Local storage dynamics of individual wetlands predict landscape scale discharge

Data Abstract: These data are posted in support of a recent paper (Klammler et al. 2020 in WRR) that describe a reduced-complexity catchment model framework for wetlandscapes with a demonstration in Big Cypress National Preserve, Florida. The data files consist of a spreadsheet with the hydrologic data utilized, a folder of the raw LiDAR subsets utilized to calculate inundation statistics, and a folder of the ECDF's that were calculated from processed LiDAR subsets.

Paper Abstract: Wetlands provide valuable hydrological, ecological, and biogeochemical functions, both alone and in combination with other elements comprising wetlandscapes (i.e., low-relief landscapes with significant distributed surface water storage). Understanding the processes and mechanisms that create wetlandscape functions, as well as their sensitivity to natural and man-made alterations, requires a sound physical understanding of wetland hydrodynamics. Here, we develop and apply a single reservoir hydrologic model to a low-relief karst wetlandscape in southwest Florida (≈ 103 km^2 of Big Cypress National Preserve) using precipitation P and potential evapotranspiration PET as climatic drivers. This simple reduced-complexity approach captures the dynamics of individual wetland storage across the entire wetlandscape and accurately predicts landscape discharge. Key model insights are the primacy of depth-dependent extinction of evapotranspiration ET, and the negligible effects of depth-dependent specific yield, effects of which are averaged by landscape roughness. We identify three phases of the wetlandscape hydrological regime: dry, wet-stagnant, and wet-flowing. The reduced-complexity model allowed a simple steady-state analysis, which demonstrated the consistent and sudden seasonal shifting between wet-stagnant and wet-flowing states indicating thresholds when P ≈ PET. Notably, stage data from any single wetland appears sufficient for accurate whole-landscape discharge prediction, reflecting the relative homogeneity in timing and duration of local wetland hydrologic connectivity in this landscape. We also show that this method will be transferable to other wetlandscapes, where individual storage elements are hydrologically synchronous, whereas model performance is expected to deteriorate for hydrologically more heterogeneous wetlandscapes.