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Best Practice Protocols For Response And Recovery Operations In Contaminated Water SystemsCenter for Water Resource StudiesWestern Kentucky UniversityKentucky Water Resources Research InstituteUniversity of KentuckyCenter for Infrastructure ResearchUniversity of LouisvilleWater Resources Research CenterUniversity of MissouriKYPipe LLC

1Hello. My name is Andy Ernest. Im the Director of the Center for Water Resource Studies at Western Kentucky University. I serve as the Principle Investigator for this project entitled Best Practice Protocols For Response And Recovery Operations In Contaminated Water Systems. I believe this is one of currently four Water Sector projects funded through the Critical Infrastructure Protection Program. Our project partners are the Kentucky Water Resources Research Institute at the University of Kentucky, the Center for Infrastructure Research at the University of Louisville, and the Water Resources Research Center at the University of Missouri. Our external commercial partner is KYPipe.Problem StatementDecision-Support Tool to Guide Response and Recovery Operations DHS -2008-002-Water: Decontamination Research

Pre-eventpost-event planning robustnessDecontamination optionsFlushno-flush?Response command structureRegulatory stakeholders, local government, law enforcement, environmental concerns, etc.Factors affecting approach selectionNIMS and ICS compatibility2This project addresses, in part, the Department of Homeland Security Capability Gap 2008-002-Water Decontamination Research in which a Decision-Support Tool to Guide Response and Recovery Operations was identified as a need. We propose to develop just such a tool to help:Evaluate the robustness of both pre-and post-event planning efforts for handling a decontamination event,Identifying options for dealing with a contaminated system, including whether or not to flush,Clarify the response command structure, including defining the roles of regulatory stakeholder, local government, low enforcement, environmental concerns, and other,Characterize the factors that influence the selection of the appropriate response and recovery approach, and,Ensure that the approach conforms to the National Incident Management System and the Incident Command System.Project FocusMulti-scaleLocal and RegionalResiliency dataDecision supportNationalExtrapolated impact and exposurePolicy supportMulti-facetedFact sheetsScale relevanceExpert systemRules-basedGraphical Decision Support Systems (DSS)Distribution systemTraining materialsWeb-delivered3We are using a multi-scale approach, allowing us to extrapolate national impact and exposure from local and regional resiliency data and decision support processes, to support policy decisions. Our approach is multi-faceted to be applicable to as broad a range of system complexities and network knowledge levels as possible. A graphical decision support system is being developed to allow local utilities to make decisions based on a visual representation of their distribution networks. Our rules-based expert system approach will guide users through the decision making process making use of whatever information they may have available. For smaller and less complex systems, we will have fact sheets and guidance documents summarizing the knowledge-base incorporated in the decision support system components. We will also develop training materials for use in a series of technology deployment workshops, and for web delivery.Project OrganizationPrinciple InvestigatorAndrew ErnestWKU/CWRSProject CoordinatorJana FatticWKU/CWRSHydraulic SystemsLindell OrmsbeeUK/KWRRIStakeholder EngagementThomas RockawayUof L/CIRBackground ResearchThomas ClevengerUof M/WRRCUtility OperationsRobert ReedUof M/WRRC4In addition to overall project direction, My contribution is in knowledge engineering and rules-based decision support tool development. Day-to-day technical and logistical project coordination is managed by Jana Fattic and Alanna Malone, part of the leadership team of the water center at WKU. Lindell Ormsbee from UK is the Hydraulic Systems lead, while Ton Rockaway from UofL is leading the Stakeholder Engagement task. The Background Research is led by Tom Clevenger from Mizzou, supported by Bob Reed in utility operations.Project ComponentsDecisionsupporttoolBackgroundresearchStakeholderengagementDecontaminationNetworkModel (DNM)Rules-BasedDecisionSupportTool (RBDST)TrainingEducationGuidance5The project kicked off with an in-depth literature review. This will drive tabletop exercises in a stakeholder engagement process designed to tease out the structure and components of the knowledgebase that will drive the remainder of this program. The Decision Support Tool will be made up of two integrated pieces. The Decontamination Network Model is a graphical model of the users distribution network, giving him or her the ability to perform visual what-if scenarios. The RulesBased Decision Support Tool is a knowledgebase and inference engine driven expert system that will recommend actions based on the facts provided by the user. The tools will then be integrated into a training and capacity development program.Literature SearchGovernment WebsitesResearch DatabasesEnvironmental Protection AgencyDepartment of Homeland SecurityCritical Infrastructure Partnership Advisory CouncilNational Incident Management SystemNational Infrastructure Protection PlanGovernment Accountability OfficeNational Institute of Standards and TechnologyNational Academy of Sciences National Research CouncilAcademic Search PremierCompendexScopusTechnology Research DatabaseWater Research Abstracts6Search phrasesASPASCECompScopusTRDWRAContaminants in drinking water810425651558103103Removing contaminants from drinking water29Contaminants in drinking water systems239Removing contaminants from drinking water systems13Summary of Literature Searches Databases:

ASP = Advanced Search Premier (EBSCO)ASCE = American Society of Civil EngineersComp = Compendex (Engineering Village)TRD = Technology Resources Database (Illumina)WRA = Water Research Abstract (Illumina) 7Examples of Decontamination Methods Removal of arsenic/heavy metalsConvent.oxidPOU filtersNanofiltrPrev osmosPolym-ligandElectrodialPhytofiltrHydrotalciteLignocellIron oxide-sandElectrocoagNanomatersSod carbonateNano/ROAdsorbentsMagnetite polymRemoval of micro-biologicalsAdv coagulPOU filtersCeram filtersMembr genChlorin/chloramUvperoxideTiO2+sunlightBiogen silverAct carb/GACAdsorb/filtLow press memberUV onlyNano materialsRemoval of OrganicsPolyelectrolytesCoagul/MIEX/nanofiltOzone oxidUV254Biodiatomic reactorAdv oxidUV+peroxSonochem+fentUV onlySlow release oxidActiv carb/GACNanopaticsNanofiltr/RONanofibersPolymers8Knowledge EngineeringOntologyModelLanguageTaxonomyTreeHierarchySemanticsDefinitionMeaning

Knowledge engineering is actually a relatively new discipline, defined in 1983 as an engineering discipline that involves integrating knowledge into computer systems in order to solve complex problems normally requiring a high level of human expertise. Core to engineering the state of knowledge about decontamination practices, is defining its ontology. This is a formal representation of knowledge as a set of concepts within, in this case, the DECON domain, and the relationships between those concepts. The DECON ontology can then be used in machine reasoning. Taxonomy and Semantics relate to the vocabulary and structure of the language we will be using to build the working DECON knowledgebase.9DECON Knowledge OntologyIssues (CIPAC 2004)Large volumesPractical solutionsTreatment worksDecision-making frameworksDistribution and collection systemsOutreach and trainingUtility communicationsCleanup levelsTreatment proceduresAgent fate and transportRoles and responsibilitiesWaivers or suspensionsResources and assetsLaboratory analysisOperator health and safetyOverarchingRemedy Evaluation Criteria (EPA Module 6 2007)Overall protection of human health and environmentCompliance with regulationsLong-term effectiveness and permanenceReduction in toxicity and mobilityGeneration of residualsShort-term effectivenessImplementabilityRelative costState, support agency, and community acceptanceWRF Project #2981?EPA Report (Pending)?

There really is not a well defined and scientifically rigorous process for distilling literature into an ontology. However, the iterative hierarchical process we go through in summarizing and categorizing literature lends itself well to the creation of an ontology. The purpose of this slide is simply to demonstrate how key categories of knowledge can be parsed from reports and manuscripts. As need knowledge comes to light, the knowledgebase expands and the ontology adjusts.Weve distilled a part of EPAs Module 6 document into a rule base. If I dont succeed in boring you to death, at the end of this presentation, Im going to try to run through a short demonstration.

10DECON Semantic Knowledge DevelopmentStakeholdersEngagement

DHS, Utilities, Trade Assoc., Bio/Chemical specialists, USEPA, CDC, DHHS, State health departments, End users, NIMS, ICS, etc

This project is guided by two separate external groups and External Advisory Panel, and a Technical Advisory Committee. The EAP serves more of an overall directional and policy driver, whereas the TAC is focused on the technical project implementation details. These groups, along with a larger set of utility and municipality participants, will drive the development of the knowledgebase through a series of stakeholder engagement activities.

11Stakeholder EngagementTabletop exerciseWorking with local utilities to develop a list ofwhat if scenarios" autility mayencounter during the decontamination processEstablishingtypical decontaminationprotocol, from boththe water quality and distributionperspectivesThe research team has begun gathering material for the table top exercise (TTX)The UofL research team is attending a workshop Tabletop Exercise Tool for Water Systems: Emergency Preparedness, Response, and Climate - November 9th, 2010Peer reviewBegan compiling a list of possible independent technical reviewers for the state-of-the-art decontamination report

12Semantic Knowledge -> Decision Support Toolnotify? flush?isolate?disposal?where?volume?when?what else?health impacts?environmental?

13The two DST components will focus on distribution and management issues.Once the location of possible incursion has been identified, distribution system issues might include:Who should be notified? How? When?Should the system be immediately flushed or isolated?If the system should be flushed, using what hydrants(s)?What will be the final disposition of the flushed water? Where will the water flow?If the system should be flushed, can the upstream part of the system be used or does the system need to be isolated and flushing water pumped through hydrant? If so, which hydrant?If the system should be isolated, using what valve(s)? What is the associated volume of water that will be isolated?What additional system components (e.g. pumps, tanks,) need to be changed in support of system flushing or isolation?How can water be provided to those denied served due to the isolation? What is the operational impact associated with the rest of the system?What operational steps need to be taken to maintain normal conditions until decontamination is complete? Once the contaminant has been identified, management questions mightinclude:Who should be notified? How? When?What are the potential health impacts?What are the environmental concerns?Should decontamination begin at the time of the detection of the contaminant or at a later time? Does retaining the contaminant within the distribution system and at the customers tap pose an immediate health concern (e.g., Do the structures pipes leak)? If so, what action should be taken?What decontamination strategy should be taken? Flush the system, Treat the contaminated pipes, In-situ, Ex-situ, Permanently isolate, drain, and leave in place, Isolate, drain, and excavateWhat post event information needs to be provided to decision makers, utility customers, and the general public?Preliminary NDM Needs AssessmentCommercially available Water Distribution analysis software (products with major market share)KYPIPE developed at the University of Kentucky in 1970s - (primary focus on small to medium sized systems all software is fully supported by original developers and engineering staff)H2ONET developed by MWHSoft - (primary focus on large systems and supporting engineering services)Water CAD developed by Haestad Methods - (Bentley Software)EPANET2 developed by Environmental Protection Agency - (limited technical support)Professional contactsKYPIPE: Dr. Don J. WoodH2ONET: Dr. Paul BoulosWater CAD: Dr. Tom WalskiEPANET2: Dr. Lewis RossmanTEVA: Dr. Jim Uber Existing technology2008 BOSC review panel of the EPA Homeland Security Program14There are several existing water distribution analysis tools that are currently used by industry. None of these models have explicit capabilities to address some of the basic questions related to decontamination questions. We will be partnering with one of those companies, KYPIPE LLC, to develop additional model functionality to address Decon issues. KYIPIPE and auxiliary software were created by Faculty at the university of Kentucky (including Dr. Ormsbee) Dr. Ormsbee will be coordinating this phase of the project. He knows all of the major researchers In the field, and was involved in the 2008 BOSC review panel of the EPA Homeland Security Program.Network Decontamination ModelUse readily available network data from the Kentucky Infrastructure Authority website to build network models of selected systems.Provide interface for automation of the process and functionality to allow for the input of other critical data (e.g. valve locations, hydrants, etc.).

GIS Datasets Network Decontamination Model (NDM)15In order to facilitate the widest distribution of the developed technology, the network decontamination model will be developed so as to allow the input of readily available GIS data sets for all the water systems in the state of Kentucky.

This feature will also serve to accentuate the utility of such data sets, and hopefully provide a template for other states as wellKIA-WRIS Geospatial DataDownload KY Water GIS coverages

Go to http://kia.ky.gov Click on the WRIS tab Select geospatial data from the menu Download water layers Extract the .zip files

This is an example of the Kentucky KIA GIS data system, showing the types of data that can be extracted

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This illustrates how the KIA data set can be uploaded into KYPIPE and converted to a network analysis data set and system visualization

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What will be the final disposition of the flushed water? Where will the water flow?If the system should be flushed, using what hydrant(s)?What is the associated volume of water that will be isolated?If the system should be flushed, can the upstream part of the system be used or does the system need to be isolated and flushing water pumped through a hydrant? If so, which hydrant?If the system needs to be isolated, using what valve(s)?Once the data set has been uploaded into KYPIPE, various background maps can also be uploaded to serve as a background for the model.

The model can then be used to evaluate the impact of an incursion at a particular point in the system as shown here the model can identify which valves will need to be closed to isolate the problem and determine which pipes would be affected.

KYPIPE will be modified to provide functionality to address the following questions.

22Export to KYPIPEWhat additional system components (e.g. pumps, tanks) need to be changed in support of system flushing or isolation?How can water be provided to those denied service due to the isolation? What is the operational impact associated with the rest of the system?What operational steps need to be taken to maintain normal conditions until decontamination is complete?

KYPIPENetwork Decontamination Model (NDM)R23Once the data file is uploaded into KYPIPE, the normal features of KYPIPE can then be used to address even more complicated questions such as:

What additional system components (e.g. pumps, tanks,) need to be changed in support of system flushing or isolation?

How can water be provided to those denied served due to the isolation?

What is the operational impact associated with the rest of the system?

What operational steps need to be taken to maintain normal conditions until decontamination is complete? Rules-Based Decision Support ToolDecisionInformation(facts)Inference engineUsers documentsKnowledge baseKnowledge Acquisition SystemHuman expertsAIdata miningUserWho should be notified? How? When?What are the potential health impacts? Immediate? Short-term?What are the environmental concerns?When should decontamination be implemented?What decontamination strategy should be taken?What post event information needs to be provided to decision makers, utility customers, and the general public?The key rationale for using a rules-based reasoning engine is to allow for the inevitable expansion of the knowledge base. In essence, an RBDST processes facts against a set of rules through an inference engine . Facts are user supplied, while the rules are derived from the knowledgebase.24Heuristic Process Validation with Mechanistic Model

Note: Project funded by the Kentucky Science and Technology Corporation (KSTC) - Commercialization FundThe RBDST product builds on technology developed under a Kentucky Science and Technology Corporation commercialization fund project we just completed. In this project, we embedded an inference engine into a Geographic Information System to optimally place sensors in a water distribution network. System facts, extracted from the distribution network map, were applied against sensor placement rules. We validated the RBDST approach against a mechanistic-deterministic optimization approach, using then EPANET hydraulic analysis tool.25Sensor Placement RulesPublic Health concern engine design Selects pipes with diameters greater or equal to 8 inches Selects where chlorine residual concentration is below 0.2mg/LTakes the sum of the pipes lengths and divide by 2 to create impact zone radiusCalculates demand of meters within each impact zoneSelects fittings with high impactCentrality engine design Selects fittings with more than 3 connectionsTakes the sum of the pipes lengths and divide by 2 to create impact zone radiusCalculate meters within each impact zoneSelects fittings with high impactAccessibility engine designLocates pipes with diameter greater than or equal to 8 inchesLocates minor pipes that are attachedCalculates reduction fraction (minor pipe flow/major pipe flow)Selects pipes with a high reduction fractionUnder the KSTC project we developed a Spatial RBDSS integrating the jDREW inference engine with ArcGIS geospatial analysis platform. Three spatial rules were applied, addressing Public Health, Accessibility and Centrality. The application of the RBDST to the DECON project is primarily intended to address management issues although incorporating distribution system issues is a simple matter of enabling spatial reasoning.26EPANET Mechanistic Response

This is sample output from an EPANET validated sensor placement run.27

Spatial RBDSS Execution

GISFactsRulesOO jDrewResultsGIS

RulebaseFactbaseResultsDistribution network data, which in this case are the facts, are exported from within a GIS environment. The exported data can then be run directly by EPANET, or be combined with the sensor placement rulebase and run through the jDREW inference engine. The results are then imported back into the GIS application.28Develop Training MaterialsSoftwareTraining notebooksQuick cardsTutorial videosVirtual environmentsSimulatorsAI-driven trainingAcademic curricula

Water system securityDistribution system decontaminationEconomic resilienceOperational hydraulicsWe will be developing training materials to help deploy and demonstrate the software. In addition to quick cards, notebooks and videos, we will be developing virtual training environments using rudimentary AI techniques. We will also expand the scope of our Water Training Institute to include a CIP water sector track.29Technology DeploymentWorkshopImplementationDemonstrationFeedbackRevisionsFeedbackRevisionsThe technology deployment phase will extend the stakeholder engagement process with a series of workshops to demonstrate and implement the product. Well start with three workshops with a broad suite or end users to demonstrate the product. Three utilities will then be selected for in depth application.30CommercializationRules-Based Decision Support Tool (RBDST) Network Decontamination Model (NDM)Open Environment, PLLCProfessional Limited Liability CompanyRoots - established 2009Center for Water Resource Studies (CWRS)Water resources capacity developmentErnest and SonsHolistic solutions for developing regionsMembersCWRS Leadership TeamKYPIPE LLC www.kypipe.comHistorically dominant pipe network analysis technology providerCurrent project commercialization partner Business model - traditional licensingCommercialization - product-based deliverables The Decontamination Network Model will be commercialized by KYPipe LLC. KYPipe is a longstanding pipe network analysis technology provide. Open Environment, PLLC was established in part to spin off incremental technologies developed by the CWRS, including the spatial DSS developed under the KSTC project. The CWRS leadership team form the core ownership of this company.31Pending TasksPrototypeWeb-service deploymentWDNDDSS integrationRules baseDecon state of the artProcess rules and geospatial fact conformanceCodification and validationTrainingMaterials developmentDeployment and validationCommercializationMarket assessmentProduct specificationLicensing and deploymentBoth the NDM and the RBDST prototypes are well developed, with some refinement and integration into the broader brainwork still to be done. Work on the rules base is dependent on the compilation of the state of the art document. The training, deployment and commercialization phases of the project are scheduled to begin in the latter part of the performance period.32Project Status - SummaryDecisionSupportToolBackgroundResearchStakeholderEngagementDecontaminationNetworkModelRules-BasedDecisionSupportToolTrainingEducationGuidance33The background research phase ct this project is almost complete, with the stakeholder engagement phase about to begin. There prototypes of the functional components of the decision support tool are well developed, with constriction of the integrating framework, development of training materials, deployment and commercialization yet to be started.