Caribbean Permeable Surface (Southeast Blueprint Indicator)

Reason for Selection Impervious cover is easy to monitor and model and is widely used and understood by diverse partners. It is also strongly linked to water quality, estuary condition, eutrophication, and freshwater inflow. Impervious surface affects not only aquatic habitats and biodiversity, but also human communities. High levels of impervious surface cause more frequent flooding by increasing the volume of stormwater runoff, reduce the amount of available drinking water by preventing groundwater recharge, and pollute waterways where people swim and fish (Chesapeake 2023, USGS 2018, EPA 2018). The 90% permeable surface threshold (i.e., 10% impervious) is a well-documented signal of major, negative changes to aquatic ecosystems (Schueler et al. 2009). The 95% permeable surface threshold (i.e., 5% impervious) has been documented to impact Piedmont fish [tricolor shiner (Cyprinella trichroistia), bronze darter (Percina palmaris), Etowah darter (Etheostoma etowahae)] (Wenger et al. 2008) and estuarine species [blue crab (Callinectes sapidus), white perch (Morone americana), striped bass (M. Saxatilis) and spot (Leiostomus xanthurus)] (Uphoff Jr. et al. 2011). While most of these species do not occur in Puerto Rico and the U.S. Virgin Islands, we kept these thresholds in the Caribbean for consistency with the continental version of the indicator. Input Data * [Southeast Blueprint 2023 subregions]: Caribbean * [Southeast Blueprint 2023 extent] * 2012 [National Oceanic and Atmospheric Administration (NOAA) Coastal Change Analysis Program (C-CAP) land cover files for the U.S. Virgin Islands] (St. Thomas, St. John, and St. Croix are provided as separate rasters) accessed 11-10-2022; learn more about [C-CAP high resolution land cover and change products] * 2010 [NOAA C-CAP land cover files for Puerto Rico], accessed 11-10-2022; learn more about [C-CAP high resolution land cover and change products] * [National Hydrography Dataset Plus High Resolution] (NHDPlus HR) National Release catchments, accessed 11-30-2022; [download the data] Catchments A catchment is the local drainage area of a specific stream segment based on the surrounding elevation. Catchments are defined based on surface water features, watershed boundaries, and elevation data. It can be difficult to conceptualize the size of a catchment because they vary significantly in size based on the length of a particular stream segment and its surrounding topography—as well as the level of detail used to map those characteristics. To learn more about catchments and how they’re defined, check out these resources: * [An article from USGS explaining the differences between various NHD products] * The glossary at the bottom of [this tutorial for an EPA water resources viewer], which defines some key terms * [NOAA Continuously Updated Shoreline Product] (CUSP), accessed 1-11-2023; [read a 1-page factsheet about CUSP]; view and download CUSP data in the [NOAA Shoreline Data Explorer] (to download, select “Download CUSP by Region” and select Southeast Caribbean) Mapping Steps * NHDPlus HR catchments are currently only available for the islands of Puerto Rico, Vieques, Culebra, St. Croix, St. John, and St. Thomas. Because the catchments don’t cover many of the smaller islands, use CUSP to add islands larger than 900 sq m (the area of a 30 m pixel). Start by converting CUSP shoreline lines to polygons. * Dissolve interior waterbodies on islands to represent each island with only one polygon. * To eliminate alignment issues between the CUSP and catchment polygons, remove most island areas that overlap with or are near (<10 m from) the NHDPlus HR catchments, ensuring that all of Culebra is retained. * The original NHDPlus HR catchment data was missing coverage of a small area on the west coast of Puerto Rico (just east of Parcelas Aguas Claras). Create an additional catchment polygon for this missing area so that the indicator covers the entire island of Puerto Rico. * The missing area is essentially outlined by extremely thin catchment polygons. To fill the gap, make a new rectangular feature class covering the missing area, then union it together with the original NHDPlus HR catchments. From that output, select the newly created polygon that fills in the hole. * The resulting polygon is a multipart feature, so use the explode tool to separate out just the missing catchment. Export it as a shapefile. * Union together the missing catchment with the other NHDPlus HR catchments and use that combined output as the catchment layer for the rest of the mapping steps. * Remove islands created from the CUSP dataset that are less than 900 sq m. * Merge the remaining CUSP islands with the NHDPlus catchments to create a single set of polygons in which to calculate average permeable surface. * Convert the C-CAP land cover rasters for Puerto Rico (2 m resolution) and the U.S. Virgin Islands (separate downloads for St. Thomas, St. John, and St. Croix with 2.4 m resolution) from .img format to .tif using the Copy Raster function. * For each individual C-CAP layer, use the ArcPy Conditional function to make a binary raster assigning the impervious class a value of 100 (representing fully impervious) and all other classes a value of 0 (representing fully permeable). This mimics the data format of the 2019 National Land Cover Database used in the continental Southeast permeable surface indicator, which provides a continuous impervious surface value ranging from 0 to 100. * Using the ArcPy Mosaic to New Raster function, mosaic all 4 rasters into 1 raster. Reproject to match the Blueprint projection and the 2 m cell size of the original Puerto Rico C-CAP data. * Calculate the average percent of impervious surface for each NHDPlus catchment or CUSP island using the ArcPy Spatial Analyst Zonal Statistics “MEAN” function, assigning the average impervious surface value to each catchment or island. * Convert percent impervious to percent permeable using the formula [percent permeable = 100 - percent impervious] to maintain consistent scoring across Southeast Blueprint indicators (where high values indicate better ecological condition). * Reclassify the above raster into 4 classes, seen in the final indicator values below. * Clip to the Caribbean Blueprint 2023 subregion. * As a final step, clip to the spatial extent of Southeast Blueprint 2023. Note: For more details on the mapping steps, code used to create this layer is available [in the Southeast Blueprint 2025 Data Download] or [Caribbean-only Southeast Blueprint 2025 Data Download] under > 6_Code. Final indicator values Indicator values are assigned as follows: 4 = >95% of catchment or small island permeable (likely high water quality and supporting most sensitive aquatic species) 3 = >90-95% of catchment or small island permeable (likely declining water quality and supporting most aquatic species) 2 = >70-90% of catchment or small island permeable (likely degraded water quality and not supporting many aquatic species) 1 = ≤70% of catchment or small island permeable (likely degraded instream flow, water quality, and aquatic species communities) Known Issues * This indicator may not account for differences in permeability between different types of soils and land uses. * The C-CAP impervious layer used in this indicator contains classification inaccuracies that may cause this indicator to overestimate or underestimate the amount of permeable surface in some catchments. * C-CAP dates from 2010 for Puerto Rico and 2012 for the U.S. Virgin Islands. As a result, this indicator likely overestimates permeable surface values in areas that have been developed since the data was collected. * C-CAP landcover is not available for some islands over 900 sq m. While these islands exceeded the size threshold for inclusion in this indicator, they are therefore scored as NoData. This indicator only covers areas where C-CAP landcover is present, and either NHDPlus HR catchments or islands over 900 sq m that were generated using CUSP data are also present. * NHDPlus HR contains multiple catchments that are very small. The reduced size of these catchments may result in exaggerating their values in the indicator. Other Things to Keep in Mind * The impervious surface in the C-CAP data has impervious surface as one class in the landcover, which differs from the 2019 NLCD percent developed impervious layer used in the continental Southeast version of the permeable surface indicator. NLCD 2019 is served up as a continuous raster ranging from 0-100% impervious. * We used the Caribbean island size and extent layer for this indicator and not others because landcover data was available for small islands that were not covered by catchments, which otherwise would have been excluded. This was not the case for other indicators. For example, while we use catchments in natural landcover in floodplains, the floodplains and flowlines did not occur on small islands, anyway, so we did not leave any data out by using the catchments only and not supplementing with the islands layer. Disclaimer: Comparing with Older Indicator Versions There are numerous problems with using Southeast Blueprint indicators for change analysis. Please consult Blueprint staff if you would like to do this (email [hilary_morris@fws.gov]). Literature Cited Chesapeake Bay Program. 2023. Stormwater Runoff. Accessed September 7, 2023. [[https://www.chesapeakebay.net/issues/threats-to-the-bay/stormwater-runoff]]. Environmental Protection Agency. EnviroAtlas. Data Fact Sheet. January 2018. Percent of Stream and Shoreline with 15% or More Impervious Cover within 30 Meters. Accessed September 7, 2023. [[https://enviroatlas.epa.gov/enviroatlas/DataFactSheets/pdf/ESN/Percstreamw15percentimperviousin30meters.pdf]]. Moore, R.B., McKay, L.D., Rea, A.H., Bondelid, T.R., Price, C.V., Dewald, T.G., and Johnston, C.M., 2019, User’s guide for the national hydrography dataset plus (NHDPlus) high resolution: U.S. Geological Survey Open-File Report 2019– 1096, 66 p., [[https://doi.org/10.3133/ofr20191096]]. National Oceanic and Atmospheric Administration, Office for Coastal Management. “C-CAP Land Cover Files for Puerto Rico and US Virgin Islands”. Coastal Change Analysis Program (C-CAP) High-Resolution Land Cover. Charleston, SC: NOAA Office for Coastal Management. Accessed November 2022. [[https://www.coast.noaa.gov/htdata/raster1/landcover/bulkdownload/hires/]]. Schueler, T., Fraley-McNeal, L., and Cappiella, K. 2009. “Is Impervious Cover Still Important? Review of Recent Research.” J. Hydrol. Eng. 14, SPECIAL ISSUE: Impervious Surfaces in Hydrologic Modeling and Monitoring, 309–315. [[https://chesapeakestormwater.net/wp-content/uploads/2022/07/3322-3.pdf]]. Uphoff Jr. JH, McGinty M, Lukacovic R, Mowrer J, Pyle B. 2011. Impervious surface, summer dissolved oxygen, and fish distribution in Chesapeake Bay subestuaries: linking watershed development, habitat conditions, and fisheries management. North American Journal of Fisheries Management 31:554-566. [[https://dnr.maryland.gov/fisheries/Documents/2011_Impervious_Surface.pdf]]. U.S. Geological Survey (USGS). Water Science School. Impervious Surfaces and Flooding. June 5, 2018. Accessed September 7, 2023. [[https://www.usgs.gov/special-topics/water-science-school/science/impervious-surfaces-and-flooding]]. U.S. Geological Survey (USGS). National Hydrography Dataset Plus High Resolution (NHDPlus HR). Accessed November 30, 2022. [[https://www.usgs.gov/national-hydrography/nhdplus-high-resolution]]. Wenger, S. J., J. T. Peterson, M. C. Freeman, B. J. Freeman, D. D. Homans. 2008. Stream fish occurrence in response to impervious cover, historic land use and hydrogeomorphic factors. Canadian Journal of Fisheries and Aquatic Sciences 65, 1250-1264. [[https://cdnsciencepub.com/doi/10.1139/F08-046]].