Floods are part of the natural hydrological cycle (the seasonal fluctuation of water levels) and occur along rivers and streams somewhere in Canada every year. Flooding is a common natural hazard that has caused 260 known disasters since 1900, resulting in the loss of 235 lives and 8.7 billion dollars in damage. This map depicts 260 flood disaster events from 1902 - 2005.

Weather Disaster Costs and Deaths

Costs and Deaths of Billion Dollar Weather Disasters in the US

By Throwback Thursday [source]

About this dataset

The Billion Dollar Weather Disasters in the US dataset is a valuable resource containing comprehensive historical data on weather events in the United States that have caused billions of dollars in damages and resulted in loss of lives. It provides insights into various types and categories of weather disasters, such as hurricanes, tornadoes, floods, wildfires, and more.

The dataset includes essential information about each weather disaster event, starting with its name or title referred to as Disaster. A brief summary or description of each event is provided under the column Description, giving readers an understanding of its impact and extent. Furthermore, the dataset categorizes each disaster based on its type under the column Disaster Type. This classification helps researchers and analysts to identify patterns or common characteristics among similar types of weather disasters.

One crucial aspect covered by this dataset is the economic impact of these severe weather events. The total cost incurred due to each catastrophic occurrence has been meticulously recorded in millions of dollars. To ensure accuracy across different time periods, these costs are adjusted for inflation using the Consumer Price Index (CPI), providing a standardized measure that enables meaningful comparisons between different events.

A significant measure reflecting the severity of these weather disasters is the number of deaths they have caused. This dataset presents this valuable statistic under the column Deaths, allowing researchers to assess not only economic implications but also human impacts associated with each disaster event.

Obtained from NOAA National Centers for Environmental Information (NCEI) U.S., this data serves as a reliable source for understanding past weather calamities within US borders. Its wide range includes devastating storms, destructive wildfires, deadly heatwaves, crippling droughts; all contributing to one overarching objective – better preparedness for future climate-related challenges.

By analyzing this comprehensive dataset, researchers can gain insights into trends over time while identifying regions most vulnerable to specific types of extreme weather events. These findings allow policymakers and emergency response planners to make informed decisions regarding resource allocation, risk mitigation strategies, and community resilience-building initiatives

How to use the dataset

1. Understanding the Columns

The dataset contains several columns that provide important information about each weather disaster event. Let's understand what each column represents:

• Disaster: The name or title of the weather disaster event.
• Disaster Type: The type or category of the weather disaster event.
• Total CPI-Adjusted Cost (Millions of Dollars): The total cost of the weather disaster event in millions of dollars, adjusted for inflation using the Consumer Price Index (CPI).
• Deaths: The number of deaths caused by the weather disaster event.
• Description: A brief description or summary of the weather disaster event.

2. Exploring Total Cost and Deaths

One key aspect to explore is how much damage was caused by each weather disaster event, as well as its human impact in terms of fatalities. By analyzing these factors, you can gain insights into which types of disasters are more costly and have a higher mortality rate.

You can start by visualizing the Total CPI-Adjusted Cost (Millions of Dollars) column to identify which disasters have been more financially devastating over time. Additionally, you can analyze the Deaths column to gauge which types of disasters have had a greater impact on human lives.

3. Comparing Disasters

Another interesting analysis would involve comparing different disasters based on their characteristics such as type, cost, and fatalities. You can group similar types together and compare their costs or death tolls across different time periods.

For example, you could examine whether hurricanes tend to cause higher financial losses compared to floods or wildfires. Or, you could analyze if certain types of disasters have been more deadly than others.

4. Analyzing Descriptions

The Description column provides a brief summary of each weather disaster event. Analyzing the descriptions can give you valuable insights into the specific circumstances surrounding each event. By understanding the context and conditions, you can get a better understanding of why some events resulted i...

Abstract: This data shows the model nodes, indicating water level only and/or flow and water levels along the centre-line of rivers that have been modelled to generate the CFRAM flood maps. The nodes estimate maximum design event flood flows and maximum flood levels. Flood event probabilities are referred to in terms of a percentage Annual Exceedance Probability, or ‘AEP’. This represents the probability of an event of this, or greater, severity occurring in any given year. These probabilities may also be expressed as odds (e.g. 100 to 1) of the event occurring in any given year. They are also commonly referred to in terms of a return period (e.g. the 100-year flood), although this period is not the length of time that will elapse between two such events occurring, as, although unlikely, two very severe events may occur within a short space of time. The following sets out a range of flood event probabilities for which fluvial and coastal flood maps are typically developed, expressed in terms of Annual Exceedance Probability (AEP), and identifies their parallels under other forms of expression: 10% (High Probability) Annual Exceedance Probability which can also be expressed as the 10 Year Return Period and as a 10:1 odds of occurrence in any given year. 1% (Medium Probability - Fluvail/River Flood Maps) Annual Exceedance Probability which can also be expressed as the 100 Year Return Period and as 100:1 odds of occurrence in any given year. 0.5% (Medium Probability - Coastal Flood Maps) Annual Exceedance Probability which can also be expressed as the 200 Year Return Period and as 200:1 odds of occurrence in any given year. 0.1% (Low Probability) Annual Exceedance Probability which can also be expressed as the 1000 Year Return Period and as 1000:1 odds of occurrence in any given year. The Mid-Range Future Scenario extents where generated taking in in the potential effects of climate change using an increase in rainfall of 20% and sea level rise of 500mm (20 inches). Data has been produced for the 'Areas of Further Assessment' (AFAs), as required by the EU 'Floods' Directive [2007/60/EC] and designated under the Preliminary Flood Risk Assessment, and also for other reaches between the AFAs and down to the sea that are referred to as 'Medium Priority Watercourses' (MPWs). River reaches that have been modelled are indicated by the CFRAM Modelled River Centrelines dataset. Flooding from other reaches of river may occur, but has not been mapped, and so areas that are not shown as being within a flood extent may therefore be at risk of flooding from unmodelled rivers (as well as from other sources). The purpose of the Flood Maps is not to designate individual properties at risk of flooding. They are community-based maps. Lineage: Fluvial and coastal flood map data is developed using hydrodynamic modelling, based on calculated design river flows and extreme sea levels, surveyed channel cross-sections, in-bank / bank-side / coastal structures, Digital Terrain Models, and other relevant datasets (e.g. land use, data on past floods for model calibration, etc.). The process may vary for particular areas or maps. Technical Hydrology and Hydraulics Reports set out full technical details on the derivation of the flood maps. For fluvial flood levels, calibration and verification of the models make use of the best available data, including hydrometric records, photographs, videos, press articles and anecdotal information. Subject to the availability of suitable calibration data, models are verified in so far as possible to target vertical water level accuracies of approximately +/-0.2m for areas within the AFAs, and approximately +/-0.4m along the MPWs. For coastal flood levels, the accuracy of the predicted annual exceedance probability (AEP) of combined tide and surge levels depends on the accuracy of the various components used in deriving these levels i.e. accuracy of the tidal and surge model, the accuracy of the statistical data and the accuracy for the conversion from marine datum to land levelling datum. The output of the water level modelling, combined with the extreme value analysis undertaken as detailed above is generally within +/-0.2m for confidence limits of 95% at the 0.1% AEP. Higher probability (lower return period) events are expected to have tighter confidence limits. v101 (March 2025) The section of map near Oranmore Galway updated following a map review process see https://www.floodinfo.ie/map-review/ for further information, Map Review Code: MR019. v102 (July 2025) The section of map near Claregalway updated following a map review process see https://www.floodinfo.ie/map-review/ for further information, Map Review Code: MR057. Purpose: The data has been developed to comply with the requirements of the European Communities (Assessment and Management of Flood Risks) Regulations 2010 to 2015 (the “Regulations”) (implementing Directive 2007/60/EC) for the purposes of establishing a framework for the assessment and management of flood risks, aiming at the reduction of adverse consequences for human health, the environment, cultural heritage and economic activity associated with floods. .hidden { display: none }

Introduction

Vietnam’s geographic location and topography make it particularly susceptible to a wide range of disasters, both natural and technological.

This dataset provides data as uploaded, on the occurrence and impacts of mass disasters in Vietnam from 1953 to 2024. This includes both natural (biological, climatological, extra-terrestrial, geophysical, hydrological, meteorological), and technological (industrial accident) disasters. Data was extracted from The International Disaster Database (EM-DAT), maintained by the Centre for Research on the Epidemiology of Disasters (CRED), published by Open Development Vietnam.

It documents natural and human-related disasters in Vietnam from 1953 onward, with key fields related to: - Disaster types and sub types (e.g., storm, flood, drought, epidemic). - Start and end dates. - Human impact (deaths, injuries, people affected). - Economic damage (where data is available). - Geo-location and metadata (latitude/longitude, region, event name).

How Vietnam has changed since 1953, with a focus on climate change-driven disasters:

• Storms (including tropical cyclones).
• Floods.
• Droughts.

We explore long-term trends, decadal comparisons, regional distribution, and statistical correlations to understand Vietnam’s evolving climate vulnerability. The aim is to uncover data-driven insights that inform climate adaptation, disaster risk management, and sustainable development planning.

Recommended Reading

Saline Intrusion in the Mekong Delta (2021-2022). Part 1: The devastating effects of climate change; Mekong and Bengal Deltas. link - Kaggle

Rainfall & Temperature: Vietnam from 1901 to 2020. Part 3: The devastating effects of climate change; monsoon pattern changes. link - Kaggle

Trend Overview by Decade: vietnam_climate_disaster_trend_by_decade.csv

A markdown document with the R code for all the below visualisations. link

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F13231939%2F2808eacb7fa88dbb013546f248fe9e27%2FScreenshot%202025-06-15%2010.55.26.png?generation=1749983744158969&alt=media" alt="">

Bar Chart: - Description: - This chart presents normalised values of four metrics; Event Count, Total Affected, Total Damage Adjusted, and Total Deaths. Aggregated by decade from the 1950's to the 2020's. The normalisation allows comparison across different scales.
- Observations: - The 2000's show the highest Event Count, indicating a peak in disaster frequency. - The 1960's had a significant Total Death component. In November 1964, the quick succession of three typhoons (Iris, Joan, and Kate), caused widespread flooding in Vietnam causing 7,000 deaths, as confirmed by dataset analysis. link - Wikipedia: November 1964 Vietnam floods - Total Affected and Total Damage Adjusted peak in the 1990's and 2000's, suggesting increased vulnerability or severity during these periods. - Insights: - This visualisation highlights temporal shifts in disaster impacts, with the 1960's notable for high mortality and the 2000's for frequency, reflecting historical disaster patterns. However, the 1964 Pacific typhoon season was the most active tropical cyclone season recorded globally, with a total of 39 tropical storms forming. It had no official bounds; it ran year-round in 1964, but most tropical cyclones tend to form in the northwestern Pacific Ocean between June and December. The unprecedented and extended tropical storm season of 1964, accounted for the large amount of deaths by disasters, during the 1960's in Vietnam.

*2020s data is partial

Summary

• Rising Disaster Frequency:
  • Climate-related disasters have increased sharply since the 1980's, particularly storms and floods.
  • From just 2 recorded events in the 195...

Flood event probabilities are referred to in terms of a percentage Annual Exceedance Probability, or ‘AEP’. This represents the probability of an event of this, or greater, severity occurring in any given year. These probabilities may also be expressed as odds (e.g. 100 to 1) of the event occurring in any given year. They are also commonly referred to in terms of a return period (e.g. the 100-year flood), although this period is not the length of time that will elapse between two such events occurring, as, although unlikely, two very severe events may occur within a short space of time. The following sets out a range of flood event probabilities for which fluvial and coastal flood maps are typically developed; 5% Annual Exceedance Probability which can also be expressed as the 20 Year Return Period and as 20:1 odds of occurrence in any given year. 1% (Medium Probability) Annual Exceedance Probability which can also be expressed as the 100 Year Return Period and as 100:1 odds of occurrence in any given year. 0.1% (Low Probability) Annual Exceedance Probability which can also be expressed as the 1000 Year Return Period and as 1000:1 odds of occurrence in any given year. The Mid-Range Future Scenario extents where generated taking in the potential effects of climate change using an increase in rainfall of 20%. Data has been produced for catchments greater than 5km2 in areas for which flood maps were not produced under the National CFRAM Programme and should be read in this context. River reaches that have been modelled are indicated by the NIFM Modelled River Centrelines dataset. Flooding from other reaches of river may occur, but has not been mapped, and so areas that are not shown as being within a flood extent may therefore be at risk of flooding from unmodelled rivers (as well as from other sources). The purpose of the Flood Maps is not to designate individual properties or point locations at risk of flooding, or to replace a detailed site-specific flood risk assessment. Purpose: The data has been developed to inform a national assessment of flood risk that in turn will inform a review of the Preliminary Flood Risk Assessment required to comply with the requirements of the European Communities (Assessment and Management of Flood Risks) Regulations 2010 to 2015 (the “Regulations”) (implementing Directive 2007/60/EC) for the purposes of establishing a framework for the assessment and management of flood risks, aiming at the reduction of adverse consequences for human health, the environment, cultural heritage and economic activity associated with floods. .hidden { display: none }

A map service depicting modeled flow metrics in the United States for historical and future climate change scenarios: the percent change in modeled streamflow metrics between the historical (1977-2006) and end-of-century (2070-2099) time periods. In addition to standard NHD attributes, the streamflow datasets include metrics on mean daily flow (annual and seasonal), flood levels associated with 1.5-year, 10-year, and 25-year floods; annual and decadal minimum weekly flows and date of minimum weekly flow, center of flow mass date; baseflow index, and average number of winter floods. These files and additional information are available on the project website, https://www.fs.usda.gov/rm/boise/AWAE/projects/modeled_stream_flow_metrics.shtml. Streams without flow metrics (null values) were removed from this dataset to improve display speed; to see all stream lines, use an NHD flowline dataset.The flow regime is of fundamental importance in determining the physical and ecological characteristics of a river or stream, but actual flow measurements are only available for a small minority of stream segments, mostly on large rivers. Flows for all other streams must be extrapolated or modeled. Modeling is also necessary to estimate flow regimes under future climate conditions. Climate data such as this dataset is valuable for planning and monitoring purposes. Business use cases include: climate change and water rights assessments; analysis of water availability, runoff, groundwater, and impacts to aquatic organisms; resource management; post fire recovery; restoration activities, etc.Hydro flow metrics data can be downloaded from here.This feature layer contains a series of fields from the NHD, including the COMID, which provides a unique identifier for each NHD stream segment, as well as other basic hydrological information. It also contains the Region field, which indicates the NHD region (2-digit hydrologic unit codes) or a subdivision of regions based on NHDPlus production units (https://www.horizon-systems.com/NHDPlus/). Production units are designated by letters appended to the region code, such as 10U (the upper Missouri River basin).Additional documentation about this dataset is located in the data user guide. A StoryMap including a map viewer and map exporter by forest/region is also available. Additional climate and streamflow products from the Office of Sustainability and Climate are available in our Climate Gallery.This dataset contains the following data layers:Mean annual flow: calculated as the mean of the yearly discharge valuesMean spring flow: calculated as the mean of the March/April/May discharge values, weighted by the number of days per monthMean summer flow: calculated as the mean of the June/July/August discharge values, weighted by the number of days per monthMean autumn flow: calculated as the mean of the September/October/November discharge values, weighted by the number of days per monthMean winter flow: calculated as the mean of the December/January/February discharge values, weighted by the number of days per month1.5-year flood: calculated by first finding the greatest daily flow from each year; the 33rd percentile of the annual maximum series defines the flow that occurs every 1.5 years, on average10-year flood: the flow that occurs every 10 years, on average, calculated as the 90th percentile of the annual maximum series25-year flood: the flow that occurs every 25 years, on average, calculated as the 96th percentile of the annual maximum series1-year minimum weekly flow: the average across years of the lowest 7-day flow during each year. Year is defined either as January/December or June/May, whichever has a lower standard deviation in the date of the low-flow week. This was done so that, for example, in areas with winter droughts, a December to January drought would not be split up by the start of a new year.10-year minimum weekly flow: average lowest 7-day flow during a decade (calculated as the 10th percentile of the annual minimum weekly flows)

Abstract: This data shows the modelled extent of land that might be flooded by the sea (coastal flooding) during a theoretical or ‘design’ flood event with an estimated probability of occurrence, rather than information for actual floods that have occurred in the past. The extents have been developed taking account of effective flood defences.

Flood event probabilities are referred to in terms of a percentage Annual Exceedance Probability, or ‘AEP’. This represents the probability of an event of this, or greater, severity occurring in any given year. These probabilities may also be expressed as odds (e.g. 100 to 1) of the event occurring in any given year. They are also commonly referred to in terms of a return period (e.g. the 100-year flood), although this period is not the length of time that will elapse between two such events occurring, as, although unlikely, two very severe events may occur within a short space of time.

The following sets out a range of flood event probabilities for which fluvial and coastal flood maps are typically developed, expressed in terms of Annual Exceedance Probability (AEP), and identifies their parallels under other forms of expression: 10% (High Probability) Annual Exceedance Probability which can also be expressed as the 10 Year Return Period and as a 10:1 odds of occurrence in any given year. 1% (Medium Probability - Fluvial/River Flood Maps) Annual Exceedance Probability which can also be expressed as the 100 Year Return Period and as 100:1 odds of occurrence in any given year. 0.5% (Medium Probability - Coastal Flood Maps) Annual Exceedance Probability which can also be expressed as the 200 Year Return Period and as 200:1 odds of occurrence in any given year. 0.1% (Low Probability) Annual Exceedance Probability which can also be expressed as the 1000 Year Return Period and as 1000:1 odds of occurrence in any given year.

The Mid-Range Future Scenario extents where generated taking in in the potential effects of climate change using an increase in rainfall of 20% and sea level rise of 500mm (20 inches).

Data has been produced for the 'Areas of Further Assessment' (AFAs), as required by the EU 'Floods' Directive [2007/60/EC] and designated under the Preliminary Flood Risk Assessment, and also for other reaches between the AFAs and down to the sea that are referred to as 'Medium Priority Watercourses' (MPWs). River reaches that have been modelled are indicated by the CFRAM Modelled River Centrelines dataset.

Flooding from other reaches of river may occur, but has not been mapped, and so areas that are not shown as being within a flood extent may therefore be at risk of flooding from unmodelled rivers (as well as from other sources).

The purpose of the Flood Maps is not to designate individual properties at risk of flooding. They are community-based maps.

Lineage: Fluvial and coastal flood map data is developed using hydrodynamic modelling, based on calculated design river flows and extreme sea levels, surveyed channel cross-sections, in-bank / bank-side / coastal structures, Digital Terrain Models, and other relevant datasets (e.g. land use, data on past floods for model calibration, etc.).

The process may vary for particular areas or maps. Technical Hydrology and Hydraulics Reports set out full technical details on the derivation of the flood maps.

For coastal flood levels, the accuracy of the predicted annual exceedance probability (AEP) of combined tide and surge levels depends on the accuracy of the various components used in deriving these levels i.e. accuracy of the tidal and surge model, the accuracy of the statistical data and the accuracy for the conversion from marine datum to land levelling datum.

The output of the water level modelling, combined with the extreme value analysis undertaken as detailed above is generally within +/-0.2m for confidence limits of 95% at the 0.1% AEP. Higher probability (lower return period) events are expected to have tighter confidence limits.

Flood levels, depths and velocities are derived from the hydrodynamic models for the various event probabilities and scenarios. Flood extents are derived from the raster flood depth maps and vectorised to produce the final vector outputs.

v101 (March 2025) The section of map near Oranmore Galway updated following a map review process see https://www.floodinfo.ie/map-review/ for further information, Map Review Code: MR019.

Purpose: The data has been developed to comply with the requirements of the European Communities (Assessment and Management of Flood Risks) Regulations 2010 to 2015 (the “Regulations”) (implementing Directive 2007/60/EC) for the purposes of establishing a framework for the assessment and management of flood risks, aiming at the reduction of adverse consequences for human health, the environment, cultural heritage and economic activity associated with floods.

The Flood Map for Planning Service includes several layers of information. This includes the Flood Zones plus climate change data which shows how the combined extent of Flood Zones 2 and 3 could increase with climate change over the next century, ignoring the benefits of any existing flood defences. We have assumed no changes to flood defences or land-use that could occur in future. The effects of climate change on flood risk we may see in the future could be different to those currently considered.

Flood Zones plus climate change should be used to help planners and developers identify the need for: • a site-specific flood risk assessment • the sequential test.

The dataset can also help to inform the preparation of strategic flood risk assessments.

The Flood Zones plus climate change are a composite dataset including national and local modelled data, and information from past floods.

The Flood Zones plus climate change are designed to only give an indication of flood risk to an area of land and are not suitable for showing whether an individual property is at risk of flooding. This is because we cannot know all the details about each property.

Flood Zones plus climate change uses the following climate change allowances: • ‘Central’ allowance for the 2080s epoch (2070-2125) for risk of flooding from rivers • ‘Upper End’ allowance for risk of flooding from the sea, accounting for cumulative sea level rise to 2125.

Users of these datasets should always check they are suitable for the intended use. Attribution statement: © Environment Agency copyright and/or database right 2025. All rights reserved.

The dataset of flood’s characteristics (annual and spring): the volume of spring flood (in mm of the depth of runoff), the dates of spring flood begin and end, the length of spring flooding period, the yearly maximum daily discharge and its date were estimated for each year from the daily series of water discharges observed at the hydrometric sites. To define the dates of spring flood begin and end we applied the semi-empirical method given in Shevnina (2013). The yearly maximum water discharges have been obtained in Gudmundsson et al. (2018) for the period until 2017; this dataset gives a good agreement in the estimations for the overlapping periods. The series of volume of spring flood (in mm of the depth of runoff), the dates of spring flood begin and end, the length of spring flooding period, the yearly maximum daily discharge and its date are given in the dataset supplementing the study submitted to the Water resource research journal (https://agupubs.onlinelibrary.wiley.com/journal/19447973 ).

The daily series of water river discharges at the sites located in Finland were extracted from (a) the Global runoff database https://portal.grdc.bafg.de/ (for the period from beginning of the observations to 2017); (b) the archive of the Finnish Environmental Institute https://www.syke.fi (for the period 2018–2020) and these series can be obtained after its representatives’ permission from the author. The daily series of water discharges at the sites located in the Russian Federation were extracted from (a) the yearly hydrological books published by the State Hydrological Institute http://www.hydrology.ru/en (for the period from the beginning of observation to 2007); (b) the automated information system for state monitoring of water bodies https://gmvo.skniivh.ru/ (for the period 2008–2020) and these series are available from its web-site after a registration.

The dataset consists of the CSV/TXT files, each file contains the long term series of the characteristics listed in the header: "year", "DFB" (date when a spring flooding period begins, day of year, DOY),"DFE" (date when the spring flooding period ends, DOY),"Length" (length of the spring flooding period, days), "DFMax" (date when the yearly maximum water discharge is recorded, DOY), "Qmax" (the yearly maximum water discharge, cubic m per second), "FRD" (the volume of spring flood expressed in mm per flooding period), "YRD" (volume of annual flow, expressed in mm per year),"Ftype" (the source of annual flood equaling to 1 of the yearly maximum water discharge is recorded in the spring flooding period or 0 if it is not).

The dataset was obtained in the study funded by the Academy of Finland under the contract number 317999. It will become freely available once the manuscript is published.

References

Gudmundsson, L., Do, H. X., Leonard, M., & Westra, S. (2018), The Global Streamflow Indices and Metadata Archive (GSIM) – Part 2: Quality control, time-series indices and homogeneity assessment, Earth Syst. Sci. Data, 10, 787–804, https://doi.org/10.5194/essd-10-787-2018.

Shevnina E. (2013), Method to calculate characteristics of spring flood from daily water discharges, Problems of the Arctic and Antarctic, 1(95), pp. 12-21. In Russian

Abstract: This data shows the modelled extent of land that might be flooded by rivers (fluvial flooding) during a theoretical or ‘design’ flood event with an estimated probability of occurrence, rather than information for actual floods that have occurred in the past. The extents have been developed taking account of effective flood defences.

Flood event probabilities are referred to in terms of a percentage Annual Exceedance Probability, or ‘AEP’. This represents the probability of an event of this, or greater, severity occurring in any given year. These probabilities may also be expressed as odds (e.g. 100 to 1) of the event occurring in any given year. They are also commonly referred to in terms of a return period (e.g. the 100-year flood), although this period is not the length of time that will elapse between two such events occurring, as, although unlikely, two very severe events may occur within a short space of time.

The following sets out a range of flood event probabilities for which fluvial and coastal flood maps are typically developed, expressed in terms of Annual Exceedance Probability (AEP), and identifies their parallels under other forms of expression: 10% (High Probability) Annual Exceedance Probability which can also be expressed as the 10 Year Return Period and as a 10:1 odds of occurrence in any given year. 1% (Medium Probability - Fluvial/River Flood Maps) Annual Exceedance Probability which can also be expressed as the 100 Year Return Period and as 100:1 odds of occurrence in any given year. 0.5% (Medium Probability - Coastal Flood Maps) Annual Exceedance Probability which can also be expressed as the 200 Year Return Period and as 200:1 odds of occurrence in any given year. 0.1% (Low Probability) Annual Exceedance Probability which can also be expressed as the 1000 Year Return Period and as 1000:1 odds of occurrence in any given year.

The Present Day Scenario is also referred to as the Current Scenario. Present Day Scenario data was generated using methodologies based on historic flood data, without taking account of potential changes due to climate change. The potential effects of climate change have been separately modelled and reported on.

Data has been produced for the 'Areas of Further Assessment' (AFAs), as required by the EU 'Floods' Directive [2007/60/EC] and designated under the Preliminary Flood Risk Assessment, and also for other reaches between the AFAs and down to the sea that are referred to as 'Medium Priority Watercourses' (MPWs). River reaches that have been modelled are indicated by the CFRAM Modelled River Centrelines dataset.

Flooding from other reaches of river may occur, but has not been mapped, and so areas that are not shown as being within a flood extent may therefore be at risk of flooding from unmodelled rivers (as well as from other sources).

The purpose of the Flood Maps is not to designate individual properties at risk of flooding. They are community-based maps.

Lineage: Fluvial and coastal flood map data is developed using hydrodynamic modelling, based on calculated design river flows and extreme sea levels, surveyed channel cross-sections, in-bank / bank-side / coastal structures, Digital Terrain Models, and other relevant datasets (e.g. land use, data on past floods for model calibration, etc.).

The process may vary for particular areas or maps. Technical Hydrology and Hydraulics Reports set out full technical details on the derivation of the flood maps.

For fluvial flood levels, calibration and verification of the models make use of the best available data, including hydrometric records, photographs, videos, press articles and anecdotal information. Subject to the availability of suitable calibration data, models are verified in so far as possible to target vertical water level accuracies of approximately +/-0.2m for areas within the AFAs, and approximately +/-0.4m along the MPWs.

All fluvial models are run, and maps produced, assuming clear flow through culverts and bridges, and the models and flood maps do not account for blockage of such structures.

Flood levels, depths and velocities are derived from the hydrodynamic models for the various event probabilities and scenarios. Flood extents are derived from the raster flood depth maps and vectorised to produce the final vector outputs.

v101 (March 2025) The section of map near Oranmore Galway updated following a map review process see https://www.floodinfo.ie/map-review/ for further information, Map Review Code: MR019.

v102 (July 2025)
The section of map near Claregalway updated following a map review process see https://www.floodinfo.ie/map-review/ for further information, Map Review Code: MR057.

Purpose: The data has been developed to comply with the requirements of the European Communities (Assessment and Management of Flood Risks) Regulations 2010 to 2015 (the “Regulations”) (implementing Directive 2007/60/EC) for the purposes of establishing a

This record is for Approval for Access (AfA) product AfA006. This dataset shows, flood defences protecting against river floods with a 1 per cent (1 in 100) chance of happening each year, or sea floods with a 0.5 per cent (1 in 200) chance of happening each year, together with some, but not all, defences which protect against smaller floods. Flood defences that are not yet shown, and the areas that benefit from them, will be gradually added.

Abstract: This data indicates the maximum estimated depth of river flooding (fluvial flooding) in meters (m) at a given location, for a flood event of a particular probability. The flood depths are calculated by subtracting the ground levels from the predicted water level. The flood depths are mapped as constant depths over grid squares of 5x5m, whereas in reality depths may vary within a given square.

Flood event probabilities are referred to in terms of a percentage Annual Exceedance Probability, or ‘AEP’. This represents the probability of an event of this, or greater, severity occurring in any given year. These probabilities may also be expressed as odds (e.g. 100 to 1) of the event occurring in any given year. They are also commonly referred to in terms of a return period (e.g. the 100-year flood), although this period is not the length of time that will elapse between two such events occurring, as, although unlikely, two very severe events may occur within a short space of time. The following sets out a range of flood event probabilities for which fluvial and coastal flood maps are typically developed;

5% Annual Exceedance Probability which can also be expressed as the 20 Year Return Period and as 20:1 odds of occurrence in any given year.

1% (Medium Probability) Annual Exceedance Probability which can also be expressed as the 100 Year Return Period and as 100:1 odds of occurrence in any given year.

0.1% (Low Probability) Annual Exceedance Probability which can also be expressed as the 1000 Year Return Period and as 1000:1 odds of occurrence in any given year.

The Mid-Range Future Scenario extents where generated taking in the potential effects of climate change using an increase in rainfall of 20%.

Data has been produced for catchments greater than 5km2 in areas for which flood maps were not produced under the National CFRAM Programme and should be read in this context. River reaches that have been modelled are indicated by the NIFM Modelled River Centrelines dataset.

Flooding from other reaches of river may occur, but has not been mapped, and so areas that are not shown as being within a flood extent may therefore be at risk of flooding from unmodelled rivers (as well as from other sources).

The purpose of the Flood Maps is not to designate individual properties or point locations at risk of flooding, or to replace a detailed site-specific flood risk assessment.

Lineage: The indicative fluvial flood maps were developed using hydrodynamic modelling, based on calculated design river flows, Digital Terrain Models, and other relevant datasets (e.g. land use, data on past floods, etc.).

The process may vary for particular areas or maps.

The National Indicative Fluvial Maps provide an indication of areas that may flood during a flood of an estimated probability of occurring. As detailed in the Technical Data, a number of assumptions have been made in order to produce a dataset suitable for national level flood risk assessments.

The National Indicative Fluvial Maps are not the best achievable representation of flood extents and they are not as accurate as the Flood Maps produced under the National Catchment Flood Risk Assessment and Management (CFRAM) Programme.

The maps should not be used to assess the flood risk associated with individual properties or point locations, or to replace a detailed site-specific flood risk assessment.

Flood levels and depths are derived from the hydrodynamic models for the various event probabilities and scenarios. Flood extents are derived from the raster flood depth maps and vectorised to produce the final vector outputs.

Purpose: The data has been developed to inform a national assessment of flood risk that in turn will inform a review of the Preliminary Flood Risk Assessment required to comply with the requirements of the European Communities (Assessment and Management of Flood Risks) Regulations 2010 to 2015 (the “Regulations”) (implementing Directive 2007/60/EC) for the purposes of establishing a framework for the assessment and management of flood risks, aiming at the reduction of adverse consequences for human health, the environment, cultural heritage and economic activity associated with floods.

Abstract: This data shows the modelled extent of land that might be flooded by the sea (coastal flooding) during a theoretical or ‘design’ flood event with an estimated probability of occurrence, rather than information for actual floods that have occurred in the past. The extents have been developed taking account of effective flood defences. Flood event probabilities are referred to in terms of a percentage Annual Exceedance Probability, or ‘AEP’. This represents the probability of an event of this, or greater, severity occurring in any given year. These probabilities may also be expressed as odds (e.g. 100 to 1) of the event occurring in any given year. They are also commonly referred to in terms of a return period (e.g. the 100-year flood), although this period is not the length of time that will elapse between two such events occurring, as, although unlikely, two very severe events may occur within a short space of time. The following sets out a range of flood event probabilities for which fluvial and coastal flood maps are typically developed, expressed in terms of Annual Exceedance Probability (AEP), and identifies their parallels under other forms of expression: 10% (High Probability) Annual Exceedance Probability which can also be expressed as the 10 Year Return Period and as a 10:1 odds of occurrence in any given year. 1% (Medium Probability - Fluvial/River Flood Maps) Annual Exceedance Probability which can also be expressed as the 100 Year Return Period and as 100:1 odds of occurrence in any given year. 0.5% (Medium Probability - Coastal Flood Maps) Annual Exceedance Probability which can also be expressed as the 200 Year Return Period and as 200:1 odds of occurrence in any given year. 0.1% (Low Probability) Annual Exceedance Probability which can also be expressed as the 1000 Year Return Period and as 1000:1 odds of occurrence in any given year. The High-End Future Scenario extents where generated taking in in the potential effects of climate change using an increase in rainfall of 30% and sea level rise of 1,000 mm (40 inches). Data has been produced for the 'Areas of Further Assessment' (AFAs), as required by the EU 'Floods' Directive [2007/60/EC] and designated under the Preliminary Flood Risk Assessment, and also for other reaches between the AFAs and down to the sea that are referred to as 'Medium Priority Watercourses' (MPWs). River reaches that have been modelled are indicated by the CFRAM Modelled River Centrelines dataset. Flooding from other reaches of river may occur, but has not been mapped, and so areas that are not shown as being within a flood extent may therefore be at risk of flooding from unmodelled rivers (as well as from other sources). The purpose of the Flood Maps is not to designate individual properties at risk of flooding. They are community-based maps. Lineage: Fluvial and coastal flood map data is developed using hydrodynamic modelling, based on calculated design river flows and extreme sea levels, surveyed channel cross-sections, in-bank / bank-side / coastal structures, Digital Terrain Models, and other relevant datasets (e.g. land use, data on past floods for model calibration, etc.). The process may vary for particular areas or maps. Technical Hydrology and Hydraulics Reports set out full technical details on the derivation of the flood maps. For coastal flood levels, the accuracy of the predicted annual exceedance probability (AEP) of combined tide and surge levels depends on the accuracy of the various components used in deriving these levels i.e. accuracy of the tidal and surge model, the accuracy of the statistical data and the accuracy for the conversion from marine datum to land levelling datum. The output of the water level modelling, combined with the extreme value analysis undertaken as detailed above is generally within +/-0.2m for confidence limits of 95% at the 0.1% AEP. Higher probability (lower return period) events are expected to have tighter confidence limits. Flood levels, depths and velocities are derived from the hydrodynamic models for the various event probabilities and scenarios. Flood extents are derived from the raster flood depth maps and vectorised to produce the final vector outputs. Purpose: The data has been developed to comply with the requirements of the European Communities (Assessment and Management of Flood Risks) Regulations 2010 to 2015 (the “Regulations”) (implementing Directive 2007/60/EC) for the purposes of establishing a framework for the assessment and management of flood risks, aiming at the reduction of adverse consequences for human health, the environment, cultural heritage and economic activity associated with floods.

Abstract:This data shows the modelled extent of land that might be flooded by rivers (fluvial flooding) during a theoretical or ‘design’ flood event with an estimated probability of occurrence, rather than information for actual floods that have occurred in the past. Flood event probabilities are referred to in terms of a percentage Annual Exceedance Probability, or ‘AEP’. This represents the probability of an event of this, or greater, severity occurring in any given year. These probabilities may also be expressed as odds (e.g. 100 to 1) of the event occurring in any given year. They are also commonly referred to in terms of a return period (e.g. the 100-year flood), although this period is not the length of time that will elapse between two such events occurring, as, although unlikely, two very severe events may occur within a short space of time. The following sets out a range of flood event probabilities for which fluvial and coastal flood maps are typically developed; 5% Annual Exceedance Probability which can also be expressed as the 20 Year Return Period and as 20:1 odds of occurrence in any given year. 1% (Medium Probability) Annual Exceedance Probability which can also be expressed as the 100 Year Return Period and as 100:1 odds of occurrence in any given year. 0.1% (Low Probability) Annual Exceedance Probability which can also be expressed as the 1000 Year Return Period and as 1000:1 odds of occurrence in any given year. The Mid-Range Future Scenario extents where generated taking in the potential effects of climate change using an increase in rainfall of 20%. Data has been produced for catchments greater than 5km2 in areas for which flood maps were not produced under the National CFRAM Programme and should be read in this context. River reaches that have been modelled are indicated by the NIFM Modelled River Centrelines dataset. Flooding from other reaches of river may occur, but has not been mapped, and so areas that are not shown as being within a flood extent may therefore be at risk of flooding from unmodelled rivers (as well as from other sources). The purpose of the Flood Maps is not to designate individual properties or point locations at risk of flooding, or to replace a detailed site-specific flood risk assessment. Purpose: The data has been developed to inform a national assessment of flood risk that in turn will inform a review of the Preliminary Flood Risk Assessment required to comply with the requirements of the European Communities (Assessment and Management of Flood Risks) Regulations 2010 to 2015 (the “Regulations”) (implementing Directive 2007/60/EC) for the purposes of establishing a framework for the assessment and management of flood risks, aiming at the reduction of adverse consequences for human health, the environment, cultural heritage and economic activity associated with floods.

Historically, low-lying land adjacent to rivers and coastlines has been favoured for settlement as they provided sources of fresh water, food, transportation and waste disposal. These areas become affected by flooding during sufficiently heavy or prolonged rainfall, high tides or storm surges and cyclones. In the north-west of the State flooding is most likely to be caused by the summer monsoon or tropical cyclones while floods in the south-west are more likely to occur in response to heavy winter rainfalls. While historical flood records and information extend as far back as 1830, detailed information on peak flood levels is typically limited to the last few decades. This dataset contains the available surveyed peak flood level information for major flood events that have occurred in Western Australia. The flood levels are referenced to the Australian Height Datum (AHD). Note: To see the full scope of the historical flood mapping, 3 dataset layers are required to be loaded in the following order: FLOODPLAIN DATASET LAYERS: FPM Historical Flood Levels (m AHD) FPM Historical Extent of Flooding FPM Historical Floodplain Area Major flood events that have occurred in the past include: Blackwood River (1945, 1955, 1963, 1964, 1982) Collie River (1945, 1963, 1964, 1974, 1982) Fitzroy River (1983, 1986, 1991, 1993, 2002, 2011) Gascoyne River (1960, 1961, 1980, 1995, 2000, 2010) Greenough River (1888, 1927, 1953, 1971, 1988, 1999, 2006) Moore River (1934, 1955, 1961, 1995, 1999) Murray River (1862, 1945, 1955, 1964) Preston River (1964, 1967, 1974, 1983, 1990, 2011) Swan River (1862, 1872, 1945, 1955, 1964, 1983) The historical flood information is used in the Department of Water and Environmental Regulation's floodplain management activities to ensure that floodplains are managed for the benefit of the whole community, minimising the risk and damages and protecting environmental values. Floodplain mapping datasets and floodplain development strategies for rivers and major watercourses in Western Australia are also available from the Department of Water and Environmental Regulation. Note: The ‘Event’ dates in the attribute table are derived from various sources, including Department of Water and Environmental Regulation's Floodplain Management Section reports, records and plans, historical newspaper articles, flood survey information, Bureau of Meteorology rainfall intensity records, on-site flood information and information provided by locals. It is not always possible to obtain an exact date when the flood event has occurred because in some cases the floodwaters may take several days to subside, peaking at different times at various locations over the course, or historical records may only refer to the month or year of the event. However, considering the above date variations the ‘Event’ dates are listed as follows: 22nd December 2010: The day, month and year of the flood event (or rainfall) are known. August 1963: The month and year are known. Exact date unknown. 1954: The year is known but the month and day are unknown. Glossary: Annual exceedance probability (AEP) - the likelihood of occurrence of a flood of a given size or larger in any one year; usually expressed as a percentage. 1 in 100 AEP flood - this means that there is a 1 in 100 (or 1%) chance of a flow of this size or larger occurring in any one year. This flood has a 50% chance of being experienced at least once in a person's lifetime. The 1 in 100 AEP flood has been generally adopted in Australia and overseas as the basis for floodplain management planning. Floodplain - the portion of a river valley next to the river channel which is covered with water when the river overflows its banks during major river flows. The term also applies to land adjacent to estuaries which is subject to flooding. Australian Height Datum (AHD) - is a geodetic datum for altitude measurement in Australia. It was adopted in 1971 by the National Mapping Council as the datum to which all vertical control for mapping is to be referred. The datum is based on the mean sea level (1966-1968) being assigned the value 0.000m on the Australian Height Datum (AHD) at 30 tide gauges around the coast of the Australian continent.

Abstract: This data shows the model nodes, indicating water level only and/or flow and water levels along the centre-line of rivers that have been modelled to generate the NIFM flood maps. The nodes estimate maximum design event flood flows and maximum flood levels.

Flood event probabilities are referred to in terms of a percentage Annual Exceedance Probability, or ‘AEP’. This represents the probability of an event of this, or greater, severity occurring in any given year. These probabilities may also be expressed as odds (e.g. 100 to 1) of the event occurring in any given year. They are also commonly referred to in terms of a return period (e.g. the 100-year flood), although this period is not the length of time that will elapse between two such events occurring, as, although unlikely, two very severe events may occur within a short space of time. The following sets out a range of flood event probabilities for which fluvial and coastal flood maps are typically developed;

5% Annual Exceedance Probability which can also be expressed as the 20 Year Return Period and as 20:1 odds of occurrence in any given year.

1% (Medium Probability) Annual Exceedance Probability which can also be expressed as the 100 Year Return Period and as 100:1 odds of occurrence in any given year.

0.1% (Low Probability) Annual Exceedance Probability which can also be expressed as the 1000 Year Return Period and as 1000:1 odds of occurrence in any given year.

The High-End Future Scenario extents where generated taking in the potential effects of climate change using an increase in rainfall of 30%.

Data has been produced for catchments greater than 5km2 in areas for which flood maps were not produced under the National CFRAM Programme and should be read in this context. River reaches that have been modelled are indicated by the NIFM Modelled River Centrelines dataset.

Flooding from other reaches of river may occur, but has not been mapped, and so areas that are not shown as being within a flood extent may therefore be at risk of flooding from unmodelled rivers (as well as from other sources).

The purpose of the Flood Maps is not to designate individual properties or point locations at risk of flooding, or to replace a detailed site-specific flood risk assessment.

Lineage: The indicative fluvial flood maps were developed using hydrodynamic modelling, based on calculated design river flows, Digital Terrain Models, and other relevant datasets (e.g. land use, data on past floods, etc.).

The process may vary for particular areas or maps.

The National Indicative Fluvial Maps provide an indication of areas that may flood during a flood of an estimated probability of occurring. As detailed in the Technical Data, a number of assumptions have been made in order to produce a dataset suitable for national level flood risk assessments.

The National Indicative Fluvial Maps are not the best achievable representation of flood extents and they are not as accurate as the Flood Maps produced under the National Catchment Flood Risk Assessment and Management (CFRAM) Programme.

The maps should not be used to assess the flood risk associated with individual properties or point locations, or to replace a detailed site-specific flood risk assessment.

Flood levels and depths are derived from the hydrodynamic models for the various event probabilities and scenarios. Flood extents are derived from the raster flood depth maps and vectorised to produce the final vector outputs.

Purpose: The data has been developed to inform a national assessment of flood risk that in turn will inform a review of the Preliminary Flood Risk Assessment required to comply with the requirements of the European Communities (Assessment and Management of Flood Risks) Regulations 2010 to 2015 (the “Regulations”) (implementing Directive 2007/60/EC) for the purposes of establishing a framework for the assessment and management of flood risks, aiming at the reduction of adverse consequences for human health, the environment, cultural heritage and economic activity associated with floods.

Abstract: This data shows the model nodes, indicating water level only and/or flow and water levels along the centre-line of rivers that have been modelled to generate the NIFM flood maps. The nodes estimate maximum design event flood flows and maximum flood levels.

Flood event probabilities are referred to in terms of a percentage Annual Exceedance Probability, or ‘AEP’. This represents the probability of an event of this, or greater, severity occurring in any given year. These probabilities may also be expressed as odds (e.g. 100 to 1) of the event occurring in any given year. They are also commonly referred to in terms of a return period (e.g. the 100-year flood), although this period is not the length of time that will elapse between two such events occurring, as, although unlikely, two very severe events may occur within a short space of time. The following sets out a range of flood event probabilities for which fluvial and coastal flood maps are typically developed;

5% Annual Exceedance Probability which can also be expressed as the 20 Year Return Period and as 20:1 odds of occurrence in any given year.

1% (Medium Probability) Annual Exceedance Probability which can also be expressed as the 100 Year Return Period and as 100:1 odds of occurrence in any given year.

0.1% (Low Probability) Annual Exceedance Probability which can also be expressed as the 1000 Year Return Period and as 1000:1 odds of occurrence in any given year.

The Mid-Range Future Scenario extents where generated taking in the potential effects of climate change using an increase in rainfall of 20%.

Data has been produced for catchments greater than 5km2 in areas for which flood maps were not produced under the National CFRAM Programme and should be read in this context. River reaches that have been modelled are indicated by the NIFM Modelled River Centrelines dataset.

Flooding from other reaches of river may occur, but has not been mapped, and so areas that are not shown as being within a flood extent may therefore be at risk of flooding from unmodelled rivers (as well as from other sources).

The purpose of the Flood Maps is not to designate individual properties or point locations at risk of flooding, or to replace a detailed site-specific flood risk assessment.

Lineage: The indicative fluvial flood maps were developed using hydrodynamic modelling, based on calculated design river flows, Digital Terrain Models, and other relevant datasets (e.g. land use, data on past floods, etc.).

The process may vary for particular areas or maps.

The National Indicative Fluvial Maps provide an indication of areas that may flood during a flood of an estimated probability of occurring. As detailed in the Technical Data, a number of assumptions have been made in order to produce a dataset suitable for national level flood risk assessments.

The National Indicative Fluvial Maps are not the best achievable representation of flood extents and they are not as accurate as the Flood Maps produced under the National Catchment Flood Risk Assessment and Management (CFRAM) Programme.

The maps should not be used to assess the flood risk associated with individual properties or point locations, or to replace a detailed site-specific flood risk assessment.

Flood levels and depths are derived from the hydrodynamic models for the various event probabilities and scenarios. Flood extents are derived from the raster flood depth maps and vectorised to produce the final vector outputs.

Purpose: The data has been developed to inform a national assessment of flood risk that in turn will inform a review of the Preliminary Flood Risk Assessment required to comply with the requirements of the European Communities (Assessment and Management of Flood Risks) Regulations 2010 to 2015 (the “Regulations”) (implementing Directive 2007/60/EC) for the purposes of establishing a framework for the assessment and management of flood risks, aiming at the reduction of adverse consequences for human health, the environment, cultural heritage and economic activity associated with floods.

Billions in real estate investmentsnear the coast are going to reprice.Coastal flooding is accelerating and coming to new locations. Some may be in your portfolio. Real estate values are already taking a hit – directly by flood damage and indirectly when insurance, roads and services are impacted and as the market becomes increasingly aware of this threat.Climate Central provides measures of coastal floodrisk for any place on earth.Give us the addresses of your investments near the coast. We'll forecast how many times your properties could flood each decade as the sea rises higher.Combine forecasted floods with value and you have a great start on understanding the new risks to your portfolio, balance sheet or community. Speak to a Climate Central analyst today.SPEAK TO AN ANALYST+1.609.986.1990also featured onClimate Central is a non-profitresearch organizationproviding authoritative science-based information products to help public and corporate stakeholders make sound decisions about climate and energy. Hundreds of thousands have used our tools including professionals in real estate, insurance, banking and government.ABOUT USOur analysts bring you top research to help you manage risk in a changing climate. We provide practical information you can use in your business, organization or community.WHAT WE DOGET IN TOUCHYou worked hard to build your portfolio.Don’t be surprised. Our analysis can shed light on your risk.Fill out the form below and find out how Climate Central can help you make informed decisions about your portfolio.SPEAK TO AN ANALYSTGet in touch with a Climate Centralanalyst today+1.609.986.1990© Climate Central. All rights reserved.+1.609.986.1990Speak to an analyst today.

Historically, low-lying land adjacent to rivers and coastlines has been favoured for settlement as they provided sources of fresh water, food, transportation and waste disposal. These areas become affected by flooding during sufficiently heavy or prolonged rainfall, high tides or storm surges and cyclones. In the north-west of the State flooding is most likely to be caused by the summer monsoon or tropical cyclones while floods in the south-west are more likely to occur in response to heavy winter rainfalls. While historical flood records and information extend as far back as 1830, detailed information on peak flood levels is typically limited to the last few decades. This dataset shows the extent of flooding (polylines) that has occurred during major flood events in Western Australia. Note: To see the full scope of the historical flood mapping, 3 dataset layers are required to be loaded in the following order: FLOODPLAIN DATASET LAYERS: FPM Historical Flood Levels (m AHD) FPM Historical Extent of Flooding FPM Historical Floodplain Area The major flood events that are covered in this dataset are: Bow Bridge Townsite (June 1988) Corrigin Townsite (January 1982) Esperance Townsite (January 2007) Kupungarri to Willare (including Dales Yard & Mount Joseph gauging stations) - Fitzroy River (January 2023) Lake Grace Townsite (January 2006) Merredin Townsite (February 1979) Perth (February 2017) Tambellup Townsite (January 1982) Warmun Aboriginal Community (March 2011) York Townsite (July 2021, August 2022) Other major flood events that have occurred in the past include: Blackwood River (1945, 1955, 1963, 1964, 1982) Collie River (1945, 1963, 1964, 1974, 1982) Fitzroy River (1983, 1986, 1991, 1993, 2002, 2011) Gascoyne River (1960, 1961, 1980, 1995, 2000, 2010) Greenough River (1888, 1927, 1953, 1971, 1988, 1999, 2006) Moore River (1934, 1955, 1961, 1995, 1999) Murray River (1862, 1945, 1955, 1964) Preston River (1964, 1967, 1974, 1983, 1990, 2011) Swan River (1862, 1872, 1945, 1955, 1964, 1983) The historical flood information is used in the Department of Water and Environmental Regulation's floodplain management activities to ensure that floodplains are managed for the benefit of the whole community, minimising the risk and damages and protecting environmental values. Floodplain mapping datasets and floodplain development strategies for rivers and major watercourses in Western Australia are also available from the Department of Water and Environmental Regulation. GLOSSARY: Annual exceedance probability (AEP) - the likelihood of occurrence of a flood of a given size or larger in any one year; usually expressed as a percentage. 1 in 100 AEP flood - this means that there is a 1 in 100 (or 1%) chance of a flow of this size or larger occurring in any one year. This flood has a 50% chance of being experienced at least once in a person's lifetime. The 1 in 100 AEP flood has been generally adopted in Australia and overseas as the basis for floodplain management planning. Floodplain - the portion of a river valley next to the river channel which is covered with water when the river overflows its banks during major river flows. The term also applies to land adjacent to estuaries which is subject to flooding. Australian Height Datum (AHD) - is a geodetic datum for altitude measurement in Australia. It was adopted in 1971 by the National Mapping Council as the datum to which all vertical control for mapping is to be referred. The datum is based on the mean sea level (1966-1968) being assigned the value 0.000m on the Australian Height Datum (AHD) at 30 tide gauges around the coast of the Australian continent.

A map service depicting modeled flow metrics in the United States for historical and future climate change scenarios: the percent change in modeled streamflow metrics between the historical (1977-2006) and mid-century (2030-2059) time periods. In addition to standard NHD attributes, the streamflow datasets include metrics on mean daily flow (annual and seasonal), flood levels associated with 1.5-year, 10-year, and 25-year floods; annual and decadal minimum weekly flows and date of minimum weekly flow, center of flow mass date; baseflow index, and average number of winter floods. These files and additional information are available on the project website, https://www.fs.usda.gov/rm/boise/AWAE/projects/modeled_stream_flow_metrics.shtml. Streams without flow metrics (null values) were removed from this dataset to improve display speed; to see all stream lines, use an NHD flowline dataset.The flow regime is of fundamental importance in determining the physical and ecological characteristics of a river or stream, but actual flow measurements are only available for a small minority of stream segments, mostly on large rivers. Flows for all other streams must be extrapolated or modeled. Modeling is also necessary to estimate flow regimes under future climate conditions. Climate data such as this dataset is valuable for planning and monitoring purposes. Business use cases include: climate change and water rights assessments; analysis of water availability, runoff, groundwater, and impacts to aquatic organisms; resource management; post fire recovery; restoration activities, etc.Hydro flow metrics data can be downloaded from here.This feature layer contains a series of fields from the NHD, including the COMID, which provides a unique identifier for each NHD stream segment, as well as other basic hydrological information. It also contains the Region field, which indicates the NHD region (2-digit hydrologic unit codes) or a subdivision of regions based on NHDPlus production units (https://www.horizon-systems.com/NHDPlus/). Production units are designated by letters appended to the region code, such as 10U (the upper Missouri River basin).Additional documentation about this dataset is located in the data user guide. A StoryMap including a map viewer and map exporter by forest/region is also available. Additional climate and streamflow products from the Office of Sustainability and Climate are available in our Climate Gallery.This dataset contains the following data layers:Mean annual flow: calculated as the mean of the yearly discharge valuesMean spring flow: calculated as the mean of the March/April/May discharge values, weighted by the number of days per monthMean summer flow: calculated as the mean of the June/July/August discharge values, weighted by the number of days per monthMean autumn flow: calculated as the mean of the September/October/November discharge values, weighted by the number of days per monthMean winter flow: calculated as the mean of the December/January/February discharge values, weighted by the number of days per month1.5-year flood: calculated by first finding the greatest daily flow from each year; the 33rd percentile of the annual maximum series defines the flow that occurs every 1.5 years, on average10-year flood: the flow that occurs every 10 years, on average, calculated as the 90th percentile of the annual maximum series25-year flood: the flow that occurs every 25 years, on average, calculated as the 96th percentile of the annual maximum series1-year minimum weekly flow: the average across years of the lowest 7-day flow during each year. Year is defined either as January/December or June/May, whichever has a lower standard deviation in the date of the low-flow week. This was done so that, for example, in areas with winter droughts, a December to January drought would not be split up by the start of a new year.10-year minimum weekly flow: average lowest 7-day flow during a decade (calculated as the 10th percentile of the annual minimum weekly flows)