Civil and Environmental Engineering

Experimental Determination of Cover Surface Temperature Functions at MSW Landfills

Nicolas K. Oettle et al. — Thu, 18 Apr 2013 14:51:08 PDT

Cover temperatures were measured at four MSW landfills located in different climatic regions in North America: Michigan, New Mexico, Alaska, and British Columbia. Temperature measurements were made on a weekly basis throughout the depth of the cover profiles extending from the surface into the top layers of the underlying wastes. Bias was produced in the surface temperature data due to the combined effects of the time of day that weekly surface measurements were taken and the high diurnal variations at the surface. Analytical methods were used to obtain representative surface temperature functions for the covers from experimental data. Mean cover surface temperatures were estimated by extrapolating near-surface temperatures using exponential functions and by interpolating between air and below-surface cover temperatures using weighting factors. Surface temperature amplitudes were estimated by extrapolating near-surface amplitudes using conventional earth temperature theory. Analysis of data indicated that mean cover surface temperatures and cover temperature amplitudes can also be obtained directly from temperature measurements at 150 to 300 mm depth, when such data are available. Surface parameters obtained in this study can be used at other sites with similar climatic conditions for thermal analysis of cover systems.

Spatial Variability of Waste Temperatures in MSW Landfills

James L. Hanson et al. — Thu, 18 Apr 2013 14:51:06 PDT

Spatial variability of waste temperatures in MSW landfills was determined over different physical and temporal scales. Data have been obtained at four landfills located in different climatic regions in North America: Alaska, British Columbia, Michigan, and New Mexico. Temperatures were measured using 100 to over 250 sensors at each site. Data were obtained for 5 to 10 year periods at the sites. Temperatures were measured in wastes with a broad range of ages: newly-placed and old (up to 40-year old). The characteristic shape of waste temperature vs. depth relationships consists of a convex temperature profile with maximum temperatures observed at central locations within the middle third fraction of the depth of the waste mass. Lower temperatures with trends similar to air temperatures were observed above this central zone. Temperatures near the base of the landfills and in the liner systems were relatively steady and elevated above mean annual earth temperature, yet were below the maximum values in the central zones. The location of the maximum temperatures/heat gain is affected in the short term by waste placement temperature and in the long term by heat generation and dissipation. Sustained concave temperature profiles were observed for waste placement in cold temperatures. In British Columbia with high heat generation, temperature increases occurred for multiple years and then dissipated for tens of years. Longer periods of temperature increase were observed at the other sites with relatively lower heat generation rates. Temperatures continue to increase at these sites after approximately a decade since waste placement. The highest temperatures were observed in Michigan followed by British Columbia, New Mexico, and Alaska. The time-averaged waste temperature ranges were 0.9 to 33.0°C, 14.4 to 49.2°C, 14.8 to 55.6°C, and 20.5 to 33.6°C in Alaska, British Columbia, Michigan, and New Mexico, respectively.

Assessment of State Recycling Regulations in the United States

Nazli Yesiller et al. — Thu, 18 Apr 2013 14:51:05 PDT

This investigation was conducted to identify the current status of state recycling regulations in U.S. using an extensive survey. Questions were included regarding: baseline waste generation and recycling trends; recycling regulatory trends; quantitative thresholds; integration of science, engineering, and economic principles; material properties; and legislative status of regulations. The majority of the surveyed states had regulations for recycling activities, which were less strict than solid waste regulations, and required permits for operation of recycling facilities. A low percentage of the states regulated generators, transporters, and handlers and a high percentage regulated recyclers. In general, transfer stations and recycling centers were not regulated as solid waste facilities whereas MRFs were regulated as solid waste facilities. Exemptions were granted based on type and amount of materials and type of operation as well as for specific activities such as scrap materials, construction and demolition waste, and beneficial reuse. Quantity of incoming materials was measured somewhat more commonly than the quantity of outgoing materials. Weight based measurements were used more frequently than volume measurements. The use of numerical thresholds for residual content and in particular, putrescible content was not common. When used, residual thresholds ranged between 5 and 15% and putrescible threshold was 1%. Duration for on-site storage of materials typically was regulated and varied over a wide range (from 60 days to 3 years). Best management practices and best engineering principles/judgment were adopted in the development of regulatory schema and comprehensive science and engineering principles or risk analysis typically were not used. Variable frequencies and practices were used for inspections and also for enforcement. Annual reports typically were required for recycling operations. The majority of the surveyed states indicated that they were considering or in the process of changing regulations for recycling activities. A general lack of oversight was identified as a common problem.

Coseismic Tectonic Surface Deformation during the 2010 Maule, Chile, M_w 8.8 Earthquake

Keith Kelson et al. — Fri, 05 Apr 2013 15:43:21 PDT

Tectonic deformation from the 2010 Maule (Chile) M_w 8.8 earthquake included both uplift and subsidence along about 470 km of the central Chilean coast. In the south, deformation included as much as 3 m of uplift of the Arauco Peninsula, which produced emergent marine platforms and affected harbor infrastructure. In the central part of the deformation zone, north of Constitución, coastal subsidence drowned supratidal floodplains and caused extensive shoreline modification. In the north, coastal areas experienced either slight uplift or no detected change in land level. Also, river-channel deposition and decreased gradients suggest tectonic subsidence may have occurred in inland areas. The overall north-south pattern of 2010 coastal uplift and subsidence is similar to the average crestal elevation of the Coast Range between latitudes 33°S and 40°S. This similarity implies that the topography of the Coast Range may reflect long-term permanent strain accrued incrementally over many earthquake cycles.

Shear-Wave Velocity–Based Probabilistic and Deterministic Assessment of Seismic Soil Liquefaction Potential

R. Kayen et al. — Wed, 27 Mar 2013 13:41:01 PDT

Shear-wave velocity (Vs) offers a means to determine the seismic resistance of soil to liquefaction by a fundamental soil property. This paper presents the results of an 11-year international project to gather new Vssite data and develop probabilistic correlations for seismic soil liquefaction occurrence. Toward that objective, shear-wave velocity test sites were identified, and measurements made for 301 new liquefaction field case histories in China, Japan, Taiwan, Greece, and the United States over a decade. The majority of these new case histories reoccupy those previously investigated by penetration testing. These new data are combined with previously published case histories to build a global catalog of 422 case histories of Vsliquefaction performance. Bayesian regression and structural reliability methods facilitate a probabilistic treatment of the Vscatalog for performance-based engineering applications. Where possible, uncertainties of the variables comprising both the seismic demand and the soil capacity were estimated and included in the analysis, resulting in greatly reduced overall model uncertainty relative to previous studies. The presented data set and probabilistic analysis also help resolve the ancillary issues of adjustment for soil fines content and magnitude scaling factors.

Model Performance Sensitivity to Objective Function during Automated Calibrations

Misgana Muleta — Thu, 26 Jul 2012 15:06:15 PDT

Previous studies have reported limitations of the efficiency criteria commonly used in hydrology to describe goodness of model simulations. This study examined sensitivity of model performance to the objective function used during automated calibrations. Nine widely used efficiency criteria were evaluated for their effectiveness as objective function, and goodness of the model predictions were examined using 13 criteria. Two cases (Case I: Using observed streamflow data and Case II: Using simulated streamflow) were considered to accomplish objectives of the study using a widely used watershed model (SWAT) and good-quality field data from a well-monitored experimental watershed. Major findings of the study include (1) automated calibration results are sensitive to the objective function group—group that work based on minimization of the absolute deviations (Group I), group that work based on minimization of square of the residuals (Group II), and groups that use log of the observed and simulated streamflow values (Group III)—but not to objective functions within the group; (2) efficiency criteria that belong to Group I were the most effective when used as objective function for accurate simulation of both low flows and high flows; (3) Group I and Group II objective functions complement each other’s performance; (4) with regard to the capability to describe goodness of model simulations, efficiency criteria that belong to Group I showed superior robustness; (5) for the study watershed, use of the long-term interannual calendar day mean as baseline model did not improve capability of an efficiency criterion to describe model performance; and (6) even for ideal conditions where uncertainty in input data and model structure are fully accounted for, identifying the so-called global parameters values through calibration could be daunting as parameter values that were significantly divergent from predetermined values produced model simulations that can be considered near perfect even when judged using multiple efficiency criteria.

Improving Model Performance Using Season-Based Evaluation

Misgana Muleta — Thu, 26 Jul 2012 15:06:06 PDT

Computer models have become vital decision-making tools in many areas of science and engineering including water resources. However, models should be properly evaluated before use to improve the likelihood of making sound decisions based on their results. The model evaluation technique practiced today in hydrology assumes that model parameters are season insensitive and attempts to identify “optimal” values that would describe watershed behavior during dry and wet seasons. This assumption could compromise accuracy of model predictions. This study demonstrates performance improvement that would be achieved when a season-based model evaluation approach is pursued. A global sensitivity analysis (SA) model has been used to investigate seasonal sensitivity of streamflow parameters of a watershed simulation model on the headwaters of the Little River Watershed, one of the United States Department of Agriculture’s experimental watersheds. Two separate analyses have been performed: the conventional approach in which model parameters are assumed to be season insensitive; and a season-based evaluation in which the influential parameters may vary for months with a low runoff coefficient and months with a high runoff coefficient. The sensitivity analysis helped to identify dominant model and watershed behaviors for the conventional annual approach and for the wet and dry seasons. The SA results show that the influential parameters exhibited modest seasonal sensitivity for the experimental watershed. Model calibration was then performed by using the dynamically dimensioned search (DDS) algorithm for the conventional and season-based approaches using the principal parameters identified by the global SA model. Performance of the calibration attempts have been verified with the traditional split-sampling technique and also by assessing effectiveness of the model in predicting internal watershed behaviors through comparison of simulated streamflow with observations at multiple internal sites not used for calibration. Several efficiency measures have been used to test goodness of the model simulations. The season-based model evaluation technique showed superior performance compared with the traditional method of assuming constant model parameters across seasons. The watershed simulation model exhibited reasonable accuracy in simulating streamflow at the internal sites and for the verification periods when parameter values are allowed to vary from dry to wet season. The “optimal” parameter values identified by the calibration attempts showed significant seasonal sensitivity.

Assessment of Public Perception of User-Based Fees and Tolls to Finance Transportation Infrastructure Improvements

Anurag Pande et al. — Thu, 31 May 2012 12:14:03 PDT

With aging infrastructure and declining purchasing power of tax receipts new mechanisms of financing transportation alternatives are gaining increasing interest. Fuel taxes are and have been for some time the primary source of transportation finance in United States. Fuel taxes are fixed amounts that rarely change and which lose purchasing power over time as prices escalate. In addition, improvements in fuel economy can further erode the revenue stream from the gas tax. This study explores the public’s attitude about user based fees collected through tolls that are directed at specific infrastructure projects using the Inland Empire region of California as a case study. The premise of this research is that tolls can complement existing funding sources for improving infrastructure.

Public perception of such directed user based fees as tolls has traditionally been considered a barrier in the wide scale implementation of these financing mechanisms. However, according to a recent publication from National Cooperative Highway Research Program, public perception of user based fees may not be as negative as once thought (Zmud, 2008). This study identified and addressed the research need for a framework to assess the general public’s perception of user-based fees and tolls as instruments of transportation finance.

Variability and Accuracy of Target Displacement from Nonlinear Static Procedures

Rakesh K. Goel — Mon, 21 May 2012 11:55:06 PDT

This paper compares the target displacement estimate from four current nonlinear static procedures—FEMA-356 CM, ASCE41 CM, ATC-40 CSM, and FEMA-440 CSM—with the value derived from recorded motions of five strongly shaken reinforced concrete buildings.This comparison provides useful insight into two important questions: (1) how much does the target displacement vary among the four nonlinear static procedures? and (2) can the engineering profession “accurately” predict the response of a real building during an earthquake event using currently available modeling techniques and pushover analysis procedures? It is shown that these procedures may lead to significantly different estimates of the target displacement, particularly for short-period buildings responding in the nonlinear range. Furthermore, various nonlinear static procedures applied to nonlinear models developed using generally accepted engineering practice provide either significant over estimation or under estimation of the target roof displacement when compared to the value derived from recorded motions.

Comparison of Base Shears Estimated from Floor Accelerations and Column Shears

Rakesh K. Goel — Fri, 17 Feb 2012 13:09:22 PST

This paper compares base shears computed from floor accelerations (inertial base shear) and column shears (structural base shear) for two mid-rise, multistory buildings due to a suite of 30 earthquake ground motions. The presented results demonstrate that the inertial base shear exceeds the structural base shear in the median by 10% to 20% and may exceed the structural base shear by as much as 70% for individual ground motions. Therefore, it is concluded that the inertial base shear computed from strong motion records should be used with caution to estimate the structural base shear.

Seismic Response of Peaty Organic Soils as a Levee Foundation Material

Robb E.S. Moss et al. — Thu, 02 Feb 2012 10:04:52 PST

The dynamic response of peaty organic soils is not well understood but its poor competency as an engineering material is well known. Its use as a foundation material is generally avoided through careful selection of project location, or removal and replacement with more suitable material. In certain situations peaty organic soils are unavoidable because of prior land use and subsequent development of infrastructure. In a delta environment levees are often found to be overlying peaty organic deposits, the California Bay Delta and New Orleans levee systems are two important examples. The Bay Delta is in a seismically active area and dynamic response of peaty organics underlying these levees is a concern. This research develops a first‐order estimate of the large strain dynamic response of peaty organic soils, with the goal of improving system reliability estimates of the Bay Delta levee network. Suites of cyclic triaxial tests on manufactured and sampled peaty organic soil specimens have been carried out, the results of which are used to inform finite element modeling of the levees subjected to seismic loading. We use a finite element program with existing constitutive models to provide deformation estimates of typical levee cross‐sections in the Bay Delta. The deformation estimates are in turn used to improve the system reliability estimates of the Bay Delta levees. A full understanding of the dynamic response of peaty organics will require more testing and the development of more specific constitutive models; however for the goal of improving system reliability estimates this first‐order approach is adequate within the bounds of all other contributing uncertainties.

Shake Table Testing of Seismic Soil-Foundation-Structure-Interaction

Robb E.S. Moss et al. — Thu, 02 Feb 2012 10:04:49 PST

This research involves shake table testing of 1g scale models that mimic the coupled seismic response of a structure on a shallow mat foundation and the foundation soil (termed soil‐foundation‐structure‐interaction or SFSI). In previous research, SFSI effects have been quantified through analytical models, numerical analyses, and limited field data. This research is working towards increasing the amount of empirical data through scale model shake table testing. A suite of earthquake times histories are considered in evaluating a 10^th scale soil‐structure model using a flexible wall barrel on a 1‐D shake table. San Francisco Young Bay Mud (YBM) is used as the prototype soil and a 3‐5 story narrow building the prototype structure. Foundation embedment depth, fundamental mode of the structure, dynamic soil strength, and seismic loading function are varied to generate a large database of SFSI results under controlled conditions. The structural response is compared to free‐field response to determine the magnitude of the SFSI. A presentation of the full test results is anticipated at the time of the conference.

Bounding the Probability of Failure for Levee Systems

Justin C. Hollenback et al. — Thu, 02 Feb 2012 10:04:46 PST

An exact solution for the probability of failure of large complex infrastructure systems is rarely obtainable; however the probability of failure can often be bounded. An example of this type of system is the levee system in the California Bay Delta. Large levee systems often consist of many components arranged in series and parallel sub‐systems. There is the problem of defining component (or reach) length, and therefore the total number of components in the system where component length is dependent on failure mode. Methods of bounding probability of failure based on uni‐, bi‐, and tri‐modal component probability of failure are discussed. The bounds are highly sensitive to the total number of components in the system. Characterization of spatial variability using semi‐variograms is used to define component length for various failure modes. Combining the statistically defined component length with system probability of failure bounds allow for a more accurate estimate of failure probability. Demonstration of these methods and results for specific levee systems in the California Bay Delta are shown in this paper.

Teaching Reliability at the Undergraduate Level

Robb E.S. Moss — Thu, 02 Feb 2012 10:04:42 PST

For Cal Poly's Civil and Environmental Engineering curriculum a stand‐alone introductory course called Engineering Risk Analysis introduces concepts of reliability analysis. This course encompasses all the sub‐disciplines in civil and environmental engineering. After five years of teaching this course there are a number of lessons that may be useful to other instructors including; solving a simple example problem using multiple methods, focusing on the normal and lognormal distributions for a quick preliminary solution, using reliability spreadsheet solutions, and allowing the students to develop their own applications of probabilistic tools. A discussion of the course format, references and resources, pedagogy devices, and in‐ class examples are covered. The higher goal of this course is to educate students in probabilistic methods, familiarize them with risk analysis procedures, and to elevate the basic level of understanding of uncertainty in engineering and how to properly deal with it.

Using Genetic Algorithms and SWAT to Minimize Sediment Yield From an Agriculturally Dominated Watershed

Misgana K. Muleta et al. — Mon, 21 Nov 2011 12:05:00 PST

Non-point source pollution is well recognized as one of the most critical environmental hazards of modern times. In Illinois, non-point source pollution is the major cause of water quality problems, and soil erosion from agricultural lands is the major source of such pollution. Accelerated by anthropogenic activities, soil erosion reduces crop productivity and leads to subsequent problems from deposition on farmlands and in water bodies. Watershed management, however, promotes protection and restoration of these natural resources while allowing for sustainable economic growth and development. In this study a discrete time optimal control methodology and computational model are developed for determining land use and management alternatives that minimize sediment yield from agriculturally dominated watersheds. The methodology is based on an interface between a genetic algorithm and a U.S. Department of Agriculture watershed model known as Soil and Water Assessment Tool (SWAT). The original structure of the SWAT model is preserved and modifications are embedded for computational efficiency. The analysis is based on a farm field level to capture the perspectives of different stakeholders. The model thus supports Illinois EPA’s plan of developing a program based on enabling and empowering local stakeholders to take charge of the fate of their watershed. Management alternatives available for all land uses modeled by SWAT are developed considering rotation patterns of three years. The decision support tool is applied to Big Creek sub-watershed in the Cache River watershed, located in Southern Illinois. Big Creek subwatershed has been sighted by the Illinois EPA for excessive sediment and nutrient loadings and has been targeted by the Illinois Pilot Watershed Program. This research is part of an ongoing effort to develop a comprehensive decision support tool that uses multi-criteria evaluation to address social, economic and hydrologic issues for integrative watershed management.

A Multiobjective SDSS for Management of Urbanizing Watersheds: The Case of the Lower Kaskaskia Basin, Illinois

Kyle O. Allred et al. — Mon, 21 Nov 2011 12:04:46 PST

The conversion of natural and agriculturally dominated watersheds to industrial, commercial and residential developments leads to a cascade of adjustments in runoff quantity and stream quality at locations further downstream. The use of sophisticated hydrologic simulation models and Geographic Information Systems (GIS) has become the standard for evaluating these impacts of urban sprawl on water resources systems. Simulation and GIS models alone, however, are incapable of directly revealing optimal land development patterns that meet specified objectives. This paper describes the development of a multi-objective Spatial Decision Support System (SDSS) designed to overcome this limitation. The SDSS is created by integrating the U.S. Department of Agriculture’s Soil and Water Assessment Tool (SWAT) for comprehensive hydrologic simulation, a GIS for generating input and visualizing output, and a genetic algorithm (GA) for identifying weighted, optimal land use patterns. In addition to the GA, future research will involve the integration of a second search mechanism, the artificial life algorithm, to verify optimal results. The optimal landscape is that which minimizes sediment yield in subsequent streams, while simultaneously maximizing approximate anticipated profit from urban development. The SDSS could be a useful visualization tool for land use managers and watershed management institutions in planning new developments. The SDSS has been tested on the Lower Kaskaskia watershed, located in the Metro East area of southwestern Illinois. Evidenced by a historical survey of population growth and hydrologic and water quality variability, this basin is an example of a watershed that is undergoing extensive water resources changes as a result of urbanization. An investigation of watershed planning activities and stakeholder groups in the watershed has also been undertaken. Meetings with these individuals have allowed direct dissemination of the research to affected groups and have been useful for generating feedback on future work and model modifications.

An Innovative Geocentric Decision Support Solution to Comprehensive Planning, Design, Operation, and Management of Urban Drainage Systems

Paul F. Boulos et al. — Mon, 21 Nov 2011 12:04:32 PST

Geographic Information System (GIS) is quickly becoming a critical component to develop and sustain asset management for today’s wastewater utilities as most of their data is geographically referenced. This technology offers sophisticated data management and spatial analysis capabilities that can greatly improve and facilitate urban drainage infrastructure modeling and analysis applications. This paper presents a comprehensive GIS-based decision support system that integrates several technologies for use in the effective management of urban stormwater collection systems. It explicitly integrates ESRI ArcGIS geospatial model with advanced hydrologic, hydraulic, and water quality simulation algorithms, nature-based global optimization techniques including genetic algorithms for design and calibration of stormwater management models, automated dry weather flow generation and allocation, and automated subcatchment delineation and parameter extraction tools to address every facet of urban drainage infrastructure management. The geocentric interface allows seamless communication among the various modules. The resulting decision support system effortlessly reads GIS datasets, extracts necessary modeling information, and automatically constructs, loads, designs, calibrates, analyzes and optimizes a representative urban drainage model considering hydrologic and hydraulic performance requirements. It also makes it easy to run, simulate and compare various modeling scenarios, identify system deficiencies, and determine cost-effective physical and operational improvements to achieve optimum performance and regulatory compliance. These combined capabilities provide favorable geospatial environment to assist wastewater utilities in planning, designing, and operating reliable systems and in optimizing their capital improvement programs.

Using Genetic Algorithms and Particle Swarm Optimization for Optimal Design and Calibration of Large and Complex Urban Stormwater Management Models

Misgana K. Muleta et al. — Mon, 21 Nov 2011 12:04:06 PST

Computer models are vital for the evaluation and management of urban drainage systems. Usefulness of these models, however, depends on how well they are calibrated. Properly calibrated models can be used to conceive, evaluate and compare various design improvement alternatives. Unfortunately, calibration and design of urban stormwater models, especially with the commonly used trial-and-error approach, are an expensive, time-consuming process and normally represent the most painful step of a modeling exercise. Their success depends mainly on the engineering expertise of the modeler and budget availability. The effort is complicated by the fact that these models normally necessitate the evaluation of a large number of variables and parameters in order to adequately describe the complex relationships that exist between rainfall, runoff, watershed characteristics, and system hydraulics in an urban setting. The trial-and-error evaluation of all calibration and design/improvement options is therefore unlikely to be practically feasible or manageable, and even knowledgeable modelers often fail to obtain good results. In this paper, a rigorous optimal calibration and design methodology is presented, which eliminates the need of the traditional trial-and-error technique. The optimal calibration and design problems are cast as nonlinear optimization problems and solved using genetic algorithms (GA) optimization and particle swarm optimization (PSO). The EPA storm water management model (SWMM5) is employed to perform hydrologic and hydraulic analyses. The optimal calibration model determines the set of calibration parameters that best matches field observations of flow, depth or velocity to accurately mirror actual system performance. The optimal design model determines the set of design parameters that best meets desired system performance requirements at minimum cost. Design parameters can include any combination of pipe slope and size, storage, pumping, and new piping. System performance criteria include explicit constraints on the maximum allowable depth to diameter ratio, minimum and maximum pipe velocities, and maximum head loss for force mains. The proposed optimal calibration and design models are demonstrated by application to an example urban stormwater collection system. Enhancement of urban drainage system planning, design, operation and management is a principal benefit of the proposed methodology.

Multiobjective Optimization for Optimal Design of Urban Drainage Systems

Misgana K. Muleta et al. — Mon, 21 Nov 2011 12:03:44 PST

Control of sewer overflows, the leading cause of water pollution in the nation’s water bodies, is vital to reducing risks to public health and protecting the environment. The most common solutions for mitigating sewer overflows include adding storage volume, increasing conduit capacity, expanding pumping capacity, and implementation of real time operational controls to more effectively utilize existing system storage. Obviously, comprehensive modeling and analysis of these sewer systems becomes necessary for developing sound cost-effective and reliable solutions for enhancing system integrity and performance to convey sewer flows without causing overflows. However, identification of the optimal remedial solution that effectively circumvents overflow problems with the least expenditure is a daunting task. The current practice involves a tedious trial-and-error evaluation procedure that seldom leads to the most effective or most economical solutions. Another emerging design approach utilizes single objective optimization that identifies the solution that best satisfies a predefined criterion. The performance criterion used with single objective optimization subjectively lumps the economics objective with metrics that measure effectiveness of the remedial solution from the perspective of avoiding overflows (e.g., minimizing the number of flooding events or reducing the flooding volume). Consequently, the design solution identified using single objective optimization depends on the weights subjectively placed on the two incommensurable and conflicting objectives, and may not represent the global optimal solution. A preferable approach is to seek tradeoff solutions commonly referred to as non-dominated solutions or Pareto-optimal solutions. The methodology proposed here links an extended version of the EPA SWMM 5 model, a comprehensive drainage network simulator, with NSGA-II, an evolutionary multiobjective optimization method with a proven history of identifying Pareto-optimal solutions for a wide range of engineering problems. The method should prove useful to any wastewater utility attempting to improve system integrity, reliability and performance and optimize its capital improvement program.

Analysis and Calibration of RDII and Design of Sewer Collection Systems

Misgana K. Muleta et al. — Mon, 21 Nov 2011 12:03:28 PST

Excessive wet weather flow resulting from rainfall-derived inflow and infiltration (RDII) is a major source of sanitary sewer overflows (SSOs). SSOs pose serious problem to the public and the environment by causing back up into basements and sewer overflows to streets and rivers. Control of sewer overflows is, therefore, vital to reducing risks to public health and protecting the environment from water pollution. Computer modeling of sewer collection systems plays an important role in determining sound and economical remedial solutions that reduce RDII, improve system integrity, reliability and performance, and avoid overflows. This paper presents a rigorous and efficient three-step optimization methodology for use in solving the sewer overflow problem. The first step analyzes measured sewer flow and rainfall data and decomposes the flow data into dryweather flow and wet-weather flow components. The second step computes the optimal RTK parameters of the tri-triangular unit hydrograph that is commonly used to model RDII into the sewer collection system. The optimal RTK parameters are calibrated with genetic algorithm so that the simulated RDII flows closely match the RDII time series generated by decomposing the measured flow data. In the final step, the calibrated model is then used with genetic algorithm to design cost-effective solutions for existing SSO problems. Design parameters can include any combinations of pipe size, storage, slope, and pumping. The proposed wet-weather flow decomposition, optimal calibration, and optimal design models are demonstrated using an example sewer collection system. The methodology seems a good alternative to other methods proposed in the literature and should prove useful for engineers and planners that are involved in mitigating complex SSO problems.