In the majority of existing studies, streams are conceived as static objects that occupy predefined regions of the landscape. However, empirical observations suggest that stream networks are systematically and ubiquitously featured by significant expansion/retraction dynamics produced by hydrologic and climatic variability. This contribution presents novel empirical data about the active drainage network dynamics of a 5 km 2 headwater catchment in the Italian Alps. The stream network has been extensively monitored with a biweekly temporal resolution during a field campaign conducted from July to November 2018. Our results reveal that, in spite of the wet climate typical of the study area, more than 70% of the observed river network is temporary, with a significant presence of disconnected reaches during wet periods. Available observations have been used to develop a set of simple statistical models that were able to properly reconstruct the dynamics of the active stream length as a function of antecedent precipitation. The models suggest that rainfall timing and intensity represent major controls on the stream network length, while evapotranspiration has a minor effect on the observed intraseasonal changes of drainage density. Our results also indicate the presence of multiple network expansion and retraction cycles that simultaneously operate at different time scales, in response to distinct hydrological processes. Furthermore, we found that observed spatial patterns of network dynamics and unchanneled lengths are related to the underlying heterogeneity of geological attributes. The study offers novel insights on the physical mechanisms driving stream network dynamics in low-order alpine catchments.

Natural wetlands are ecological, biogeochemical, and hydrological hot spots yet continue to disappear under human pressure. Their shapes and sizes control their hydroecological functions. We propose that elevation data can be used to delineate potential wetlands and that the (statistical) distributions of potential wetlands should be identical to the distributions of actual wetlands. We compare the shape and size distributions of wetlands reported in the National Wetland Inventory with those of potential wetlands identified using a topographic depression identification model. We estimated area and perimeter distributions as well as shoreline fractal dimension in six contrasting locations in the United States. Pareto distributions described the tails of these distributions, with similar slopes for both model and data. The shape of shorelines was also similar, and their fractal dimension clustered around D = 4/3, a pervasive value in nature. We also analyzed the entire wetland inventory data set for the conterminous United States (~20 million wetlands) for reference and found the statistics to be invariant across scales. Our results demonstrate that a simple topographic model can identify most reported wetlands as well as potential wetlands missing from the inventory. These findings could inform strategic surveys and the conservation of wetlandscapes.

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Wetlands play an important role in watershed eco‐hydrology. The occurrence and distribution of wetlands in a landscape are affected by the surface topography and the hydro‐climatic conditions. Here, we propose a minimalist probabilistic approach to describe the dynamic behaviour of wetlandscape attributes, including number of inundated wetlands and the statistical properties of wetland stage, surface area, perimeter, and storage volume. The method relies on two major assumptions: (a) wetland bottom hydrologic resistance is negligible; and (b) groundwater level is parallel to the mean terrain elevation. The approach links the number of inundated wetlands (depressions with water) to the distribution of wetland bottoms and divides, and the position of the shallow water table. We compared the wetlandscape attribute dynamics estimated from the probabilistic approach to those determined from a parsimonious hydrologic model for groundwater‐dominated wetlands. We test the reliability of the assumptions of both models using data from six cypress dome wetlands in the Green Swamp Wildlife Management Area, Florida. The results of the hydrologic model for groundwater‐dominated wetlands showed that the number of inundated wetlands has a unimodal dependence on the groundwater level, as predicted by the probabilistic approach. The proposed models provide a quantitative basis to understand the physical processes that drive the spatiotemporal hydrologic dynamics in wetlandscapes impacted by shallow groundwater fluctuations. Emergent patterns in wetlandscape hydrologic dynamics are of key importance not only for the conservation of water resources, but also for a wide range of eco‐hydrological services provided by connectivity between wetlands and their surrounding uplands.