Bed form‐induced hyporheic exchange flux (qH) is increasingly viewed as a key process controlling water fluxes and biogeochemical processes in river networks. Despite the fact that streambeds are inherently heterogeneous, the majority of bed form flume‐scale studies were done on homogeneous systems. We conducted salt and dye tracer experiments to study the effects of losing and gaining flow conditions on qH using a laboratory recirculating flume system packed with a heterogeneous streambed, and equipped with a drainage system that enabled us to apply losing or gaining fluxes. We found that when either losing or gaining fluxes increased (regardless of whether the flux was upward or downward), qH followed an exponential decline, the volume of the hyporheic flow cell drastically reduced, and the mean residence times declined moderately. A numerical flow model for the heterogeneous streambed was set up and fitted against the experimental data in order to test whether an equivalent homogeneous case exists. The measured qH were accurately predicted with the heterogeneous model, while it was underestimated using a homogeneous model characterized by the geometric mean of the hydraulic conductivity. It was also shown that in order to produce the results of the heterogeneous model with an equivalent hydraulic conductivity, the latter had to be increased as the losing or gaining fluxes increase. The results strongly suggest that it is critical to adequately account for the heterogeneous streambed structure in order to accurately predict the effect of vertical exchange fluxes between the stream and groundwater on hyporheic exchange.
Optical sensing technologies provide opportunities for in situ oxygen sensing capable of capturing the whole range of spatial and temporal variability. We developed a miniaturized Distributed Oxygen Sensor ("mDOS") specifically for long-term in situ application in soil and sediment. The mDOS sensor system enables the unattended, repeated acquisition of time series of in situ oxygen profiles at a subcentimeter resolution covering a depth of up to one meter. As compared to existing approaches, this provides the possibility to reveal highly variable and heterogeneous oxygen dynamics at a high, quasi-continuous resolution across both scales. The applicability of the mDOS to capture both intra- and interday fine-scale variability of spatiotemporal oxygen dynamics under varying hydrological conditions is exemplarily demonstrated. We specifically aim at estimating the dependency between oxygen dynamics and hydrologic conditions along the measured profiles. The mDOS system enables highly detailed insights into oxygen dynamics in various aquatic and terrestrial environments and in the inherent transition zones between them. It thus represents a valuable tool to capture oxygen dynamics to help disentangling the coupling between underlying hydrological and biogeochemical process dynamics.
Abstract. Automatic samplers represent a convenient way to gather
rain samples for isotope (δ18O and δ2H) and water
quality analyses. Yet, most commercial collectors are expensive and do not
reduce post-sampling evaporation and the associated isotope fractionation
sufficiently. Thus, we have developed a microcontroller-based automatic rain
sampler for timer-actuated collection of integral rain samples. Sampling
periods are freely selectable (minutes to weeks), and the device is low-cost,
simple, robust, and customizable. Moreover, a combination of design features
reliably minimizes evaporation from the collection bottles. Evaporative
losses were assessed by placing the pre-filled sampler in a laboratory oven
with which a diurnal temperature regime (21–31 ∘C) was simulated
for 26 weeks. At the end of the test, all bottles had lost less than 1 %
of the original water amount, and all isotope shifts were within the
analytical precision. These results show that even multi-week field deployments of the device
would result in rather small evaporative mass losses and isotope shifts.
Hence, we deem our sampler a useful addition to devices that are currently
commercially available and/or described in the scientific literature. To
enable reproduction, all relevant details on hard- and software are openly
accessible.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.