Permeable Surface (Southeast Blueprint Indicator)

Reason for Selection Impervious cover is 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 surfac e 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). Input Data 2021 National Land Cover Database (NLCD): Percent developed imperviousness Southeast Blueprint 2024 extent National Hydrography Dataset Plus (NHDPlus) Version 2.1 medium resolution catchments (note: V2.1 is just the current sub-version of the dataset generally called NHDPlusV2); view the user guide 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 Mapping Steps The NLCD impervious surface raster uses a value of 127 as NoData. Use the Set Null function to change these values to NoData so they won’t impact the analysis. Calculate percent impervious for each NHDPlus catchment using the NLCD 2021 impervious surface layer and the ArcPy Spatial Analyst Zonal Statistics “MEAN” function. The Zonal Statistics Mean calculates the average of the impervious surface values in each catchment and assigns that value to all the cells inside that catchment. Convert percent impervious to percent permeable using the formula [percent permeable = 100 - percent impervious] to maintain consistent scoring across Southeast indicators (high values indicate better ecological condition). Reclassify the above raster into 4 classes, seen in the final indicator values below. As a final step, clip to the spatial extent of Southeast Blueprint 2024. Note: For more details on the mapping steps, code used to create this layer is available in the Southeast Blueprint Data Download under > 6_Code. Final indicator values Indicator values are assigned as follows: 4 = >95% of catchment permeable (likely high water quality and supporting most sensitive aquatic species) 3 = >90-95% of catchment permeable (likely declining water quality and supporting most aquatic species) 2 = >70-90% of catchment permeable (likely degraded water quality and not supporting many aquatic species) 1 = ≤70% of catchment 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 catchment boundaries are inconsistent in how far they extend toward the ocean. As a result, this indicator does not consistently apply to estuaries, coastal areas, and barrier islands in different parts of the Southeast. The catchment boundaries cross the United States/Mexico border, but the NLCD impervious data does not; as a result, the values along the United States/Mexico border are only based on the portion of the catchment where there are NLCD impervious values. The NLCD percent impervious layer contains classification inaccuracies that may cause this indicator to overestimate or underestimate the amount of permeable surface in some catchments. 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 [e-mail]). Literature Cited Chesapeake Bay Program. 2023. Stormwater Runoff. Accessed September 7, 2023. [https://www.chesapeakebay.net/issues/threats-to-the-bay/stormwater-runoff]. Dewitz, J., 2023, National Land Cover Database (NLCD) 2021 Products: U.S. Geological Survey data release. [https://doi.org/10.5066/P9JZ7AO3]. 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].

选择依据
不透水覆盖层（Impervious cover）与水质、河口状况、富营养化及淡水输入密切相关。不透水表面不仅影响水生栖息地与生物多样性，还会对人类社区造成影响。高占比的不透水表面会通过增加暴雨径流量加剧洪涝发生频率，通过阻碍地下水补给减少可利用饮用水资源，并污染人们游泳、垂钓的水域（切萨皮克湾项目2023，美国地质调查局2018，美国环境保护署2018）。90%透水表面阈值（即10%不透水占比）是水生生态系统发生重大负面变化的公认信号（Schueler等2009）。另有研究表明，95%透水表面阈值（即5%不透水占比）会对皮埃蒙特地区鱼类[三色真小鲤（Cyprinella trichroistia）、青铜镖鲈（Percina palmaris）、埃托瓦镖鲈（Etheostoma etowahae）]（Wenger等2008）以及河口物种[蓝蟹（Callinectes sapidus）、白鲈（Morone americana）、条纹鲈（M. Saxatilis）与斑点鳉（Leiostomus xanthurus）]（Uphoff Jr.等2011）产生影响。

输入数据
2021年全国土地覆盖数据库（National Land Cover Database, NLCD）：开发区域不透水占比
2024年东南部蓝图（Southeast Blueprint 2024）研究范围
第二版2.1分辨率中等分辨率集水区（National Hydrography Dataset Plus, NHDPlus Version 2.1）（注：V2.1为通常所称NHDPlusV2的当前子版本）；可查阅用户指南

集水区
集水区指基于周边地形高程划定的特定河段的局部汇水区，其划定依据地表水特征、流域边界与高程数据。由于集水区规模会随对应河段长度、周边地形以及制图细节程度产生显著差异，因此其尺寸较难直观认知。若需了解更多集水区相关信息及其划定规则，可参考以下资源：美国地质调查局一篇阐述各类NHD产品差异的文章，以及某EPA水资源查看器教程末尾的术语表（其中定义了部分关键术语）

制图步骤
NLCD不透水表面栅格以127作为无数据（NoData）值。可使用设置空值（Set Null）工具将该值转换为无数据，避免其对分析造成干扰。利用2021年NLCD不透水表面图层与ArcPy空间分析工具的分区统计“均值”（MEAN）函数，计算每个NHDPlus集水区的不透水占比。分区统计均值工具会计算每个集水区内不透水表面数值的平均值，并将该值赋予集水区内所有栅格单元。通过公式「透水占比=100-不透水占比」将不透水占比转换为透水占比，以确保与东南部蓝图各项指标的评分逻辑一致（分值越高代表生态状况越优）。将上述栅格重分类为4个等级，对应最终指标值如下。最后一步为裁剪至2024年东南部蓝图的空间范围。注：若需了解制图步骤的更多细节，可在东南部蓝图数据下载页面>6_代码中获取用于生成该图层的代码。

最终指标值
指标值赋值规则如下：
4 = 集水区透水占比>95%（水质大概率优良，可支撑多数敏感水生生物）
3 = 集水区透水占比>90%~95%（水质大概率有所下降，可支撑多数水生生物）
2 = 集水区透水占比>70%~90%（水质大概率退化，无法支撑多数水生生物）
1 = 集水区透水占比≤70%（河道径流、水质与水生生物群落大概率出现退化）

已知问题
本指标未考虑不同类型土壤与土地利用方式之间的透水性能差异。集水区边界向海洋延伸的范围并不统一，因此本指标无法一致适用于东南部不同区域的河口、沿海地区与障壁岛。部分集水区边界跨越美墨边境，但NLCD不透水数据并未覆盖该区域，因此美墨边境沿线的指标值仅基于存在NLCD不透水数据的集水区部分计算得出。NLCD不透水占比图层存在分类误差，可能导致部分集水区的透水表面占比被高估或低估。

免责声明：与旧版指标版本的对比
使用东南部蓝图指标进行变化分析存在诸多问题。若需开展此类分析，请咨询蓝图项目工作人员（邮箱：[e-mail]）。

引用文献
切萨皮克湾项目。2023。暴雨径流。2023年9月7日访问。[https://www.chesapeakebay.net/issues/threats-to-the-bay/stormwater-runoff]。
Dewitz, J., 2023, 2021年全国土地覆盖数据库（NLCD）产品：美国地质调查局数据发布。[https://doi.org/10.5066/P9JZ7AO3]。
美国环境保护署。环境地图集（EnviroAtlas）。数据事实表。2018年1月。「30米范围内不透水覆盖占比≥15%的溪流与岸线占比」。2023年9月7日访问。[https://enviroatlas.epa.gov/enviroatlas/DataFactSheets/pdf/ESN/Percstreamw15percentimperviousin30meters.pdf]。