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There is not 100% confidence in the elevation data and/or mapping process. It is important not to focus on the exact extent of inundation, but rather to examine the level of confidence that the extent of inundation is accurate (see mapping confidence tab).

The four relative sea level rise (RSL) scenarios shown in this tab are derived from the 2022 Sea Level Rise Technical Report using the same methods as the U.S. Army Corps of Engineers Sea Level Change Curve Calculator. These new scenarios were developed by the U.S. Sea Level Rise and Coastal Flood Hazard Scenarios and Tools Interagency Task Force as input into the U.S. Global Change Research Program Sustained Assessment process and, Fifth National Climate Assessment. These RSL scenarios provide an update to the NOAA 2017 scenarios, which were developed as input to the Fourth National Climate Assessment.

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Note: We do not show the low scenario, as it is a continuation of the current global trend since the early 1990s and has been determined to have a low probability of occurring by 2100. Furthermore, this scenario would be associated with low levels of risk even if it did occur.

Another important change from the 2017 scenarios is the exclusion of the extreme (2.5 meter) scenario. Based on the most recent scientific understanding, and as discussed in the IPCC AR6, the uncertain physical processes that could lead to much higher increases in sea level are now viewed as less plausible in the coming decades before potentially becoming a factor toward the end of the 21st century. A GMSL increase of 2.5 meters is thus viewed as less plausible and the associated scenario has been removed.

Blue areas denote a high confidence of inundation, orange areas denote a high degree of uncertainty, and unshaded areas denote a high confidence that these areas will be dry given the chosen water level.

In this application 80% is considered a high degree of confidence such that, for example, the blue areas denote locations that may be correctly mapped as 'inundated' more than 8 out of 10 times. Areas with a high degree of uncertainty represent locations that may be mapped correctly (either as inundated or dry) less than 8 out of 10 times. For a detailed description of the confidence levels and their computation, see the methods document.

Predictions represent the potential distribution of each wetland type (see legend) based on their elevation and how frequently they may be inundated under each scenario. As sea levels increase, some marshes may migrate into neighboring low-lying areas, while other sections of marsh will change type or be lost to open water.

Note: We do not show the low scenario as it is a continuation of the current global trend since the early 1990s and has been determined to have a low probability of occurring by 2100. Furthermore, this scenario would be associated with low levels of risk even if it did occur.

The Social Vulnerability Index, which shows areas of high human vulnerability to hazards, is based on population attributes from Census 2010 (e.g., age and poverty) and the built environment. By looking at the intersection of potential sea level rise and vulnerable Census tracts, one can get an idea of how vulnerable populations might be affected by sea level rise. Dark red indicates tracts having a high vulnerability, and the lighter reds indicate decreasing vulnerability.

The purpose of this map viewer is to provide federal, state, and local coastal resource managers and planners with a preliminary look at sea level rise and coastal flooding impacts. The viewer is a screening-level tool that uses best-available, nationally consistent data sets and analyses. Data and maps provided can be used at several scales to help estimate impacts and prioritize actions for different scenarios.

Row-level security (RLS) with Power BI can be used to restrict data access for given users. Filters restrict data access at the row level, and you can define filters within roles. In the Power BI service, users with access to a workspace have access to semantic models in that workspace. RLS only restricts data access for users with Viewer permissions. It doesn't apply to Admins, Members, or Contributors.

You can configure RLS for data models imported into Power BI with Power BI. You can also configure RLS on semantic models that are using DirectQuery, such as SQL Server. For Analysis Services or Azure Analysis Services lives connections, you configure row-level security in the model, not in Power BI. The security option doesn't show up for live connection semantic models.

By default, row-level security filtering uses single-directional filters, whether the relationships are set to single direction or bi-directional. You can manually enable bi-directional cross-filtering with row-level security by selecting the relationship and checking the Apply security filter in both directions checkbox. Note that if a table takes part in multiple bi-directional relationships you can only select this option for one of those relationships. Select this option when you've also implemented dynamic row-level security at the server level, where row-level security is based on username or login ID.

You can quickly and easily define row-level security roles and filters within Power BI using the enhanced row-level security editor. With this editor, you can toggle between using the default drop-down interface and a DAX interface. When you publish to Power BI, you also publish the role definitions.

Not all row-level security filters supported in Power BI can be defined using the default editor. Limitations include expressions that today can only be defined using DAX including dynamic rules such as username() or userprincipalname(). To define roles using these filters switch to use the DAX editor.

Question: Can I use RLS to limit the columns or measures accessible by my users?

Answer: No, if a user has access to a particular row of data, they can see all the columns of data for that row. To restrict access to columns and column metadata, consider using object-level security.

The establishment of the United Nations High-level Political Forum on Sustainable Development (HLPF) was mandated in 2012 by the outcome document of the United Nations Conference on Sustainable Development (Rio+20), "The Future We Want". The format and organizational aspects of the Forum are outlined in General Assembly resolution 67/290.

The Forum meets annually under the auspices of the Economic and Social Council for eight days, including a three-day ministerial segment and every four years at the level of Heads of State and Government under the auspices of the General Assembly for two days.

The HLPF is the main United Nations platform on sustainable development and it has a central role in the follow-up and review of the 2030 Agenda for Sustainable Development and the Sustainable Development Goals (SDGs) at the global level. General Assembly resolutions 70/299 and 75/290 B provide further guidance on the follow-up and review of the 2030 Agenda and the SDGs.

As stipulated in the 2030 Agenda for Sustainable Development, the HLPF has a central role in the follow-up and review of the 2030 Agenda and its 17 SDGs at the global level, working coherently with the General Assembly, the Economic and Social Council and other relevant organs and forums.

The HLPF also undertakes annual thematic reviews of the SDGs including cross-cutting issues. As decided in General Assembly resolution 75/290 B, for the remainder of the current cycle of the high-level political forum, the themes shall be:

For the remainder of the current cycle of the high-level political forum convened under the auspices of the Economic and Social Council, the sets of Sustainable Development Goals to be reviewed in-depth shall be:

For further information please see General Assembly resolution 67/290 on the format and organizational aspects of the Forum and resolution 70/299 on the follow-up and review of the 2030 Agenda for Sustainable Development at the global level.

On the High-level Political Forum on Sustainable Development (HLPF), the General Assembly decided in 2016 in its resolution 70/299 to review progress in implementing resolution 70/299 and resolution 67/290 on the format and organizational aspects of the HLPF at its 74th session. The review was to benefit from lessons learned in the first four-year cycle of the forum, including the SDG Summit in September 2019, as well as from other processes under the GA and ECOSOC related to the follow-up and review of the implementation of the 2030 Agenda for Sustainable Development.

The General Assembly then adopted, in August 2020, resolution 74/298 on the review of the implementation of General Assembly resolution 67/290 on the high-level political forum on sustainable development, resolution 70/299 on the follow-up and review of the 2030 Agenda for Sustainable Development at the global level and resolution 72/305 on the strengthening of the Economic and Social Council. Due to the limits to the negotiation process resulting from the COVID-19 pandemic. The resolution deferred much of the review of ECOSOC and HLPF to the following session of the General Assembly.

The General Assembly further adopted, on 25 June 2021, resolution 75/290 A on the Review of the implementation of GA resolution 72/305 on the strengthening of ECOSOC and resolution 75/290 B on the Review of the implementation of GA resolutions 67/290 on the format and organizational aspects of the HLPF and 70/299 on the follow-up and review of the 2030 Agenda for Sustainable Development at the global level:

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