No abstract

Rivers are important ecosystems under continuous anthropogenic stresses. The hyporheic zone is a ubiquitous, reactive interface between the main channel and its surrounding sediments along the river network. We elaborate on the main physical, biological, and biogeochemical drivers and processes within the hyporheic zone that have been studied by multiple scientific disciplines for almost half a century. These previous efforts have shown that the hyporheic zone is a modulator for most metabolic stream processes and serves as a refuge and habitat for a diverse range of aquatic organisms. It also exerts a major control on river water quality by increasing the contact time with reactive environments, which in turn results in retention and transformation of nutrients, trace organic compounds, fine suspended particles, and microplastics, among others. The paper showcases the critical importance of hyporheic zones, both from a scientific and an applied perspective, and their role in ecosystem services to answer the question of the manuscript title. It identifies major research gaps in our understanding of hyporheic processes. In conclusion, we highlight the potential of hyporheic restoration to efficiently manage and reactivate ecosystem functions and services in river corridors.

[1] Streambed seepage can be predicted using an analytical solution to the one-dimensional heat transport equation to take advantage of the relationship between streambed thermal properties, seepage flux, and the amplitude ratio and phase shift associated with streambed temperature signals. This paper explores the accuracy of streambed-seepage velocity estimates from this method when uncertainty in input parameters exists. Uncertainty in sensor spacing, thermal diffusivity, and the accuracy of temperature sensors were examined both individually and in combination using Monte Carlo analysis. The analytical solution correctly reproduced known thermal front velocities above 1.25 m d À1 , using both the amplitude-ratio and phase-shift methods, despite introduced uncertainty in any of the variables. Noise in temperature measurements (because of sensor accuracy) caused erroneous prediction of velocity for gaining stream conditions using both the amplitude ratio and phase shift. Uncertainty in the thermal diffusivity and sensor spacing resulted in incorrect velocity, primarily under gaining conditions, when using the amplitude ratio and near-zero velocity using the phase shift. For a sensor accuracy of 0.15 C, we present combinations of parameters for which the resulting signal amplitude is sufficiently large for use with the Stallman equation.