Using a GIS Model to Identify Internally Drained Areas and Runoff Contribution in a Glaciated Watershed1

Macholl, Jacob A., Katherine A. Clancy, and Paul M. McGinley, 2011. Using a GIS Model to Identify Internally Drained Areas and Runoff Contribution in a Glaciated Watershed. Journal of the American Water Resources Association (JAWRA) 47(1):114‐125. DOI: 10.1111/j.1752‐1688.2010.00495.x Abstract: Glaciated watersheds are not easily delineated using geographic information systems’ elevation‐based algorithms, especially where stream networks are disconnected and there are large regions of internally drained areas. This paper presents the results of an analysis using the Potential Contributing Source Area (PCSA) model to identify potential contributing areas, defined as areas from which runoff is physically capable of reaching a drainage network. The investigation was conducted to define the potential contributing areas in a glaciated region of northwest Wisconsin. The curve number (CN) method was used to predict runoff volumes in the watershed. The streamflows of four tributaries were measured and the runoff portion of the hydrograph quantified to be compared with runoff estimates calculated using the potential contributing areas and the traditional catchment area. Runoff producing events occurred, but the use of area‐weighted CN values was unsuccessful in modeling runoff due to all precipitation depths during the study period falling below the initial abstraction. A distributed CN approach provided runoff estimates that were generally better using the potential contributing areas compared with using the traditional catchment area. The extent of the minimum contributing area, estimated for a range of precipitation events, was found to be substantially less than the potential contributing areas, suggesting that the PCSA model delimits the maximum boundary of potential contributing areas.     

FACTORS THAT AFFECT ACTIVATED SLUDGE PHOSPHATE RELEASE1

The activated sludge process can remove significant amounts of phosphorus from sewage, but the removal efficiency is usually significantly reduced by the release of phosphate back to solution during subsequent treatment steps. This research presents a study of soluble phosphate release from activated sludge with emphasis on defining the factors that affect such release and the actual release mechanisms. Laboratory units were used for experimental purposes. The experiments were designed to study the relationship between soluble phosphate release and various environmental factors such as redox potential (ORP), dissolved oxygen (DO), pH, solids concentration, solids destruction, and sulfate salt addition. The effect of substrate utilization on phosphate uptake and the relationship between uptake characteristics and subsequent phosphate release were also studied. The results show that some phosphate storage occurs during aerobic substrate utilization. Following substrate utilization, activated sludge phosphate release is directly related to the amount of biological stress the organisms are subjected to, and the mechanism of release is primarily cell lysis. The phosphate released per unit sludge under anoxic conditions is relatively constant. Under normal environmental conditions, neither ORP or pH change have a significant affect on phosphate release.     

A quantitative risk management framework for dust and hybrid mixture explosions

Dust and hybrid-mixture explosions continue to occur in industrial processes that handle fine powders and flammable gases. Considerable research is therefore conducted throughout the world with the objective of both preventing the occurrence and mitigating the consequences of such events. In the current work, research has been undertaken to help move the field of dust explosion prevention and mitigation from its current emphasis on hazards (with an accompanying reliance on primarily engineered safety features) to a focus on risk (with an accompanying reliance on hierarchical, risk-based, decision-making tools). Employing the principles of quantitative risk assessment (QRA) of dust and hybrid-mixture explosions, a methodological framework for the management of these risks has been developed.The QRA framework is based on hazard identification via credible accident scenarios for dust explosions, followed by probabilistic fault-tree analysis (using Relex – Reliability Excellence – software) and consequence severity analysis (using DESC – Dust Explosion Simulation Code – software). Identification of risk reduction measures in the framework is accomplished in a hierarchical manner by considering inherent safety measures, passive and active engineered devices, and procedural measures (in that order). An industrial case study is presented to show how inherent safety measures such as dust minimization and dust/process moderation can be helpful in reducing dust and hybrid-mixture explosion consequences in a 400-m³ polyethylene storage silo.     

Analyzing system safety and risks under uncertainty using a bow-tie diagram: An innovative approach

A bow-tie diagram combines a fault tree and an event tree to represent the risk control parameters on a common platform for mitigating an accident. Quantitative analysis of a bow-tie is still a major challenge since it follows the traditional assumptions of fault and event tree analyses. The assumptions consider the crisp probabilities and “independent” relationships for the input events. The crisp probabilities for the input events are often missing or hard to come by, which introduces data uncertainty. The assumption of “independence” introduces model uncertainty. Elicitation of expert's knowledge for the missing data may provide an alternative; however, such knowledge incorporates uncertainties and may undermine the credibility of risk analysis.This paper attempts to accommodate the expert's knowledge to overcome missing data and incorporate fuzzy set and evidence theory to assess the uncertainties. Further, dependency coefficient-based fuzzy and evidence theory approaches have been developed to address the model uncertainty for bow-tie analysis. In addition, a method of sensitivity analysis is proposed to predict the most contributing input events in the bow-tie analysis. To demonstrate the utility of the approaches in industrial application, a bow-tie diagram of the BP Texas City accident is developed and analyzed.