Modeling Connectivity of Non‐floodplain Wetlands: Insights, Approaches, and Recommendations

Abstract

Representing hydrologic connectivity of non‐floodplain wetlands (NFWs) to downstream waters in process‐based models is an emerging challenge relevant to many research, regulatory, and management activities. We review four case studies that utilize process‐based models developed to simulate NFW hydrology. Models range from a simple, lumped parameter model to a highly complex, fully distributed model. Across case studies, we highlight appropriate application of each model, emphasizing spatial scale, computational demands, process representation, and model limitations. We end with a synthesis of recommended “best modeling practices” to guide model application. These recommendations include: (1) clearly articulate modeling objectives, and revisit and adjust those objectives regularly; (2) develop a conceptualization of NFW connectivity using qualitative observations, empirical data, and process‐based modeling; (3) select a model to represent NFW connectivity by balancing both modeling objectives and available resources; (4) use innovative techniques and data sources to validate and calibrate NFW connectivity simulations; and (5) clearly articulate the limits of the resulting NFW connectivity representation. Our review and synthesis of these case studies highlights modeling approaches that incorporate NFW connectivity, demonstrates tradeoffs in model selection, and ultimately provides actionable guidance for future model application and development.

Assessment of Surface Hydrological Connectivity in an Ungauged Multi-Lake System with a Combined Approach Using Geostatistics and Spaceborne SAR Observations

“…However, it is often time-consuming and costly to detect all hydrological connections across an entire basin or even a sub-basin through this method [10]. Hydrological models can be used to extend the empirical findings of hydrological connectivity to larger spatiotemporal scales under diverse scenarios of system change [11][12][13][14], and are therefore particularly useful for hindcasting and forecasting hydrological connectivity at defined spatiotemporal scales [15]. However, hydrological models may suffer from over-parameterization and equifinality (i.e., when different parameter sets lead to similar simulation results) [16].…”

Featured Collection Introduction: The Emerging Science of Aquatic System Connectivity II

“…Jones, Ameli, et al. () review the current capabilities of hydrologic models and their ability to simulate hydrologic connectivity of non‐floodplain wetlands. They present four distinct case studies that employ process‐based models which vary in complexity, spatial representation of hydrologic processes, and fidelity (i.e., the models ability to faithfully represent reality).…”

“…Jones, Ameli, et al. () ends with a synthesis of five best modeling practices to guide future model application and development.…”

“…In contrast to Ameli and Creed (2019), Green et al (2019) determined the drained upland depressions in this region have insufficient storage capacity to significantly alter regional and local flood events. Jones, Ameli, et al (2019) review the current capabilities of hydrologic models and their ability to simulate hydrologic connectivity of non-floodplain wetlands. They present four distinct case studies that employ process-based models which vary in complexity, spatial representation of hydrologic processes, and fidelity (i.e., the models ability to faithfully represent reality).…”

“…They present four distinct case studies that employ process-based models which vary in complexity, spatial representation of hydrologic processes, and fidelity (i.e., the models ability to faithfully represent reality). Jones, Ameli, et al (2019) ends with a synthesis of five best modeling practices to guide future model application and development.…”