För modellering av risker vid naturkatastrofer är GIS ett grundläggande verktyg. HAZUS-MH är ett GIS-baserat riskanalysverktyg, utvecklat av den amerikanska myndigheten FEMA. HAZUS-MH har en välutvecklad metodologi för modellering av naturkatastrofer, vilket är något som efterfrågas på europeisk nivå inom ramen för översvämningsdirektivet. Därför föreligger ett intresse för implementering av HAZUS-MH för icke amerikanska förhållanden. Denna studies syfte är att fördjupa kunskaperna för implementering och användning av HAZUS-MH i Sverige. För att möjliggöra implementering behöver svenska data bearbetas för att matcha datastrukturen i HAZUS-MH. Metoden innefattar en litteraturgenomgång av tidigare studier och manualer samt databearbetning. Erfarenheter av databearbetningen samlades in för att bygga upp en manual för databearbetning samt för att utvärdera möjligheter och hinder för implementering i Sverige. Resultatet visar hur systemkrav och övriga inställningar för användning av HAZUS-MH ser ut. De övriga inställningarna berör koppling till HAZUS-MH databas med mera. För anpassning av svenska data beskrivs databehov (administrativ indelning, inventeringsdata och hydrologiska data), data-bearbetning (rekommenderad arbetsgång för att fylla shape-filer och tabeller med information) och dataimport. Vidare redogör resultatet för tillämpningen av HAZUS-MH med svenska data. Denna studie identifierar flera möjligheter hos HAZUS-MH. Möjligheterna att skapa risk- och sårbarhetskartor samt dataimport är de största. Tidsåtgången för att utföra anpassningen av svenska data var runt 15 arbetsdagar. Denna studie uppskattar att med hjälp av manualer för anpass-ningen kan denna tid kortas till 3 arbetsdagar. Om processen att anpassa svenska data automat-iseras kan tiden kortas ytterligare. Den största barriären enligt denna studie är insamling av data. För att kunna använda HAZUS-MH fulla potential behövs omfattande datainsamling. En annan barriär är begränsningar i hydro-logiska data, det är nödvändigt med externa hydrologiska data för en så korrekt analys som möjligt. Vidare forskning inom området bör enligt denna studie fokusera på metoder för att samla in data samt hur en automatisk process för att anpassa data skulle kunna se ut. / When modeling risks for natural disasters, GIS is a fundamental tool. HAZUS-MH is a GIS-based risk analysis tool, developed by the American authority FEMA. HAZUS-MH has a well-developed methodology for modeling natural disasters, which is something that is demanded at European level within the flood directive framework. Hence, there is an interest in implementing HAZUS-MH for non-US conditions. The aim of the study is to deepen the knowledge for the implementation and use of HAZUS-MH in Sweden. To enable implementation, Swedish data is required to be processed to match the data structure of HAZUS-MH. Methods for this study are a literature review of previous studies and manuals and data processing. Experiences of the data processing were collected to build a manual for data processing and to evaluate opportunities and obstacles for implementation in Sweden. The result shows how system requirements and other settings for using HAZUS-MH look like. The other settings include connection to the HAZUS-MH database et cetera. For adaption of Swedish data, requirements including data (administrative division, inventory data and hydrological data), data processing (recommended workflow to fill shape-files and attribute tables with information) and data import are described. The result also describes the application of HAZUS-MH with Swedish data. This study identifies several possibilities of HAZUS-MH. The opportunities for creating risk and vulnerability maps and data import are the largest. The time required to perform the adaptation of Swedish data was approximately 15 working days. This study estimates that with the help of manuals for the adaption, this time could be shortened to approximately 3 working days. If the process of adapting data is automated, this time could be shortened further. The largest obstacle under this study is the data collection process, to use the full potential of HAZUS-MH extensive data collection is needed. Another obstacle is the limitation of hydrological data, external hydrological data is necessary to get as accurate analysis as possible. Further research in the field should, according to this study, focus on methods of collecting data and development of an automatic process for managing data.

Agriculture is one of the major economic drivers and the production is highly dependable on the climatic conditions and very sensitive to the natural hazards like the flood. The Federal Emergency Management Agency (FEMA) of United States developed Hazard-US model (HAZUS), a tool to estimate the loss to several sectors due to natural hazards like floods, hurricanes, and earthquakes. The study assesses the influence of input model parameters for HAZUS flood loss to crops. This thesis analyzes different combinations of input parameters for the Middle Cedar River Watershed in Iowa. The parameters have been modified based on the cropping pattern of the study region and the pricing trends. The results include the computation of the loss distribution and the determination of the most influential parameters. The study has found that some parameters are more influential in the loss estimation. The influence of parameters for the average annual loss (AAL) calculation is similar. Floods at the end of the cropping season are much more severe than floods at the beginning of the cropping season. Corns are more at risk than soybean because of the longer cropping season. Some counties experience more loss than others based on AAL. The results indicate that the agricultural sector is more vulnerable to floods at the end of the cropping season. The estimation of loss can help emergency planning for floods affecting agriculture, and optimize the agricultural resource management. The inclusion of additional parameters like flood velocity and water quality in the model can increase the accuracy of the estimation.

This study uses an empirical approach to develop algorithms to estimate population dislocation following a natural disaster. It starts with an empirical reexamination of the South Dade Population Impact Survey data, integrated with the Miami-Dade County tax appraisal data and 1990 block group census data, to investigate the effects of household and neighborhood socioeconomic characteristics on household dislocation. The empirical analyses found evidence suggesting that households with higher socio-economic status have a greater tendency to leave their homes following a natural disaster. Then one of the statistical models is selected from the empirical analysis and integrated into the algorithm that estimates the probability of household dislocation based on structural damage, housing type, and the percentages of Black and Hispanic population in block groups. This study also develops a population dislocation algorithm using a modified Hazard-US (HAZUS) approach that integrates the damage state probabilities proposed by Bai, Hueste and Gardoni in 2007, accompanied with dislocation factors described in HAZUS to produce structural level estimates. These algorithms were integrated into MAEviz, the Mid-American Earthquake Centers Seismic Loss Assessment System, to produce post-disaster dislocation estimates at either the structure or block group level, whichever is appropriate for the user's planning purposes. Sensitivity analysis follows to examine the difference among the estimates produced by the two newly-developed algorithms and the HAZUS population dislocation algorithm.

In this study, Hazus-MH (v 2.1 SP 2) flood-loss estimation tools were assessed for their sensitivity to an array of different building and model parameters. The purpose of this study is to help guide users of the Hazus-MH flood-loss modeling tool in the selection of most appropriate model parameters. Six model parameters (square footage of the building, building age, construction types, foundation types, first floor heights, and the number of stories in the building) were assessed for their impacts on flood losses using the Hazus-MH user defined and aggregate flood-loss models. Building stock databases for these analyses were developed using county assessor records from two Illinois counties. A validation assessment was also performed using observed flood-damage survey data collected after the 2011 Mississippi River Flood which inundated the Olive Branch Area in Alexander County, Illinois. This analysis was performed to assess the accuracy of the detailed Hazus-MH User Defined Facility (UDF) flood-loss modeling tool. The foundation types and its associated first floor heights and number of stories in the building were found to substantially impact flood-loss estimates using the Hazus-MH flood-loss modeling tool. The model building parameters square footage, building age and construction type had little or no effect on the flood-loss estimates. The validation assessment reveled Hazus-MH UDF flood-loss modeling tool is capable of providing a reasonable estimate of actual flood losses. The validation assessment showed the modeled results to be within 23% of actual losses. The validation study results attained in this study using the detailed UDF flood-loss modeling tool where more realistic (within 23% of actual losses versus > 50% of actual losses) than previous Hazus-MH flood-loss validation assessments. The flood-loss estimates could be further improved by modifying or choosing a more region specific depth-damage curve, using higher resolution DEM and improving the flood-depth grid by incorporating more detailed flood elevation data or estimates using detailed hydraulic models that better reflects the local inundation conditions.

This study combined flood-frequency analysis, 1-D (one-dimensional) hydraulic modeling using HEC-RAS, and flood-loss modeling using FEMA's Hazus-MH (Hazards U.S. Multi-Hazard) in order to: 1) quantify how different flood-frequency methodologies affect flood-risk assessments, and 2) quantify the impacts of different floodplain-management scenarios along the Middle Mississippi River (MMR). The nine scenarios tested here included various combinations of flood-frequency methodology, buyouts, and levee configurations. The levee configurations analyzed included: 1) current levee configuration, 2) no levees, 3) a 1500 m levee setback, 4) a 1000 m levee setback, and 5) a customized levee setback designed to maximize protection around existing infrastructure. Two study reaches were chosen: (1) an Urban Study Reach within St. Clair and northern Monroe Counties, IL, with levees designed to withstand the 500-year flood and (2) an Agricultural Study Reach within Union and Jackson Counties, IL, with <100-year levees. A flood-frequency analysis was completed for the St. Louis, MO gauging station, and detailed building inventories were used to estimate flood losses on a structure-by-structure basis (Hazus-MH UDF analysis) for an array of floods ranging from the 2- to the 500-year events. These flood-loss estimates were combined with a stochastic levee-failure model. Finally, estimated flood damages from Hazus-MH were integrated across the full range of flood recurrences in order to calculate expected annual damage (EAD). This study's flood-frequency analysis and corresponding flood-loss assessment demonstrate how differences in flood-frequency methodology can significantly impact flood-risk assessments. EAD based on the UMRSFFS (Upper Mississippi River System Flow Frequency Study) flood frequencies was 68% ($45.4 million) lower than EAD based on this study's flood frequencies. This decrease in EAD demonstrates that the UMRSFFS flood frequencies and corresponding stages may significantly underestimate flood risk within the Urban Study Reach. The 100-year discharge in the UMRSFFS appears to be underestimated by an estimated 17% (187,000 cfs), resulting in a 10% (1.6 m) underestimation of the 100-year flood level. Given the magnitude of the EAD, discharge, and stage differences documented here, a reanalysis of the MMR flood frequencies, flood profiles, and flood maps should be considered. The hydraulic modeling completed here showed that levee setbacks and levee removal successfully reduce stages for all recurrence intervals. For the 100-year flood, average reductions ranged from 0.20 m for a 1000 m levee setback to 1.61 m with levees removed. In general, stage reductions increased with increasing discharge and with increasing setback distance. The flood-level reductions are attributed to increased floodwater storage and conveyance across the reconnected floodplain. Compared to the current conditions, the levee setback and levee removal scenarios tested here reduced flood losses for large, infrequent flooding events but increased flood losses for smaller, more frequent flood events. When combined with buyouts of unprotected structures, levee setbacks reduced flood losses for all recurrence intervals. The 1000 m and 1500 m levee setbacks required buyouts in order to reduce EAD; however, a levee setback carefully planned around existing high-value structures reduced EAD with or without buyouts. The planned levee setback configuration combined with buyouts resulted in the largest decreases in EAD: a $16.8 million (55%) decrease in the Urban Study Reach and an $8.3 million (93%) decrease in the Agricultural Study Reach. Overall, this project showed that levee setbacks in combination with buyouts are an economically viable approach for flood-risk reduction along the study reaches and likely elsewhere where levees are widely employed for flood control. Designing a levee setback around existing high-value infrastructure can maximize the benefit of the setback while simultaneously minimizing the costs. Potentially, this type of planned levee configuration could be used as a template for the replacement of aging or failing levee systems.

Mississippi State University is one of the many public institutions in Mississippi located near a seismic hazard zone known as the New Madrid Seismic Zone (NMSZ). Previous studies reveal the possibility of damage to the campus during an earthquake is in the order of ten percent. Risk assessment for building structures on campus was carried out using HAZUS-MH MR3 software package, for several earthquake scenarios defined to replicate historic and hypothetical earthquake events.The study predicts peak ground accelerations of 0.09g to 0.2g relating to 0.67% to 4.28% building loss ratios respectively, which amounts to a loss of $8.2 million to $53 million. Wood and reinforced masonry buildings show significant resistance to earthquakes compared to concrete and unreinforced masonry buildings. The results of this study suggest that there is a considerable seismic risk to Mississippi State University buildings from a seismic event originating in NMSZ.

Se sabe que la mayoría de las viviendas en el Perú no cumplen con las normas de edificaciones, por ello abunda la autoconstrucción debido muchas veces a las limitaciones económicas. Esto puede presentar mayor vulnerabilidad frente a algún movimiento telúrico en la costa peruana. Es necesario cuantificar el daño estructural de las edificaciones comunes producido por un sismo mediante las curvas de fragilidad. Los métodos empleados para evaluar el riesgo sísmico generalmente son abstrusos ya que se necesita evaluar la curva de capacidad de cada vivienda seleccionada, utilizando un análisis no lineal o por desempeño sísmico; por ello en un área de mayor amplitud como en el caso de un distrito se vuelven poco convencionales para la estimación de perdidas. Por este motivo, en el presente trabajo de investigación, se emplea un método de la vulnerabilidad sísmica utilizando las curvas de fragilidad propuestas por el FEMA. Si bien las construcciones americanas presentan características propias de lugar y la calidad de los materiales de las diferentes tipologías estructurales, se puede utilizar la metodología HAZUS pero adaptándolas a la realidad peruana. Debido a esto, las viviendas serán analizadas en el mapa de riesgo sísmico para escenarios que comprenden las siguientes clasificaciones de intensidad del sismo: frecuente, ocasional, raro y muy raro, analizando así el comportamiento y los niveles de daño alcanzados para cada caso, con ello se podrá determinar las pérdidas para cada situación. / It is known that most of the houses in Peru do not comply with the building standards, therefore self-construction abounds, often due to economic limitations. This may present greater vulnerability to any telluric movement on the Peruvian coast. It is necessary to quantify the structural damage of common buildings produced by an earthquake using the fragility curves. The methods used to evaluate the seismic risk are generally abstruse since it is necessary to evaluate the capacity curve of each selected dwelling, using a nonlinear analysis or by seismic performance; therefore, in a larger area, such as a district, they become unconventional for loss estimation. For this reason, in this research work, a seismic vulnerability method is used using the fragility curves proposed by FEMA. Although the American constructions present their own characteristics of place and the quality of the materials of the different structural typologies, the HAZUS methodology can be used but adapting them to the Peruvian reality. Due to this, the houses will be analyzed in the seismic risk map for scenarios that include the following earthquake intensity classifications: frequent, occasional, rare and very rare, thus analyzing the behavior and the levels of damage achieved for each case, with this can determine the losses for each situation. / Tesis

Manitoba’s flooding is one of the principal sources of costs associated with flood disasters. Despite the tremendous financial investments in structural mitigation, flood cost, continue to rise. Currently at the national and provincial level, there exists no standardized operational framework and tool for flood risk assessment. The primary role of this research was two-fold. First, Hazus-MH a Quantitative Risk Assessment (QRA) tool was evaluated as a potential flood-loss estimation model in a Manitoba context. Secondly, to examine the application of a QRA tool in policy, a face-to-face questionnaire was completed with flood experts in municipal and provincial government and with consultants. The study results suggested that Hazus-MH has the potential to be applied as a standard QRA tool in Manitoba. This research found that developing a standard QRA tool in Manitoba, would empower communication between decision-makers, centralize data to support disaster planning, and reduce the cost of recovery. / May 2016

Flooding is a major hazard in the Midwest, accounting for more economic damage than any other hazard. Recent major flooding events in Iowa have created a greater need for the monitoring of floodplain areas. The objective of this paper is to evaluate flood risk through the synthesis of geospatial data with flood maps for thirteen Hydrologic Unit Codes (HUC 8s) in southwest Iowa. Using ArcGIS, exposure of ecosystem services, population, and environmental hazards can be located within the 10, 50, 100, 500 year floodplains. Additionally, the effectiveness of hydric soils as a floodplain proxy is evaluated using SSURGO soil data. An overview of FEMA HAZUS-MH 2.0 flood loss estimation software is provided and a model of the East Nishnabotna HUC 8 is evaluated. An alternative economic loss framework based on an NED land use raster and structure data is compared for the region. This study aims to provide beneficial floodplain information for development and regulation decisions.

In last decades, the importance of flood damage and loss estimation systems has increased significantly because of its social and economic outcomes. Flood damage and loss estimation systems are useful to understand possible impacts of flooding and prepare better resilience plans to manage and allocate resources for emergency decision makers. Recent web-based technologies can be utilized to create a system that can help to analyze flood impact both on the urban and rural area. With taking advantage of web-based systems, decision makers can observe effects of flooding considering many different scenarios with requiring less effort. Most of the emergency management plans have been created using paper-based maps or GIS (Geographical Information System) software. Paper-based materials generally illustrate floodplain maps and give basic instructions about what to do during flooding event and show main roads to evacuate people from their neighborhood. After the development of GIS (Geographic Information System) software, these plans have been prepared with giving more detail information about demographics, building, critical infrastructure etc. With taking advantage of GIS, there are several software have been developed for the understanding of disaster impacts on the community. One of the widely-used GIS-based software called Hazus-MH (Multi-Hazard) which is created by FEMA (Federal Emergency Management Agency) can analyze disaster effects on both urban and rural area. Basically, it allows users to run a disaster simulation (earthquake, hurricane, and flood) to observe disaster effects. However, its capabilities are not broad as web-based technologies. Hazus-MH has some limitations in terms of working with specific software requirements, the ability to show a limited number of flood scenarios and lack of representing real time situation. For instance, the software is only compatible with Windows operated computers and specific version of ArcMap rather than other GIS software. Users must have GIS expertise to operate the software. In contrast, web-based system allows use to reduce all these limitations. Users can operate the system using the internet browser and do not require to have GIS knowledge. Thus, hundreds of people can connect to the system, observe flood impact in real time and explore their neighborhood to prepare for flooding. In this study, Iowa Flood Damage Estimation Platform (IFDEP) is introduced. This platform is created using various data sources such as floodplain maps and rasters which are created by IFC (Iowa Flood Center), default Hazus-MH data, census data, National Structure Inventory, real-time USGS (United States Geological Survey) Stream gage data, real time IFC bridge sensor data, and flood forecast model which created by IFC. To estimate damage and loss, damage curves which are created by Army Corps of Engineers are implemented. All of these data are stored in PostgreSQL. Therefore, hundreds of different flood analyses can be queried with making cross-sectional analyses between floodplain data and census data. Regarding to level analyses which are defined by FEMA as three level, Level 3 type analysis can be done on the fly with using web-based technology. Furthermore, better and more accurate results are presented to the users. Using real-time stream gauge data and flood forecast data allow to demonstrate current and upcoming flood damage and loss which cannot be provided by current GIS-based desktop software. Furthermore, analyses are visualized using JavaScript and HTML5 for better illustration and communication rather than using limited visualization selection of GIS software. To give the vision of this study, IFDEP can be widened using other data sources such as National Resources Inventory, National Agricultural Statistics Service, U.S. census data, Tax Assessor building data, land use data and more. This can be easily done on the database side. Need to address that augmented reality (AR) and virtual reality (VR) technologies can enhance to broad capabilities of this platform. For this purpose, Microsoft HoloLens can be utilized to connect IFDEP, real-time information can be visualized through the device. Therefore, IFDEP can be recruited both on headquarters for emergency managers and on the field for emergency management crew.