1. ERDC Knowledge Core
  2. Engineer Research and Development Center (ERDC)
  3. Coastal and Hydraulics Laboratory (CHL) - (before 9/1981 - present)
  4. Publication
  5. Technical Report
Please use this identifier to cite or link to this item: https://hdl.handle.net/11681/33883
Full metadata record
DC FieldValueLanguage
dc.contributor.authorSkahill, Brian E. (Brian Edward)-
dc.contributor.authorKanney, Joseph.-
dc.date.accessioned2019-08-28T13:37:23Z-
dc.date.available2019-08-28T13:37:23Z-
dc.date.issued2019-08-
dc.identifier.govdocERDC/CHL TR-19-14-
dc.identifier.urihttps://hdl.handle.net/11681/33883-
dc.identifier.urihttp://dx.doi.org/10.21079/11681/33883-
dc.descriptionTechnical Report-
dc.description.abstractThis report introduces a framework for probabilistic flood hazard assessment (PFHA) whose basis leverages recent advances in the science of spatial extremes. The framework basis includes a latent variable model (LVM) or a max-stable process application wherein for either case model inference is likelihood based. The framework is flexible in that it can leverage robust approaches to quantify model uncertainty while also supporting the capacity to readily combine additional relevant data types; for example, historical and/or paleoflood data for flood frequency analyses. This report profiles applications of Bayesian inference for flood hazard curve development for at-site and spatial LVM analyses. Pointwise spatial model development using an LVM or a max-stable process requires the parameters of the model characterizing the pointwise extremes to vary spatially as a function of gridded covariate data relevant to the hydrometeorological extreme under consideration. Recent advances in mathematical regularization facilitate spatial pointwise model reduction. The PFHA framework accommodates the multiple model parameterizations encapsulated within a given LVM or max-stable process deployment by generalizing model choice using information criteria.en_US
dc.description.sponsorshipU.S. Nuclear Regulatory Commission.en_US
dc.description.tableofcontentsAbstract ................................................................................................................................................... ii Figures and Tables .................................................................................................................................. v Preface ..................................................................................................................................................... x 1 Introduction ..................................................................................................................................... 1 1.1 Background .................................................................................................................... 1 1.2 Objective ........................................................................................................................ 1 1.3 Approach ........................................................................................................................ 2 2 Background ..................................................................................................................................... 3 3 Framework ...................................................................................................................................... 9 3.1 Station specific analysis ............................................................................................. 14 3.1.1 Systematic data only ................................................................................................. 14 3.1.2 Combining Different Observed Data Types .............................................................. 34 3.1.3 Seasonality ................................................................................................................ 38 3.1.4 Expert elicitation ....................................................................................................... 39 3.1.5 Non-stationary climate condition ............................................................................. 42 3.2 Multiple station analysis ............................................................................................. 46 3.2.1 WRB summary description ....................................................................................... 47 3.2.2 Annual maxima data summary description ............................................................. 47 3.2.3 Covariate data .......................................................................................................... 49 3.2.4 Spatial Bayesian hierarchical modeling .................................................................. 50 3.2.5 Max-stable process model application .................................................................... 60 3.3 Muliti-model averaging ................................................................................................ 71 4 Discussion and Recommendations ............................................................................................ 75 References ............................................................................................................................................ 78 Appendix A: Extreme Value Theory .................................................................................................... 87 Appendix B: Other Distributions for Extreme Rainfall Analysis ...................................................... 92 Appendix C: Generalization of Model Selection ............................................................................... 94 Appendix D: Bayesian Inference Methodology and Markov Chain Monte Carlo Simulation ..................................................................................................................................... 96 Appendix E: Spatial Bayesian Hierarchical Modeling ..................................................................... 98 Appendix F: Modeling Results and Related Observations for 3.1.5.1 Case Study Demonstration - White Sands National Monument Rainfall Station IDF Curve Development .............................................................................................................................. 100 Appendix G: The Willamette River Basin (WRB), Including Hydrography, Projects, and Cities Located in the Basin and Its Relative Location in the State of Oregon ................... 111 Report Documentation Page-
dc.format.extent124 pages / 5.955 Mb-
dc.format.mediumPDF-
dc.language.isoen_USen_US
dc.publisherCoastal and Hydraulics Laboratory (U.S.)en_US
dc.publisherEngineer Research and Development Center (U.S.)-
dc.relation.ispartofseriesTechnical Report (Engineer Research and Development Center (U.S.)) ; no. ERDC/CHL TR-19-14-
dc.rightsApproved for Public Release; Distribution is Unlimited-
dc.sourceThis Digital Resource was created in Microsoft Word and Adobe Acrobat-
dc.subjectFlood controlen_US
dc.subjectFlood damage preventionen_US
dc.subjectFloodsen_US
dc.subjectNuclear facilitiesen_US
dc.subjectRain and rainfallen_US
dc.subjectRainfall probabilitiesen_US
dc.titleProbabilistic flood hazard assessment framework development : extreme rainfall analysisen_US
dc.typeReporten_US
Appears in Collections:Technical Report

Files in This Item:
File Description SizeFormat 
ERDC-CHL TR-19-14.pdf6.1 MBAdobe PDFThumbnail
View/Open
Show simple item record