River Discharge Research Articles

Flood modeling prior to the instrumental era reveals limited magnitude of 1931 Yangtze flood

The global flood risk urges an improved understanding of flood magnitude and its mechanism, which needs insights from pre-instrumental flood investigations. Due to data scarcity, reconstructing pre-instrumental flood magnitudes relies on statistical downscaling, failing to capture nonlinear and dynamic characteristics. We developed a dynamical approach, NorESM-WRF-SWAT, integrating a global climate, a regional, and a hydrologic model to investigate the 1931 Yangtze River flood (the deadliest in the world) and compared it with the 1998’s. Through validation, our method outperforms the statistical method in simulating precipitations and river discharges. For the first time, we presented detailed insights into the intensity and duration of the 1931 flood, revealing a smaller magnitude but associated with an amplified loss, likely due to social vulnerability and reduced societal resilience compared to the 1998’s. While successful simulation can be interfered with by model variability, our dynamical method shows promise for simulating pre-instrumental flood and building a long-term pre-instrumental-hydrology database.

State of the art modelling for the Black Sea ecosystem to support European policies.

The Black Sea is affected by numerous anthropogenic pressures, such as eutrophication and pollution through coastal and river discharges, fisheries overexploitation, species invasions, and the impacts of climate change. Growing concerns regarding the cumulative effects of these pressures have necessitated the need for an ecosystem approach to assessing the state of this basin. In recent years, the European Commission-JRC has developed a scientific and modelling tool, the Blue2 Modelling Framework with the aim of exploring the consequences of EU management and policy options on marine ecosystems. This framework has been designed to provide information on specific ecological indicators set out in EU legislation. Here, we present the Blue2 framework for the Black Sea ecosystem. The model represented the mid-1990s' conditions in the Black Sea ecosystem including trophic levels from primary producers to marine mammals and sea birds. The model simulations covered a period from 1995-2021. The results showed that gulls & cormorant seabirds, sprat, horse mackerel and mugilidae had structuring role in the food web. Fishing fleets had indirect negative impacts on marine mammals in addition to commercially exploited species. Analysis of the ecosystem indicators confirmed the overall temporal degradation of the Black Sea when comparing results with other Black Sea models, whilst the comparison with the Mediterranean Sea allowed us to identify comparable indicators between similar model structures. The spatial/temporal model successfully simulated the overall ongoing declining dynamics of the Black Sea ecosystem as the biomasses of the majority of the functional groups had significant observed decreasing trends during the simulation period. This model is the first attempt to represent the historical and current state of the Black Sea ecosystem spatially and temporally, serving as a reference baseline for evaluating policy scenarios and assisting policy makers in the evaluation of potential environmental impacts of management options.

Hydrological Drivers of Flooding in Niamey (Niger): The Role of the Sirba River

Abstract In recent decades, floods have become a major global concern. In Niamey (Niger) in West Africa, flooding is primarily caused by the significant increase in surface runoff resulting from heavy rainfall occuring between July and September in the upstream river basins of the three major tributaries of the Middle Niger River (Sirba, Gorouol and Dargol catchments). While the Sirba is empirically considered as the largest driver to flooding in Niamey, its contribution have not been precisely established. This study analyzes the influence of these tributaries on the Niger River discharges at Niamey during the rainy season, with a particular focus on the Sirba River basin. Daily annual maximum discharge (AMAX) data from 1990 to 2022 timeseries are used as inputs to various statistical analyses, including trend analyses, change point detection, concordance analysis and flood dependency assessment. The results reveal a significant change point in 2009 and increasing trends between the Sirba and Niger River stations. The flood propagation time delay varies from 1 to 4 days between the upstream river basins tributaries and Niamey station, with a strong concordance in peak discharges, particularly dominant with the Sirba River. The Dynamic Time Warping (DTW) and the Gumbel copula analyses highlighted the significant control of the Sirba River basin on flooding in Niamey, while also highlighting the important roles played by other tributaries. These findings are crucial for improving flood prevention and further refine urban flood management strategies in Niamey and other cities globally, affected by fluvial floods.

Exploring River’s Flood Dynamics: Integrating HEC-RAS 1-D Modelling and Geospatial Techniques for the Karjan River in Gujarat’s Narmada Basin, India

Floods rank among the most devastating natural disasters, causing extensive damage to property and severe impacts on communities. Effective management and mitigation of flood risks necessitate reliable data regarding flood depth, discharge, and extent. The Karjan River Basin’s low-lying regions experienced significant flooding in 2020. This research utilizes the latest new HEC-RAS version for one-dimensional hydrodynamic flood modelling for the Karjan River in low-lying areas and the merging point of the Karjan River Basin in Narmada River, emphasizing geospatial techniques. The study showcases the analytical process of the new HEC-RAS v6 in spatial analysis. River features like bank lines and cross-sections were derived from ALOS Palsar for flood modeling. An unsteady flow simulation was conducted to model water dynamics, yielding water depth results viewable in the HEC-RAS geospatial RAS mapper. Flood depth maps created for 2020 reveal that areas low lying area i.e. Dhamncha, bhadam, Juna Rundh and surrounding area near the merging point of Karjan River are prone to floods when river discharge surpasses 8836 cubic meters per second. Model accuracy was verified by comparing simulated outcomes with historical data from the mentioned events, demonstrating the model’s precision and reliability.

Compound coastal flooding in San Francisco Bay under climate change

The risk of compound coastal flooding in the San Francisco Bay Area is increasing due to climate change yet remains relatively underexplored. Using a novel hybrid statistical-dynamical downscaling approach, this study investigates the impacts of climate change induced sea-level rise and higher river discharge on the magnitude and frequency of flooding events as well as the relative importance of various forcing drivers to compound flooding within the Bay. Results reveal that rare occurrences of flooding under the present-day climate are projected to occur once every few hundred years under climate change with relatively low sea-level rise (0.5 m) but would become annual events under climate change with high sea-level rise (1.0 to 1.5 m). Results also show that extreme water levels that are presently dominated by tides will be dominated by sea-level rise in most locations of the Bay in the future. The dominance of river discharge to the non-tidal and non-sea-level rise driven water level signal in the North Bay is expected to extend ~15 km further seaward under extreme climate change. These findings are critical for informing climate adaptation and coastal resilience planning in San Francisco Bay.

Machine Learning Assessment of Dredging Impacts on the Phytoplankton Community on the Brazilian Equatorial Margin: A Multivariate Analysis.

Dredging in estuarine systems significantly impacts phytoplankton communities, with suspended particulate matter (SPM) and dissolved aluminum (Al) serving as indicators of disturbance intensity. This study assessed the effects of dredging in the São Marcos Estuarine Complex (SMEC), Brazil, over three distinct events (2015, 2017, 2020), involving varying sediment volumes and climatic influences. Prolonged dredging operations and increased sediment volumes led to a pronounced 43.81% reduction in species diversity, with diatoms and dinoflagellates being the most affected. Climatic variability, particularly El Niño events, exacerbated environmental dispersion, amplifying the complexity of ecosystem responses. Despite these losses, certain centric diatoms persisted, reflecting resilience mechanisms within this tropical macrotidal estuary. Machine learning approaches, specifically Random Forest (RF) models, revealed SPM and dissolved Al as critical stressors influencing species diversity. Additionally, river discharge and salinity were identified as key predictors of phytoplankton biomass. Generalized Additive Models (GAMs) confirmed that chlorophyll-a concentrations responded negatively to elevated SPM and Al levels but were less sensitive to dredging than diversity metrics. This study provides novel insights into the compounded effects of dredging and climatic variability, emphasizing the utility of RF and GAM models for predicting ecosystem responses and guiding management strategies. Recommendations include optimizing operations to reduce biodiversity impacts, minimizing sediment resuspension, and integrating predictive tools to mitigate long-term disturbances. These findings offer a data-driven framework for sustainable dredging in sensitive estuarine ecosystems.

Enhanced Transport Induced by Tropical Cyclone and River Discharge in Hangzhou Bay

Enhanced Transport Induced by Tropical Cyclone and River Discharge in Hangzhou Bay

Tidal Modulation of the Fraser River Plume

AbstractProperties of the Fraser River plume in the Strait of Georgia, BC, are significantly influenced by the tide. However, the dynamics and magnitude of this tidal influence on the plume area are not known. Here, we use 17 years of daily satellite observations of suspended particulate matter to understand the tidal variability of the plume area. A consistent inverse relationship between the Fraser River plume area and the tidal elevation with a phase lag of 1–2 hr is revealed from two independent analyses: one by correcting for temporal aliasing and extracting tidal signal from the whole image set and the other using only same‐day image pairs. The plume area increases/decreases by about 20% after ebb/flood tides, and a lower river discharge typically leads to a more dramatic tidal variation in the plume area. A simple analytical model based on the volume conservation and salinity balance equations is developed to analyze the mechanism of the tidal variability in the plume size. The observed tidal patterns of the plume area are largely reproduced using tidally modulated plume salinity (observed from instrumented ferries) and river discharge (from numerical model outputs). Tidal flux in both river discharge and entrainment rate is found to be important in explaining plume area variability.

River discharge - tide interactions and tide propagation in the mesotidal tropical estuary of the Van Uc river, Red River delta, Vietnam

River discharge - tide interactions and tide propagation in the mesotidal tropical estuary of the Van Uc river, Red River delta, Vietnam

Statistical analysis of water quality and cyclone impacts along the south Odisha coast, east coast of India

Water quality along south Odisha coast (25km stretch), east coast of India was studied collecting monthly samples at 10 different sampling stations from June 2008 to March 2011 and June 2012 to May 2017. The samples were analysed for salinity, dissolved oxygen (DO), total suspended solids (TSS) and pH. In addition, river discharge, siltation, rainfall and wind speed data were also collected from 2008 to 2017 at the study region and their impacts on coastal water quality were assessed along with the impacts of cyclonic storms. Anomalies of water quality parameters and their seasonal variability were assessed. Spatio-temporal variation of these parameters and multivariate statistical techniques such as factor analysis, correlation coefficient and, descriptive statistics were applied to the observed datasets. Results indicate that, salinity is positively correlated with wind speed at 0.05 significance level while negatively correlated with river discharge. TSS is positively correlated with siltation at 0.01 significance level. DO values are also positively correlated with strong wind speed. Nutrient driven primary production helps pH to be higher at Rushikulya river mouth during monsoon and post-monsoon as compared to at all other stations. Throughout the year, the study environment remains alkaline. Due to impacts of cyclonic storms, water quality parameters show significant reduction in salinity and enhancement in TSS, DO and pH during the post-cyclone period while the seasonal trend is maintained during the pre-cyclone period. Factor analysis reveals the factors controlling the hydrographic behaviour of seawater. The spatial variation in coastal water quality is very high and dominates over the temporal variation. Importance of coastal water quality assessment in relation to coastal ecosystem and disaster is discussed.

Discerning Natural and Anthropogenic Factors Driving the Variation of Estuarine CH 4 and N 2 O

Estuaries are commonly recognized as a major source of greenhouse gases due to the massive anthropogenic input of organic matter and nutrients, which is associated with highly active microbial assemblages. However, the combined effects of natural and anthropogenic factors and their relative contributions to estuarine greenhouse gas emissions are not well understood, particularly at the confluence of fresh water and seawater. In this study, biweekly sampling was conducted from November 2021 to January 2024 at the main outlet of the Pearl River in south China, which is characterized by a subtropical climate, a eutrophic environment, and heavy anthropogenic activity. Measurements were obtained of the dissolved methane (CH 4 ), nitrous oxide (N 2 O), and associated seasonally varying physical and chemical parameters at a high temporal resolution. Analysis of the measurement data revealed that the dissolved CH 4 and N 2 O concentrations were decreased by increases in the river discharge, which enhanced the dilution effect, and reductions in anthropogenic activities, such as the enforcement of measures to prevent COVID-19. The different dynamic processes of the nitrogen and carbon cycles may have contributed to the differences in the variations of the CH 4 and N 2 O concentrations (e.g., N 2 O varied within a narrower range than CH 4 ). By presenting and analyzing the 2-year time series of estuarine CH 4 and N 2 O with a high temporal resolution under complex natural and anthropogenic forcing, this study underscores the importance of human influence on greenhouse gas inventories and emissions.

In search of non-stationary dependence between estuarine river discharge and storm surge based on large-scale climate teleconnections

Compound floods may happen in low-lying estuarine environments when sea level above normal tide co-occurs with high river flow. Thus, comprehensive flood risk assessments for estuaries should not only account for the individual hazard arising from each environmental variable in isolation, but also for the case of bivariate hazard. Characterization of the dependence structure of the two flood drivers becomes then crucial, especially under climatic variability and/or change that may affect their relationship. In this article, we demonstrate our search for evidence of non-stationarity in the dependence between river discharge and storm surge along the East and Gulf coasts of the United States, driven by large-scale climate variability, particularly El-Niño Southern Oscillation and North Atlantic Oscillation (NAO). Leveraging prolonged overlapping observational records and copula theory, we recover parameters of both stationary and dynamic copulas using state-of-the-art Markov Chain Monte Carlo methods. Physics-informed copulas are developed by modeling the magnitude of dependence as a linear function of large-scale climate indices, i.e., Oceanic Niño Index or NAO index. After model comparison via suitable Bayesian metrics, we find no strong indication of such non-stationarity for most estuaries included in our analysis. However, when non-stationarity due to these climate modes cannot be neglected, this work highlights the importance of appropriately characterizing bivariate hazard under non-stationarity assumption. As an example, we find that during a strong El-Niño year, Galveston Bay, TX, is much more likely to experience a coincidence of abnormal sea level and elevated river stage.

How Marine Megabenthos Fauna Responds to River Discharge and Artificial Flood in Large River Estuary.

Estuaries are ecologically sensitive areas influenced by river regulation. Knowledge of how marine megabenthos responds to river regulation and artificial flooding events remains limited. The study aims to provide a comprehensive understanding of the impacts of river regulation on marine megabenthic fauna. The oceanographic investigations were conducted at the Yellow River Estuary and its adjacent area during three distinct periods of river discharge, that is, spring low-flow (IA), summer low-flow (IB), and artificial flood (IC) periods. Samples of megabenthos and 14 mainly environmental parameters were investigated during different periods. The comprehensive indices of biodiversity (C-diversity), phylogeny (C-phyl), and stability (C-stability) were synthesized from 24 basic indices to characterize the overall traits of megabenthos faunas. All 210 species were collected during three periods, belonging to 16 classes and 51 orders. The typical estuarine communities were mainly distributed in the key area within 30 km of the estuary during the low-flow periods. The estuarine community presented with low biodiversity (C-diversity = 0.15) but high stability (C-stability = 0.64) during the IA period, followed by an increase in biodiversity during the IB period (C-diversity = 0.35, C-phyl = 0.69). The community underwent dramatic changes during the IC period, which bifurcated into distinct northern and southern groups. The northern community maintained high biodiversity and homeostasis (C-stability = 0.60), whereas the southern stability decreased sharply (0.11). On the whole, the artificial flood reshaped the geographical distribution of megabenthic fauna in the estuarine area within 20 days, mainly as a result of the dramatic changes in seawater salinity and nutrient structure caused by flow pulse. An eco-friendly discharge management of the Yellow River is needed to mitigate the impact.

Time Series Analysis of River Discharge, Water Stage, and Rainfall at Lokoja Section of Benue River, Kogi State, Nigeria

This study carried out a time analysis of river water level (stage), rainfall, and discharge in the Lokoja section of River Benue and assessed their implications for flooding. The specific objectives that guided the study were focused on monthly and annual variability in water level, rainfall, and discharge are examined, along with their interrelationships. Data on water level and discharge were acquired from the Nigeria Hydrological Services Agency (NHSA), Abuja covering 22 years (2001 -2021), while rainfall data were obtained from the Nigeria Meteorological Agency (NiMet), Lagos Operational Headquarters. Time series analysis was carried out using the Least Square Regression Model. The significance of the trend was tested using the student’s t-test at a 0.05 (95%) confidence level. While descriptive statistics employed are mean, standard deviation, and coefficient of variation. The results indicate a decline in water levels from January to April, followed by a significant rise from May to October. Annual water levels show a significant positive trend over 21 years (R² = 0.2968, r= 0.5448), with notable fluctuations. Peak discharge exhibits a fluctuating monthly pattern, with a significant increasing trend over the years (R² = 0.2451, r = 0.4951), indicating potential flood risks. Monthly rainfall varies significantly, with notable peaks between April and August. Although annual rainfall shows a slight increasing trend, it’s not statistically significant. Strong correlations exist between peak discharge and water levels (r ≈ 0.982), while relationships between discharge and rainfall, and water levels and rainfall are moderate. Multiple regression analysis reveals water level significantly influences discharge (β ≈ 30.27, R² = 0.960). The study recommends implementing seasonal water management plans to address seasonal fluctuations, enhancing flood forecasting systems, adopting adaptive management strategies, investing in long-term monitoring and research, and promoting stakeholder collaboration. These measures aim to improve water resource management resilience, flood preparedness, and response capabilities in the face of climate variability and change.

Geochemistry and formation conditions of the natural water composition in the nothern outskirts of Kazan

Kazan is located on the left bank of the Kuibyshev water reservoir in the east of the Russian Plain. The Blue Lakes, which are unique salt-water karst lakes in the Middle Volga region, appear to be a real natural treasure in the northern outskirts of the city. On the basis of field and analytical data obtained in 2023, the geochemical composition of the natural water is studied in the Blue Lakes, the Solonka and Kazanka rivers, uprising springs, and snow cover. Significant variations in the hydrochemical field are controlled by the effect of discharging relatively deep sulfate calcium groundwater from the lower Permian carbonate-sulfate deposits with a mineralization of about 2.5 g/l. The shares of these artesian waters in the river discharge have been determined. They are about 80% for the mouth of the Solonka River in the initial period of summer low water and about 50–60% for the lower reaches of the Kazanka River in the initial period of winter low water. Maximum values of deep water inflows are observed in river valleys along fracture zones of submeridional and northeastern orientation. The stability of hydrochemical parameters in the studied water bodies over time is shown, which is due to a high rate of water exchange and a low anthropogenic impact on the environment. Complexes of microcomponents concentrated in artesian and near-surface waters have been identified. In artesian waters such components are: Ca, Sr, Mg, Li, U, Re, Se; and in the near-surface – K, Fe, Mn, Ba, As, Co. It is noted that in order to determine the degree of surface water pollution, it is important to take into account the conditions of their composition formation and to distinguish between excess concentrations caused by natural and anthropogenic factors.

Community size and disturbance history jointly explain the interplay between stochastic and deterministic community variation in benthic invertebrates

Community ecology has so far struggled to integrate both deterministic and stochastic processes into a global model of community variation. To address this issue, we aimed to characterise the ecological conditions that determine the relative importance of deterministic and stochastic community variation in benthic macroinvertebrates. We sampled macroinvertebrate and algal periphyton communities, and microhabitat conditions at monthly intervals over a five year period in two sampling sites in the regulated Durance River and one site in the Asse River (a natural tributary of the Durance). The relative importance of stochastic and deterministic processes was estimated over time as functional and taxonomic spatial β‐deviation (i.e. β‐diversityobs − mean β‐diversitynull/SD β‐diversitynull) for each sampling date and site. We additionally quantified deterministic variation as the trait–environment relationship and predicted a positive correlation with β‐deviation metrics. We found evidence of overdispersal in both functional and taxonomic β‐diversities compared to null expectations. Spatial β‐deviation was highly variable over temporal scales and was jointly explained by invertebrate community size, disturbance (i.e. flooding), periphyton diversity and to a lesser extent, microhabitat diversity. The key factor that explained β‐deviation was recent river discharge (< 90 days), which had a strong negative effect on community size but was also directly associated with higher β‐deviation, likely related to recolonization processes post‐flood. Lastly, we found that when β‐deviation was high, the hydraulic trait–environment relationship was stronger. This indicates that spatial heterogeneity in hydraulic conditions was the main driver of deterministic variation in invertebrate community structure. This study demonstrates that the importance of stochastic processes can vary greatly over short (~ months) and long (~ years) temporal windows with significant consequences for trait–environment relationships. Our study provides an example of how stochastic community variation can be modelled to better interpret deterministic patterns of community structure in natural communities.

Comparing surface currents near the mouth of three bays along the U.S. East Coast: Chesapeake Bay, Delaware Bay, and New York Bay

Monthly surface currents at 2 km resolution near the mouths of three U.S. east coast bays were obtained from high-frequency radars (Coastal Ocean Dynamics Application Radar, CODAR) during 2012–2024. The currents near these bays, the Chesapeake Bay (CB), the Delaware Bay (DB) and the New York Bay (NB) were analyzed to infer similarity and differences, as well as potential common forcing from regional and basin-scale factors. The contribution to flow variability from local and remote forcing is evaluated by comparing surface currents with (a) river discharges into each bay, (b) with local and regional winds, and (c) with the North Atlantic Oscillation (NAO). The results show that surface flow variability near the mouth of the bays is linked with all three driving factors. The three bays often show similar flow patterns not only of the seasonal cycle, but also during extreme weather events. For example, increased surface flow into the bays from the Atlantic Ocean is seen when hurricanes are observed offshore in the fall, and increased surface flow from the bays is seen during winter storms. During positive NAO phases, eastward flow from all three bays increased due to intensified westerly winds, while during negative NAO phases flow decreased with weakening winds in the region. River discharges into the bays increased during 2012–2019 but decreased during 2019–2024. This change in river discharge trend was especially large in the CB, resulting in a change in trends of the surface currents. Monthly currents of each bay are only weakly correlated with the monthly river flow (R ~ 0.2–0.3; P < 0.05), while the seasonal cycles of rivers and currents have higher correlations (R ~ 0.6–0.7). Local winds show high correlations with the monthly currents (R ~ 0.75) with the current direction ~ 45° to the right of the wind, as expected from Ekman theory. However, contributions to current variability from regional and remote factors cannot be ignored. The results demonstrate the complex nature of the currents near the mouth of bays since multiple drivers, including estuarine, coastal and open ocean dynamics contribute to the observed variability.

Target and Nontarget Analysis of Organophosphorus Flame Retardants and Plasticizers in a River Impacted by Industrial Activity in Eastern China.

Industrial activities are a major source of organophosphorus flame retardants (OPFRs) and plasticizers in aquatic environments. This study investigated the distribution of 40 OPFRs in a river impacted by major industrial manufacturing plants in Eastern China by target analysis. Nontarget analysis using high-resolution mass spectrometry was further employed to identify novel organophosphorus compounds (NOPs). Thirty-four OPFRs were detected in river water samples, with total concentrations of 62.9-1.06 × 103 ng/L (median: 455 ng/L). Triphenylphosphine oxide and diphenyl phosphoric acid were ubiquitously detected up to 620 and 127 ng/L, respectively. Among 26 identified NOPs, 17 were reported for the first time in the environment, including 14 novel organophosphate esters (especially 4 heterocycles and 3 oligomers), 2 organophosphites, and an organophosphonate. Bis(2,4-di-tert-butylphenyl) hydrogen phosphate and 2,2-dimethylpropoxy(propyl)phosphinic acid with high predicted persistence or toxicity were widely detected, with semiquantified concentrations up to 990 and 1.0 × 103 ng/L, respectively. Structurally similar organophosphorus heterocycles exhibited consistent variation trends, suggesting a common emission source. Estimated annual river discharges to the sea were 20.6-37.0 kg/yr for OPFRs and 30.8-161 kg/yr for NOPs. These findings indicate that industrial activities contribute OPFRs and NOPs to the river catchment and its estuary, posing ecological risks to both terrestrial and marine environments.

Indian Ocean Dipole intensifies Benguela Niño through Congo River discharge

Benguela Niños are episodes of unusual El Niño-like warming in the upwelling zone off the coast of southwest Africa, with consequential impacts on marine ecosystems, coastal fisheries and regional weather. The strongest Benguela Niño in the past 40 years occurred in February–April 1995 with local sea surface temperature anomalies up to 4 °C off the coast of Angola and Namibia. Here, we show that a strong Indian Ocean Dipole in September–November 1994 helped boost the amplitude of the 1995 Benguela Niño through a land bridge involving Congo River discharge. We use atmospheric, oceanic, and hydrological data to demonstrate the sequential linkage between Indian Ocean Dipole development, unusually high rainfall in the Congo River basin, high Congo River discharge, low salinity near the Congo River mouth, and southward advection of this low salinity water into the Benguela upwelling region. The low salinity water isolated the surface mixed layer from the thermocline, which limited vertical mixing with colder subsurface waters and led to enhanced sea surface temperature warming. We also discuss how other Indian Ocean Dipole events may have similarly affected subsequent Benguela Niños and the possibility that Indian Ocean Dipole impacts on Benguela Niños may become more prominent in the future.

Macroplastic pollution in riparian corridors of urban and pristine mountain streams in Patagonia (Argentina).

Plastic pollution has garnered much more attention in marine environments, while scientific research on freshwater and terrestrial ecosystems has been relatively overlooked. Numerous studies worldwide have highlighted the presence of macroplastics (>2.5cm) in mountain riverine environments, revealing that even these seemingly pristine ecosystems are not invulnerable to plastic contamination. We investigated the composition and spatial variation of macroplastic debris in the riparian corridors of nine watercourses in Patagonia. Four types of river reaches were assessed: Reference (without urbanization), Upstream-Urban, Urban, and Downstream-Urban, each with varying degrees of urbanization. We analyzed the intrinsic characteristics of the plastics (manufacture and resin type) and environmental factors with possible incidence in plastic distribution (geomorphology, land use, riparian vegetation quality, and climate) during the Southern Hemisphere's spring season. The most abundant macroplastic debris originated from domestic sources, primarily bags (high- and low-density polyethylene), food wrappers (polypropylene), and beverage bottles (polyethylene terephthalate). The number of inhabitants and proximity to urban areas were the strongest drivers of riverside litter accumulation. Climatic variables such as wind speed and rainfall have incidence in macroplastic abundance, but other factors, such as river discharge possibly played a role in their mobilization. Macroplastics number positively correlated with urban area and negatively with non-woody vegetation. The quality of the riparian corridor, as measured by the QBRp index, had low explanatory power for litter accumulation. Lower QBRp scores were associated with a high number of macroplastic items suggesting that vegetation played a limited role in trapping litter, possibly because urban reaches were heavily anthropized. This study highlights the importance of identifying critical areas of litter accumulation on riverbanks. Our findings provide a foundation for developing strategies to mitigate plastic pollution, improve waste management, and raise public awareness about the challenges of macroplastic contamination and its proper disposal in Patagonia.