LANLoad NEEPP: Landscape Assessment of Nutrient Loading to Waterbodies (LANLoad) in the Northern Everglades and Estuaries Protection Program (NEEPP) region
Description
LANLoad is a geospatial screening tool designed to facilitate water quality management decisions. It provides an estimate of the relative likelihood that nutrient inputs applied at specific locations on land will impact water quality. LANLoad is based solely on physical characteristics and may be used independently or with other relevant datasets. LANLoad NEEPP was developed by the USF Ecohydrology Research Group in collaboration with the FDEP (OEAT). A publication is in review (Guerron-Orejuela et al.) and additional process documentation is available in the dataset metadata. LANLoad NEEPP is available as a single comprehensive file "LANLoad_NEEPP_Overall" and as subsets corresponding to intersections between NEEPP and 15 FL counties. The datasets consist of cells (9.6 m x 9.6 m) ranked to reflect the likelihood that nutrients applied to a given location will reach a 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 6 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. However, LANLoad NEEPP can be used to gauge the likelihood of nutrient transport to surface waterbodies from other, similar, nutrient sources. The resulting AHP model had high internal consistency (Consistency Ratio: 0.01) and returned the following parameter weights: • Distance to Waterbody, 30.0% • Depth to Water, 21.6% • Hydraulic Conductivity, 20.7% • Potential for Flooding, 10.9% • Slope, 9.8% • Surficial Karstic Deposits, 7.0% Geospatial datasets representative of these parameters were acquired (2025 & 2026) and combined using a weighted overlay to produce LANLoad NEEPP. Performance was evaluated at multiple locations (selected via a random stratified process) within NEEPP by classifying LANLoad ranks less than or equal to 4 as “lower” and those more than or equal to 6 as “higher”. Then, 2 assessment methods were applied, both conducted blind: 1) SMEs evaluated 30 locations using best professional judgment while viewing only the underlying datasets. There was a 92% consistency rate with LANLoad NEEPP classifications. 2) The groundwater numerical model ArcNLET-Py was used to simulate uniform nutrient loading in 10 subregions containing at a total of 500 model points. This yielded a 100% consistency rate with the LANLoad NEEPP classifications where subregions identified by LANLoad NEEPP as "higher likelihood" corresponded with the highest modeled cumulative nutrient loads, while "lower likelihood" locations matched the lowest modeled cumulative nutrient loads. Contact: Kai Rains, PhD, PWS USF Ecohydrology Research Group
Files
Steps to reproduce
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. The geospatial datasets incorporated in LANLoad NEEPP (2026) were obtained in 2025 & 2026 from: Florida Department of Environmental Protection (DEP), Federal Emergency Management Agency (FEMA), Florida Geological Survey (FGS), National Resources Conservation Service (NRCS), and the U.S. Geological Survey (USGS). Standard geoprocessing workflows and authoritative reference materials were utilized to cleanse data, fill spatial gaps, and eliminate null values in source datasets prior to use. 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. Additional details are available in the metadata that accompanies each geospatial dataset.
Institutions
- University of South FloridaFlorida, Tampa
Categories
Funders
- Florida Department of Environmental ProtectionGrant ID: AT020, AT015