Introduction
Sea level rise and channel-deepening projects can increase saltwater intrusion in coastal estuaries, which can reshape estuarine habitat over time. In our case study on the Lower St. Johns River Estuary (Florida), we used EFDC+ and the EFDC_Explorer Modeling System to (1) model long-term salinity intrusion and (2) translate modeled salinity patterns into actionable habitat indicators for submerged aquatic vegetation (SAV) and wetlands. Full technical details—including setup choices, calibration/validation periods, and performance tables—are provided in our published article: Estuarine Salinity Intrusion and Implications for Aquatic Habitat: A Case Study of the Lower St. Johns River Estuary, Florida (Mathis et al., 2019).
What We Built
DSI developed a 3D hydrodynamic + salinity model using EEMS and ran simulations with EFDC+. The model domain extends from the open ocean (about 25 miles offshore of Mayport, Florida) to roughly 120 miles upstream to Lake George and Crescent Lake. Figure 1 shows the extent of model domain with stations we used for driving the model and calibration/validation processes. The model consists of 19,882 cells with a maximum of 4 vertical layers. We used the Sigma-Zed (SGZ) vertical layering approach so deeper areas had appropriate vertical resolution while maintaining computational efficiency for large, long-duration runs. The table below shows model grid information.
| Property | Average | Minimum | Maximum |
|---|---|---|---|
| Cell Length (m) | 327.2 | 12.1 | 1,944.9 |
| Cell Width (m) | 307.3 | 5.4 | 1,405.3 |
| Cell Area (m²) | 172,516 | 372.2 | 2,225,209 |
| Orthogonal Deviation (°) | -0.09 | -23.46 | 17.0 |
Result #1: Identifying Drivers of Salinity Intrusion
Using the production run results, we analyzed how far upstream salinity intruded by tracking the upstream distance of the 2 ppt isohaline through time shown in Figure 2. Over the production period, the 2 ppt isohaline typically ranged about 20 to 80 miles upstream of the river mouth, which provides an intuitive “intrusion extent” indicator that can be compared across scenarios. The freshwater inflow from upstream (blue, lower panel) shows a negative correlation with the 2 ppt isohaline (blue, upper panel), meaning when strong freshwater enters upstream, the 2 ppt isohaline was pushed downstream, especially during the storm period (grey bands). Statistically, freshwater inflow showed the strongest relationship with intrusion extent with a R² value of 0.5, while wind speed and regional tidal forcing showed much weaker correlations (R²<0.1), helping focus scenario testing on the drivers that’s most likely to move the needle.
Result #2: Translating Salinity into Habitat Indicators
The most decision-useful step is turning salinity fields into simple exposure metrics that align with how habitat responds over time. We selected a set of littoral cells representing existing and potential SAV beds and computed acres per day above salinity thresholds using a conservative 90-day running average. Thresholds used in the study were 3, 5, 10, 15, and 25 ppt, which turns a complex 3D model result into a concise “how much area is exposed, and how often” summary.
For wetlands, we classified shoreline cells by the percentage of daily high-tide salinity values exceeding 1 ppt into tidal swamp (<12%), transitional (12–25%), and tidal marsh (>25%) as shown in Figure 3. The production run shows a relatively short transition zone to buffer the freshwater wetlands from increase in salinity over longer periods of time. As development continues to encroach on wetland habitat around Jacksonville, changes in the volume of upstream inflow or the contents of that inflow could have important effects on the long-term sustainability of these aquatic ecosystems.
For Our Users
This case study demonstrates how to bridge the gap between physics-based simulation and habitat management with the aid of EFDC_Explorer Modeling System. Once calibrated, the model becomes a baseline for comparing management alternatives and future-change scenarios (for example: flow changes, sea level rise, navigation modifications) using consistent metrics for intrusion extent and habitat stress/exceedance. Practically, this means you can move from “What does salinity do?” to “Which areas cross thresholds, how often, and under which scenario?” using a similar workflow.
For complete model setup, calibration/validation detail, and the full habitat post-processing methodology, read the full paper: (PDF) Estuarine Salinity Intrusion and Implications for Aquatic Habitat… (Mathis et al., 2019) — ResearchGate.
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