Improved Prediction of Managed Water Flow into Everglades National Park Using Empirical Dynamic Modeling

A new approach using empirical dynamic modeling (EDM) significantly improves the accuracy and simplifies predictions of managed water flows into Everglades National Park. Unlike the previous linear model, which relied on six variables, EDM demonstrated that only two—upstream and downstream water levels—are necessary to forecast weekly target flows more effectively. This advancement addresses the nonlinear dynamics of flow drivers, enhancing management strategies under the Comprehensive Everglades Restoration Plan (CERP). The findings highlight the potential for more efficient hydrologic forecasting, benefiting both scientific research and practical conservation efforts in this critical ecosystem.

Saberski, E., Park, J., Hill, T., Stabenau, E., & Sugihara, G. (2022). Improved Prediction of Managed Water Flow into Everglades National Park Using Empirical Dynamic Modeling. Journal of Water Resources Planning and Management, 148(12). https://doi.org/10.1061/(asce)wr.1943-5452.0001598