LANLoad NEEPP - Charlotte County: Landscape Assessment of Nutrient Loading to Waterbodies (LANLoad) in the Northern Everglades and Estuaries Protection Program (NEEPP) Region
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This raster dataset consists of cells (9.6m x 9.6m) ranked to reflect the likelihood that nutrients applied to a given terrestrial location will reach the nearest downgradient surface waterbody. Possible ranks range from 1 to 9 with values increasing as the likelihood of nutrient transport to downgradient surface waterbodies increases. Ranks are based on six physical landscape parameters selected by Subject Matter Experts (SMEs) who also assigned relative weights to each parameter using the Analytical Hierarchy Process (AHP). During this exercise, the location considered by SMEs was the pilot study area, St. Lucie County, FL, and the focal nutrient source was Onsite Sewage and Treatment Disposal Systems (OSTDS). Despite the original focus on OSTDS, LANLoad NEEPP can be used to gauge the likelihood of nutrient transport to surface waterbodies from other, similar, nutrient sources. The resulting AHP model demonstrated high internal consistency (Consistency Ratio: 0.01) and resulted in the following parameters and weights, in order of importance: Distance to Waterbody, 30.0%; Depth to Water, 21.6%; Hydraulic Conductivity, 20.7%; Potential for Flooding, 10.9%; Slope, 9.8%; and Surficial Karstic Deposits, 7.0%. The weights assigned by SMEs in the St. Lucie County pilot were deemed applicable to the NEEPP region due to highly similar geologic/hydrologic conditions. Relative parameter weights might not be applicable to regions without such similarities. Geospatial datasets representative of these parameters were combined using a weighted overlay to produce LANLoad NEEPP. The performance of LANLoad NEEPP was evaluated across randomly selected, stratified locations within the NEEPP region. LANLoad NEEPP categories were classified into “lower” likelihood (LANLoad NEEPP categories ≤ 4) and “higher” likelihood (LANload NEEPP categories ≥ 6). We subjected these classifications to two independent, blind evaluation methods. First, SMEs evaluated 30 locations using their best professional judgment. This expert review yielded a 92% consistency rate with LANLoad NEEPP classifications. Second, the groundwater numerical model ArcNLET-Py was used to simulate uniform nutrient loading across 10 locations, analyzing a total of 500 model points. This yielded a 100% consistency rate with the LANLoad NEEPP classifications where the locations identified by LANLoad NEEPP as "higher likelihood" directly corresponded with the highest simulated nutrient loads, while "lower likelihood" locations matched the lowest simulated nutrient loads. LANLoad NEEPP was developed in ArcGIS Pro 3.5.2 (ESRI) at a 9.6-meter resolution, using the NAD83 (2011) Datum and the Florida GDL Albers Ellipsoid: GRS 1980 projection. Standard geoprocessing workflows and authoritative reference materials were utilized to cleanse data, fill spatial gaps, and eliminate null values for the hydraulic conductivity, depth to groundwater, the National Flood Hazard Layer, and the Surficial Geology of Florida geospatial datasets. Three geospatial datasets derived from source data, Waterbodies, Distance to Waterbodies and Slope, were developed by the Balmoral Group in collaboration with the University of South Florida - Ecohydrology Research Group. Table 1: The geospatial datasets incorporated in LANLoad NEEPP (2026). Abbreviations: Federal Emergency Management Agency (FEMA), Florida Department of Environmental Protection (DEP), National Resources Conservation Service (NRCS), United States Geological Survey (USGS), University of South Florida - Ecohydrology Research Group (USF-ERG) Parameter Geospatial Dataset Source Date Acquired Waterbodies Florida NHD Waterbody Polygons DEP 3/2026 Florida NHD Area Polygons DEP 3/2026 Florida NHD Flowlines DEP 3/2026 Soil Survey Geographic Dataset (SSURGO) - FL NRCS 3/2026 Statewide Land Use Land Cover (Codes 5000 and 6000) DEP 3/2026 Distance to Waterbodies Waterbodies The Balmoral Group 3/2026 DEM USGS 3/2026 Depth to Groundwater Soil Survey Geographic Dataset (SSURGO) -FL NRCS 3/2026 Hydraulic Conductivity Soil Survey Geographic Dataset (SSURGO) -FL NRCS 3/2026 Potential for Flooding National Flood Hazard Layer FEMA 3/2026 Slope Distance to Waterbodies The Balmoral Group 5/2026 DEM USGS 3/2026 Surficial Geology Surficial Geology of Florida DEP 11/2025 Contact Information Kai C. Rains, PhD, PWS – krains@usf.edu Dataset Citation Rains, Kai; Guerron-Orejuela, Edgar; Davis, Sara; Okonkwo, Moses; Rains, Mark (2026), “LANLoad NEEPP: Landscape Assessment of Nutrient Loading to Waterbodies (LANLoad) in the Northern Everglades and Estuaries Protection Program (NEEPP) region”, University of South Florida, v03, doi: 10.17632/7nw285j9bk.3 License CC BY 4.0 Links: USF Ecohydrology Research Group LANLoad Phase III Final Report Florida Geographic Information Office Logos:
本栅格数据集由9.6米×9.6米的栅格单元组成，各单元按分值排序，以反映施加于某一陆地区域的营养物质抵达最近下坡方向地表水体的可能性。分值区间为1至9，分值越高，营养物质输送至下坡方向地表水体的可能性就越大。 排序依据为主题专家（Subject Matter Experts, SMEs）遴选的六项自然景观参数，专家同时采用层次分析法（Analytical Hierarchy Process, AHP）为各参数分配相对权重。在此研究过程中，专家选定的研究区域为佛罗里达州圣卢西县试点区域，核心营养物质来源为现场污水处置系统（Onsite Sewage and Treatment Disposal Systems, OSTDS）。尽管本数据集最初聚焦于现场污水处置系统，但LANLoad NEEPP仍可用于评估其他类似营养物质来源向地表水体输送营养物质的可能性。 最终构建的层次分析法模型展现出极高的内部一致性（一致性比率：0.01），按重要性排序得到以下参数及其权重：距水体距离（30.0%）、地下水埋深（21.6%）、导水率（20.7%）、洪水潜势（10.9%）、坡度（9.8%）以及表层喀斯特沉积（7.0%）。主题专家在圣卢西县试点研究中确定的权重，因与NEEPP区域的地质/水文条件高度相似，被认为适用于该区域。若区域不具备此类相似条件，则参数相对权重可能不适用。 通过加权叠加法整合上述参数对应的地理空间数据集，最终生成LANLoad NEEPP数据集。在NEEPP区域内随机选取的分层点位上，对LANLoad NEEPP的性能进行了评估。LANLoad NEEPP的分值区间被划分为"低可能性"（分值≤4）与"高可能性"（分值≥6）两类。 我们采用两种独立的盲评方法对该分类结果进行验证：其一，主题专家凭借其专业判断对30个点位进行评估，该专家评审结果与LANLoad NEEPP分类结果的一致性达92%。其二，采用地下水数值模型ArcNLET-Py对10个点位开展均匀营养物质负荷模拟，共分析500个模型节点。结果显示，LANLoad NEEPP分类结果与模拟结果完全一致：被LANLoad NEEPP标记为"高可能性"的点位，其模拟营养负荷均为最高；而"低可能性"点位的模拟营养负荷均为最低。 LANLoad NEEPP基于ArcGIS Pro 3.5.2（ESRI公司）开发，分辨率为9.6米，采用NAD83（2011）基准面与佛罗里达GDL阿尔伯斯椭球体：GRS 1980投影坐标系。针对导水率、地下水埋深、国家洪水风险图层以及佛罗里达表层地质地理空间数据集，本研究采用标准地理处理工作流与权威参考资料对数据进行清洗、填补空间缺失值并剔除空值。由源数据衍生的水体、距水体距离以及坡度三类地理空间数据集，由Balmoral集团与南佛罗里达大学生态水文学研究组合作开发。 表1：LANLoad NEEPP所纳入的地理空间数据集（2026） 缩写说明：联邦紧急事务管理局（Federal Emergency Management Agency, FEMA）、佛罗里达环境保护部（Florida Department of Environmental Protection, DEP）、美国自然资源保护局（National Resources Conservation Service, NRCS）、美国地质调查局（United States Geological Survey, USGS）、南佛罗里达大学生态水文学研究组（University of South Florida - Ecohydrology Research Group, USF-ERG） 参数、地理空间数据集、数据来源、获取日期： 1. 水体：佛罗里达国家水文数据集水体多边形，佛罗里达环境保护部（DEP），2026年3月 2. 水体：佛罗里达国家水文数据集区域多边形，佛罗里达环境保护部（DEP），2026年3月 3. 水体：佛罗里达国家水文数据集水流线，佛罗里达环境保护部（DEP），2026年3月 4. 土壤调查地理数据集（SSURGO）- 佛罗里达，美国自然资源保护局（NRCS），2026年3月 5. 全州土地利用/土地覆盖（代码5000与6000），佛罗里达环境保护部（DEP），2026年3月 6. 距水体距离：水体数据集，Balmoral集团，2026年3月 7. 数字高程模型（DEM），美国地质调查局（USGS），2026年3月 8. 地下水埋深：土壤调查地理数据集（SSURGO）- 佛罗里达，美国自然资源保护局（NRCS），2026年3月 9. 导水率：土壤调查地理数据集（SSURGO）- 佛罗里达，美国自然资源保护局（NRCS），2026年3月 10. 洪水潜势：国家洪水风险图层，联邦紧急事务管理局（FEMA），2026年3月 11. 坡度：距水体距离数据集，Balmoral集团，2026年5月；数字高程模型（DEM），美国地质调查局（USGS），2026年3月 12. 表层地质：佛罗里达表层地质，佛罗里达环境保护部（DEP），2025年11月 联系方式：Kai C. Rains，博士，PWS——krains@usf.edu 数据集引用：Rains, Kai; Guerron-Orejuela, Edgar; Davis, Sara; Okonkwo, Moses; Rains, Mark (2026)，"LANLoad NEEPP：北佛罗里达大沼泽地与河口保护计划（NEEPP）区域水体营养负荷景观评估（LANLoad）数据集"，南佛罗里达大学，版本v03，doi: 10.17632/7nw285j9bk.3 许可协议：CC BY 4.0 相关链接：南佛罗里达大学生态水文学研究组LANLoad第三阶段最终报告、佛罗里达地理信息办公室标识：
