Barbara J. Lence

First-order reliability method for estimating reliability, vulnerability, and resilience

Reliability, vulnerability, and resilience provide measures of the frequency, magnitude, and duration of the failure of water resources systems, respectively. Traditionally, these measures have been estimated using simulation. However, this can be computationally intensive, particularly when complex system-response models are used, when many estimates of the performance measures are required, and when persistence among the data needs to be taken into account. In this paper, an efficient method for estimating reliability, vulnerability, and resilience, which is based on the First-Order Reliability Method (FORM), is developed and demonstrated for the case study of managing water quality in the Willamette River, Oregon. Reliability, vulnerability, and resilience are determined for different dissolved oxygen (DO) standards. DO is simulated using a QUAL2EU water quality response model that has recently been developed for the Oregon Department of Environmental Quality (ODEQ) as part of the Willamette River Basin Water Quality Study (WRBWQS). The results obtained indicate that FORM can be used to efficiently estimate reliability, vulnerability, and resilience.

SURFACE WATER QUALITY MANAGEMENT USING A MULTIPLE-REALIZATION CHANCE CONSTRAINT METHOD

Traditional chance-constrained programming (CCP) and simulation-optimization methods of incorporating input information uncertainty in pollution management models are unsuitable for complex river systems with several critical water quality segments. Using the CCP method, characterization of the joint probability distribution of coefficients of the management model is often difficult because stream information is limited and the model formulation is generally difficult to understand and solve. For the simulation-optimization method most of the solutions produced are inferior. The multiple realization model, which includes several scenarios of design conditions simultaneously in an optimization model, overcomes such weaknesses by not requiring the joint probability distribution of the stochastic model coefficients and by producing noninferior solutions. Heuristic and neural network techniques are developed to reduce the computational time required to solve the multiple realization model, through identification and utilization of only potentially important stream and water quality information that influence the optimal solution. These techniques are applied to develop trade-off relationships between waste treatment cost and reliability of achieving dissolved oxygen objectives for an example river basin. Results show that the heuristic technique is computationally efficient when <1000 realizations are included in the model, while the neural network method is suitable when several thousand realizations are needed to adequately represent the stochastic water quality system.

Practical sustainability criteria for decision-making

SUMMARY The new paradigm of sustainability necessitates revisions to traditional decision-making processes. This paper, which is the first in a series of four, outlines the changes required for decision-making to reflect sustainability concerns. Three sustainability criteria, that are the focus of the three subsequent papers, are introduced and the rationale for each is explained. A framework for incorporating the three sustainability criteria into the decision-making process is briefly outlined. The paper ends with the introduction to a case study, the North Central Project (NCP) for electricity supply alternatives. The NCP is used in the three following papers to demonstrate the individual components of the new approach to sustainable decision-making.

Multiple Interactive Pollutants in Water Quality Trading

Efficient environmental management calls for the consideration of multiple pollutants, for which two main types of transferable discharge permit (TDP) program have been described: separate permits that manage each pollutant individually in separate markets, with each permit based on the quantity of the pollutant or its environmental effects, and weighted-sum permits that aggregate several pollutants as a single commodity to be traded in a single market. In this paper, we perform a mathematical analysis of TDP programs for multiple pollutants that jointly affect the environment (i.e., interactive pollutants) and demonstrate the practicality of this approach for cost-efficient maintenance of river water quality. For interactive pollutants, the relative weighting factors are functions of the water quality impacts, marginal damage function, and marginal treatment costs at optimality. We derive the optimal set of weighting factors required by this approach for important scenarios for multiple interactive pollutants and propose using an analytical elasticity of substitution function to estimate damage functions for these scenarios. We evaluate the applicability of this approach using a hypothetical example that considers two interactive pollutants. We compare the weighted-sum permit approach for interactive pollutants with individual permit systems and TDP programs for multiple additive pollutants. We conclude by discussing practical considerations and implementation issues that result from the application of weighted-sum permit programs.

Distributive fairness considerations in sustainable project selection

Abstract This work develops general fairness measures that may be used as criteria for sustainable project selection. Sustainable development, fair allocation objectives and empirical distance-based measures of fairness, and their evaluation are discussed. Generalized fairness measures are developed and extended for both intratemporal and intertemporal fairness comparisons. A preliminary application of the extended distance based fairness measures is then performed for a case study of the selection of an electricity supply project. The case study involves selecting between a dispersed diesel energy supply and centralized energy supply with land line energy distribution. Due to data limitations, the perceived fairness is measured in terms of the annual energy costs per megawatt-hour that result from implementing each alternative. The applied fairness measures indicate that intratemporal fairness, in terms of the distribution of user unit costs, may be increased by choosing the land line alternative and tha...

Technical hazard identification in water treatment using fault tree analysis

In this qualitative paper, a method for technical and operational hazard identification of a water treatment plant is described. Here, fault tree analysis is applied to a physicochemical ultrafiltration (UF) membrane train, with the objectives of developing a systematic approach for organizing and improving our understanding of the hazards at the treatment plant operational level that affect the risk of infection from the pathogen Cryptosporidium parvum. The approach was successful in identifying many technical and operational hazards. The fault tree shows that water treatment plant operation is a complex task where many factors must be taken into account. Regarding the removal of C. parvum oocysts, most initiating events relate to the filtration step in the UF system. In the future, quantification of the probability of fault events may help to prioritize interventions at the operational level.

Hybrid fuzzy-mechanistic models for addressing parameter variability

A simulation approach which integrates mechanistic models and fuzzy logic in order to accommodate parameter variability is developed and explored. The approach modifies a mechanistic model, such as a runoff model, for which the values of the parameters are originally fixed. Fuzzy logic is used to redefine the parameter values by varying them as a function of meaningful system indicators, such as inflow, precipitation or temperature in the case of inflow modelling. The modification adds flexibility to the structure of the mechanistic model, by allowing the values of the parameters to be reset at every time step based on the current values of the system indicators. This approach is applied to two different models, a runoff model and an algal concentration model, in order to demonstrate its versatility. The results are indicative of improved performance with the hybrid fuzzy-mechanistic models compared with the purely mechanistic models. In the case of the runoff model, the resulting description of the parameter domain also indicates a possible deficiency of the model structure, that is, a lack of clear distinction between watershed runoff and water retention through routing. The approach may be data intensive, but its implementation is straightforward. A wide range of potential applications of this approach in environmental and natural resources descriptive modelling exists, including: snowmelt modelling, fish habitat modelling, transport modelling, and species migration modelling. However, one must be careful to identify parameter-system indicator relationships that are representative of the system under study, and to avoid extrapolations beyond the known system conditions.

Distributive fairness as a criterion for sustainability: evaluative measures and application to project selection

SUMMARY In evaluating civil engineering projects and management alternatives, the distribution of project impacts among groups in the same generation (intratemporal impact distributions) and between groups in different generations (intertemporal impact distributions) may be used as indicators of project viability and potential sustainability. Empirical measures of distributive fairness among groups at one point in time have typically been applied in project selection. These measures are often based on one of three views of fairness, namely allocation of impacts based on equality, equity, or need. The appropriateness of these measures for different applications may be determined based on whether they meet a set of required characteristics. This paper classifies the common distributive fairness measures for impact distributions at one point in time, describes the required characteristics of each measure, and extends these measures for considering impact distributions that are experienced over time. New meas...

Modeling the Energy Output from an In-Stream Tidal Turbine Farm

This paper is based on a recent paper presented in the 2007 IEEE SMC conference by the same authors, discussing an approach to predicting energy output from an instream tidal turbine farm. An in-stream tidal turbine is a device for harnessing energy from tidal currents in channels, and functions in a manner similar to a wind turbine. A group of such turbines distributed in a site is called an in-stream tidal turbine farm which is similar to a wind farm. Approaches to estimating energy output from wind farms cannot be fully transferred to study tidal farms, however, because of the complexities involved in modeling turbines underwater. In this paper, we intend to develop an approach for predicting energy output of an in-stream tidal turbine farm. The mathematical formulation and basic procedure for predicting power output of a stand-alone turbine is presented, which includes several highly nonlinear terms. In order to facilitate the computation and utilize the formulation for predicting power output from a turbine farm, a simplified relationship between turbine distribution and turbine farm energy output is derived. A case study is then conducted by applying the numerical procedure to predict the energy output of the farms. Various scenarios are implemented according to the environmental conditions in Seymour Narrows, British Columbia, Canada. Additionally, energy cost results are presented as an extension.

Stochastic Fatigue Assessment for Berthing Monopiles in Inland Waterways

As an unsupported structure, a berthing monopile is often expected to work under harsh conditions. Approaching vessels may introduce considerable berthing energy, resulting in substantial tensile stress on the pile. This vessel impact occurs frequently as a primary load over the service life of the berthing monopile. In this situation, the fatigue safety of circumferential butt welds on piles becomes a crucial aspect in monopile design. This paper evaluates linear elastic fracture mechanics (LEFM)-based fatigue reliability for circumferential splice welds on steel monopiles. Studied monopiles are those installed in inland waterways, for which the predominant fatigue loading is vessel berthing. Important factors involved in the fatigue reliability assessment are addressed. A geometry function for determining the range of stress intensity factor is identified, an approximate stress concentration factor for piles under bending moment is mathematically formulated, and the beta distribution is applied to characterize the doubly bound hot-spot stress range caused by operational water-level constraints. A detailed case study is presented for illustrative purposes. This paper provides a practical approach to assessing LEFM-based fatigue reliability for steel berthing monopiles. DOI: 10.1061/(ASCE)WW.1943-5460.0000063.