Understanding patterns of expansion, contraction, and disconnection of headwater stream length in diverse settings is invaluable for the effective management of water resources as well as for informing research in the hydrology, ecology, and biogeochemistry of temporary streams. More accurate mapping of the stream network and quantitative measures of flow duration in the vast headwater regions facilitate implementation of water quality regulation and other policies to protect waterways. We determined the length and connectivity of the wet stream and geomorphic channel network in 3 forested catchments (<75 ha) in each of 4 physiographic provinces of the Appalachian Highlands: the New England, Appalachian Plateau, Valley and Ridge, and Blue Ridge. We mapped wet stream length 7 times at each catchment to characterize flow conditions between exceedance probabilities of <5% and >90% of the mean daily discharge. Stream network dynamics reflected geologic controls at both regional and local scales. Wet stream length was most variable at two Valley and Ridge catchments on a shale scarp slope and changed the least in the Blue Ridge. The density and source area of flow origins differed between the crystalline and sedimentary physiographic provinces, as the Appalachian Plateau and Valley and Ridge had fewer origins with much larger contributing areas than New England and the Blue Ridge. However, the length and surface connectivity of the wet stream depended on local lithology, geologic structure, and the distribution of surficial deposits such as boulders, glacially derived material, and colluival debris or sediment valley fills. Several proxies indicate the magnitude of stream length dynamics, including bankfull channel width, network connectivity, the base flow index, and the ratio of geomorphic channel to wet stream length. Consideration of geologic characteristics at multiple spatial scales is imperative for future investigations of flow intermittency in headwaters.

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A critical challenge for the Earth sciences is to trace the transport and flux of matter within and among aquatic, terrestrial, and atmospheric systems. Robust descriptions of isotopic patterns across space and time, called “isoscapes,” form the basis of a rapidly growing and wide‐ranging body of research aimed at quantifying connectivity within and among Earth's systems. However, isoscapes of rivers have been limited by conventional Euclidean approaches in geostatistics and the lack of a quantitative framework to apportion the influence of processes driven by landscape features versus in‐stream phenomena. Here we demonstrate how dendritic network models substantially improve the accuracy of isoscapes of strontium isotopes and partition the influence of hydrologic transport versus local geologic features on strontium isotope ratios in a large Alaska river. This work illustrates the analytical power of dendritic network models for the field of isotope biogeochemistry, particularly for provenance studies of modern and ancient animals.

Despite the advancement of remote sensing and geospatial technology in recent decades, maps of headwater streams continue to have high uncertainty and fail to adequately characterize temporary streams that expand and contract in the wet length. However, watershed management and policy increasingly require information regarding the spatial and temporal variability of flow along streams. We used extensive field data on wet stream length at different flows to create logistic regression models of stream network dynamics for four physiographic provinces of the Appalachian Highlands: New England, Appalachian Plateau, Valley and Ridge, and Blue Ridge. The topographic wetness index (TWI) was the most important parameter in all four models, and the topographic position index (TPI) further improved model performance in the Appalachian Plateau, Valley and Ridge, and Blue Ridge. We included stream runoff at the catchment outlet as a model predictor to represent the wetness state of the catchment, but adjustment of the probability threshold defining wet stream presence/absence to high values for low flows was the primary mechanism for approximating network extent at multiple flow conditions. Classification accuracy was high overall (> 0.90), and McFadden's pseudo R2 values ranged from 0.69 for the New England model to 0.79 in the Appalachian Plateau. More notable errors included an overestimation of wet stream length in wide valleys and inaccurate reach locations amid boulder deposits and along headwardly eroding tributaries. Logistic regression was generally successful for modeling headwater streams at high and low flows with only a few simple terrain metrics. Modification and application of this modeling approach to other regions or larger areas would be relatively easy and provide a more accurate portrayal of temporary headwaters than existing datasets. © 2018 John Wiley & Sons, Ltd.

Looking across a landscape, river networks appear deceptively static. However, flowing streams expand and contract following ever-changing hydrological conditions of the surrounding environment. Despite the ecological and biogeochemical value of rivers with discontinuous flow, deciphering the temporary nature of streams and quantifying their extent remains challenging. Using a unique observational dataset spanning diverse geomorphoclimatic settings, we demonstrate the existence of a general hierarchical structuring of river network dynamics. Specifically, temporary stream activation follows a fixed and repeatable sequence, in which the least persistent sections activate only when the most persistent ones are already flowing. This hierarchical phenomenon not only facilitates monitoring activities, but enables the development of a general mathematical framework that elucidates how climate drives temporal variations in the active stream length. As the climate gets drier, the average fraction of the flowing network decreases while its relative variability increases. Our study provides a novel conceptual basis for characterizing temporary streams and quantifying their ecological and biogeochemical impacts.