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                            <gco:Date>2021-01-06</gco:Date>
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        <gco:CharacterString>Data gaps and limitations: For urban areas, once the separation of streets and buildings becomes highly relevant, a higher resolution than the 10m pixel sized used for the strategic scale mapping carried out for this project becomes desirable Urban drainage systems are not considered in this mapping; this could lead to some areas modelled to accumulate standing water actually being at lower risk than they are projected to be desirable. Urban drainage systems are not considered in this mapping; this could lead to over-estimation of the standing water risk in some ares.</gco:CharacterString>
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                    <gmx:Anchor xlink:href="http://data.europa.eu/eli/reg/2010/1089">Commission Regulation (EU) No 1089/2010 of 23 November 2010 implementing Directive 2007/2/EC of the European Parliament and of the Council as regards interoperability of spatial data sets and services</gmx:Anchor>
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            <gco:CharacterString>How the map has been created: In order to create the map, a DSM for the whole of Wales was derived from Nextmap DTM and MasterMap, with MasterMap features being assigned an average height, which was then added onto the DTM. The hydrology of the derived DSM was analysed using SciMap (Durham University, 2016). SciMap was originally designed to model erosion risk throughout the landscape. However, one of the intermediate outputs produced, the network index or connectivity, can be used to approximate urban flood risk, when using a DSM model instead of a DTM model as input. The network index expresses how likely a parcel of land is to pass material (in this case, water) on to another area. The areas with a particularly high network index are at the most risk from pluvial flooding. To separate between standing water and overland flow, slope information was used, with areas on slopes less than 3° being considered as at risk from standing water, whilst areas on steeper slopes are considered to be at risk from overland flow. To determine the demand, population density was considered, with the census data being split into 5 classes using Jenks Natural breaks; the highest two classes are high priority areas, the medium class a low priority area. Additionally, the Welsh Index of Multiple Deprivation was used, in accordance with classes used on wimd.wales.gov.uk. The 2 most deprived classes (rank 1 to 382) are high priority, the medium class (rank 383 to 573) low priority.  This dataset was produced for NRW under contract by Environment Systems Ltd.</gco:CharacterString>
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