From wetlands to wetlandscapes: Remote sensing calibration of process‐based hydrological models in heterogeneous landscapes. Issue 11 (1st November 2022) - Mullen, Connor; Bertassello, Leonardo E.; Rao, P. Suresh C.; Müller, Marc F.
Abstract: Wetlands are vital components of landscapes that sustain a range of important ecosystem services. Understanding how wetland‐rich landscapes—or wetlandscapes—will evolve under a changing climate and increasing anthropogenic encroachment is urgent. Wetlandscapes are highly heterogeneous, and scaling local modelling insights from individual instrumented wetlands to characterize landscape‐scale dynamics has been a pervasive challenge. We investigate the potential to use water extent information from satellite imagery to calibrate landscape‐scale process‐based hydrological models. Applications to wetlandscapes in the Prairie Pothole Region (PPR) in North Dakota and the Texas Playa Lakes (TPL) shed light on two important trade‐offs. First, in‐situ monitoring provides accurate water extent information on an arbitrary subset of wetlands, whereas satellite imagery captures landscape‐scale hydrological dynamics but suffers persistent water‐detection challenges. Satellite imagery is a superior source of data for model calibration in sparsely monitored and spatially heterogeneous landscapes like the PPR, where the sampling uncertainty of monitored wetlands exceeds the water detection uncertainty of remote sensing. The two data sources are equivalent for more homogeneous landscapes like the TPL. The second tradeoff concerns the spatial resolution and temporal coverage of satellite imagery. In that regard, the 20 years of bi‐weekly images captured by Landsat 7 provides unprecedented insights into the dynamic nature of the ecohydrological characteristics of wetlandscapes, such as seasonal and inter‐annual changes of their metapopulation capacity. In the PPR, the amplitude of these dynamics far exceeds the bias introduced by Landsat's inability to capture ecologically important connectivity details due to its coarse spatial resolution compared to more recent imagery. Abstract : Monthly water masks derived from satellite images are used to calibrate landscape‐scale hydrologic wetlandscape models. Compared to instrumented wetland data, remote sensing images have higher detection errors but no sampling biases. The longer coverage of Landsat 7 captures dominant temporal dynamics of wetlandscapes despite its comparatively coarse resolution.