Longitudinal propagation of aquatic disturbances following the largest wildfire recorded in New Mexico, USA.

Wildfire disturbance propagation along fluvial networks remains poorly understood. We use incident, atmospheric, and water-quality data from the largest wildfire in New Mexico's history to quantify how this gigafire affected surface runoff processes and mobilized wildfire disturbances into fluvial networks after burning 1382 km2. Surface runoff post-fire increased compared to pre-fire conditions, and precipitation events that are frequently observed in the affected watershed (<2-year recurrence) and fell during the post-fire first rainy season resulted in uncorrelated, less frequently observed runoff events (10-year recurrence). Besides these shifts in runoff generation, the magnitude and fluctuation of daily water quality parameters and relevant ecosystem processes also shifted over multiple months, even at sites located >160 km downstream of the burn perimeter. Our findings emphasize the need to incorporate spatially resolved longitudinal sampling designs into wildfire water quality research and highlight the spatiotemporal co-dependency among atmospheric, terrestrial, and aquatic processes in defining the net outcome of wildfire disturbance propagation along impacted fluvial networks.

Evidence of deviations between experimental and empirical mixing lengths: Multi-discharge field tests in an arid river system.

Despite advances in wastewater treatment plant (WWTP) efficiencies, multiple contaminants of concern, such as microplastics, pharmaceuticals, and per- and poly-fluoroalkyl substances (PFAS) remain largely untreated near discharge points and can be highly concentrated before they are fully mixed within the receiving river. Environmental agencies enforce mixing zone permits for the temporary exceedance of water quality parameters beyond targeted control levels under the assumption that contaminants are well-mixed and diluted downstream of mixing lengths, which are typically quantified using empirical equations derived from one-dimensional transport models. Most of these equations were developed in the 1970s and have been assumed to be standard practice since then. However, their development and validation lacked the technological advances required to test them in the field and under changing flow conditions. While new monitoring techniques such as remote sensing and infrared imaging have been employed to visualize mixing lengths and test the validity of empirical equations, those methods cannot be easily repeated due to high costs or flight restrictions. We investigated the application of Lagrangian and Eulerian monitoring approaches to experimentally quantify mixing lengths downstream of a WWTP discharging into the Rio Grande near Albuquerque, New Mexico (USA). Our data spans river to WWTP discharges ranging between 2-22x, thus providing a unique dataset to test long-standing empirical equations in the field. Our results consistently show empirical equations could not describe our experimental mixing lengths. Specifically, while our experimental data revealed "bell-shaped" mixing lengths as a function of increasing river discharges, all empirical equations predicted monotonically increasing mixing lengths. Those mismatches between experimental and empirical mixing lengths are likely due to the existence of threshold processes defining mixing at different flow regimes, i.e., jet diffusion at low flows, the Coanda effect at intermediate flows, and turbulent mixing at higher flows, which are unaccounted for by the one-dimensional empirical formulas. Our results call for a review of the use of empirical mixing lengths in streams and rivers to avoid widespread exposures to emerging contaminants.

Development of The Navigator: A Lagrangian sensing system to characterize surface freshwater ecosystems.

Most freshwater aquatic studies rely on Eulerian monitoring, i.e., water quality and quantity are monitored using grab samples or semi-continuous sensors deployed at fixed cross-sections. While Eulerian monitoring is practical, it provides a limited understanding of spatial and temporal heterogeneity. We designed and built The Navigator, a Lagrangian (i.e., along a flow path) monitoring system that offers cost-effective solutions for in-situ, real-time data collection in surface freshwater ecosystems. The Navigator features a suite of technologies, including an autonomous surface vehicle with GPS and LTE connectivity, water quality sensors, a depth sonar, a camera, and a webpage dashboard to visualize real-time data. With these technologies, The Navigator provides insight into where, how, and why water quality and quantity change over time and space as it moves with the current or follows user-specified pathways. We tested The Navigator monitoring water quality parameters at high spatial-temporal resolution in multiple surface water bodies in New Mexico (USA) to: (1) identify water quality changes associated with land use changes along a 7th-order reach in the Rio Grande, (2) identify the fate of wildfire disturbances ∼175 km downstream of a burned watershed affected by the largest wildfire ever recorded in the state, (3) monitor the water quality of a recreational fishing pond in the City of Albuquerque. Our three successful tests confirm that The Navigator is an affordable (USD 5,101 in 2023) monitoring system that can be used to address questions involving mass and energy balances in surface waters.