AndreaBozzo/ceres-open-data-index huggingface dataset:
Modelled fluvial flood depth and climate change depth difference data created 2004: 0.1  percent annual chance for grid reference SS

The depth difference dataset (2004) is a depth grid showing the difference between modelled fluvial flood depths and modelled fluvial flood depths under climate change conditions (an increase in peak flows of 20%). 

Modelled fluvial flood depth and climate change depth difference data* was created for both the 0.1% annual chance of flooding situations and was produced as a by-product from the 2004 generalised modelling project. The purpose of the generalised modelling project was to fill the gaps where there was no detailed local modelled data in 2004, in order to define the extents of Flood Zones for spatial planning.

A two-dimensional hydrodynamic model called JFlow was used to produce both the modelled fluvial flood depth and modelled fluvial flood depth with climate change data. This depth difference data, using these 2 datasets, is provided on a 5x5m grid.

Since 2004, some local detailed modelling projects have included scenarios for climate change however this depth difference dataset has not been updated.

INFORMATION WARNING: This data is not suitable for identifying whether an individual property will flood due to climate change, for detailed decision making or for use in site specific Flood Risk or Strategic Flood Risk Assessments. Where this data is used further evidence, verification and studies should be undertaken. Climate change allowances have changed since this work was completed in 2004.

More recent, accurate and local detailed modelling depth data with climate change is available for some places. Please contact your local Environment Agency office to see if detailed modelling is available for your area of interest. 

This metadata record is for Approval for Access product AfA480 2004 1 in 1000 Fluvial Depth Grid Climate Change Difference

Modelled fluvial flood depth data with climate change are available for the whole of England, however this data is for the 100x100km squared Ordnance Survey National Grid reference SS. If you are interested in data for another grid reference refer to this Ordnance Survey National Grid document to find the relevant referencing code and search on Data.gov.uk again to download the data. Attribution statement: © Environment Agency copyright and/or database right 2016. All rights reserved. Some features of this information are based on digital spatial data licensed from the Centre for Ecology & Hydrology © NERC (CEH). Defra, Met Office and DARD Rivers Agency © Crown Copyright. © Cranfield University. © James Hutton Institute.  Contains OS data © Crown copyright and database right 2015. Land & Property Services © Crown copyright and database right.

Tags: environment, flood, flooding, risk assessment
Organization: Environment Agency
1991 AP

<div style='text-align:left;'><p style='font-size:12pt;'>The primary objective from this project was to acquire historical shoreline information for all of the Northern Ireland coastline. Having this detailed understanding of the coast’s shoreline position and geometry over annual to decadal time periods is essential in any management of the coast.</p><div style='text-align:left;'><p style='font-size:12pt;'>The
historical shoreline analysis was based on all available Ordnance Survey maps
and aerial imagery information. Analysis looked at position and geometry over
annual to decadal time periods, providing a dynamic picture of how the
coastline has changed since the start of the early 1800s.<br /></p><div style='text-align:left;'><p><span style='font-size:12pt;'>Once
all datasets were collated, data was interrogated using the ArcGIS package –
Digital Shoreline Analysis System (DSAS). DSAS is a software package which
enables a user to calculate rate-of</span><font size='3'>-change s</font><span style='font-size:12pt;'>tatistics from multiple historical
shoreline positions. Rate-of-change was collected at 25m intervals and
displayed both statistically and spatially allowing for areas of
retreat/accretion to be identified at any given stretch of coastline.</span><br /></p><p><span style='font-size:16px;'>The DSAS software will produce the following rate-of-change statistics:</span></p><p></p><ol><li><span style='font-size:16px;'>Net Shoreline Movement (NSM) – the distance between the oldest and the youngest shorelines.</span></li><li>Shoreline Change Envelope (SCE) – a measure of the total change in shoreline movement considering all available shoreline positions and reporting their distances, without reference to their specific dates.</li><li>End Point Rate (EPR) – derived by dividing the distance of shoreline movement by the time elapsed between the oldest and the youngest shoreline positions.</li><li>Linear Regression Rate (LRR) – determines a rate of change statistic by fitting a least square regression to all shorelines at specific transects.</li><li>Weighted Linear Regression Rate (WLR) - calculates a weighted linear regression of shoreline change on each transect. It considers the shoreline uncertainty giving more emphasis on shorelines with a smaller error.</li></ol><p></p><p><span style='font-size:16px;'>The end product provided by Ulster University is an invaluable tool and digital asset that has helped to visualise shoreline change and assess approximate rates of historical change at any given coastal stretch on the Northern Ireland coast.</span></p></div></div></div>

Tags: 3D, Analysis, Coastal, Historic, Ireland, Marine, Northern, Observatory, Rates, Shoreline change, Shorelines, Survey
Organization: OpenDataNI
March 2022 - North Coast Post-Storm Survey - Digital Surface Model

<div style='text-align:Left; font-size:12pt;'><p>Fugro were commissioned to undertake a post-storm LiDAR survey of the soft sedimentary areas along the north coast of Northern Ireland in March 2022 This survey was to cover the following areas: Curran Strand, Portrush East Strand, Portstewart Strand and Downhill Beach to Magilligan.</p><div style='text-align:Left; font-size:12pt;'><p>This project was commissioned following the successive storm events during February and March 2022 (Storm Dudley, Storm Eunice and Storm Franklin) which did considerable damage to the sandy beaches along the North Coast. The objective of this survey was to ascertain change which has occurred along these soft sediment coastlines at the north coast since the baseline survey, which was acquired in 2021.</p><div style='text-align:Left; font-size:12pt;'><p>Data was provided in the same format as the topographic LiDAR data collected in the Northern Ireland 3-Dimensional Coastal Survey to allow changes between these two datasets to be ascertained.</p><div style='text-align:Left; font-size:12pt;'><p>This is the Digital Surface Model created from the post-storm LiDAR data.<br /></p></div></div></div></div></div></div></div>

Tags: 3d, Coastal, DSM, Digital Surface Model, Ireland, LiDAR, Northern, Observatory, Post, Storm
Organization: OpenDataNI
2021 NI 3D Coastal Survey - Topographic LiDAR - Orthophotography Colour Infrared

<div style='text-align:Left; font-size:12pt;'><p>Orthophotography is aerial imagery that has been geometrically corrected. An orthophoto is an image that is free of distortion, and which is characterised by a uniform scale over its entire surface - it has been ortho-rectified. </p><div>Orthophotography was captured as part of the 2021 NI 3D Coastal Survey. Coverage extends across the entire Northern Ireland coastline, including the intertidal area, and extending approximately 200 meters landward of the high water mark. </div><div><br /></div><div>Colour Infrared <span style='font-size:15px;'>orthophotography </span>imagery was captured with a 10cm resolution. </div></div>

Tags: 3D, Coastal, Marine, Observatory, Ortho, Orthophotography, Survey
Organization: OpenDataNI
Satellite Derived Bathymetry

<div style='text-align:Left; font-size:12pt;'><p>In 2021 a high resolution (minimum 10 meters) satellite-derived bathymetry survey was complete for the full extent of the Northern Ireland marine area to a maximum depth of 8-11 meters. This was undertaken as part of the NI 3D Coastal Survey.</p><div style='text-align:Left; font-size:12pt;'><p>Images which were used date from 2012 but the majority were captured from 2018 onwards.  Data was acquired from two sources: </p><p>•	Sentinel 2 sensors which produces a 10m spatial resolution bathymetric grid and </p><p>•	Commercial satellite data, which allow for a higher 2m spatial resolution.
</p><div style='text-align:Left; font-size:12pt;'><p>This is the Digital Terrain Model that was created from the satellite-derived bathymetry dataset.</p><div style='text-align:Left; font-size:12pt;'></div></div></div></div>

Tags: 3D, Bathymetry, Coastal, Derived, Marine, Observatory, Satellite, Survey
Organization: OpenDataNI
2014 Ortho OSNI

<div style='text-align:left;'><p style='font-size:12pt;'>The primary objective from this project was to acquire historical shoreline information for all of the Northern Ireland coastline. Having this detailed understanding of the coast’s shoreline position and geometry over annual to decadal time periods is essential in any management of the coast.</p><div style='text-align:left;'><p style='font-size:12pt;'>The
historical shoreline analysis was based on all available Ordnance Survey maps
and aerial imagery information. Analysis looked at position and geometry over
annual to decadal time periods, providing a dynamic picture of how the
coastline has changed since the start of the early 1800s.<br /></p><div style='text-align:left;'><p><span style='font-size:12pt;'>Once
all datasets were collated, data was interrogated using the ArcGIS package –
Digital Shoreline Analysis System (DSAS). DSAS is a software package which
enables a user to calculate rate-of</span><font size='3'>-change s</font><span style='font-size:12pt;'>tatistics from multiple historical
shoreline positions. Rate-of-change was collected at 25m intervals and
displayed both statistically and spatially allowing for areas of
retreat/accretion to be identified at any given stretch of coastline.</span><br /></p><p><span style='font-size:16px;'>The DSAS software will produce the following rate-of-change statistics:</span></p><p></p><ol><li><span style='font-size:16px;'>Net Shoreline Movement (NSM) – the distance between the oldest and the youngest shorelines.</span></li><li>Shoreline Change Envelope (SCE) – a measure of the total change in shoreline movement considering all available shoreline positions and reporting their distances, without reference to their specific dates.</li><li>End Point Rate (EPR) – derived by dividing the distance of shoreline movement by the time elapsed between the oldest and the youngest shoreline positions.</li><li>Linear Regression Rate (LRR) – determines a rate of change statistic by fitting a least square regression to all shorelines at specific transects.</li><li>Weighted Linear Regression Rate (WLR) - calculates a weighted linear regression of shoreline change on each transect. It considers the shoreline uncertainty giving more emphasis on shorelines with a smaller error.</li></ol><p></p><p><span style='font-size:16px;'>The end product provided by Ulster University is an invaluable tool and digital asset that has helped to visualise shoreline change and assess approximate rates of historical change at any given coastal stretch on the Northern Ireland coast.</span></p></div></div></div>

Tags: 3D, Analysis, Coastal, Historic, Ireland, Marine, Northern, Observatory, Rates, Shoreline change, Shorelines, Survey
Organization: OpenDataNI
Agricultural Critical Risk Areas

<div style='text-align: left;'><div><div><p><span>The agricultural risk map is based on activity classed as arable horticulture or improved grassland by the CEH land cover map 2007, which is carried out on land parcels scored against a matrix of risk factors and the 2015 status of WFD enrichment indicators. These risk factors have the potential to contribute to in-stream biological, chemical and physiochemical impact. The land cover classes arable horticulture and improved grassland together delineate the boundary areas of intensive agriculture and constrain the area for relative risk assessment. They also contribute to the risk factor scores with a distinction made between their relative risks.</span></p><p><span>A modelling application SciMAP was applied with a 5m DTM to produce sediment source and deposition areas as well as identifying significant hydrological links to the river network.</span></p><p><span>Each risk factor has been assigned a relative weighting from 0 – 1 dependant on its contribution to the overall risk (expert judgement/advice and literature review). These weightings have been used as multipliers for a three category risk index, 1 - 3 relating to banding of risk factor variables into increasing risk. The scores are then totalled to provide an overall risk for each land parcel. These can also be filtered on hydrological significance.</span></p><p><span>Risk categories boundaries are determined by selecting +/- 1 standard deviation of the distribution of the scores. This provides a statistical basis for the low, medium and high risk category limits. Further categories can be created by increasing or relaxing the standard deviation applied. The extent of the area included in each category is dependent on the stringency of the standard deviation applied.</span></p><p><span>CEH landcover 2007 and Met Office rainfall data used in the model.</span></p></div></div></div>

Tags: Agricultural land Risk, DAERA, NIEA, Northern Ireland Environment Agency, Science, Soil Risk Model, Surface Runoff Risk, Water
Organization: OpenDataNI
Historic Shoreline Analysis

<div style='text-align:left;'><p style='font-size:12pt;'>The primary objective from this project was to acquire historical shoreline information for all of the Northern Ireland coastline. Having this detailed understanding of the coast’s shoreline position and geometry over annual to decadal time periods is essential in any management of the coast.</p><div style='text-align:left;'><p style='font-size:12pt;'>The
historical shoreline analysis was based on all available Ordnance Survey maps
and aerial imagery information. Analysis looked at position and geometry over
annual to decadal time periods, providing a dynamic picture of how the
coastline has changed since the start of the early 1800s.<br /></p><div style='text-align:left;'><p><span style='font-size:12pt;'>Once
all datasets were collated, data was interrogated using the ArcGIS package –
Digital Shoreline Analysis System (DSAS). DSAS is a software package which
enables a user to calculate rate-of</span><font size='3'>-change s</font><span style='font-size:12pt;'>tatistics from multiple historical
shoreline positions. Rate-of-change was collected at 25m intervals and
displayed both statistically and spatially allowing for areas of
retreat/accretion to be identified at any given stretch of coastline.</span><br /></p><p><span style='font-size:16px;'>The DSAS software will produce the following rate-of-change statistics:</span></p><p></p><ol><li><span style='font-size:16px;'>Net Shoreline Movement (NSM) – the distance between the oldest and the youngest shorelines.</span></li><li>Shoreline Change Envelope (SCE) – a measure of the total change in shoreline movement considering all available shoreline positions and reporting their distances, without reference to their specific dates.</li><li>End Point Rate (EPR) – derived by dividing the distance of shoreline movement by the time elapsed between the oldest and the youngest shoreline positions.</li><li>Linear Regression Rate (LRR) – determines a rate of change statistic by fitting a least square regression to all shorelines at specific transects.</li><li>Weighted Linear Regression Rate (WLR) - calculates a weighted linear regression of shoreline change on each transect. It considers the shoreline uncertainty giving more emphasis on shorelines with a smaller error.</li></ol><p></p><p><span style='font-size:16px;'>The end product provided by Ulster University is an invaluable tool and digital asset that has helped to visualise shoreline change and assess approximate rates of historical change at any given coastal stretch on the Northern Ireland coast.</span></p></div></div></div>

Tags: 3D, Analysis, Coastal, Historic, Ireland, Marine, Northern, Observatory, Rates, Shoreline change, Shorelines, Survey
Organization: OpenDataNI
DWPA abstraction point hydrological catchments

<DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>This layer shows the Drinking Water Protected Areas (DWPA) which have been identified and designated in accordance with Article 8 of The Water Environment (Water Framework Directive) Regulations (Northern Ireland) 2017. Each polygon represents a holistic upstream hydrological catchments which supply surface drinking water abstraction points.</SPAN></P></DIV></DIV></DIV>

Tags: Abstractions, DAERA, DWPA, Groundwater, Northern Ireland, Northern Ireland Environment Agency, Protected Areas, WFD, Water, Water Framework Directive, drinking water, drinking water protected areas, potable water
Organization: OpenDataNI
Image

<div style='text-align:Left; font-size:12pt;'><p>Fugro were commissioned to undertake a post storm LiDAR survey of the soft sedimentary areas along the north coast of Northern Ireland in March 2022. This survey was to cover the following areas: Curran Strand, Portrush East Strand, Portstewart Strand and Downhill Beach to Magilligan.</p><div style='text-align:Left; font-size:12pt;'><p>This project was commissioned following the successive storm events during February and March 2022 (Storm Dudley, Storm Eunice and Storm Franklin) which did considerable damage to the sandy beaches along the North Coast. The objective of this survey was to ascertain change which has occurred along these soft sediment coastlines at the north coast since the baseline survey, which was acquired in 2021.</p><div style='text-align:Left; font-size:12pt;'><p>Data was provided in the same format as the topographic LiDAR data collected in the Northern Ireland 3-Dimensional Coastal Survey to allow changes between these two datasets to be ascertained.</p><div style='text-align:Left; font-size:12pt;'><p>Later in the year Fugro were commissioned to undertake a second LiDAR survey of the north coast from White Rocks to Magilligan in September 2022. The aim of this repeat survey was to ascertain the levels of recovery along the soft sediment coastlines since March 2022.</p><div style='text-align:Left; font-size:12pt;'><p>As with the initial survey undertaken by Fugro this topographic LiDAR survey collected data from the intertidal area to 10m inland for the same soft sediment areas along the north coast, with data being acquired at 0.5m resolution. The survey was quite restrictive when it could be flown: it had to be 2 hours either side of Low Water, during clear conditions below 6000ft, sun had to be at a suitable angle to capture imagery and as photography was being captured the survey could only be flown during day light hours. <div style='text-align:Left; font-size:12pt;'><p>All data collected was to be directly comparable with the data collected in the initial post storm Survey undertaken, as this would help us to understand and accurately quantify how our soft, sedimentary coastlines respond and recover from extreme storm events.</p><div style='text-align:Left; font-size:12pt;'><p>This is the orthophotography that was collected as part of the post-storm recovery survey. <br /></p></div></div></div></div></div></div></div></p>

Tags: 3D, Coastal, DTM, Digital Terrain Model, Ireland, Marine, Northern, Observatory, Ortho, Orthophotography, Post Storm, Recovery, Survey
Organization: OpenDataNI
River Water Quality Monitoring 1990 to 2018 - Biochemical Oxygen Demand

<DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>This table provides the raw data from river monitoring sites including Water Framework Directive monitoring sites. It should be noted that, as the data set is in its raw state, it cannot be used to provide a status without processing. The data set does not show Limits of Detection or Limit of Quantitation which would require a value to be treated as a half value for WFD calculation. In addition both altitude and alkalinity affect status calculations for some parameters. The data set may contain results which are erroneous due to typos, sampling error or contamination, such data points are usually several orders or magnitude above expected values.</SPAN></P><P><SPAN>This is the first in a series of water data sets being made available as Open Data. Other data sets remain available on request via waterinfor@daera-ni.gov.uk</SPAN></P><P><SPAN>The European Water Framework Directive (2000/60/EC) has been transposed into Northern Ireland regulations through The Water Environment (Water Framework Directive) Regulations (Northern Ireland) 2017. The Water (Amendment) (Northern Ireland) (EU Exit) Regulations 2019 ensures that the Water Framework Directive (WFD) (as transposed) and the various supporting pieces of water legislation continue to operate here after 1 January 2021. The regulation encourage the active involvement of interested parties and the general public.</SPAN></P><P><SPAN>The regulations set out the requirement to achieve 'Good Ecological Status' and 'Good Chemical Status' for all ground and surface waters (rivers, lakes, transitional waters, and coastal waters) within Northern Ireland.</SPAN></P><P><SPAN>Surface waters are assessed according to the following criteria:</SPAN></P><UL><LI><P><SPAN>Biological quality (fish, invertebrates, flora)</SPAN></P></LI><LI><P><SPAN>Hydromorphological</SPAN></P></LI><LI><P><SPAN>Physico-chemical properties like temperature, oxygenation and nutrient conditions.</SPAN></P></LI><LI><P><SPAN>Chemical quality assessed against environmental quality standards for specific pollutants and priority substances.</SPAN></P></LI></UL><P><SPAN>The following physio-chemical and chemical parameters are included in the data set:</SPAN></P><P><SPAN>BOD(mg/l)- Biochemical oxygen Demand</SPAN></P></DIV></DIV></DIV>

Tags: DAERA, Lakes, Monitoring Sites, NIEA, Northern Ireland, Protected Areas, Rivers, Science, Surface waters, WFD, Water, Water Framework Directive, Water Quality
Organization: OpenDataNI