The morphology and abundance of streams control the rates of hydraulic and biogeochemical exchange between streams, groundwater, and the atmosphere. In large river systems, the relationship between river width and abundance is fractal, such that narrow rivers are proportionally more common than wider rivers. However, in headwater systems, where many biogeochemical reactions are most rapid, the relationship between stream width and abundance is unknown. To constrain this uncertainty, we surveyed stream hydromorphology (wetted width and length) in several headwater stream networks across North America and New Zealand. Here, we find a strikingly consistent lognormal statistical distribution of stream width, including a characteristic most abundant stream width of 32 ± 7 cm independent of discharge or physiographic conditions. We propose a hydromorphic model that can be used to more accurately estimate the hydromorphology of streams, with significant impact on the understanding of the hydraulic, ecological, and biogeochemical functions of stream networks.
Streamflow recession analysis is a widely used hydrologic tool that uses readily available discharge measurements to estimate otherwise unmeasurable watershed-scale properties, predict low flows, and parameterize many lumped hydrologic models. Traditional methods apply the simplifying assumptions of outflow from a Boussinesq aquifer, which predicts the slope of the recession curve relating streamflow to its derivative in log-log space to decrease from early-stage to late-stage recession. However, this prediction has not been validated in actual watersheds. Also, recent studies have shown that slopes of observed recession events are often much greater than traditional methods that predict with data point clouds. We analyze recession behavior of 1,027 streams from across the continental United States for periods of 10 to 118 years, identifying over 155,000 individual recession events. We find that the average slope of observed recession events is greater than that of the point cloud for all streams. Further, recession slopes of observed events decrease with time in only 10% of cases and instead increase with time in 74% of cases. We identify only nine watersheds where observed streamflow behavior often conforms to the predictions of traditional recession analysis, each of which is arid and flat with low permeability. Analysis of our extensive empirical results with a regionalization of catchment hydrologic characteristics indicates that heterogeneity of subsurface flow paths increases the nonlinearity and convexity of observed recession, likely as a function of watershed memory. The practical implications of our analysis are that streamflow is more stable during periods of extended drought than generally predicted.
Baseflow is often treated according to a unique storage‐discharge relationship. However, recent innovations in baseflow recession analysis have allowed novel findings regarding the variability of both the stability of baseflow and its nonlinearity (i.e., the concavity of the hydrograph), as well as the regional clustering of these characteristics. We investigate spatial and temporal patterns in the character of baseflow recession for over 1,000 watersheds in the continental United States. We discover seasonal patterns in both the stability and nonlinearity of baseflow which vary systematically across large regions. Further, we relate these baseflow characteristics to their potential physical drivers, including estimates of evapotranspiration, watershed storage, the distribution of watershed storage, and precipitation. While coincident watershed storage is the best predictor of baseflow stability in many regions (particularly the Appalachian Mountains), evapotranspiration from 2 to 3 months previous is the best predictor of baseflow stability in other regions (particularly the Pacific Northwest). We also discuss the novel finding that baseflow nonlinearity has increased significantly in most watersheds across the United States since 1980.
In headwater catchments, streamflow recedes between periods of rainfall at a predictable rate generally defined by a power–law relationship relating streamflow decay to streamflow. Research over the last four decades has applied this relationship to predictions of water resource availability as well as estimations of basin‐wide physiographic characteristics and ecohydrologic conditions. However, the interaction of biophysical processes giving rise to the form of these power–law relationships remains poorly understood, and recent investigations into the variability of streamflow recession characteristics between discrete events have alternatively suggested evapotranspiration, water table elevation, and stream network contraction as dominant factors, without consensus. To assess potential temporal variability and interactions in the mechanism(s) driving streamflow recession, we combine long‐term observational data from a headwater stream in the southern Appalachian Mountains with state and flux conditions from a process‐based ecohydrologic model. Streamflow recession characteristics are nonunique and vary systematically with seasonal fluctuations in both rates of transpiration and watershed wetness conditions, such that transpiration dominates recession signals in the early growing season and diminishes in effect as the water table elevation progressively drops below and decouples with the root zone with topographic position. As a result of this decoupling, there exists a seasonal hysteretic relationship between streamflow decay and both evapotranspiration and watershed wetness conditions. Results indicate that for portions of the year, forest transpiration may actively compete with subsurface drainage for the same water resource that supplies streamflow, though for extended time periods, these processes exploit distinct water stores. Our analysis raises concerns about the efficacy of assessing humid headwater systems using traditional recession analysis, with recession curve parameters treated as static features of the watershed, and we provide novel alternatives for evaluating interacting biological and geophysical drivers of streamflow recession.
Shallow aquifers are an important source of water resources and provide base flow to streams; yet actual rates of groundwater recharge are difficult to estimate. While climate change is predicted to increase the frequency and magnitude of extreme precipitation events, the resulting impact on groundwater recharge remains poorly understood. We quantify empirical relations between precipitation characteristics and episodic groundwater recharge for a wide variety of geographic and land use types across North Carolina. We extract storm duration, magnitude, average rate, and hourly weighted intensity from long-term precipitation records over periods of 12-35 years at 10 locations. Using time series of water table fluctuations from nearby monitoring wells, we estimate relative recharge to precipitation ratios (RPR) to identify statistical trends. Increased RPR correlates with increased storm duration, whereas RPR decreases with increasing magnitude, average rate, and intensity of precipitation. Agricultural and urban areas exhibit the greatest decrease in RPR due to increasing storm magnitude, average rate, and intensity, while naturally vegetated areas exhibit a larger increase in RPR with increased storm duration. Though RPR is generally higher during the winter than the summer, this seasonal effect is magnified in the Appalachian and Piedmont regions. These statistical trends provide valuable insights into the likely consequences of climate and land use change for water resources in subtropical climates. If, as predicted, growing seasons lengthen and the intensity of storms increases with a warming climate, decreased recharge in Appalachia, the Piedmont, and rapidly growing urban areas of the American Southeast could further limit groundwater availability.
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