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.

Apportioning sources of chemicals of emerging concern along an urban river with inverse modelling.

Concentrations of chemicals in river water provide crucial information for assessing environmental exposure and risks from fertilisers, pesticides, heavy metals, illicit drugs, pathogens, pharmaceuticals, plastics and perfluorinated substances, among others. However, using concentrations measured along waterways (e.g., from grab samples) to identify sources of contaminants and understand their fate is complicated by mixing of chemicals downstream from diverse diffuse and point sources (e.g., agricultural runoff, wastewater treatment plants). To address this challenge, a novel inverse modelling approach is presented. Using waterway network topology, it quantifies locations and concentrations of contaminant sources upstream by inverting concentrations measured in water samples. It is computationally efficient and quantifies uncertainty. The approach is demonstrated for 13 contaminants of emerging concern (CECs) in an urban stream, the R. Wandle (London, UK). Mixing (the forward problem) was assumed to be conservative, and the location of sources and their concentrations were treated as unknowns to be identified. Calculated CEC source concentrations, which ranged from below detection limit (a few ng/L) up to 1µg/L, were used to predict concentrations of chemicals downstream. Using this approach, >90% of data were predicted within observational uncertainty. Principal component analysis of calculated source concentrations revealed signatures of two distinct chemical sources. First, pharmaceuticals and insecticides were associated with a subcatchment containing a known point source of treated effluent from a wastewater treatment plant. Second, illicit drugs and salicylic acid were associated with multiple sources, interpreted as input from untreated sewage including Combined Sewer Overflows (CSOs), misconnections, runoff and direct disposal throughout the catchment. Finally, a simple algorithmic approach that incorporates network topology was developed to design sampling campaigns to improve resolution of source apportionment. Inverse modelling of contaminant measurements can provide objective means to apportion sources in waterways from spot samples in catchments on a large scale.

A cost-effective and efficient framework to determine water quality monitoring network locations.

A crucial part in designing a robust water quality monitoring network is the selection of appropriate water quality sampling locations. Due to cost and time constraints, it is essential to identify and select these locations in an accurate and efficient manner. The main contribution of the present article is the development of a practical methodology for allocating critical sampling points in present and future conditions of the non-point sources under a case study of the Khoy watershed in northwest Iran, where financial resources and water quality data are limited. To achieve this purpose, the river mixing length method (RML) was applied to propose potential sampling points. A new non-point source potential pollution score (NPPS) was then proposed by the analytic network process (ANP) to classify the importance of each sampling point prior to selecting the most appropriate locations for a river system. In addition, an integrated cellular automata-Markov chain model (CA-Markov) was applied to simulate future change in non-point sources during the period 2026-2036. Finally, by considering anthropogenic activities through land-use mapping, the hierarchy value, the non-point source potential pollution score values and budget deficiency in the study area, the seven sampling points were identified for the present and the future. It is not expected, however, that the present location of the proposed sampling points will change in the future due to the forthcoming changes in non-point sources. The current study provides important insights into the design of a reliable water quality monitoring network with a high level of assurance under certain changes in non-point sources. Furthermore, the results of this study should be valuable for water quality monitoring agencies looking for a cost-effective approach for selecting sampling locations.

Influence of calcite on uranium(VI) reactive transport in the groundwater-river mixing zone.

Calcite is an important, relatively soluble mineral phase that can affect uranium reactive transport in subsurface sediments. This study was conducted to investigate the distribution of calcite and its influence on uranium adsorption and reactive transport in the groundwater-river mixing zone of the Hanford 300A site, Washington State. Simulations using a two-dimensional (2D) reactive transport model under field-relevant hydrological and hydrogeochemical conditions revealed the development of a calcite reaction front through the mixing zone as a result of dynamic groundwater-river interactions. The calcite concentration distribution, in turn, affected the concentrations of aqueous carbonate and calcium, and pH through dissolution, as river waters intruded and receded from the site at different velocities in response to stage changes. The composition variations in groundwater subsequently influenced uranium mobility and discharge rates into the river in a complex fashion. The results implied that calcite distribution and concentration are important variables that need to be quantified for accurate reactive transport predictions of uranium, especially in dynamic groundwater-river mixing zones.