The dataset contains reconstructed daily streamflow records for 816 snowmelt-dominated catchments worldwide covering the period 1950-2023. Streamflow series were reconstructed using an observation-prioritized, performance-based weighted ensemble framework that integrates deep learning models and differentiable hybrid hydrological models. The reconstruction framework was developed to generate continuous daily streamflow records in catchments affected by incomplete observations and varying data availability. The dataset is distributed as a pickle file ( ensemble_1950_2023_obs_prioritized.pickle ). The file contains a dictionary in which each key corresponds to a unique basin identifier (e.g., GRDC_1 ), and each value is a pandas DataFrame containing daily streamflow records for that basin. The obs column contains the original observed streamflow records where available. The ensemble column provides continuous daily streamflow estimates for the entire study period, including both observed and missing intervals. The file gauge_information.csv contains geographic information and reconstruction statistics for the 816 snowmelt-dominated catchments included in the reconstructed streamflow dataset. The file includes the following variables: gauge_id : Unique identifier of the gauging station obtained from the Global Runoff Data Centre (GRDC). lat : Latitude of the gauging station (decimal degrees). long : Longitude of the gauging station (decimal degrees). reconstruction_rate : Percentage of reconstructed daily streamflow values relative to the total length of the streamflow record. This variable quantifies the proportion of missing observations that were filled using the ensemble reconstruction framework. Higher values indicate a greater degree of reconstruction, whereas a value of 0% indicates a fully observed streamflow record.
The dataset comprises a comprehensive 15-year spatiotemporal record of the unvegetated Sulengguole River, integrating high-resolution satellite imagery, field surveys, and derived morphodynamic metrics to document a complete post-avulsion cascade. High-resolution optical imagery and in-situ photographs visually capture the multi-stage morphological evolution, detailing the 2019 annexational flow capture, subsequent rapid channel widening, and the critical emergence of alternate bars. These visual observations are directly substantiated by extensive quantitative spatial analyses, which track the downstream kinematic propagation of both the channel-widening waves and the critical half-width-to-depth ratio ( β ) instability fronts. Ultimately, this combination of planform imagery and extracted geometric data explicitly links the macroscopic avulsion-driven reorganization to the extreme, width-dependent acceleration of local meander migration.
This repository contains: "predicted_nitrate_concentrations_global.txt" - global dataset with ensemble averaged long-term mean ntirate concentration (mean_nit, mg/l), their standard deviation (sd_nit, mg/l), coefficient of variation (cv_nit, %), median (p50_nit, mg/l), 10th (p10_nit, mg/l) and 90th (p90_nit, mg/l) percentile of predicted nitrate concentrations across 1000 models in 2895895 global river segments (MERIT Hydro COMID used as identifiers) along with their landuse, aridity class, income class, rural-urban class and stream order "global_river_nitrate_model_v1.0.0.zip" - code used to generate global river nitrate dataset Global River Nitrate Model V1.0.0 A global scale approach for estimating long term mean nitrate concentrations across the global river network using land use, climate, soil and other catchment attributes Overview Nitrate continues to be a persistent global problem, causing eutrophication, endangering aquatic life and human health, and driving higher drinking water treatment costs. Human nitrogen input is considered as the main driver of high nitrate concentrations. Catchment factors including climate, soil and aquifer properties are known to moderate the effect of human nitrogen input; yet there is a lack of global framework explaining these interactions. While rivers in North America and Europe are relatively well monitored, rivers in other continents have huge gaps in their monitoring network. This work aims to 1) generate a global map of river nitrate concentrations and 2) show ariditiy as an important control over river nitrate concentrations along with nitrogen input. For this purpose, an ensemble of 1000 machine learning (boosted regression tree) models was trained on data from 7213 sites (Global River Quality Archive, GRQA) representing 6601 river segments to predict nitrate concentration across the global river network (Multi-Error-Removed Improved Terrain Hydrography, MERIT-Hydro). The predicted nitrate concentrations were used to additionally assess the global area and population exposed to high nitrate concentrations. Repository Structure - `data/` - Input datasets - `raw/` - Unprocessed input data (from original databases or repositories) - `processed/` - Processed data created by scripts for model training and prediction - `models` - Models are saved here - `results` - Predicted river nitrate concentrations - `scripts` - Scripts that clean raw data, trains model on it and predict nitrate concentrations - `01_nitrate_data_cleaning` - cleans raw data and calculate mean river nitrate concentrations in GRQA sites - `02_identify_river_segments_with_data` - identifies the river segments on which the GRQA sites are located - `03_train_BRT_model` - trains 1000 machine learning models to predict mean nitrate concentrations - `04_predict_global_nitrate` - predicts nitrate concentration in 2895896 segments in the global river network Requirements The scripts run in R (version 4.3.2) and requires the following packages: - readr (2.1.5) - dplyr (1.1.4) - lubridate (1.9.4) - sf (1.0.16) - parallel (4.3.2) - caret (6.0.94) - xgboost (1.7.7.1) - hydroGOF (0.6.0) Data Nitrate concentration data: Global River Quality Archive (GRQA) (1) Global river network: Multi-Error-Removed Improved Terrain Hydrography (MERIT Hydro) (2) Catchment characteristics: - Terra and Aqua combined Moderate Resolution Imaging Spectroradiometer (MODIS) Land Cover Type MODIS Land Cover Type Product (MCD12Q1, version 6.1) (3) - Climatologies at High Resolution for the Earth's Land Surface Areas (CHELSA version 2.1) (4) - Global Multi-resolution Terrain Elevation Data 2010 (GMTED2010) (5) - SoilGrids version 2.0 (6) - Global Geo-processed Data of Aquifer Properties by 0.5° Grid, Country and Water Basins (7) Notes The data for training the models are provided in the file "BRT_train_data_7213_catchments.txt" in the folder "data/processed". The "BRT_input_global_subset.txt" file in the same folder contains catchment characteristics for 5000 river segments as an example dataset to demonstrate prediction of river nitrate concentration in these segments. Citation 1. H. Virro, G. Amatulli, A. Kmoch, L. Shen, E. Uuemaa, GRQA: global river water quality archive. Earth System Science Data Discussions 2021, 1-30 (2021) 2. D. Yamazaki et al., MERIT Hydro: A high‐resolution global hydrography map based on latest topography dataset. Water Resources Research 55, 5053-5073 (2019) 3. M. Friedl, D. Sulla-Menashe, MODIS/Terra+ Aqua land cover type yearly L3 Global 0.05 Deg CMG V061, MCD12C1. 061, NASA EOSDIS Land Processes Distributed Active Archive Center (DAAC), (2022) 4. D. N. Karger et al., Climatologies at high resolution for the earth's land surface areas. Scientific data 4, 1-20 (2017) 5. J. J. Danielson, D. B. Gesch, Global multi-resolution terrain elevation data 2010 (GMTED2010), US Geological Survey, (2011) 6. L. Poggio et al., SoilGrids 2.0: producing soil information for the globe with quantified spatial uncertainty. Soil 7, 217-240 (2021) 7. H. Niazi et al., Global Geo-processed Data of Aquifer Properties by 0.5 Grid, Country and Water Basins, MultiSector Dynamics-Living, Intuitive, Value-adding, Environment, (2024)
Peifer, Daniel · Beer, Alexander · Glotzbach, Christoph · et al.
8.0 MB
This repository contains the data and code supporting Peifer et al., "Cascading river captures drive windgap propagation and drainage reversal". It includes raw numerical model outputs for the simulations used to generate SI Appendix Movies S1 to S14, source tables for the quantitative analyses reported in the manuscript and SI Appendix, vector geometries used to define baseline and paired U100 windgap and adjacent divide measurement domains, model generation scripts, calculation workflows and reproducibility documentation.
This dataset supports the manuscript "A differentiable Xinanjiang model with multi-layer soil moisture state correction for runoff simulation". The dataset contains public input data, model evaluation metrics, and public model-output files for the Daning River basin and ten CAMELS-US basins. It includes processed CAMELS-US forcing, public CAMELS-US runoff observations, prepared soil moisture inputs, model performance metrics, simulated runoff, model parameters, and state-correction diagnostics. Daily observed runoff and station precipitation for the Daning River basin are not included because they are subject to data-provider restrictions. Source code, neural-network weight files, training logs, and intermediate optimization databases are also not included.
YU, Lujia · DE LEO, Annalisa · STOCCHINO, ALESSANDRO
This study presents a Lagrangian analysis of floating particle transport dynamics in the Pearl River Estuary region, addressing critical gaps in understanding long-term variability and density-dependent anisotropy. Based on a 40-year ensemble of 100 representative hydrodynamic scenarios simulated by a regional circulation model, a lagrangian transport model was used to generate trajectories for particles of three densities, together with neutrally buoyant water tracers. Zonal ($R_{uu}$) and meridional ($R_{vv}$) velocity autocorrelation functions were computed for each trajectory and classified using k-means clustering. This data-driven approach objectively partitions the trajectories into five centroids, further grouped into looping, transient and non-looping regimes. Spatially, looping regimes dominate estuarine channels and offshore recirculation corridors, whereas non-looping regimes prevail in semi-enclosed bays and sheltered coastlines. A systematic density-controlled transition is observed: decreasing particle density attenuates oscillatory memory and increases the probability of non-looping behavior due to enhanced windage and Stokes drift. In these systems, transport dynamics exhibit a strong anisotropy governed by the alignment of seasonal monsoons with the estuarine geometry, which controls the spatial distribution of zonal and meridional decorrelation scales. Nonlinear stochastic fitting further shows that looping regimes exhibit a consistent tidal period of approximately 12 hours across all densities, whereas transient regimes experience a collapse of coherent oscillations. Using the Pearl River Estuary as a prototype, this framework provides a physically interpretable and transferable tool for identifying transport regimes and guiding targeted monitoring strategies across highly dynamic, river-dominated coastal environments.
40 RGB PNG frames of ERA5 vertically integrated water-vapour transport (IVT) magnitude over the North Pacific, 6-hourly from 2 to 11 February 2017, derived from the public ARCO-ERA5 archive (IVT = sqrt(u^2 + v^2)). Each frame renders an atmospheric river as a bright filament on a dark background and is named NPacific_IVT_0000.png ... NPacific_IVT_0039.png. This is the Earth-observation dataset for the Galaxy Training Network tutorial 'Object tracking using CellProfiler' (https://gxy.io/GTN:T00516), used to demonstrate that a CellProfiler nucleus-tracking pipeline can be reused to detect and track atmospheric rivers. Preprocessing notebooks, full Galaxy run provenance, and the software archive: https://github.com/annefou/fiesta-galaxy-cellprofiler-eo (DOI 10.5281/zenodo.20811614). Part of the OSCARS-FIESTA project.
This article presents a comparison of sediment input by rivers and by coastal erosion into both the Laptev Sea and the Canadian Beaufort Sea (CBS). New data on coastal erosion in the Laptev Sea, which are based on field measurements and remote sensing information, and existing data on coastal erosion in the CBS as well as riverine sediment discharge into both the Laptev Sea and the CBS are included. Strong regional differences in the percentages of coastal erosion and riverine sediment supply are observed. The CBS is dominated by the riverine sediment discharge (64.45210**6 t/a) mainly of the Mackenzie River, which is the largest single source of sediments in the Arctic. Riverine sediment discharge into the Laptev Sea amounts to 24.10210**6 t/a, more than 70% of which are related to the Lena River. In comparison with the CBS, the Laptev Sea coast on average delivers approximately twice as much sediment mass per kilometer, a result of higher erosion rates due to higher cliffs and seasonal ice melting. In the Laptev Sea sediment input by coastal erosion (58.4210**6 t/a) is therefore more important than in the CBS and the ratio between riverine and coastal sediment input amounts to 0.4. Coastal erosion supplying 5.6210**6 t/a is less significant for the sediment budget of the CBS where riverine sediment discharge exceeds coastal sediment input by a factor of ca. 10.
Moore, Jennifer A. · Tallmon, David A. · Nielsen, Julie · et al.
Understanding the impact of natural and anthropogenic landscape features on population connectivity is a major goal in evolutionary ecology and conservation. Discovery of dispersal barriers is important for predicting population responses to landscape and environmental changes, particularly for populations at geographic range margins. We used a landscape genetics approach to quantify the effects of landscape features on gene flow and connectivity of boreal toad (Bufo boreas) populations from two distinct landscapes in Southeast Alaska (Admiralty Island, ANM, and the Chilkat River Valley, CRV). We used two common methodologies for calculating resistance distances in landscape genetics studies (resistance based on least-cost paths and circuit theory). We found a strong effect of saltwater on genetic distance of CRV populations, but no landscape effects were found for the ANM populations. Our discordant results show the importance of examining multiple landscapes that differ in the variability of their features, in order to maximize detectability of underlying processes and allow results to be broadly applicable across regions. Saltwater serves as a physiological barrier to boreal toad gene flow and affects populations on a small geographic scale, yet there appear to be few other barriers to toad dispersal in this intact northern region.
Fry, Lauren · Seglenieks, Frank · Shrestha, Narayan Kumar · et al.
3 files · 22 MB · sevenzipdeclared
In response to flooding on Lake Ontario and the St. Lawrence River in 2017 and 2019, the U.S. and Canadian governments directed the Great Lakes - St. Lawrence River Adaptive Management (GLAM) Committee to expedite review of Lake Ontario outflow regulation Plan 2014 ahead of its usual 15-year review cycle. The dataset includes (1) a baseline record based on data from 1961-2020, (2) a set of stochastic scenarios that incorporates extremes that may not be in the historical record but are plausible under current hydroclimate conditions, and (3) a set of climate change scenarios to support evaluation of the plan under plausible decadal-scale hydroclimate changes. All data required to simulate Lake Ontario water levels, outflows, and downstream water levels are provided for each scenario. The data have been compressed into the following files: Baseline.7z - Baseline hydroclimate record from 1961-2020 Climate.7z - 8 future climate hydroclimate records Stochastic.7z - 500 stochastic hydroclimate records Within each compressed file are subdirectories that contain the files for each water supply sequence. The following table lists the files that are provided for each of the water supply sequences. For each file there is a description of the variable contained in the file, the location of the data in the file, and the unit of the data in the file if applicable. Filename Variable Location Units dpmi_flw_cms_qm48_na.csv Flow Des Prairies and Mille Iles River cms rich_flw_cms_qm48_na.csv Flow Richelieu River at Rapides Fryer cms stfr_flw_cms_qm48_na.csv Flow St. Francois River at Chut Hemming cms stmc_flw_cms_qm48_na.csv Flow St. Maurice River at La Gabelle cms ont_nbs_cms_qm48_na.csv Net Basin Supply Lake Ontario cms ont_nbs_cms_qm48_na_spinup.csv Net Basin Supply Lake Ontario cms eri_flw_cms_qm48_na.csv Outflow Lake Erie cms eri_flw_cms_qm48_na_spinup.csv Outflow (one year spinup) Lake Erie cms slon_flw_cms_qm48_na.csv SLON flow St. Lawrence River (Lake St. Louis) cms slon_flw_cms_qm48_na_spinup.csv SLON flow (one year spinup) St. Lawrence River (Lake St. Louis) cms stl_icw_cms_qm48_na.csv Ice/weed retardation St. Lawrence River cms stl_tde_m_qm48_na.csv Tidal Signal St. Lawrence River m ont_mlv_m_qm48_na_spinup.csv Water Level (one year spinup) Lake Ontario m stl_ics_xx_qm48_na.csv Ice status indicator St. Lawrence River N/A bati_rgh_xx_qm48_na.csv Ice/weed roughness factor Batiscan N/A card_rgh_xx_qm48_na.csv Ice/weed roughness factor Cardinal N/A corn_rgh_xx_qm48_na.csv Ice/weed roughness factor Cornwall N/A intw_rgh_xx_qm48_na.csv Ice/weed roughness factor International Tail Water N/A irhw_rgh_xx_qm48_na.csv Ice/weed roughness factor Iroquois Head Water N/A irtw_rgh_xx_qm48_na.csv Ice/weed roughness factor Iroquois Tail Water N/A jty1_rgh_xx_qm48_na.csv Ice/weed roughness factor Montreal Jetty No. 1 N/A lspr_rgh_xx_qm48_na.csv Ice/weed roughness factor Lake St. Pierre N/A lstd_rgh_xx_qm48_na.csv Ice/weed roughness factor Long Sault Dam N/A morr_rgh_xx_qm48_na.csv Ice/weed roughness factor Morrisburg N/A ogde_rgh_xx_qm48_na.csv Ice/weed roughness factor Odgensburg N/A ptcl_rgh_xx_qm48_na.csv Ice/weed roughness factor Pointe - Claire N/A sahw_rgh_xx_qm48_na.csv Ice/weed roughness factor Saunders Head Water N/A sorl_rgh_xx_qm48_na.csv Ice/weed roughness factor Sorel N/A summ_rgh_xx_qm48_na.csv Ice/weed roughness factor Summerstown N/A triv_rgh_xx_qm48_na.csv Ice/weed roughness factor Trois Rivières N/A vare_rgh_xx_qm48_na.csv Ice/weed roughness factor Varennes N/A na_fst_xx_qm48_na.csv Forecast indicator N/A N/A
Ikramova M. · Allayorova D. · Tashmatov K. · et al.
1 files · 338 KB · pdfdeclared
Abstract The article addresses the pressing engineering-hydraulic issue of forecasting the siltation of channel reservoirs characterized by high turbulence and significant solid runoff. A balanced mathematical model and a step-by-step algorithm for calculating sediment dynamics using the section method for the conditions of the Tuyamuyun Hydro Complex Channel Reservoir on the Amu Darya River have been developed. The transport capacity of the flow, the dynamics of turbidity changes along the riverbed, and the sedimentation intensity of suspended particles were evaluated, which are described by the exponential law of mass conservation. To conduct rapid forecasts, a calculation scheme adapted to various water availabilities (low-water, medium-water, and high-water years) was implemented with an integration step of one month. The proposed algorithm allows for the calculation of sediment volumes and the modeling of reservoir bed sedimentation dynamics with a high degree of sensitivity to hydrodynamic flow parameters.
The patterns of spatial variation of diatom assemblages from surface sediments in Lake Lama were quantified using a combined approach of ordination and geostatistics. The aims were (i) to estimate the amount of variation between diatom assemblages within the lake, (ii) to model the spatial variability of the diatom assemblages and their diversity, and (iii) to map the diatom distributions in the lake. A correspondence analysis (CA) separated the diatom assemblages into a planktonic and a periphytic group. Rheophilic taxa were found within the periphytic group. Variogram analysis showed that only the sample scores of the first CA axis and the Shannon diversity index were spatially structured. The range of spatial correlation was estimated to be 55 km for both variables. The diversity and, to a lesser extent, the sample scores had considerable small-scale variability of about 20 and 3%, respectively. Estimates of the first component of the CA and the Shannon index were derived using block-kriging. The maps of the estimates provided a basis for partitioning Lake Lama according to the spatial structures into an eastern and a western basin, a north–south connection between the basins, and a north–south directed tip at the far eastern end. It was shown that variation in diatom assemblages is mainly spatially structured at the catchment scale and that there is a considerable amount of variation at smaller scales. According to the modeled spatial distribution, the assemblages are most likely affected by the lake size, morphology, and the water and nutrient input introduced by rivers. This has to be taken into account when paleolimnological interpretations are drawn from records of complex lake systems like Lake Lama.
Stein, Ruediger · Dittmers, Klaus Hauke · Fahl, Kirsten · et al.
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11 numeric · 1 categorical
In this paper, we summarize data on terrigenous sediment supply in the Kara Sea and its accumulation and spatial and temporal variability during Holocene times. Sedimentological, organic-geochemical, and micropaleontological proxies determined in surface sediments allow to characterize the modern (riverine) terrigenous sediment input. AMS-14C dated sediment cores from the Ob and Yenisei estuaries and the adjacent inner Kara Sea were investigated to determine the terrigenous sediment fluxes and their relationship to paleoenvironmental changes. The variability of sediment fluxes during Holocene times is related to the post-glacial sea-level rise and changes in river discharge and coastal erosion input. Whereas during the late/middle Holocene most of the terrigenous sediments were deposited in the estuaries and the areas directly off the estuaries, huge amounts of sediments accumulated on the Kara Sea shelf farther north during the early Holocene before about 9 cal kyr BP. The maximum accumulation at that time is related to the lowered sea level, increased coastal erosion, and increased river discharge. Based on sediment thickness charts, echograph profiles and sediment core data, we estimate an average Holocene (0–11 cal kyr BP) annual accumulation of 194,106 t/yr of total sediment for the whole Kara Sea. Based on late Holocene (modern) sediment accumulation in the estuaries, probably 12,106 t/yr of riverine suspended matter (i.e. about 30% of the input) may escape the marginal filter on a geological time scale and is transported onto the open Kara Sea shelf. The high-resolution magnetic susceptibility record of a Yenisei core suggests a short-term variability in Siberian climate and river discharge on a frequency of 300–700 yr. This variability may reflect natural cyclic climate variations to be seen in context with the interannual and interdecadal environmental changes recorded in the High Northern Latitudes over the last decades, such as the NAO/AO pattern. A major decrease in MS values starting near 2.5 cal kyr BP, being more pronounced during the last about 2 cal kyr BP, correlates with a cooling trend over Greenland as indicated in the GISP-2 Ice Core, extended sea-ice cover in the North Atlantic, and advances of glaciers in western Norway. Our still preliminary interpretation of the MS variability has to be proven by further MS records from additional cores as well as other high-resolution multi-proxy Arctic climate records.
This paper presents an integrated framework for evaluating flood mitigation measures by combining hydrological modelling, economic assessment, and public perception . Applied to the Gradaščica River catchment in Slovenia, the study compares different structural and nature-based measures, including wetlands, retention polders, and dams, to assess their effectiveness in reducing flood risk. By bringing together physical performance, cost-effectiveness, and societal acceptance, the research shows the value of a multidisciplinary approach for supporting more balanced and informed flood-risk management decisions. The work contributes to the SpongeScapes project by improving understanding of how different measures can enhance landscape resilience and support climate adaptation.
During spring, ammonium oxidation and nitrite oxidation rates were measured in the NW basin of the Mediterranean Sea, from mesotrophic sites (Ligurian Sea and Gulf of Lions) to oligotrophic sites (Balearic Islands). Nitrification rates (average values for 37 measurements) ranged from 72 to 144 nmol of N oxidised/l/d, except in the Rhône River plume area where the rates increased to 264-504 nmol/l/d because of the riverine inputs of nitrogen. Maximal rates were located around the peak of nitrite within the nitracline at about 40 to 60 m and just above the phosphacline. At 1 station, relatively high values of nitrification (50 to 130 nmol/l/d) were also measured deep in the water column (240 m). Day-to-day variations were measured demonstrating the response within a few hours to hydrological stress (wind-induced mixing of the water column) and showing the role of hydrological characteristics on the distribution of nitrification rates. Because of the homogenous temperature (13°C) in the Mediterranean Sea, the spatial (geographical and vertical) fluctuations of nitrifying rates were linked to the presence of substrate due to mineralisation processes and/or Rhône River inputs. We estimate the contribution of nitrate produced by nitrification to the N demand of phytoplankton to range from 16% at mesotrophic to 61% at oligotrophic stations.
DNA reference database for the fishes of the Yangtze River Basin with a particular focus on 12S and COI sequences. These sequences were compiled from four sources: 1) BOLD, 2) MIDORI2, 3) MitoFish, 4) NCBI nucleotide database (nuccore) and supplemented by local DNA sequence samples for rare taxa. See README for descriptions of each file.
Gallegos Pasco, Pedro Alvaro Edwin · Pineda Chaíña, Haydee Celia · Teves Ponce, Luz Marina · et al.
1 files · 893 KB · pdfdeclared
Water-quality indices are not only technical summaries but communication devices: they translate complex multivariate monitoring data into a few public categories used to understand and act upon environmental risk. This article reinterprets the Canadian Council of Ministers of the Environment Water Quality Index (CCME-WQI) as a communication instrument and asks how faithfully its public categories can be reconstructed from raw physicochemical data, and what is lost when a continuous risk gradient is compressed into a public message. Using 400 observations from 12 stations of Peru's National Water Authority in the Llave River Basin, supervised classifiers and a stacking ensemble were trained to recover the three public categories (Excellent, Good, Fair/Poor), while silhouette analysis and principal-component analysis probed the data structure. The categories proved only moderately recoverable: the best model reached 65% exact accuracy, a ceiling no method surpassed, yet about 91% within-one-category accuracy, almost never confusing excellent with degraded water. Nearly half the observations sit at the index ceiling and most of the rest sit just below a threshold, so distinct public messages attach to near-identical water; a near-zero category silhouette and PCA confirm a high-dimensional continuum that the labels cut across. We argue that this gap between gradient and label is the price of legibility, and discuss how category boundaries frame public risk perception and the unequal capacity of Quechua- and Aymara-speaking communities to access these messages.