LANLoad NEEPP - St. Lucie 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（raster dataset）由分辨率为9.6米×9.6米的像元（cells）组成，其分级结果用于反映施用于某一陆地区域的营养物质抵达最近的下坡向地表水体（downgradient surface waterbody）的可能性。分级取值范围为1至9，数值越高，营养物质输送至下坡向地表水体的可能性就越大。 该分级基于主题专家（Subject Matter Experts, SMEs）遴选的6项自然景观参数，主题专家还通过层次分析法（Analytical Hierarchy Process, AHP）为各参数赋予了相对权重。本次研究的试点区域为佛罗里达州圣露西县（St. Lucie County, FL），重点关注的营养物质来源为就地污水处理与处置系统（Onsite Sewage and Treatment Disposal Systems, OSTDS）。尽管最初的研究聚焦于就地污水处理与处置系统，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。 本次构建的层次分析法模型内部一致性极高（一致性比率：0.01），按重要性排序得到如下参数及权重：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%）。由于圣露西县试点区域与北奥基乔比湖与河口保护计划（Northern Everglades and Estuaries Protection Program, NEEPP）区域的地质/水文条件高度相似，因此主题专家赋予的参数权重可适用于NEEPP区域；若区域地质水文条件不具备此类相似性，则该相对参数权重可能不适用。 研究团队通过加权叠加法（weighted overlay）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区域内的随机分层采样点上，对LANLoad NEEPP的性能进行了评估。将LANLoad NEEPP的分级结果划分为“低可能性”（LANLoad NEEPP分级≤4）与“高可能性”（LANLoad NEEPP分级≥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个采样点进行评估，专家评审结果与LANLoad NEEPP分类结果的一致性达92%；其二，使用地下水数值模型（groundwater numerical model）ArcNLET-Py对10个采样点开展均匀营养物质负荷模拟，共分析500个模型点，结果显示，LANLoad NEEPP识别的“高可能性”区域与模拟得到的最高营养物质负荷区域完全对应，“低可能性”区域则与模拟得到的最低营养物质负荷区域完全对应，二者一致性达100%。 LANLoad NEEPP于ArcGIS Pro 3.5.2（ESRI）中开发，分辨率为9.6米，采用NAD83 (2011) 基准面（NAD83 (2011) Datum）与佛罗里达GDL阿尔伯斯椭球体：GRS 1980投影坐标系（Florida GDL Albers Ellipsoid: GRS 1980 projection）。本研究采用标准地理处理工作流（geoprocessing workflows）与权威参考资料，对导水率、地下水埋深、国家洪水风险图层（National Flood Hazard Layer）以及佛罗里达州表层地质地理空间数据集进行数据清洗、空间间隙填充与空值（null values）剔除。其中，水体、距水体距离与坡度这3项源自主数据的地理空间数据集由巴尔莫勒尔集团（Balmoral Group）与南佛罗里达大学生态水文学研究组（University of South Florida - Ecohydrology Research Group）合作开发。 “表1：LANLoad NEEPP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）、佛罗里达州环境保护部（Florida Department of Environmental Protection, DEP）、自然资源保护服务局（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）。各数据集详情如下： 1. 水体：佛罗里达州NHD水体多边形（Florida NHD Waterbody Polygons），来源：DEP，获取日期：2026年3月 2. 佛罗里达州NHD面积多边形（Florida NHD Area Polygons），来源：DEP，获取日期：2026年3月 3. 佛罗里达州NHD流线（Florida NHD Flowlines），来源：DEP，获取日期：2026年3月 4. 土壤调查地理数据集（Soil Survey Geographic Dataset, SSURGO）- 佛罗里达州，来源：NRCS，获取日期：2026年3月 5. 全州土地利用/土地覆盖（代码5000和6000），来源：DEP，获取日期：2026年3月 6. 距水体距离：以水体数据集为基础，来源：巴尔莫勒尔集团，获取日期：2026年3月 7. 数字高程模型（DEM），来源：USGS，获取日期：2026年3月 8. 地下水埋深：基于土壤调查地理数据集（SSURGO）- 佛罗里达州，来源：NRCS，获取日期：2026年3月 9. 导水率：基于土壤调查地理数据集（SSURGO）- 佛罗里达州，来源：NRCS，获取日期：2026年3月 10. 洪水潜势：国家洪水风险图层（National Flood Hazard Layer），来源：FEMA，获取日期：2026年3月 11. 坡度：由巴尔莫勒尔集团基于2026年5月获取的距水体距离数据以及USGS 2026年3月获取的数字高程模型生成 12. 表层地质：佛罗里达州表层地质（Surficial Geology of Florida），来源：DEP，获取日期：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: 北奥基乔比湖与河口保护计划（NEEPP）区域水体营养负荷景观评估工具（LANLoad）", 南佛罗里达大学, 版本03, DOI: 10.17632/7nw285j9bk.3 许可证：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；佛罗里达州地理信息办公室标识：
