Rivers provide essential ecosystem services, supporting biodiversity, regulating water flow, and supplying resources important for human societies. However, anthropogenic pressures and climate change are increasingly impacting riverine ecosystems, leading to widespread decline in water quality. While substantial progress has been made in understanding long-term water quality trends, our understanding of water quality variations within different catchments is still limited. Moreover, there is a lack of insight into how these variations relate to each other across catchments, making it difficult to predict and manage water quality dynamics at larger spatial scales. Most studies to date have focused on individual sites or small catchment networks, providing valuable insights into site-specific functioning. However, these site-specific studies only offer limited support for understanding and predicting water quality dynamics across larger spatial scales and complex river networks. Understanding the drivers of these complex water quality dynamics is crucial for effective river management and the protection of aquatic ecosystems.

This study addresses this gap by analysing high-frequency water quality data from over 50 sites across England. We focus on key parameters, such as dissolved oxygen, turbidity, pH, and chlorophyll-a, and investigate how water quality fluctuates on diurnal, seasonal, and event-based timescales. We explore the role of event and catchment conditions—such as precipitation, temperature, antecedent conditions, and seasonal variation—in driving water quality variability, and how their importance shifts across time and space.

This research advances our mechanistic understanding of the complex and dynamic processes that govern water quality in rivers across England, with implications for water resource management, environmental monitoring, and the development of more effective strategies for mitigating pollution and protecting aquatic ecosystems.

How to cite: Knapp, J. and Worrall, F.: Mechanistic controls on river water quality dynamics across catchments, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-16699, https://doi.org/10.5194/egusphere-egu25-16699, 2025.

Rewetting of previously drained peatlands in boreal regions has become a highly promoted solution to combat rising carbon dioxide emissions. By plugging drainage ditches and by raising the water table of peatlands, carbon storage is enhanced, and biological breakdown of stored organic carbon is halted. However, how the rise in water tables affects downstream water quality is not yet fully clarified. Possible effects on downstream water quality include increased mercury leaching, increased phosphorous leaching, increased dissolved organic matter and dissolved organic carbon concentrations in runoff, especially during rain events, as well as browning of downstream water bodies. These adverse effects on water quality may have implications for recipient ecosystems and drinking water production. Here we are presenting a field investigation in southern Sweden, that aims at clarifying the effects of peatland rewetting on downstream water quality. In addition to water quality parameters, we propose to measure peatland hydrology and water table depth, both before and after rewetting. The goal of the project is to inform policy makers of best monitoring practices for peatland rewetting efforts. Care must be taken to conduct thorough baseline studies at least during one - preferably two -years before rewetting. To understand the long-term effects of rewetting on downstream water quality, long time series are imperative. Monitoring should thus be continued for multiple years to decades after rewetting.

How to cite: Liess, A., Borgert, J., Rankinen, J., Klante, C., and Alsterberg, C.: Rewetting of a drained peatland – implications for water quality, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-5709, https://doi.org/10.5194/egusphere-egu25-5709, 2025.

Tidal wetlands serve as critical interfaces between terrestrial and aquatic ecosystems, playing a significant role in nutrient cycling and pollutant attenuation. This study investigates the dynamics of reactive solute dispersion in tidal wetlands, specifically examining the influence of reversible and irreversible reactions under pulsatile wind conditions. By employing Mei's multi-scale homogenization technique [1], we aim to elucidate how unsteady wind patterns affect the transport and reaction mechanisms of solutes in these unique environments. The impacts of reaction parameters, such as the Damköhler number (Da) and irreversible reaction rate, along with wind parameters and vegetation factors, on solute mixing have been analyzed. It has been found that an increase in the wind oscillation period (τ_w) corresponds to a decrease in the frequency of wind oscillations, which no longer effectively resist flow pulsation but instead enhance it when the wind aligns with the flow direction, regardless of its strength. When the wind opposes the primary flow, an interesting trend in the dispersion coefficient has been observed for varying wind oscillation periods and amplitudes. The dispersion coefficient first decreases with increasing wind strength, reaches a minimum, and then begins to increase. Vegetation-induced drag is more pronounced when the wind opposes the flow. This significantly reduces dispersion compared to wind flowing in the same direction as the primary flow. Results also indicate that slow phase exchange kinetics (Da<<1)  lead to higher dispersion coefficients compared to fast kinetics (Da>>1)  in both wind directions. Introducing an irreversible reaction rate causes absorption at the wetland bed, lowering the solute concentration near the channel bed. This creates a depletion effect, where solutes are continuously removed from the fluid phase, leading to an overall reduction in fluid-phase concentration throughout the wetland system.

How to cite: Hossain, S. and W. Tsai, C.: Dispersion dynamics of reactive solutes in tidal wetlands under pulsatile wind conditions, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-17391, https://doi.org/10.5194/egusphere-egu25-17391, 2025.

Headwater streams account for 70% or more of total stream length in most catchments, making it crucial to better understand the processes and controlling factors governing streamflow generation as well as water quality. In this context, stream water chemistry longitudinal profiles can provide valuable insights. This study examines longitudinal stream chemistry profiles across six headwater catchments in three mid-mountain ranges in Germany: The Ore Mountains (catchments OM 1 and OM 2), Black Forest (BF 1 and BF 2), and Sauerland (SL 1 and SL 2).

Three to four snapshot sampling campaigns were conducted per catchment across different seasons and catchment wetness conditions. During the campaigns, water samples were collected from 22 stream monitoring points in the Ore Mountains catchments, 14 in the Black Forest, and 14 in Sauerland, and the samples were analyzed for major cations, anions, and dissolved organic carbon. Subsequently, the longitudinal profiles observed were grouped into spatial and temporal patterns.

In the Ore Mountains, solute concentrations were generally stable over time. However, the spatial patterns varied between the two neighbouring catchments (OM 1 and OM 2). OM 2 exhibited chemostatic longitudinal profiles for most solutes, while OM 1 showed pronounced spatial variability in solutes such as nitrate, dissolved organic carbon (DOC), chloride, and sodium. This variability is usually linked to monitoring points located near springs, tributaries, and drainage systems. However, some spikes in ion concentrations along the stream were not linked to these obvious inflows, thus potentially indicating hotspots for groundwater inflow. The Sauerland catchments showed elevated concentrations of DOC, magnesium, calcium, and sodium in July 2023, a period associated with lower streamflow. An increase in concentration from upstream to downstream was here seen in both streams for solutes like calcium and sodium, during all snapshot campaigns. However, other solutes, like nitrate and sulfate, showed different longitudinal patterns and notable shifts in solute concentration during the snapshot campaigns in SL 2. The shifts in patterns indicate a dependency on time-variant factors like seasonal changes in water input, and land use practices. BF 1 catchment in the Black Forest showed a decreasing pattern in DOC, from upstream to downstream, while the neighbouring catchment BF 2 showed a chemostatic trend. These trends could be influenced by the land use changes within the catchments. Notable increased nitrate concentrations were seen along reaches adjacent to grassland areas and at sampling points near tile drains in OM 1, BF 1, SL 1, and SL 2.

Overall, solute spatial and temporal patterns were stream-specific, with no universal behaviour observed across all catchments. This variability likely results from the interplay of factors such as geology, soils, land use, stream morphology, and climate. High-resolution spatial sampling enabled the identification of point sources and hotspots of groundwater inflow which could be missed by sparse sampling. These findings enhance our understanding of the processes regulating water quality and flow in headwater systems, providing a basis for better management of these systems.

How to cite: Gariremo, N., Kuleshov, A., Vis, G., Hartmann, A., Blume, T., and Hopp, L.: Longitudinal Profiles of Stream Chemistry in Headwater Catchments in Germany, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-12321, https://doi.org/10.5194/egusphere-egu25-12321, 2025.

Excess nutrients in aquatic ecosystems cause toxic algal blooms, deoxygenation, fish kills and health risks for humans, resulting in high costs for the environment and society. Next to absolute nitrogen (N) and phosphorus (P) concentrations, the stoichiometric ratio of N to P affects biological activity and thus on potential nutrient retention and the occurrence of adverse eutrophication effects. P inputs to streams have been largely reduced by improved wastewater treatment since the 1980s/1990s. In contrast, N inputs, mainly stemming from diffuse sources, have been reduced more recently and with slower rates. Moreover, diffuse inputs travel from the catchments’ surface along different pathways until reaching the streams with time lags up to decades from application to export, while wastewater is usually disposed directly into streams. These asynchronous changes in N and P inputs and distinct pathways suggest widespread increases in instream N:P ratios. However, little is known about the spatial and temporal variability of these shifts across catchments, their ecological implications, and whether recent improvements in N control and fading P reductions have reversed this trend. 

To fill this knowledge gap, we analyze instream N:P trajectories in 767 catchments in France, Germany and Denmark in the period from 1990 to 2019. We classify the catchments based on ecologically relevant classes of molar N:P ratios and their decadal changes. For classification, we consider N-depletion for N:P < 20, P-depletion for N:P > 50 and N&P co-depletion in between, following Guildford and Hecky (2000), both for annual and summer periods.

We found 

(1) a widespread increase of N:P in 1990-2010 that is levelling off in the last decade and partly even reversing, primarily controlled by trends in P. 

(2) that 40% of catchments experienced at least one shift in depletion class over the decades.

(3) summer N:P ratios to be lower with 50% of the catchments remaining N- or N&P co-depleted in the last decade, despite overall positive N:P trends.

This indicates that, although shifts in nutrient management have intensified P depletion, notable spatial and temporal variations remain, which we intend to investigate in more detail. This study provides the first comprehensive analysis of N:P trajectories in Western European streams, offering new insights into stream water quality and its ecological implications for aquatic ecosystems.

Guildford, S. J., & Hecky, R. E. (2000). Total nitrogen, total phosphorus, and nutrient limitation in lakes and oceans: Is there a common relationship? Limnology and Oceanography, 45(6), 1213-1223. https://doi.org/10.4319/lo.2000.45.6.1213

How to cite: Ebeling, P., Turner, N., Graeber, D., Musolff, A., Dupas, R., Fleckenstein, J. H., Kumar, R., and Winter, C.: Trends in Instream Nitrogen-to-Phosphorus Ratios: A 30-Year Study of Ecological Relevance Across 750 Catchments, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-6390, https://doi.org/10.5194/egusphere-egu25-6390, 2025.

High-frequency sampling enables the observation of rapid and subtle variations that can be missed with less frequent observations, which is crucial for understanding the complex interplay of factors influencing water quality. This research analyzes high-frequency data to understand water quality dynamics in the Bode river basin in central Germany, a region characterized by diverse climatic, geological, and land-use conditions.

Using data collected from five monitoring stations over seven years (2013–2020), six variables (electrical conductivity, nitrate, turbidity, water discharge, water temperature, and pH) were analyzed with Principal Component Analysis (PCA). The first principal component (PC1) explained 46% of the variance, and described the typical effect of stream discharge fluctuations throughout the seasons. PC2 highlighted the influence of saline groundwater upwelling during low-flow conditions, while PC3 revealed the role of photosynthetic activity in driving diurnal and seasonal pH fluctuations. Other components unraveled localized processes, including turbidity variability during discharge peaks (PC4, PC5 and PC6), anthropogenic effects, such as the discharge of treated acid mine drainage into the river system (PC7), and agricultural runoff influencing nitrate dynamics (PC8). Together, these components demonstrated how PCA can disentangle diverse influences on water quality, from climatic patterns to human interventions.

Collectively, the PCA results elucidated a wide range of factors influencing water quality, encompassing climatic variations and anthropogenic impacts. High-resolution temporal data revealed intricate dynamics that would otherwise remain undetected with less frequent sampling intervals. PCA proved to be an effective quantitative tool for synthesizing complex, multivariate datasets across multiple monitoring sites, enabling the identification of dominant hydrological controls and interactions between natural and human-driven processes. This methodological framework is adaptable to larger datasets, offering the potential for pattern recognition at regional or global scales and advancing hydrological synthesis. Its application can support adaptive water resource management in regions subject to diverse environmental and anthropogenic pressures.

How to cite: Gutiérrez, K., Lischeid, G., and Rode, M.: Disentangling Spatiotemporal Water Quality Dynamics in a Heterogeneous Catchment Using High-Frequency Data and Principal Component Analysis, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-3542, https://doi.org/10.5194/egusphere-egu25-3542, 2025.

Nitrogen cycling has been dramatically altered by anthropogenic activities, impacting water quality and ecosystem functioning of river systems worldwide. Understanding the (a)synchrony between discharge (Q) and nitrate concentration (N) is crucial to revealing the temporal-spatial processes that govern nitrogen dynamics and identify the controlling factors to improve monitoring and management strategies. Here data collected from 66 river catchments across England, spanning 20 years, were analysed to characterise Q-N synchrony patterns and assess spatiotemporal variability. QMax-synced catchments (i.e. max N occurred with max Q, accounting for 28.8% of catchments) are mainly smaller, agricultural catchments, where high-flow conditions can mobilise accumulated nitrate from agricultural soils. By contrast, QMin-synced catchments (i.e. max N occurred with min Q, 25.8% of catchments) have higher proportions of urban area and displayed stronger point-source influences. These catchments are generally larger and have a higher proportion of surface runoff during high-flow periods, diluting nitrate-rich point sources and shifting peak nitrate concentrations to the period of lowest flow. Asynced catchments (46.8%) are also generally larger but with a larger mixture of land use and therefore point and diffuse nitrate sources. Furthermore, the synchrony variability is primarily influenced by sharp topography in QMax-synced catchments, while anthropogenic activities like sewage treatment plant density mainly impact that in QMin-synced and Asynced catchments. Our results demonstrate that the seasonal timing of peak nitrate has a strong and highly contrasting dependence on hydrological conditions that shift with catchment size and availability of diffuse and point sources, with important implications for monitoring and management.

How to cite: Yang, L., Larsen, J., Khamis, K., and Knapp, J. L. A.: Spatial-temporal synchrony between Nitrate and Discharge Varies with environmental and anthropogenic controls, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-17984, https://doi.org/10.5194/egusphere-egu25-17984, 2025.

Improving water quality at the catchment scale proves difficult as indicated by shifting deadlines of the Water Framework Directive for achieving good chemical and ecological status in European freshwaters. Low-hanging fruits of reducing point sources of pollution have already been targeted in most catchments, with more challenging and persistent diffuse pollution jeopardising widespread water quality improvements. Diffuse pollution originates from a range of anthropogenic activities such as agriculture, forestry and mining and leads to gradual accumulation of pollutants in impacted catchments. These abundant pools of pollution, also known as legacies, can control water quality and limit the effectiveness of mitigation measures in the long term. Yet, our understanding of hydrological and biogeochemical processes controlling mobilisation, transformation, transport and impact of pollution legacies in catchments is still limited. Here, we present results from multiple projects focusing on identifying processes controlling eutrophication and erosion in headwater agricultural catchments to support management and mitigation. We use a suite of experimental and modelling tools from high-frequency stream chemistry data, in situ measurements of dominant processes, laboratory assays, and process-based models to quantify hydrological and biogeochemical processes. Our results show that despite common pollution pressures, agricultural catchments differ in how they modulate pollution legacies. Their resilience/sensitivity to pollution depends on the interplay between hydrological and biogeochemical processes. Biogeochemical processes such as sorption, sedimentation and denitrification show potential for pollution retention and removal; however, their capacity is rapidly exhausted during hydrologic events mobilising large fluxes of legacy pollutants. As the importance of hydrological accumulation increases with catchment size, the cumulative impact of mitigation measures on water quality declines along the stream network. Finally, our modelling approach shows that only large-scale mitigation interventions are likely to bring the required water quality improvements, particularly under future climatic conditions with accelerated biogeochemical and hydrological processes. Understanding these processes is key to effective mitigation and reducing potential pollution swapping in heavily impacted catchments.

How to cite: Bieroza, M., Livsey, J., Hallberg, L., Wynants, M., and Prischl, L.-A.: Improving water quality at the catchment scale through process-informed management and mitigation, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-4228, https://doi.org/10.5194/egusphere-egu25-4228, 2025.

We review anthropogenic water pollution, and find that it is spreading in rivers and aquifers at an alarming rate. Actions advocated by the United Nations have thus far resulted in more improvements in water quality of surface water than that of groundwater. Here, we argue that the nature of anthropogenic pollution has evolved over time, so that traditional indicators such as biological oxygen demand are no longer adequate. We further argue that overexploitation of groundwater and climate change (extremes and, possibly, reduction of rainfall and/or increase in evapotranspiration) are causing a reduction of the environmental services of groundwater dependent aquatic ecosystems and, specifically, the pollutant removal capacity. Therefore, concerted efforts are needed to restore natural surface water-groundwater interactions. To this end, we need to either reduce pumping (e.g., through conjunctive use) or expand managed aquifer recharge. While these measures would help in improving water quantity and quality simultaneously, current regulations favor neither because of concerns about their possible negative impacts. Determining how to implement these solutions is itself a challenge. Considering that the scientific literature is still centered upon water scarcity and declining water levels, we call for a common front of researchers in hydrology and sister sciences to address this fast-evolving pollution crisis in our water systems. As Bill Clinton famously said,”it’s the pollution, stupid!”.

How to cite: Carrera, J., Bronstert, A., Sawyer, A., Krause, S., deGraaf, I., Zheng, Y., Zheng, C., Morales-Casique, E., and Yadav, B. K.: The blind spot in water sustainability: why do we have such low desire for good water quality?, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-20325, https://doi.org/10.5194/egusphere-egu25-20325, 2025.

In North America, the Great Lakes contain approximately 20% of the available surface fresh water in the world. As a result, the Great Lakes Basin (GLB) is a well-known region for its extensive agricultural and food production activities. Such agricultural activities are considered one of the most significant non-point sources of nutrient transport, particularly nitrogen and phosphorus, to surface water and groundwater. This is mainly because of the application of synthetic fertilizers and manure for enhanced crop productivity and soil fertility. Such elevated nutrient concentrations can disrupt aquatic ecosystems, degrade surface and groundwater quality, and harm both human and aquatic life. However, quantification of nutrient concentrations in agricultural watersheds is challenging because it is influenced by different process parameters including soil type, climate, and land use conditions. These parameters are highly non-linear and uncertain which hinders the applicability of typical mathematical models in nutrient transport applications in surface water and groundwater quality. Therefore, data-driven models using machine learning (ML) algorithms have been extensively applied to unravel the complexities of nutrient transport in surface water and groundwater, tackling the main challenges associated with the mathematical models. This is mainly because ML algorithms can deal with complex datasets with high uncertainty and non-linearity while considering the interdependence between the process parameters. By leveraging historical datasets, ML algorithms can model the explain the cause-result and intricate interdependencies between process parameters, making them well-suited for simulating nutrient transport processes in surface and sub-surface water applications. In the current study, different ML algorithms were adopted to predict nutrient concentrations in surface water and groundwater in a sand plain agricultural watershed within the GLB in Ontario, Canada. These ML algorithms included regression (e.g., artificial neural network) and classification (e.g., decision trees) techniques to better simulate nutrient concentrations in surface water and groundwater. The ML input variables involved meteorological (e.g., precipitation), hydrogeological (e.g., groundwater levels), and water physico-chemical (e.g., pH) conditions. The performance of these ML algorithms was evaluated using different evaluation metrics such as root-mean squared error and F1-score for regression and classification models, respectively. The optimal ML models were selected according to the outcomes of these evaluation metrics. In addition, the interdependence between the involved process parameters (e.g., land use and precipitation) and nutrient concentrations was interpreted to determine the governing parameters on the nutrient transport process in surface and sub-surface water. The main outcomes of this study can help decision-makers in assessing the most effective management efforts to protect and improve surface water and groundwater quality in agricultural watersheds. In addition, these insights enable the interpolation of nutrient concentrations from discrete sampling points, facilitating predictions at unmonitored locations across the watersheds.

How to cite: Elsayed, A., Levison, J., Binns, A., Larocque, M., and Goel, P.: Harnessing Machine Learning for Water Quality Prediction in Agricultural Watersheds, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-14665, https://doi.org/10.5194/egusphere-egu25-14665, 2025.

Declines in riverine biodiversity are impacted by catchment connectivity to potential nutrient sources.  Many studies have focused on biodiversity as a direct expression of instream attributes, thus neglecting the critical role of catchment connectivity to the river network as key determinants of biodiversity. To protect and restore the ecological integrity and wider ecosystem function of riverine systems, the spatial connectivity of the stream networks to their catchments must be considered in mitigation measures. Given their extent and high connectivity with the surrounding landscape, low-order streams are particularly vulnerable to land-use pressures and demonstrate high sensitivity to nutrients (N and P), impacting the composition and seasonally persistence of benthic algal communities.

Here, we utilise the Sensitive Catchment Integrated Mapping Analysis Platform (SCIMAP) to explore the spatial risk to land-use-driven nutrient pollutant pressures across the River Eden (NW England) catchment.Our results show that the potential source areas for the examined pollutants are in specific locations in the catchment. Therefore, the most effective locations for management measures will differ for different pollutant or ecological endpoints.  This means that the Programme of Measures under the Water Framework Directive requires the integration of multiple lines of ecological evidence at the appropriate spatiotemporal scales. We demonstrate that this approach can guide prediction on instream ecological status and identify spatial sources, thus providing a more quantitatively transparent and accurate risk assessment for catchment management and mitigation

How to cite: Reaney, S., Snell, M., and Barker, P.: Identifying the source of anthropic pressures on in-stream benthic algae communities within the River Eden catchment, UK, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-11654, https://doi.org/10.5194/egusphere-egu25-11654, 2025.

This study examines the effects of groundwater depletion on salinity and nitrate contamination in a detritic unconfined alluvial aquifer. Over the past five decades, the aquifer has transitioned from shallow groundwater (<20 m) in the 1970s to predominantly deep groundwater (>40 m) due to significant water table declines. Groundwater analysis reveals moderate contamination, with nitrate levels highest in shallow zones but detectable at all depths. Dominant hydrochemical processes influencing salinity include rock weathering, halite dissolution, and reverse ion exchange.  
The Haouz Plain, located in central Morocco, covers a significant area within the Tensift Basin. Characterized by an arid to semi-arid climate, it is a center of intensive agricultural and industrial activities, making its water resources highly susceptible to contamination risks.
The thick unsaturated zone formed by water table decline has mitigated surface-borne contamination and reduced evapotranspiration impacts. However, vertical flow dynamics induced by pumping have allowed younger, nitrate-rich groundwater to mix with older, deeper groundwater. Tritium dating indicates that nitrate in deep groundwater likely originates from historical fertilizer use, highlighting the long-term legacy of agricultural practices on water quality.  
Continued aquifer depletion poses serious risks. Pumping deep groundwater could mobilize salts, increasing salinity. Moreover, contaminants accumulated in the thick unsaturated zone could migrate downward over time or with increased recharge, further degrading groundwater quality. These findings emphasize the vulnerability of depleted aquifers to salinization and nitrate contamination, underscoring the need for sustainable groundwater management strategies.  

Keywords: Pollution, irrigation, hydrochemistry, salinity, quality.

How to cite: Sahraoui, H., Fakir, Y., Bouimouass, H., Tweed, S., and Leblanc, M.: Groundwater Contamination Processes in Depleting Alluvial Aquifers, Haouz Plain Morocco, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-20250, https://doi.org/10.5194/egusphere-egu25-20250, 2025.

This study derives an analytical solution of the two-dimensional concentration distribution of a pollutant in a prismatic channel flow with asymmetric velocity pattern over its cross-section. This study also examines pollutant transport phenomena influenced by both irreversible and reversible reactions, along with the bulk chemical reaction of the pollutant with the channel boundaries and the fluid flows, respectively. The effects of mean and transverse concentration distributions are analyzed under the influence of various parameters, including adsorption, desorption, absorption, the asymmetric velocity distribution parameters (α and β), and the bulk chemical reaction parameter. The transverse concentration distribution up to the second-order approximation is derived using Mei's homogenization technique. Over the past two decades, researchers have emphasized that the Taylor dispersion model primarily predicts the longitudinal dispersion of the mean concentration. However, the study of transverse concentration distribution has gained significant importance due to its relevance in environmental engineering and industrial applications. According to the investigation’s findings, an increase in  α and β  enhances the overall velocity, resulting in a sharper velocity profile when α = β or a more asymmetric profile when α ≠ β . The dispersion coefficient  shows non-monotonic behavior influenced by the velocity parameters   α and β . Smaller   α and β  yield moderate velocity gradients and weaker shear, reducing dispersion. As   α and β  increase, sharper or asymmetric velocity profiles enhance shear effects, increasing dispersion. The mean concentration of the pollutant decreases with increasing   α and β  in both cases, but the decrease is more gradual in the asymmetric case. Increasing bed absorption and bulk chemical reaction parameters significantly reduces the transverse concentration, while increasing adsorption or desorption parameters raises the transverse concentration. Adsorption and desorption reactions at the boundaries reduce transverse concentration variation in both symmetric and asymmetric cases. The variation decreases with increased reaction rates, with slight non-uniformity observed when α ≠ β. The findings are crucial for enhancing natural stream quality, reducing pollution, and mitigating the effects of reactions.

How to cite: Barik, S. and Srinivasa Raghavan, R.: Pollutant transport in asymmetric velocity distributions influenced by phase exchange kinetics between two parallel plates, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-20033, https://doi.org/10.5194/egusphere-egu25-20033, 2025.