resources and historical droughts of Africa, drought indices, vulnerability, impact of global warming and land use for drought-prone regions in West, southern and the Greater Horn of Africa, which have suffered recurrent severe droughts in the past. Recent studies detected warming and drying trends in Africa since the mid 20th century. Based on the Fourth Assessment Report of the Intergovernmental Panel on Climate Change and the Coupled Model Intercomparison Project Phase 5 (CMIP5), both northern and southern Africa are projected to experience drying, such as decreasing precipitation, runoff and soil moisture in the 21st century and could become more vulnerable to the impact of droughts. The daily maximum temperature is projected to increase by up to 8°C (RCP8.5 of CMIP5), precipitation indices such as total wet day precipitation (PRCPTOT) and heavy precipitation days (R10 mm) could decrease, while warm spell duration (WSDI) and consecutive dry days...

A generalized likelihood uncertainty estimation (GLUE) framework coupling with artificial neural network (ANN) models in two surrogate schemes (i.e. GAE-S1 and GAE-S2) was proposed to improve the efficiency of uncertainty assessment in flood inundation modelling. The GAE-S1 scheme was to construct an ANN to approximate the relationship between model likelihoods and uncertain parameters for facilitating sample acceptance/rejection instead of running the numerical model directly; thus, it could speed up the Monte Carlo simulation in stochastic sampling. The GAE-S2 scheme was to establish independent ANN models for water depth predictions to emulate the numerical models; it could facilitate efficient uncertainty analysis without additional model runs for locations concerned under various scenarios. The results from a study case showed that both GAE-S1 and GAE-S2 had comparable performances to GLUE in terms of estimation of posterior parameters, prediction intervals of water depth, and probabilistic i...

Regional air pollution is a major concern for almost every country because it not only directly relates to economic development, but also poses significant threats to environment and public health. In this study, an inexact fuzzy-chance-constrained air quality management model (IFAMM) was developed for regional air quality management under uncertainty. IFAMM was formulated through integrating interval linear programming (ILP) within a fuzzy-chance-constrained programming (FCCP) framework and could deal with uncertainties expressed as not only possibilistic distributions but also discrete intervals in air quality management systems. Moreover, the constraints with fuzzy variables could be satisfied at different confidence levels such that various solutions with different risk and cost considerations could be obtained. The developed model was applied to a hypothetical case of regional air quality management. Six abatement technologies and sulfur dioxide (SO2) emission trading under uncertainty were taken into consideration. The results demonstrated that IFAMM could help decision-makers generate cost-effective air quality management patterns, gain in-depth insights into effects of the uncertainties, and analyze tradeoffs between system economy and reliability. The results also implied that the trading scheme could achieve lower total abatement cost than a nontrading one.

Sustainable development has been widely recognised as an effective means for harmonising human society and natural systems. However, achieving the goal of sustainability is difficult since many conflicting factors have to be balanced due to the complexities of real-world problems. Previously, many efforts have been made to clarify the concept of sustainable development and to develop related theoretical and practical tools. Nevertheless, there is still a lack of effective methods that can integrate optimisation of resources allocation and visualisation of spatial and temporal dimensions of socio-economic and environmental interactions within a general framework. In this study, an optimisation-based environmental decision support system (EDSS) was developed for supporting sustainable rural development. The system included a dynamic database system, a graphical user interface, and a mixed integer linear programming (MILP) model. Yongxin County, located in Jiangxi Province, China, was chosen as the study cas...

A simulation-based stochastic-multi-criteria decision analysis (MCDA) approach was developed for optimizing groundwater remediation operations through integrating the contaminant transport modeling, dual-phase vacuum extraction (DPVE) process modeling, deterministic MCDA, and Monte Carlo simulation into a general framework. A petroleum-contaminated site in western Canada was selected as the study case for demonstrating the applicability of the proposed method. Totally, 12 scenarios were designed for site remediation. Nine criteria were used for evaluating each alternative through the developed MCDA methods. The economical factors consisted of operational cost associated with DPVE and groundwater remediation. Environmental performances were determined based on the magnitude of risky and highly risky areas of benzene, toluene, ethyl-benzene, and xylene (BTEX contamination that were predicted through developed models. The study results demonstrated that the proposed stochastic MCDA method provides m...

Energy plays a vital role in economic development and in our daily lives. Since the industrial revolution, economic development has been accompanied by growth in the consumption of fossil fuels, wi...

Petroleum waste management has been of much concern in recent years since pollution from petroleum industries may lead to various impacts and risks to environmental systems. In this study, an interval fuzzy two-stage chance-constrained linear programming (IFTCP) method is developed for planning petroleum waste management systems. The IFTCP improves upon the existing optimization methods by allowing uncertainties presented in terms of intervals, fuzzy sets, and probability distributions to be effectively incorporated within the optimization framework. Moreover, it can support the analysis of policy scenarios that are associated with economic penalties when the promised targets are violated. The developed method is then applied to a case of long-term petroleum waste management planning. Interval solutions, which are associated with different levels of constraint-violation risk and system satisfaction degree, have been obtained by solving two submodels based on an interactive algorithm. They can be ...

Geologic storage of CO2 in depleted oil reservoirs is considered to be an effective approach for both facilitating GHG sequestration and enhancing oil recovery. However, as a potential problem in the long run, risks associated with geological storage of CO2, such as leakage to the groundwater and atmosphere, might pose significant threats to local communities and surrounding environment. Identification and evaluation of such risks are essential for the long-term management of CO2 storage. Doing so requires a set of advanced technologies in order to well understand the long-range transportation of CO2 and its impact mechanisms. This study developed an integrated decision support framework for the Weyburn Field. This system included modules of data management, inexact hybrid numerical simulation, optimization for CO2 EOR processes, hybrid fuzzy-stochastic risk assessment, and post-modeling analysis. A user-friendly interface was designed through visual language programming. Such an effort would pro...

Composting processes are normally complicated with a variety of uncertainties arising from incomplete or imprecise information obtained in real-world systems. Previously, there has been a lack of studies that focused on developing effective approaches to incorporate such uncertainties within composting process models. To fill this gap, a fuzzy composting process model (FCPM) for simulating composting process under uncertainty was developed. This model was mainly based on integration of a fractional fuzzy vertex method and a comprehensive composting model. Degrees of influence by projected uncertain factors were also examined. Two scenarios were investigated in applying the FCPM method. In the first scenario, model simulation under deterministic conditions was conducted. A pilot-scale experiment was provided for verifications. The result indicated that the proposed composting model could provide an excellent vehicle for demonstrating the complex interactions that occurred in the composting process. In the second scenario, application of the proposed FCPM was conducted under uncertainties. Six input parameters were considered to be of uncertain features that were reflected as fuzzy membership functions. The results indicated that the uncertainties projected in input parameters will result in significant derivations on system predictions; the proposed FCPM can generate satisfactory system outputs, with less computational efforts being required. Analyses on degree of influence of system inputs were also provided to describe the impacts of uncertainties on system responses. Thus, suitable measures can be adopted either to reduce system uncertainty by well-directed reduction of uncertainties of those high-influencing parameters or to reduce the computational requirement by neglecting those negligible factors.

A robust decision-support system (DSS) was developed to provide environmental managers with an integrated measure for tackling subsurface contamination problems. Such a DSS included components of mathematical modeling, risk assessment, remediation-technique screening, and monitoring-program design. A visual-language-based software package, named NRSRM, was developed for facilitating a variety of functions within the DSS. It provided a collection of measures for analyzing and visualizing subsurface contamination problems. A contaminated site located in western Canada was examined to demonstrate its applicability. By exploring different remedial technologies, NRSRM recommended six alternatives for cleaning up the site. Users can click selected items under each alternative to acquire more information of the related actions and efficiencies.