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The Everglades Depth Estimation Network (EDEN) is an integrated network of real-time water-level monitoring, groundelevation modelling, and water-surface modelling that provides scientists and water managers with current (2000-present), on-line water-level and water-depth information for the freshwater Everglades. Continuous daily spatial interpolations of surface water-level gage data from the EDEN water-surface model are presented on grid with 400-m spacing. The direct model output is continuous daily surface-water level, and other hydrologic data such as water depth and hydroperiod can be derived together with ground digital elevation models.This paper validated the spatially continuous EDEN water-surface model for the Everglades, Florida by using an independent field-measured dataset. Three model applications were also demonstrated: to estimate site-specific ground elevation, to create water-depth time series for tree islands, and to generate contiguous water coverage areas. We found that there were no statistically significant differences between model-predicted and field-observed water-level data in central Everglades (p D 0Ð51). Over 95% of the predicted-water levels matched observed-water levels within the range of š5 cm. Overall, the model is reliable by a root mean square error (RMSE) of 3Ð3 cm.The accurate, high-resolution hydrological data, generated over broad spatial and temporal scales by the EDEN watersurface model, provides a previously missing key to understanding the habitat requirements and linkages among native and invasive populations, including fish, wildlife, wading birds, and plants. The EDEN model is a powerful tool that could be adapted for other ecosystem-scale restoration and management programs worldwide.

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