Despite decades of concern over the carcinogenic potential of agricultural pesticides, toxicological studies relying on single endpoints have yet to establish a definitive link between environmental pesticide exposure and cancer in real-world contexts. Here we use an integrative spatial Bayesian framework that merges high-resolution environmental pesticide risk modelling with comprehensive cancer registry data to map pesticide-linked cancer clusters in Peru with unprecedented precision. Our process-based model, encompassing 31 key pesticide active ingredients, together with an innovative stratification of cancer cases by developmental lineage, reveals a robust spatial association between environmental pesticide exposure risk and cancer incidence. In pesticide-associated cancer hotspots, exposomic profiling of liver tissue-a primary target of chemical carcinogens-uncovers a distinct transcriptomic signature of pesticide exposure, implicating a non-genotoxic mode of action that disrupts core regulatory circuitries sustaining cell identity. Collectively, these findings strongly support a mechanistic link between pesticide exposure and cancer, challenging assumptions of human non-carcinogenicity derived from reductionist experimental models. This study redefines the exposome as a lineage-conditioned, mechanistically tractable framework and shows how complex pesticide mixtures can contribute to carcinogenic trajectories, with profound and far-reaching implications for global health policy and socio-ecological equity.

Peatlands are globally significant carbon sinks; however, their response to recent climate warming remains poorly understood in tropical high-elevation regions. In the tropical Andes, rising temperatures, altered precipitation seasonality, and widespread glacier retreat over the past 65 years may have influenced peatland hydrology and carbon storage. Here, we reconstructed carbon accumulation rates (CARs) using four radiocarbon-dated peat cores from two Distichia muscoides–dominated high-Andean peatlands in the Central Peruvian Andes (APA1 and APA2). Basal ages ranged from 1957 to 1972 CE. CARs were exceptionally high, averaging 250 g C m−2 yr−1 at APA2 and 440 g C m−2 yr−1 at APA1, with peaks of up to 960 g C m−2 yr−1, reflecting rapid peat accumulation and the high organic carbon content characteristic of D. muscoides. Both sites exhibited a pronounced decline in peat accumulation rates and CARs from the early 1980s. This decline coincided with a regional increase in air temperature as indicated by NCEP/NCAR Reanalysis data and was corroborated by a temperature-sensitive proxy based on the stable carbon isotope composition (δ13C) of Distichia, the trends of which exceeded those expected from changes in atmospheric δ¹ ³C–CO₂ alone. These findings indicate that warming-driven enhancement of organic matter decomposition has reduced net carbon sequestration. Our results demonstrate that high-Andean peatlands are highly sensitive to recent climate warming and hydrological stress, and future temperature increases are likely to further weaken their function as long-term carbon sinks.

Abstract. The glacierized mountains are impacted by dramatic changes in the context of global warming with large implications for hydrology. However, the projection of icemelt contribution to streamflow remains a complicated task and is subject of large uncertainties, especially when the calibration-validation process was performed with little or no cryospheric data. In this study, we present the integration of a glacier module in the distributed conceptual hydrological model J2000, taking into consideration the evolution of glacier surface in the simulations. A calibration and a validation was done using a large panel of hydro-cryospheric datasets, including glacier mass balance observations and simulations, snow reanalyses, snow-cover by satellites and stream gauges. The calibration-validation was performed by applying J2000-Rhône-glaciers to the entire Rhône basin in the historical period (1976–2022) using the SAFRAN climate reanalysis at 8 km horizontal resolution. The set of parameters identified in the past and meteorological data from 5 “GCM-RCM” chains of climate projections under RCP 8.5 scenario were used to simulate the hydrological response of the Rhône basin under climate change projections (1976–2095). The results show that snowmelt, icemelt and streamflow are satisfactorily simulated by J2000-Rhône-glaciers in the Rhône basin. The projections show a decrease of annual streamflow expected by the end of the 21st century due to a decrease of precipitation and glacier shrinkage in highly glaciated subbasins. The results of the simulations also show an increase of streamflow in winter but a dramatic decrease in summer mainly due to a change in snow seasonality. The icemelt will become extremely low in Isère, Drac and Durance subbasins, while in the Arve, upper Rhône, and along the Rhône River, the future evolution of icemelt contribution to summer streamflow is very uncertain. Despite these uncertainties, our results suggest that the remaining glaciers will still be crucial to sustain the summer streamflow at the end of the century. However, the peak water may be passed by 2040s in the Arve subbasin, and 2050s in the upper Rhône, and the change in snow seasonality will still threaten the availability of water resources in most of the Rhône subbasins. The use of multi-source cryospheric datasets allowed to gain confidence in the projections of icemelt contribution to streamflow in a large basin in the Alps.

Snow is a critical component of the Andean hydrological system, supporting water supply for drinking, irrigation, hydropower, and industry. Persistent cloud cover and limited in situ observations have hindered long-term assessments of snow dynamics across the Andes, the world’s longest mountain range. Here, we present a continent-scale analysis of snow persistence (SP) and snowline elevation from 2000 to 2025 using daily MODIS Terra–Aqua products enhanced with advanced temporal and spatial cloud-reduction algorithms. Cloud persistence was reduced from 49% to 29%, substantially increasing the usable observational record for snow detection, although cloud-related limitations remain in tropical and southern Patagonia regions. Our results reveal that snow responses are strongly heterogeneous along the mountain chain. There is a marked and spatially coherent decline in SP between 29 °S and 36 °S, where an area equivalent to approximately 80,000 km2 of snow cover has been lost over the past 26 years. In this region, the snowline rose by 5–15 m yr⁻¹, reaching cumulative increases of up to 500 m. At the watershed scale, only basins in the Central Andes (29 °S – 36 °S) exhibit statistically significant SP declines and rising snowlines, while tropical watersheds show minimal snow presence and southern Patagonia displays mixed patterns partially influenced by persistent cloud cover. The accelerating loss of seasonal snow in the central Andes has profound implications for water security in regions where snowmelt is a dominant hydrological input. Our results underscore the need for higher-resolution multispectral and radar observations, expanded ground-based monitoring, and integrative modeling approaches to quantify snow water equivalent and anticipate future changes. Collectively, this study provides one of the most comprehensive assessments to date of Andean snow dynamics and highlights the central Andes as a hotspot of cryospheric sensitivity to ongoing climate change.

Permafrost degradation significantly affects the stability of rockwalls in high altitude regions. Monitoring rockwall permafrost is essential for assessing potential geohazards. While borehole temperature measurements are the most direct permafrost monitoring approach, they lack sufficient spatial representation in such highly heterogeneous ground conditions. Conversely, geoelectrical measurements can provide more comprehensive insights into these complex patterns and dynamics. This study investigates the permafrost dynamics and intends to detect potential hydrogeological processes at the Aiguille du Midi (3842 m a.s.l. (meter above sea level), French Alps) using repeated and Automated-Electrical Resistivity Tomography (A-ERT) approaches, covering a period of 3.5 years (June 2020-December 2023). A total of three geoelectrical profiles have been installed on three faces of the Aiguille du Midi (N-W, S and E). An automated acquisition system for permanent resistivity monitoring and remote data acquisition is implemented. A time-lapse inversion technique is employed to get the temporal and spatial variations of electrical resistivity at seasonal and interannual time scales. The data revealed significant variations in active layer thickness across rock faces, along with a slight decrease in electrical resistivity at depth, indicating permafrost warming over time. However, they did not provide clear evidence of water pressurization in rock fractures. Using a petrophysical model, calibrated with laboratory measurements of the temperature dependence of electrical resistivity of granite sample, we estimated the temperature within the frozen zone from the resistivity measurements, under favorable conditions at surface in summer and autumn. Validation against direct temperature measurements in a 10 m depth borehole along the NW profile indicates a mean absolute error less than 1 degrees C within the frozen zone. This research underscores the efficacy of ERT as a promising, non-invasive tool for quantitative monitoring of permafrost dynamics in Alpine environments. It also reveals challenges associated with conducting A-ERT in high mountain rockwalls where the contact resistance is very high (similar to 500k Omega) and sometimes intermittent due to factors such as thunder strikes and rockfalls.

Mountain headwaters in the tropical Andes are vital for regional water security, yet the extensive Puna grassland biome remains largely understudied. To help address this gap, we employed a paired-catchment design in two Peruvian Puna catchments and used high-resolution hydrometric data, over the period [2012-2014] at hourly time-step, to investigate controls on hydrological partitioning and subsurface storage. Our findings provide a field-based perspective on the classic 'sponge versus pipe' paradox by showing that peat-forming wetlands (bofedales) perform a dual hydrological role. Their saturated surfaces act as efficient 'pipes' that enhance event runoff, while their porous subsurface provides event-scale buffering that dampens hydrograph recessions, defining them as seasonal buffers rather than long-term dry-season stores. Streamflow recession analysis further supports a dual-reservoir conceptualization, in which infiltrated water is partitioned between a shallow system connected to local streamflow and a deeper system linked to regional groundwater recharge. The catchment with greater apparent percolation capacity produced lower annual water yield, consistent with a 'leaky' catchment interpretation involving inter-catchment groundwater flow that bypasses the topographic outlet. Our comparison also suggests that the naturally flashier response of this catchment may be further accentuated by more intensive grazing, although this land-use signal should be interpreted as secondary to hydrogeomorphic controls. Overall, the results indicate that hydrological functioning is organized hierarchically: subsurface and surficial hydrogeomorphic setting controls the distribution of bofedales and flow paths, while land use modulates the resulting response. This perspective reframes Puna headwater catchments as three-dimensional systems characterized by a trade-off between local streamflow resilience and regional aquifer recharge, underscoring the need to preserve bofedal connectivity and mitigate soil-degrading land uses.

La cuenca con presencia glaciar en los Andes tropicales presenta continuo derretimiento, como efecto del cambio climático, lo que influencia en la generación de escorrentía y en los procesos hidrológicos. El estudio se realizó entre los años 2013 y 2020 en la microcuenca Yanamarey (Cordillera Blanca, Perú), utilizando las imágenes de satélite y modelización hidro-glaciológica, aplicando los modelos semidistribuidos GSM y SOCONT, para estimar procesos glaciológicos e hidrológicos distribuidos por bandas de altitud. En este periodo, en el glaciar se determinaron en promedio 0.27 km2 de superficie y 1.65 hm3 de volumen; la contribución hídrica promedio en la microcuenca es de 93 l/s, distribuidos de la siguiente forma: 8 % de hielo, un 15 % de nieve, un 27 % de agua subterránea y un 50 % de precipitación (directa). Además, los caudales de hielo y nieve presentan una tendencia negativa anual de 0.5 y 0.7 l/año, respectivamente. Produciendo al final de siete años en: a) proceso glaciológico, la fusión de hielo de 14 m debajo de la altitud de 4 800 msnm, la acumulación de nieve de 12.7 m encima de la altitud de 5 000 msnm; b) proceso hidrológico (zona no glaciar), en suelo limpio, el agua acumulada se infiltra de 118 m (0.19 cm/h) y agua superficial acumulada de 34 m (0.06 cm/h). Los valores estimados de la contribución hídrica y la variación de disponibilidad anual de la masa glaciar por altitudes dan una idea de los procesos hídricos que ocurren en cabecera de cuenca y de la importancia de sus efectos para la vida útil de los glaciares.

Assessing future water contributions from glaciers is crucial for managing water resources, preventing disasters, and protecting ecosystems and communities. However, Andean glacier runoff remains poorly understood because of missing regional and local research studies. We evaluated eight CMIP6 models (1990–2049), projected future changes in glacier runoff (2030–2049) and peak water throughout the 21st century in 778 Andean catchments (11°N-55°S), using the Open Global Glacier Model (OGGM) under two extreme climate change scenarios (SSP1-2.6 and 8.5). Projections for the mid-21st century show warming trends across the Andes, particularly in the Tropical Andes (+ 0.7 °C), while precipitation declines slightly in the Southern Andes (-1 to -3%). These changes significantly impact glacier runoff, with substantial decreases projected for the Tropical Andes (-43%) and Dry Andes (-37%) by 2030–2049. Notably, changes in glacier runoff vary greatly across the Dry Andes, as evidenced by the simulations for the Atuel (-62%) and Tupungato (+ 32%) catchments in Argentina. More than 95% of Andean catchments are expected to reach peak water before 2030 (75th percentile), with significant regional differences. Our study highlights the critical need to examine regional disparities in glacier runoff at the catchment scale, particularly in the Dry Andes of Chile and Argentina. It calls on these governments to actively fund hydrological research in this region, which is essential for effectively managing current and future water resources.

The recent sixth IPCC report highlighted the lack of studies on the impacts of climate change in the Global South. While paradoxically these countries have the weakest resilience capacity to adapt to these forthcoming changes. In this context, a co-construction workshop was organized in 2022 to define the multi-sectoral needs of different academic or institutional actors working on the impacts of climate change. Bridging together meteorological and hydrological agencies, universities, research centers, and private companies from Africa, Europe, South Asia, and South America, this workshop allowed defining the types of data and their modalities of access, that are the most adapted to conduct impact studies of climate change in different domains. The main difficulties in accessing climate data identified for researchers working on climate change impacts were related to the lack of technical capability to retrieve and process the worldwide databases of climate models data and also the need for expertise to exploit this wealth of data efficiently. Following this workshop, a climate services platform was implemented in 2023 (https://climatsuds.ird.fr/) to access a large dataset of bias-corrected CMIP6 climate models simulations, as well as a set of climate indices relevant for impacts assessment (heavy rains, extreme heat..) and impact models outputs (ISIMIP2a) in different sectors (water, vegetation, agriculture, and health). The web platform enables data extraction by point, by country, or by free polygons, visualization in graphic formats, and export to NetCDF or CSV files. Besides data access functionalities, the web portal will gradually integrate different training resources for the users and new datasets according to their needs.

The Alps are impacted by dramatic changes in the context of global warming with large implications for hydrology. The Rhône bassin, draining a large part of the french and Swiss Alps, has already been the subject of hydrological modelling using J2000-Rhone. In this study, we present the integration of a glacier algorithm in the hydrological model J2000-Rhône, the validation of snowmelt, icemelt and streamflow, and the future projections of these processes. The results show that snowmelt, icemelt and streamflow are satisfactorly simulated by J2000-glaciers in the Rhone basin. By the end of the 21st century, the major changes will be a large increase of streamflow in winter but a decrease in summer associated to earlier snowmelt, a decrease of precipitation and glacier shrinkage. On the Arve and upper Rhône catchments, the remaining glaciers will still be crucial to sustain the streamflow in dry summers.

The watershed with glacier presence in the Tropical Andes presents continuous melting, as an effect of climate change, which influencing runoff generation and hydrological processes. The study was conducted between 2013 and 2020 in the Yanamarey micro-watershed (Cordillera Blanca, Peru), using satellite images and hydro-glaciological modeling, applying the semi-distributed models GSM and SOCONT, to estimate glaciological and hydrological processes distributed by altitude bands. During this period, an average of 0.27 km2 of surface area and 1.65 hm3 of volume were determined in the glacier; the average water contribution in the micro-basin is 93 l/s, distributed as follows: 8 % ice, 15 % snow, 27 % groundwater and 50 % precipitation (direct). In addition, the ice and snow flows show a negative annual trend of 0.5 and 0.7 l/year, respectively. Producing at the end of seven years in: a) glaciological process, ice melt of 14 m below the altitude of 4 800 masl, snow accumulation of 12.7 m above the altitude of 5 000 masl; b) hydrological process (non-glacial zone), in clean soil, accumulated water infiltrates of 118 m (0.19 cm/h) and accumulated surface water 34 m (0.06 cm/h). The estimated values of the water contribution and the variation of annual availability of the glacier mass by altitude give us an idea of the water processes that occur at the headwaters of the basin and the importance of their effects on the lifespan of the glaciers.

In the face of climate change and increasing anthropogenic pressures, a reliable water balance is crucial for understanding the drivers of water level fluctuations in large lakes. However, in poorly gauged hydrosystems such as Lake Titicaca, most components of the water balance are not measured directly. Previous estimates for this lake have relied on scaling factors to close the water balance, which introduces additional uncertainty. This study presents an integrated modeling framework based on conceptual models to quantify natural hydrological processes and net irrigation consumption. It was implemented in the Water Evaluation and Planning System (WEAP) platform at a daily time step for the period 1982–2016, considering the following terms of the water balance: upstream inflows, direct precipitation and evaporation over the lake, and downstream outflows. To estimate upstream inflows, we evaluated the impact of snow and ice processes and net irrigation withdrawals on predicted streamflow and lake water levels. We also evaluated the role of heat storage change in evaporation from the lake. The results showed that the proposed modeling framework makes it possible to simulate lake water levels ranging from 3808 to 3812 m a.s.l. with good accuracy (RMSE = 0.32 m d−1) over a wide range of long-term hydroclimatic conditions. The estimated water balance of Lake Titicaca shows that upstream inflows account for 56 % (958 mm yr−1) and direct precipitation over the lake for 44 % (744 mm yr−1) of the total inflows, while 93 % (1616 mm yr−1) of the total outflows are due to evaporation and the remaining 7 % (121 mm yr−1) to downstream outflows. The water balance closure has an error of −15 mm yr−1 without applying scaling factors. Snow and ice processes, together with net irrigation withdrawals, had a minimal impact on variations in the lake water level. Thus, Lake Titicaca is primarily driven by variations in precipitation and high evaporation rates. These results will be useful for supporting decision-making in water resource management. We demonstrate that a simple representation of hydrological processes and irrigation enables accurate simulation of water levels. The proposed modeling framework could be replicated in other poorly gauged large lakes because it is relatively easy to implement, requires few data, and is computationally inexpensive.

For decision making, it is crucial to provide an estimate of the main water balance fluxes to help understand trends and drivers of lake fluctuation in the past and in the future. However, the quantification of fluxes is a complicated task due to the scarcity of hydro-climatic data in space and over time, which hampers addressing all the local and regional hydrological processes at play, notably in the face of multi-decadal climatic and anthropogenic changes. These challenges are addressed at the scale of the Lake Titicaca hydro-system (57000 km2). Lake Titicaca (8400 km2) is located at 3812 m a.s.l. in the Altiplano of South America. Lake water levels measured since the beginning of the last century show extreme fluctuations within a range of approximately 6 m. This study presents an approach to disentangle the climatic and anthropogenic drivers of past fluctuation of Lake Titicaca. For this, we implemented a conceptual integrated modeling chain that represents the following components: (i) production and routing processes based on a precipitation-runoff model including snow and glacier as well as net water consumption from irrigation in order to estimate lake inflows; and (ii) lake basic functioning according to inflows, direct precipitation and evaporation, bathymetry and outflows. The modeling chain was implemented in the Water Evaluation and Planning System (WEAP) platform at a daily time step over a 30-year period (1985–2015) and was driven by climate inputs derived from ground station data and ERA5 reanalysis. Model calibration and evaluation was based on geodetic mass balance, catchment streamflow, and lake water levels. The results indicate that the estimated annual water balance in the upstream catchments shows that the climate regime is mainly dominated by rainfall since snowfall only represents 1% of total precipitation (716 mm). Ice melt also accounts for 1% of total precipitation. The simulated actual evapotranspiration represents on average 565 mm year-1, of which 3% correspond to net irrigation consumption. Runoff is approximately 173 mm year-1. By scaling this runoff to the lake area, upstream inflow represents 53% of the total inflows into the lake (1818 mm year-1), the remaining 47% corresponding to direct precipitation over the lake. Evaporation losses from the lake are estimated to mean annual value of 1718 mm and downstream outflows 142 mm. Then, the Lake Titicaca is primarily driven by interannual variations in precipitation. The evaporation rate can exacerbate conditions in dry years. The integrated modeling chain will later be used to assess how water levels could be altered by climate change and management options such as water withdrawals and lake releases.

La precipitación representa uno de los elementos más importantes dentro del ciclo del agua para la representación de la oferta hídrica en cuencas hidrográficas. Debido a una inadecuada distribución de estaciones, seguridad, relieve, accesibilidad, etcétera, existe escasez de estos datos en cuencas andinas del Perú. Esto representa uno de los principales inconvenientes que afrontan los investigadores en ciencias de la tierra y ciencia del clima para la representación de manera espacial y temporal de la precipitación. En los últimos años, el avance de las tecnologías permite la estimación de las variables hidrológicas a partir de técnicas de sensoramiento remoto. Estos datos deben ser evaluados con observaciones meteorológicas. En esta investigación se evaluaron 11 productos de precipitación estimada por sensoramiento remoto (PPEDsr) que estiman la precipitación. La evaluación de los PPEDsr se realizó para el periodo 1981-2018 a paso de tiempo: diario, de diez días y mensual. Se utilizaron los estadísticos descriptivos: error medio (ME), correlación de Pearson (R), raíz del error medio cuadrático (RMSE), error absoluto medio (MAE) y BIAS relativo (BIAS). Además, de los estadísticos categóricos: probabilidad de detección (POD), tasa de falsas alarmas (FAR), índice de éxito crítico (CSI). Los productos MSWEP, CHIRPS, TRMM-3B42 y PERSIANN-CDR resultaron ser más eficientes para representar la variabilidad espacial de las precipitaciones diarias y acumuladas en la cuenca del Vilcanota. Los datos de sensoramiento remoto mostraron ser útiles para representar la variabilidad espacio-temporal de la precipitación la cuenca Vilcanota, los resultados sugieren que los datos de sensoramiento remoto podrían ser utilizados para simular el balance hidrológico en cuencas hidrográficas de montaña andinas con escasa información in-situ.

En casi 58 años analizados, el comportamiento de la cantidad de población que utiliza el recurso hídrico proveniente del glaciar tropical presenta una relación inversa, provocando un incremento del déficit de agua en las cuencas glaciares. Por ello es necesario un análisis exhaustivo reciente de los glaciares tropicales. El estudio se realizó para las cordilleras de los Andes peruanos del año (1962 y 2020) para conocer el estado de conservación de los glaciares (superficie y volumen), la distribución (5 tamaños de glaciares y 3 zonas de los Andes) y la reserva hídrica del hielo per cápita por habitantes. La metodología fue utilizar las fotografías aéreas e imágenes (Sentinel y Spot) para identificar los glaciares y validarla con puntos de GPS en algunos glaciares, DEM para el modelo de GlabTop que calcula el volumen de glaciares y los censos poblacionales en la demarcación de los distritos con presencia de glaciares. Los resultados muestran que la superficie y volumen en año 1962 (2.349,20 km2 y 69.564 hm3) y en año 2020 (1.049 km2 y 31.686 hm3), ocupando mayor masa glaciar en los Andes Centrales y Andes del Norte. Y a la vez, presenta al año 2020 una evidencia de disminución significativa en superficie (55 %) y volumen (54 %), con una concentración de 86 % en cantidad de glaciares de tamaño < 1 km2. Respecto a la población y la reserva hídrica hielo per cápita, aumentó de más 650.000 habitantes a 1.200.000 habitantes, y se reduce de 106,66 m3 por habitante a 24,85 m3 por habitante, respectivamente. Los cambios decrecientes en los tamaños de glaciares situados en los Andes peruanos requieren la importancia de un monitoreo continuo y la necesidad de gestionar adecuadamente estos recursos vulnerables en una población creciente continua.

Study region: Santa River catchment, Cordillera Blanca, Peruvian Andes. Study focus: The effects of global change on the hydrological cycle are amplified in the highly-dynamic tropics. In the high Andes (identified as a hotspot of climate change), a warming climate impacts the cryosphere, and, therefore, alters the composition of downstream discharge. Quantifying these compositions, and evaluating the contributions of meltwater components, is vital for sustainable water resources management under changing hydrological regimes. For such analyses, we used the spatially-distributed cryosphere-hydrological model ‘Spatial Processes in Hydrology,’ forced with PISCO and RAIN4PE distributed meteorological data to simulate daily discharge components (rainfall-runoff, snowmelt, glacier melt, baseflow). We then computed a compensation metric to assess how meltwater compensated for the lack of rainfall-runoff during drought events, and further evaluated if the compensating flows were sufficient to maintain environmental flow requirements. New hydrological insights for the region: During 35 drought events, snowmelt contributions tended to decrease, while glacier melt contributions tended to increase. In total, meltwater contributions generally increased, and were able to compensate for reductions in rainfall-runoff. Meltwater proved critical during 85 % of identified drought events to ensure the total discharge reached an environmentally safe threshold.This research advances the understanding of the compensating effect of meltwater during droughts, which can inform water management in glacier-influenced catchments and shed light on climate change impacts in the tropical Andes.

Precipitation represents one of the most important elements within the water cycle for assessing water supply in hydrographic basins. Due to inadequate station distribution, security, terrain, accessibility, etc., there is a scarcity of this data in the Andean basins of Peru. This represents one of the main challenges faced by earth scientists and climatologists in spatially and temporally representing precipitation. In recent years, technological advancements have enabled the estimation of hydrological variables through remote sensing techniques. These data need to be evaluated alongside meteorological observations. This research assessed 11 products of remotely sensed estimated precipitation (RSEP) that estimate precipitation. The evaluation of RSEP was conducted for the period 1981-2018 at daily, ten-day, and monthly time steps. Descriptive statistics were used: mean error (ME), Pearson correlation (R), root mean square error (RMSE), mean absolute error (MAE), and relative bias (BIAS). Additionally, categorical statistics were employed: Probability of Detection (POD), False Alarm Rate (FAR), Critical Success Index (CSI). The products MSWEP, CHIRPS, TRMM-3B42, PERSIANN-CDR were found to be more efficient in representing the spatial variability of daily and accumulated precipitation in the Vilcanota basin. Remote sensing data proved useful in representing the spatiotemporal variability of precipitation in the Vilcanota basin; the results suggest that remote sensing data could be used to simulate the hydrological functioning of Andean mountainous catchments with limited in-situ information.

The impacts of the accelerated glacier retreat in recent decades on glacier runoff changes are still unknown in most Andean catchments, increasing uncertainties in estimating water availability. This particularly affects the outer tropics and Dry Andes, heavily impacted by prolonged droughts. Current global estimates overlook climatic and morphometric disparities, which significantly influence model parameters, among Andean glaciers. Meanwhile, local studies have used different approaches to estimate glacier runoff in a few catchments. Improving 21st-century glacier runoff projections relies on calibrating and validating models using corrected historical climate inputs and calibrated parameters across diverse glaciological zones. Here, we simulate glacier evolution and related runoff changes between the periods 2000–2009 and 2010–2019 across 786 Andean catchments (11 282 km2 of glacierized area, 11° N to 55° S) using the Open Global Glacier Model (OGGM). TerraClimate atmospheric variables were corrected using in situ data, getting a mean temperature bias by up to 2.1 °C and enhanced monthly precipitation. Glacier mass balance and volume were calibrated, where melt factor and the Glen A parameter exhibited significant alignment with varying environmental conditions. Simulation outcomes were validated against in situ data in three documented catchments (with a glacierized area > 8 %) and monitored glaciers. Our results at the Andes scale reveal an average reduction of 8.3 % in glacier volume and a decrease of 2.2 % in surface area between the periods 2000–2009 and 2010–2019. Comparing these two periods, glacier and climate variations have led to a 12 % increase in mean annual glacier melt (86.5 m3 s−1) and a decrease in rainfall on glaciers of −2 % (−7.6 m3 s−1) across the Andes, with both variables comprising the glacier runoff. We confirmed the utility of our corrected regional simulations of glacier runoff contribution at the catchment scale, where our estimations align with previous studies (e.g., Maipo 34° S, Chile) as well as provide new insights on the seasonal glaciers' largest contribution (e.g., La Paz 16° S, Bolivia) and new estimates of glacier runoff contribution (e.g., Baker 47° S, Chile).

The 2022-23 hydrological year in the Lake Titicaca, Desaguadero River, and Lake Poopó hydrological system (TDPS) over the South American Altiplano constituted a historically dry period. This drought was particularly severe during the pre-wet season (October–December), when the TDPS and the adjacent Andean-Amazon region experienced as much as 60% reductions in rainfall. Consequently, Titicaca Lake water levels decreased by 0.05 m from December to January, which is part of the rising lake level period of normal conditions. Such conditions have not been seen since the El Niño-related drought of 1982-83. Using a set of hydroclimatic, Sea Surface Temperature (SST) and atmospheric reanalysis datasets, we find that this new historical drought was associated with enhanced southerly moisture flux anomalies, reducing the inflow of moisture-laden winds from the Amazon basin to the TDPS. Such anomalies in moisture transport were not seen since at least the 1950s. The atmospheric dynamics associated with this drought are related to La Niña SST anomalies via subtropical teleconnections associated with Rossby wave trains towards South America, further extended by subtropical Atlantic Ocean SST anomalies. This feature reduced the atmospheric moisture inflow from the Amazon and weakened the development of the Bolivian High in the upper troposphere. These results document a new atmospheric mechanism related to extreme droughts in the TDPS associated with La Niña SST anomalies during the pre-wet season. This goes beyond the traditional understanding of El Niño events, especially the strongest ones, being associated with dry conditions in the TDPS during the wet season (December–March).