This dataset contains data on Public Assistance project awards (obligations), including the project obligation date(s); dollar amount of Federal Share Obligated for each project and its obligation date(s); FEMA Region; State; Disaster Declaration Number; descriptive cause of the declaration (Incident Type); Entity requesting public assistance (Applicant Name); and distinct name for the repair, replacement or mitigation work listed for assistance (Project Title). rnrnAs part of disaster declarations, the President can make federal funding (Public Assistance) available through FEMA to eligible state, local and tribal governments and certain private nonprofit organizations. This is done on a cost-sharing basis for emergency work and the repair, replacement, or mitigation work for facilities damaged by the disaster event. rnrnAs part of Congressional bill HR 152 - the Sandy Recovery Improvement Act of 2013, FEMA is providing the following information for our stakeholders: Region, Disaster Declaration Number, Disaster Type, State, Applicant, County, Damage Category Code, Federal Share Obligated, and Date Obligated.rnrnNote: FEMA obligates funding for a project directly to the Recipient (State or Tribe). It is the Recipient's responsibility to ensure that the eligible subrecipient (listed in the dataset as Applicant Name) receives the award funding.rnrnThis dataset lists details about project versions (occurring when the scope/cost changes for a project). Versions adjust the cost of the project with positive additions called obligations and subtractions called deobligations. Combined, they reconcile to reflect the Total Federal Share Obligation, but reconciliation occurs over the life of the project - sometimes years after the declaration date. The dataset represents project obligations within a seven-day period prior to the listed date but does not include obligations uploaded on the same day as the publication. Open projects still under pre-obligation processing are not represented. For more information on the Public Assistance process see: https://www.fema.gov/assistance/public/processrnrnThis is raw, unedited data from FEMA's Emergency Management Mission Integrated Environment (EMMIE) system and as such is subject to a small percentage of human error. The financial information is derived from EMMIE and not FEMA's official financial systems. Due to differences in reporting periods, status of obligations and how business rules are applied, this financial information may differ slightly from official publication on public websites such as usaspending.gov. This dataset is not intended to be used for any official federal financial reporting.rnrnFEMA's terms and conditions and citation requirements for datasets (API usage or file downloads) can be found on the OpenFEMA Terms and Conditions page: https://www.fema.gov/about/openfema/terms-conditionsrnrnFor answers to Frequently Asked Questions (FAQs) about the OpenFEMA program, API, and publicly available datasets, please visit: https://www.fema.gov/about/openfema/faqrnrnIf you have media inquiries about this dataset, please email the FEMA News Desk at FEMA-News-Desk@fema.dhs.gov or call (202) 646-3272. For inquiries about FEMA's data and Open Government program, please email the OpenFEMA team at OpenFEMA@fema.dhs.gov.

Identifying High-Risk Flood Areas

Flood Risk Analysis (NFHL)

By Finance [source]

About this dataset

This dynamic dataset offers comprehensive coverage of the nation's flood hazards and risk, making it ideal for use in flood risk analysis. The National Flood Hazards Layer (NFHL) contains data that describes the potential for flooding from bodies of water as well as from man-made sources. Each hazard category contains a description of the type and depth of flooding likely to result in an area, along with categories rating its intensity. With this data, assessments can be made about potential flood impacts on humans and their property. Furthermore, by using topographic information, such experts can estimate which areas may be at higher levels of risk compared to others across the country. NFHL is an invaluable tool for those interested in predicting floods or planning smart land use decisions that account for a location’s likelihood to experience flooding from nearby rivers or other sources such as wastewater overflows into local streams or residential stormwater runoff problems in urban settings

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How to use the dataset

The National Flood Hazard Layer (NFHL) provides information about potential flood risks in the United States. This dataset is essential for performing a comprehensive assessment of potential flood hazards and associated risks in the US. In order to use this dataset effectively, there are some steps you need to follow:

Research Ideas

• Determining the most cost-effective ways for governments to invest in flood protection measures, such as dams, levees and other infrastructure.
• Prioritizing areas for evacuation when a major flood event is predicted.
• Implementing proactive planning measures to reduce the economic and human impact of floods by providing simulations before disaster events occur

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

License: Open Database License (ODbL) v1.0 - You are free to: - Share - copy and redistribute the material in any medium or format. - Adapt - remix, transform, and build upon the material for any purpose, even commercially. - You must: - Give appropriate credit - Provide a link to the license, and indicate if changes were made. - ShareAlike - You must distribute your contributions under the same license as the original. - Keep intact - all notices that refer to this license, including copyright notices. - No Derivatives - If you remix, transform, or build upon the material, you may not distribute the modified material. - No additional restrictions - You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.

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Acknowledgements

If you use this dataset in your research, please credit the original authors. If you use this dataset in your research, please credit Finance.

The frequency and magnitude of natural disasters are increasing in most regions across the world with water-related disasters being the most common and recurrent. The economic cost and toll of these disasters are enormous and are significant obstacles to eradicating poverty and achieving human security and sustainable socio-economic development. As climate change increases the frequency and intensity of extreme weather, water-related disasters such as floods, droughts, landslides, waves, and surges will pose an ever-increasing threat to vulnerable communities and to sustainable development. The study presents an overview of water-related disasters in the PRC and their management. Putting water-related disasters in the context of climate change predictions, the report considers impacts, current management and policies to reduce risk, and opportunities for strengthening IDRM. The review will also be of interest to staff of PRC’s government agencies, the private sector, other donors and nongovernment organizations to raise awareness about and strengthen capacity to manage risks of water related disasters in the PRC.

This record description is for the EMMIE portion of the unioned query required due to migration of Public Assistance (PA) Recovery records into the Fac-trax database. This dataset contains data on Public Assistance project awards (obligations), including the project obligation date(s); dollar amount of Federal Share Obligated for each project and its obligation date(s); FEMA region; state; disaster declaration number; descriptive cause of the declaration (incident type); entity requesting public assistance (applicant name); and distinct name for the repair, replacement or mitigation work listed for assistance (Project Title). The PA Grant Awards Activities dataset does not collect, maintain, use, or disseminate any Personally Identifiable Information (PII).rnrnAs part of Congressional bill HR 152 - the Sandy Recovery Improvement Act of 2013, FEMA is providing the following information for our stakeholders:rn• Regionrn• Disaster Declaration Numberrn• Disaster Typern• Statern• Applicantrn• Countyrn• Damage Category Codern• Federal Share Obligatedrn• Date ObligatedrnrnFEMA obligates funding for a project directly to the Recipient (State or Tribe). It is the Recipient's responsibility to ensure that the eligible subrecipient (listed in the dataset as Applicant Name) receives the award funding.rnThis dataset lists details about project versions. Versions occur when the scope/cost changes for a project. Versions adjust the cost of the project with positive additions called obligations and subtractions called deobligations. Combined, they reconcile to reflect the Total Federal Share Obligation, but reconciliation occurs over the life of the project, sometimes years after the declaration date. The dataset represents project obligations within a seven-day period prior to the listed date but does not include obligations uploaded on the same day as the publication. Open projects still under pre-obligation processing are not represented.rnFor more information on the Public Assistance process see: https://www.fema.gov/assistance/public/process.rnThis is raw, unedited data from FEMA's Emergency Management Mission Integrated Environment (EMMIE) system and as such is subject to a small percentage of human error. The financial information is derived from EMMIE and not FEMA's official financial systems. Due to differences in reporting periods, status of obligations and application of business rules, this financial information may differ slightly from official publication on public websites such as usaspending.gov. This dataset is not intended to be used for any official federal reporting.rnIf you have media inquiries about this dataset, please email the FEMA News Desk at FEMA-News-Desk@fema.dhs.gov or call (202) 646-3272. For inquiries about FEMA's data and Open Government program, please email the OpenFEMA team at OpenFEMA@fema.dhs.gov.

Flooding is among the most common and costly natural disasters in the United States. Flood impacts have been on the rise as flood mitigating habitats are lost, development places more people and infrastructure potentially at risk, and changing rainfall results in altered flood frequency. Across the nation, communities are recognizing the value of flood mitigating habitats and employing green infrastructure alternatives, including restoring some of those ecosystems, as a way to increase resilience. However, communities may under value green infrastructure, because they do not recognize the current benefits of risk reduction they receive from existing ecosystems or the potential benefits they could receive through restoration. Freshwater wetlands have long been recognized as one of the ecosystems that can reduce flood damages by attenuating surface water. Small-scale community studies can capture the flood-reduction benefits from existing or potentially restored wetlands. However, scalability and transferability are limits for these high resolution and data intensive studies. This paper details the development of a nationally consistent dataset and a set of high-resolution indicators characterizing where people benefit from reduced flood risk through existing wetlands. We demonstrate how this dataset can be used at different scales (regional or local) to rapidly assess flood-reduction benefits. At a local scale we use other national scale indicators (CRSI, SoVI) to gauge community resilience and recoverability to choose Harris County, Texas as our focus. Analysis of the Gulf Coast region and Harris County, Texas identifies communities with both wetland restoration potential and the greatest flood-prone population that could benefit from that restoration. We show how maps of these indicators can be used to set wetland protection and restoration priorities.

Natural disasters such as hurricanes, cyclones, and tropical depressions cause average annual direct losses of US$284 million in the Pacific. With a combined population of fewer than 10 million people, annual losses are the highest in the world on a per-capita basis. Extreme weather events such as heavy rainfall are closely linked to climate change, suggesting that Pacific Island nations face increasing risk of disasters such as flooding and landslides. Proactive management through infrastructure development, social solutions, and/or ecosystem-based adaptation can mitigate these risks. However, there are a paucity of data pertaining to the costs, effectiveness, and feasibility of most management options. In the wake of two major flood events and a cyclone occurring between January and December 2012, we conducted a state-of-the-science assessment of disaster risk reduction for flooding in the Ba and Penang River catchments in Viti Levu, Fiji to identify the most cost-effective management options for communities and households (Figure E1). The analysis accounted for the biophysical and socioeconomic impacts of flooding, the costs, benefits, and feasibility of management, and the potential impacts of climate change.copy of pdf for uploadingCall Number: [EL]

This dataset contains important categories (per an extensive literature review) in relation to vulnerability to water hazards within Utah at the County level. Although social and physical vulnerability to water hazards (i.e. flooding) data has been collected extensively in many coastal areas, this is a costly problem in Utah and many other non-coastal areas. The variables shown here are categorized by type and collection method. 1. General data is shown for all Counties in Utah. These are taken from the 2010 Census. 2. Literature suggests that there are various approaches which local governments take to mitigate the impacts of flood events. Indicators of these approaches are captured in the section entitled Web Survey. A web survey was conducted of each County. The data includes evaluations of content including water hazard education, land use restrictions described in the code, freeboard requirements, and emergency operations plan implementations. 3. A social vulnerability index as created by the University of South Carolina is shown here. More information can be found at their website. 4. Event data is summarized for number of events and estimated monetary damages. This NOAA dataset helps us understand the nature of past experience and physical exposure to water hazards. Utah's Hazard Mitigation Plan 2014 includes a flood vulnerability score. It is included here for reference but is not critiqued as part of this dataset. 5. Fema has modeling software known as HAZUS which can be used to estimate damages for certain hazards including flooding. A county level summary is included here with estimated of building damage and exposure. 6. Dams are a man-made structure which play a part on flood management and can also create additional exposure. 7. Much of social vulnerability and disaster management should consider those with special needs. Census and the Division of Hazard Mitigation of Utah help us understand more of this important context.

Together these data paint a picture of Utah's vulnerabilities to flood hazards and potential exposure to other natural hazard events. Place level statistics were also collected and add insight at that spatial scale. they can be found here: http://repository.iutahepscor.org/dataset/hazard-mitigation-and-capacity-in-utah-census-places. The variables are different as prescribed in the readme file there.

Further details of the data collection methods can be found in the data dictionary within the spreadsheet workbook or in the ReadMe file included as a resource here.

Economic damage from natural hazards can sometimes be prevented and always mitigated. However, private individuals tend to underinvest in such measures due to problems of collective action, information asymmetry and myopic behavior. Governments, which can in principle correct these market failures, themselves face incentives to underinvest in costly disaster prevention policies and damage mitigation regulations. Yet, disaster damage varies greatly across countries. We argue that rational actors will invest more in trying to prevent and mitigate damage the larger a country’s propensity to experience frequent and strong natural hazards. Accordingly, economic loss from an actually occurring disaster will be smaller the larger a country’s disaster propensity – holding everything else equal, such as hazard magnitude, the country’s total wealth and per capita income. At the same time, damage is not entirely preventable and smaller losses tend to be random. Disaster propensity will therefore have a larger marginal effect on larger predicted damages than on smaller ones. We employ quantile regression analysis in a global sample to test these predictions, focusing on the three disaster types causing the vast majority of damage worldwide: earthquakes, floods and tropical cyclones.

This database contains summary information on 168 Canadian flood disasters that occurred between 1900 and June 1997. The database is not, by sany means, a complete list of flood events in Canada since the vast majority of the floods did not cause disasters. All mentions of damage costs have not been corrected for inflation. The database also is biased towards the more densely populated areas of Canada where floods are more likely to impact humans.

Emergency Department Visit Rate Due To Asthma - This indicator shows the rate of emergency department visits due to asthma per 10,000 population. Asthma is a chronic health condition which causes very serious breathing problems. When properly controlled through close outpatient medical supervision, individuals and families can manage their asthma without costly emergency intervention. In Maryland, there are nearly 50,000 emergency department visit related to asthma each year.

The rates on this Schedule of Equipment Rates are for applicant-owned equipment in good mechanical condition, complete with all required attachments. Each rate covers all costs eligible under the Robert T. Stafford Disaster Relief and Emergency Assistance Act, 42 U.S.C. § 5121, et seq., for ownership and operation of equipment, including depreciation, overhead, all maintenance, field repairs, fuel, lubricants, tires, OSHA equipment and other costs incidental to operation. Standby equipment costs are not eligible.rnrnEquipment must be in actual operation performing eligible work in order for reimbursement to be eligible. Labor costs of the operator are not included in the rates and should be approved separately from equipment costs.rnrnInformation regarding the use of the Schedule is contained in 44 CFR § 206.228 Allowable Costs. Rates for equipment not listed will be furnished by FEMA upon request. Any appeals shall be in accordance with 44 CFR § 206.206 Appeals.

Building more in-house datacenters to backup explosively growing scientific datasets is neither cost-effective nor in line with government green initiative. Cloud computing is emerging as a viable platform for data storage, collaboration and disaster recovery. We are going to develop a suite of "backup-to-cloud" tools that allows user to backup scientific datasets and applications into the cloud, and use cloud storage as a distribution platform. Our tool is optimized under technical and economical constraints posed by common cloud storage. We use both public and private cloud platforms to conduct feasibility study from performance, security, scalability and cost perspectives.

This dataset was developed by the Missouri Department of Health and Senior Services. End-Stage Renal Disease facilities are facilities that provide dialysis care to individuals in kidney failure.The Medicare End Stage Renal Disease (ESRD) Program is a national health insurance program for people with ESRD. The program is designed to encourage self-care dialysis and kidney transplantation and clarify reimbursement procedures to achieve effective cost control.Most ESRD’s are certified and approved to participate in the federal Medicare program by application and adherence to federal standards.DHSS through an agreement with the Centers for Medicare and Medicaid (CMS), performs initial and periodic surveys, and conducts complaint investigations in regard to patient care provided in ESRD’s. March 2020 Update.