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In the last two decades, rainfall estimates provided by the Tropical Rainfall Measurement Mission (TRMM) have proven applicable in hydrological studies. The Global Precipitation Measurement (GPM) mission, which provides the new generation of rainfall estimates, is now considered a global successor to TRMM. The usefulness of GPM data in hydrological applications, however, has not yet been evaluated over the Andean and Amazonian regions. This study uses GPM data provided by the Integrated Multi-satellite Retrievals (IMERG) (product/final run) as input to a distributed hydrological model for the Amazon Basin of Peru and Ecuador for a 16-month period (from March 2014 to June 2015) when all datasets are available. TRMM products (TMPA V7, TMPA RT datasets) and a gridded precipitation dataset processed from observed rainfall are used for comparison. The results indicate that precipitation data derived from GPM-IMERG correspond more closely to TMPA V7 than TMPA RT datasets, but both GPM-IMERG and TMPA V7 precipitation data tend to overestimate, in comparison to observed rainfall (by 11.1% and 15.7%, respectively). In general, GPM-IMERG, TMPA V7 and TMPA RT correlate with observed rainfall, with a similar number of rain events correctly detected (~ 20%). Statistical analysis of modeled streamflows indicates that GPM-IMERG is as useful as TMPA V7 or TMPA RT datasets in southern regions (Ucayali basin). GPM-IMERG, TMPA V7 and TMPA RT do not properly simulate streamflows in northern regions (Marañón and Napo basins), probably because of the lack of adequate rainfall estimates in northern Peru and the Ecuadorian Amazon. [ABSTRACT FROM AUTHOR]

ABSTRACT At low latitudes, strong seasonal changes in cloud cover and precipitation largely control the mass balance of glaciers. Measurements of shortwave and longwave radiation fluxes reaching Zongo glacier, Bolivia (16°S, 5060 m asl), were analysed from 2005 to 2013 to investigate cloud radiative properties. Cloud shortwave attenuation and longwave emission were greater in the wet summer season ( DJF) than in the dry winter season ( JJA) probably because most DJF clouds were low warm cumulus associated with local convection, whereas JJA clouds were frequently altostratus associated with extra-tropical perturbations. Solar irradiance was high all year round and cloud radiative forcing on down-welling fluxes was strongly negative, with monthly averages ranging from -60 to -110 W m−2 from the dry to the wet season, respectively. In the wet season, high extraterrestrial solar irradiance and low shortwave transmissivity caused very negative cloud forcing despite the high longwave emissivity of convective clouds. Reanalysis of wind and geopotential height anomalies and outgoing longwave radiation satellite data were used to characterize the regional atmospheric circulation causing thick cloud covers (10% thickest clouds) during the dry ( JJA), transition ( SON), and wet ( DJF) seasons. Around 87% (80%) of cloud events in JJA ( SON) occurred during the incursion of low-level southern wind from southern South America to the Bolivian Andes, which caused 2-3 days of cold surge episodes in the Cordillera Real. Around 13% of cloudy days in JJA were associated with high-level low-pressure conditions over the Chilean coast around 45°S, including cut-off lows. In SON, 20% of cloudy days were associated with summer conditions, characterized by an active Bolivian High and moist air advection from the Amazon basin. In the wet season, only 46% of thick cloud events were associated with low-level southern wind incursions, the other events being associated with the South American Monsoon. [ABSTRACT FROM AUTHOR]

The Madeira River is the second largest Amazon tributary, contributing up to 50% of the Amazon River's sediment load. The Madeira has significant hydropower potential, which has started to be used by the Madeira Hydroelectric Complex (MHC), with two large dams along the middle stretch of the river. In this study, fine suspended sediment concentration (FSC) data were assessed downstream of the MHC at the Porto Velho gauging station and at the outlet of each tributary (Beni and Mamoré Rivers, upstream from the MHC), from 2003 to 2017. When comparing the pre-MHC (2003–2008) and post-MHC (2015–2017) periods, a 36% decrease in FSC was observed in the Beni River during the peak months of sediment load (December–March). At Porto Velho, a reduction of 30% was found, which responds to the Upper Madeira Basin and hydroelectric regulation. Concerning water discharge, no significant change occurred, indicating that a lower peak FSC cannot be explained by changes in the peak discharge months. However, lower FSCs are associated with a downward break in the overall time series registered at the outlet of the major sediment supplier—the Beni River—during 2010. [ABSTRACT FROM AUTHOR]

Due to its size and geographical features, different average annual rainfall regimes co‐exist in the Amazon basin, with distinct year‐to‐year variability dependent on regions within the basin. In this study, we define and explain the seasonal regional types of annual regimes, that is, years with similar seasonal anomalies. Our work is based on a 205 rain gauge network distributed over five Amazonian countries, spanning a period over 30 years. Using a spectral clustering method, we identified seven sub‐regions within the basin in which annual rainfall regimes are spatially homogenous. For each sub‐domain, we estimated specific parameters that characterize the rainy season (onset and demise dates, sign and duration of rainfall anomalies). Finally, using spectral analysis we identified between two and four 'seasonal type' of precipitation in these seven sub‐domains. Most of these seasonal types are in phase with the large‐scale atmospheric circulation, which explains the temporal link with rainfall anomalies. The seasonal types result of the superposition of inter‐annual and intra‐seasonal variability whose factors are then difficult to identify and attribute. Part of the rainfall anomalies characterizing seasonal types is related to the inter‐annual variability of the sea surface temperature in the Atlantic or the Pacific oceans, especially in the northeast and southeast part of the Amazon basin, whereas in other parts, strong intra‐seasonal and local factors have a larger impact. The same sign and duration of anomalies do not concomitantly affect the various regions of the Amazon basin, confirming that one mode of variability does not homogeneously affect precipitation in different parts of the basin. [ABSTRACT FROM AUTHOR]

In this study, we analyze the atmospheric mechanisms associated with the main rainfall patterns in the tropical Andes ( 20 ∘ S – 1 ∘ N ) on seasonal and interannual time scales. Using a homogeneous and high spatial resolution precipitation data set ( 0. 05 ∘ × 0. 05 ∘ ) at monthly time step (CHIRPS; 1981–2016), in-situ precipitation from 206 rain-gauge stations, power spectrum and EOF analysis, we identify three Andean regions characterized by specific seasonal and interannual rainfall modes: the equatorial Andes (EA, 5 ∘ S – 1 ∘ N ), the transition zone (TZ, 8 ∘ S – 5 ∘ S ) and the southern tropical Andes (STA, 20 ∘ S – 8 ∘ S ). On seasonal time scales, the main mode of precipitation in the EA and STA are characterized by a unimodal regime, while the TZ is represented by a bimodal regime. The EA and the TZ share the same wet season in the February–April period, which is associated with a weakened Walker Cell, the southerly position of the Intertropical Convergence Zone (ITCZ) and a strong westward humidity transport from the equatorial Amazon. This latter mechanism and a reduced elevation of the Andes are associated with the October–November wet season in the TZ. The presence of the Bolivian High and the northward extension of the Low Level Jet are associated with the precipitation over Andean regions between 20 ∘ S and 8 ∘ S in the December–March period. On interannual time scales, extreme monthly wet events (EMWE) in the STA (TZ) are related to convection over the western (equatorial) Amazon during the December–March (February–April) period, showing an atmospheric relationship between the Amazon and the Andes. Extreme monthly dry events (EMDE) in the TZ and in the EA during the February–April period are related to a strengthened Walker Cell, especially in the eastern Pacific. In addition, EMWE (EMDE) in the EA are associated with an anomalous southward (northward) displaced eastern Pacific ITCZ. Moreover, we find a relationship between precipitation at higher elevations in the Andes north of 10 ∘ S and easterly winds at 200 hPa during February–April EMWE. Finally, extreme monthly events in the EA (STA) are related to sea surface temperature anomalies in the western (central) equatorial Pacific. [ABSTRACT FROM AUTHOR]

Highlights • Daytime and nighttime MODIS LST data over the Andean region between 7 °S and 20 °S were obtained from 2000 to 2017. • Season (winter) trends of daytime and nighttime LST were computed using Sen´s method. • Winter daytime LST trend showed a clear elevation-warming dependency. • Lake Titicaca temperature show a warming based on daytime and nighttime MODIS LST measurements. • Relation between mean monthly daytime LST and mean monthly maximum air temperature. Abstract In this study, we report on the assessment of elevation-dependent warming processes in the Andean region between 7 °S and 20 °S, using Land Surface Temperature (LST). Remotely sensed LST data were obtained from Moderate Resolution Imaging Spectroradiometer (MODIS) sensor in an 8-day composite, at a 1 km resolution, and from 2000 to 2017 during austral winter (June-July-August, JJA). We analysed the relation between mean monthly daytime LST and mean monthly maximum air temperature. This relation is analysed for different types of coverage, obtaining a significant correlation that varies from 0.57 to 0.82 (p < 0.01). However, effects of change in land cover were ruled out by a previous comparative assessment of trends in daytime LST and normalized difference vegetation index (NDVI). The distribution of the winter daytime LST trend was found to be increasing in most areas, while decreasing in only a few areas. This trend shows that winter daytime LST is increasing at an average rate of 1.0 °C/decade. We also found that the winter daytime LST trend has a clear dependence on elevation, with strongest warming effects at higher elevations: 0.50 °C/decade at 1000–1500 masl, and 1.7 °C/decade above 5000 masl. However, the winter nighttime LST trend shows a steady increase with altitude increase. The dependence of rising temperature trends on elevation could have severe implications for water resources and high Andean ecosystems. [ABSTRACT FROM AUTHOR]

Identifying rainfall regions associated with specific modes of variability is of practical interest for water resources management, seasonal forecasting, and mitigation of weather‐related risks. This study aims to identify homogeneous rainfall regions within the ~1 million km2 Upper Madeira River basin—southwestern Amazon—by their interannual and decadal variability and relates this variability to ocean indices. An observed dataset of 146 ground‐based rainfall stations, distributed throughout the Andes and the Amazon, and homogenized at the monthly time‐step for the period 1980–2016, was used for the analysis. With no spatial constraints, hierarchical cluster analysis and principal component analysis (PCA) optimally grouped stations into 10 rainfall homogenous regions. The value of the regionalization for interpreting the rainfall variability was evaluated by relating the seasonal rainfall time series of the regions with ocean indices. Then, by applying PCA to seasonal rainfall series and linking the principal components to sea surface temperature and ocean indices, an insight into the main large‐scale drivers of the rainfall spatio‐temporal variability in this basin at interannual and decadal scales is provided. This analysis identified differences in the year‐round influences of the tropical Pacific and/or Atlantic oceans on the 10 homogenous regions. [ABSTRACT FROM AUTHOR]

Recently developed methodologies such as climate reanalysis make it possible to create a historical record of climate systems. This paper proposes a methodology called Hydrological Retrospective (HR), which essentially simulates large rainfall datasets, using this as input into hydrological models to develop a record of past hydrology, making it possible to analyze past floods and droughts. We developed a methodology for the Amazon basin, where studies have shown an increase in the intensity and frequency of hydrological extreme events in recent decades. We used eight large precipitation datasets (more than 30 years) as input for a large scale hydrological and hydrodynamic model (MGB-IPH). HR products were then validated against several in situ discharge gauges controlling the main Amazon sub-basins, focusing on maximum and minimum events. For the most accurate HR, based on performance metrics, we performed a forecast skill of HR to detect floods and droughts, comparing the results with in-situ observations. A statistical temporal series trend was performed for intensity of seasonal floods and droughts in the entire Amazon basin. Results indicate that HR could represent most past extreme events well, compared with in-situ observed data, and was consistent with many events reported in literature. Because of their flow duration, some minor regional events were not reported in literature but were captured by HR. To represent past regional hydrology and seasonal hydrological extreme events, we believe it is feasible to use some large precipitation datasets such as i) climate reanalysis, which is mainly based on a land surface component, and ii) datasets based on merged products. A significant upward trend in intensity was seen in maximum annual discharge (related to floods) in western and northwestern regions and for minimum annual discharge (related to droughts) in south and central-south regions of the Amazon basin. Because of the global coverage of rainfall datasets, this methodology can be transferred to other regions for better estimation of future hydrological behavior and its impact on society. [ABSTRACT FROM AUTHOR]

The Kunming-Montreal Global Biodiversity Framework (GBF) of the Convention on Biological Diversity has set the target of protecting 30 % of the world's land and sea by 2030. Previous conservation planning approaches have been based primarily on biodiversity elements, particularly for Peru, a mega-biodiverse country whose protected areas network need to be expanded. However, achieving this ambitious 30 % target requires careful consideration of numerous ecological and social aspects. To cover these aspects, we present a terrestrial conservation planning approach that integrates biodiversity, ecosystem services, human impact, ecological connectivity and ecoregional representativeness. Our approach has been co-produced with national organisations and NGOs and includes advanced Artificial Intelligence (AI) methods. Our results identify areas of high ecological value to supplement the 17.88 % of areas already protected, to reach 30 %. The integration of these areas could close gaps in the current system, particularly those vital for water related ecosystem services, ecoregional representativity and ecological connectivity. Integrated AI-based optimization methods (i.e., integer linear programming, constraint programming, reference point method) enabled us to obtain optimal, constraint-satisfying and balanced protected areas selected on the basis of integrated variables, and constitute a robust alternative compared with heuristic methods (e.g., Marxan, Zonation) commonly used. This work can be used as a fundamental component of Peru's territorial planning, and paves the way on future research on conservation planning, which should integrate advanced spatial conservation planning methods, ecological and social factors in an even more comprehensive way. [ABSTRACT FROM AUTHOR]

The decadal variability in summer precipitation over the Central Andes (10°–30°S) is investigated from 1921 to 2010 using low‐pass filtered time series of the central and eastern El Niño–Southern Oscillation (ENSO) Pacific (C and E) indices, the South Pacific Convergence Zone (SPCZ) index, the Atlantic SST indices, Atlantic Multidecadal Oscillation (AMO) index, North Atlantic Oscillation (NAO) index, and ERA‐20C reanalysis. Additionally, an empirical‐statistical downscaling (ESD) model was built. A rotated empirical orthogonal function (REOF) analysis shows that the first leading mode of precipitation (RPC1) represents 38.2% of the total decadal variance. RPC2, RCP3, and RPC4 represent 18.8, 12.8, and 9.7% of the total decadal variance, respectively. Furthermore, RPC1 features highest loadings over most of the region. RPC2 features a dipole of highest loadings over the southernmost Bolivian Altiplano and lowest loadings over the northwestern Argentinian Andes. Conversely, RPC3 presents highest loadings over the eastern‐central Bolivian Altiplano and northwestern Argentinian Andes. RPC4 features highest loadings over the southern Bolivian Andes. RPC1 and RPC3 wet summers are associated with moisture transport from the Amazon basin, but RPC1 features the strengthening upper‐level Bolivian high‐Nordeste low system over South America. Conversely, RPC2 and RPC4 wet summers are associated with local processes induced by southward displacement of the South Atlantic Convergence Zone and warm sea surface temperature (SST) anomalies over the Indian Ocean, respectively. According to the ESD model, the decadal variability in the central and eastern Pacific (CP and EP) and Atlantic Ocean reproduces the decadal component of the DJF precipitation over most of the Central Andes. [ABSTRACT FROM AUTHOR]

Summary Satellites are an alternative source of rainfall data used as input to hydrological models in poorly gauged or ungauged regions. They are also useful in regions with highly heterogeneous precipitation, such as the tropical Andes. This paper evaluates three satellite precipitation datasets (TMPA, CMORPH, PERSIANN), as well as a dataset based only on rain gauge data (HYBAM), and their impacts on the water balance of the Western Amazon basin, a region where hydrological modeling and hydrological forecasting are poorly developed. These datasets were used as inputs in the MGB-IPH hydrological model to simulate streamflows for the 2003–2009 period. The impacts of precipitation on model parameterization and outputs were evaluated in two calibration experiments. In Experiment 1, parameter sets were separately defined for each catchment; in Experiment 2, a single parameter set was defined for the entire basin. TMPA shows overestimated precipitation over the northern region, while CMORPH and PERSIANN significantly underestimate rainfall in the same that region and along the Andes. TMPA and CMORPH lead to similar estimates of mean evapotranspiration (∼2 mm/day) for different regions along the entire basin, while PERSIANN is the least accurate (∼0.5 mm/day). Overall, better scores for streamflow simulations are obtained with Experiment 1 forced by HYBAM and TMPA. Nevertheless, results using the three satellite datasets indicate inter-basin differences, low performance in the northern and high in the southern regions. Low model performances are mainly related to scale issues and forcing errors in small basins over regions that present very low rainfall seasonality. [ABSTRACT FROM AUTHOR]

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As the largest river basin on Earth, the Amazon is of major importance to the world's climate and water resources. Over the past decades, advances in satellite‐based remote sensing (RS) have brought our understanding of its terrestrial water cycle and the associated hydrological processes to a new era. Here, we review major studies and the various techniques using satellite RS in the Amazon. We show how RS played a major role in supporting new research and key findings regarding the Amazon water cycle, and how the region became a laboratory for groundbreaking investigations of new satellite retrievals and analyses. At the basin‐scale, the understanding of several hydrological processes was only possible with the advent of RS observations, such as the characterization of "rainfall hotspots" in the Andes‐Amazon transition, evapotranspiration rates, and variations of surface waters and groundwater storage. These results strongly contribute to the recent advances of hydrological models and to our new understanding of the Amazon water budget and aquatic environments. In the context of upcoming hydrology‐oriented satellite missions, which will offer the opportunity for new synergies and new observations with finer space‐time resolution, this review aims to guide future research agenda toward integrated monitoring and understanding of the Amazon water from space. Integrated multidisciplinary studies, fostered by international collaborations, set up future directions to tackle the great challenges the Amazon is currently facing, from climate change to increased anthropogenic pressure. Plain Language Summary: The Amazon basin is the largest river basin in the world, characterized by complex hydrological processes that connect high rates of precipitation, extensive floodplains, dense tropical forests, complex topography, and large variations in freshwater storage and discharge. It plays a key role in the water, energy, and carbon cycles and interacts with the global climate system. Earth observations have played a major role in supporting research in Amazon hydrology, and the characterization of several hydrological processes was only possible with the help of remote sensing data. The basin is now facing great risk under current climate change and increased anthropogenic pressure and the resulting environmental alterations require a better understanding of the overall basin's water cycle across scales. We review the strengths and limitations of observations from satellites in the context of the current and upcoming hydrology‐oriented satellite missions, and we make recommendations for improving satellite observations of the Amazon basin water cycle, along with an interdisciplinary and stepwise approach to guide research for the next decades. Key Points: Integrated view of scientific advances in Amazon hydrology with remote sensingExpected progress to understand the water cycle, aquatic ecosystems, and environmental changes with upcoming hydrology‐oriented missionsNeed to translate advanced knowledge from remote sensing to support water management and environmental governance [ABSTRACT FROM AUTHOR]

The frequency and spatial distributions of precipitation extremes (PEs) and deep convective clouds (DCC) across the Amazon region were assessed using satellite-derived data. For PEs, CHIRPS dataset for the period 1981–2018 were used to calculate a set of absolute, threshold, duration, and percentile-based threshold indices defined by the Expert Team on Climate Change Detection and Indices. DCC occurrence was assessed based on the Advanced Microwave Sounding Unit data for the period 2002–2018. In northern Amazon (north of 5 ∘ S ) PEs and DCC are more frequent ( ≥ 60 % frequency) during February–June. Averaged trends over these months have shown increase in daily rainfall above 20 mm of near 3 days over the 1981–2018 period, and an increase of 2 consecutive wet days (P ≥ 1 mm ) in the same period. South of 5 ∘ S prevalence of PEs and DCC is largely observed during November–March ( ≥ 60 % frequency), whereas the longest persistence of dry days is observed during June–August. Though all PE trends point to an intensification of rainfall in November–March, only consecutive dry days in winter (JJA) and spring (SON) show significant trends, pointing to an increase of 7 days over the 38-yr winters. Rainfall extremes over the entire Amazon region were found to be moderate to strongly correlated with the mean vertically integrated moisture divergence, and in southern Amazon also to upper level divergence and upward vertical velocity. Increased frequency of DCC were found over the whole basin ( ∼ 18 % yr - 1 ), in contrast to decreased convective overshooting (up to ∼ 15.4 % yr - 1 ). [ABSTRACT FROM AUTHOR]

This paper focuses on the representation of the air surface temperature and precipitation using high spatiotemporal simulations (3 km–1 h) of the WRF3.7.1 model in the central Peruvian area. It covers, from east to west, the coastal zone, the western slope of the Andes, the Andean Mantaro basin (500–5000 masl), and the Andes-Amazon transition region in the eastern Andes. The study covers the January months from 2004 to 2008. Three experiments were conducted using different topography and land use data sources: (1) a control simulation using the default WRF topography and land use datasets from the United States Geological Survey (USGS); (2) a simulation changing only the topography by using the SRTM topography dataset; and (3) a simulation changing the land use data of (2) by a new dataset adapted from Eva et al. (2004). SRTM topography performed better than the control simulation for representing the actual altitudes of 57 meteorological stations that were used for precipitation and surface air temperature data. As a result, the simulations of experiments (2) and (3) produced lower bias values than that of (1). Topography change (experiment (2)) showed improvements in temperature bias that were directly associated with linear modifications of -5.6 and -6.7 °C∙km−1 in minimum and maximum temperature, respectively. Increasing (decreasing) precipitation with topography or land use change was clearly controlled by changes in the moisture flux patterns and its convergence (divergence) in the Andes-Amazon transition. On the western slope, precipitation increase could be associated with the increase in easterly flow by the smaller altitudes of the Andes mountains in SRTM topography and by increasing evaporation with new land use. Inside the Mantaro Basin, low level moisture flux seems to control the rainfall changes. Overall, relative changes (positive or negative) in precipitation due to topography or land use change could reach values above 25%. • Simulations are performed at complex terrain in the Peruvian central Andes during the rainiest month. • Differences between SRTM and USGS topography databases can reach >1 km in the Andes of Peru. • Major impacts on rainfall and temperature are found in the eastern slope of the Andes. • Better representation of topography reduces the bias of rainfall and temperature. [ABSTRACT FROM AUTHOR]

Madden–Julian Oscillation (MJO) impact on the Amazon intraseasonal precipitation assessed by different MJO indices is investigated through an analysis of composite events and observed case studies. The MJO indices diagnosing skill is described in detail using reanalysis, satellite, and gauge-based gridded rainfall data. Three types of existing MJO indices are considered: (1) OLR-based MJO (OMI index); (2) dynamically- or circulation-based MJO (VPM index); and (3) combined convectively- and dynamically-based MJO (Wheeler–Hendon RMM index). Our results suggest that, in the large-scale (i.e., around the global tropics), even in the regional domain, the MJO OLR-only index well-represent the dynamical and convective features associated with the intraseasonal variability. On the other hand, each index gives diverging results on rainfall characterization over the Amazon Basin (AB). For instance, the cumulative distribution of precipitation for each MJO phase and index depicts considerable differences in the main climatic regions of the AB, indicating a diverging intraseasonal representation for extreme rainfall values. In addition, when event-by-event is assessed, details as well as the identification of events themselves can differ among indices. This characteristic is particularly observed during extreme rainfall events in the AB. A significant percentage of MJO activity is detected only by the MJO OLR-based index. Because the large-scale zonal circulation dominates the dynamically-based indices (RMM and VPM), the MJO impact in these indices is not an appropriate measure of convective MJO activity. Since the convective component of the MJO is our primary objective, the results presented in this study show that the OLR-based MJO index is able to better account for the MJO impacts over the AB. The indices considered in this study are often used for monitoring and forecasting the MJO activity over South America. However, given the dissimilarity of the representation of precipitation in the AB, our findings also support the consideration of a regional index for monitoring and forecasting the MJO impacts. [ABSTRACT FROM AUTHOR]

The Amazon River sediment discharge has been estimated at between 600 and 1200 Mt/year, of which more than 50% comes from the Solimões River. Because of the area's inaccessibility, few studies have examined the sediment discharge spatial and temporal pattern in the upper Solimões region. In this study, we use MODIS satellite images to retrieve and understand the spatial and temporal behaviour of suspended sediments in the Solimões River from Peru to Brazil. Six virtual suspended sediment gauging stations were created along the Solimões River on a 2050-km-long transect. At each station, field-derived river discharge estimates were available and field-sampling trips were conducted for validation of remote-sensing estimates during different periods of the annual hydrological cycle between 2007 and 2014. At two stations, 10-day surface suspended sediment data were available from the SO-HYBAM monitoring program (881 field SSS samples). MODIS-derived sediment discharge closely matched the field observations, showing a relative RMSE value of 27.3% (0.48 Mtday) overall. Satellite-retrieved annual sediment discharge at the Tamshiyacu (Peru) and Manacapuru (Brazil) stations is estimated at 521 and 825 Mt/year, respectively. While upstream the river presents one main sediment discharge peak during the hydrological cycle, a secondary sediment discharge peak is detected downstream during the declining water levels, which is induced by sediment resuspension from the floodplain, causing a 72% increase on average from June to September. [ABSTRACT FROM AUTHOR]

The Madeira River is the second largest tributary of the Amazon River. It contributes approximately 13% of the Amazon River flow and it may contribute up to 50% of its sediment discharge to the Atlantic Ocean. Until now, the suspended sediment load of the Madeira River was not well known and was estimated in a broad range from 240 to 715 Mt yr −1 . Since 2002, the HYBAM international network developed a new monitoring programme specially designed to provide more reliable data than in previous intents. It is based on the continuous monitoring of a set of 11 gauging stations in the Madeira River watershed from the Andes piedmont to the confluence with the Amazon River, and discrete sampling of the suspended sediment concentration every 7 or 10 days. This paper presents the results of the suspended sediment data obtained in the Madeira drainage basin during 2002–2011. The Madeira River suspended sediment load is estimated at 430 Mt yr −1 near its confluence with the Amazon River. The average production of the Madeira River Andean catchment is estimated at 640 Mt yr −1 (±30%), the corresponding sediment yield for the Andes is estimated at 3000 t km −2 yr −1 (±30%), and the average denudation rate is estimated at 1.20 mm yr −1 (±30%). Contrary to previous results that had mentioned high sedimentation rates in the Beni River floodplain, we detected no measurable sedimentation process in this part of the basin. On the Mamoré River basin, we observed heavy sediment deposition of approximately 210 Mt yr −1 that seem to confirm previous studies. But while these studies mentioned heavy sedimentation in the floodplain, we showed that sediment deposition occurred mainly in the Andean piedmont and immediate foreland in rivers (Parapeti, Grande, Pirai, Yapacani, Chimoré, Chaparé, Secure, Maniqui) with discharges that are not sufficiently large to transport their sediment load downstream in the lowlands. [ABSTRACT FROM AUTHOR]

The Cordillera Blanca (central Andes of Peru) represents the largest concentration of tropical glaciers in the world. The atmospheric processes related to precipitations are still scarcely studied in this region. The main objective of this study is to understand the atmospheric processes of interaction between local and regional scales controlling the diurnal cycle of precipitation over the Santa River basin located between the Cordillera Blanca and the Cordillera Negra. The rainy season (December–March) of 2012–2013 is chosen to perform simulations with the WRF (Weather Research and Forecasting) model, with two domains at 6 km (WRF-6 km) and 2 km (WRF-2 km) horizontal resolutions, forced by ERA5. WRF-2 km precipitation shows a clear improvement over WRF-6 km in terms of the daily mean and diurnal cycle, compared to in situ observations. WRF-2 km shows that the moisture from the Pacific Ocean is a key process modulating the diurnal cycle of precipitation over the Santa River basin in interaction with moisture fluxes from the Amazon basin. In particular, a channeling thermally orographic flow is described as controlling the afternoon precipitation along the Santa valley. In addition, in the highest parts of the Santa River basin (in both cordilleras) and the southern part, maximum precipitation occurs earlier than the lowest parts and the bottom of the valley in the central part of the basin, associated with the intensification of the channeling flow by upslope cross-valley winds during mid-afternoon and its decrease during late afternoon/early night. [ABSTRACT FROM AUTHOR]

The geochemistry of riverine sediments exported to the oceans is important for paleo-hydro-climatic reconstruction. However, climate reconstruction requires a good understanding of the relationship between geochemistry and hydrological variability and sediment sources. In this study, we analyzed the major elements, the strontium‑neodymium radiogenic isotopes signatures (87Sr/86Sr and εNd) and the mineralogy of the suspended particulate matter (SPM) sampled monthly during two hydrologic years (2007–2008, a wet year, and 2010–2011, a normal hydrological year) upstream the Tumbes River outlet. The hydroclimate of this Ecuador-Peru binational basin is particularly sensitive to ENSO (El Niño Southern Oscillation) events. While mineralogy (dominated by illite) and the chemical alteration index (from 75 to 82) remain almost constant along the two hydrological years, 87Sr/86Sr (0.7115 to 0.7176) and εNd (−7.8 to −1.9) signatures are particularly sensitive to discharge and SPM concentration variations. Along the hydrological year, two sources control the εNd variability: (1) volcanic rocks, which dominate during the dry season, and (2) plutonic/metamorphic sources, whose contribution increases during the wet season. This behavior is confirmed by the correlation between εNd signature and the monthly rainfall contribution from volcanic area (R = 0.58; p -value < 0.01), and also with the daily discharge at the outlet (R = -0.73; p- value < 0.01). For most of the samples, 87Sr/86Sr is less variable along the hydrological year. However, two exceptional high discharge and SPM concentration conditions sampled exhibit more radiogenic (higher) 87Sr/86Sr signatures when plutonic/metamorphic rocks derived sediments are released in sufficient quantities to notably change the SPM isotopic Sr value of the Tumbes River. Hence, this study demonstrates that 87Sr/86Sr and εNd signatures can be used as powerful proxies for paleoclimate reconstructions based on sediment core's analysis in relation with spatial rainfall distribution and intensity in Pacific sedimentary basins submitted to the diversity of ENSO events. • Suspended sediments were sampled monthly in the Tumbes River along 2 hydrological years. • εNd signatures indicates source provenance in relation with rainfall distribution. • 87Sr/86Sr signatures is particularly sensitive to anomalous wet conditions. • Nd and Sr isotopes are powerful tracers of paleo-ENSO and sediments dynamics. [ABSTRACT FROM AUTHOR]

The Amazon River Basin's extraordinary social-ecological system is sustained by various water phases, fluxes, and stores that are interconnected across the tropical Andes mountains, Amazon lowlands, and Atlantic Ocean. This "Andes-Amazon-Atlantic" (AAA) pathway is a complex hydroclimatic system linked by the regional water cycle through atmospheric circulation and continental hydrology. Here, we aim to articulate the AAA hydroclimate pathway as a foundational system for research, management, conservation, and governance of aquatic systems of the Amazon Basin. We identify and describe the AAA pathway as an interdependent, multidirectional, and multiscale hydroclimate system. We then present an assessment of recent (1981 to 2020) changes in the AAA pathway, primarily reflecting an acceleration in the rates of hydrologic fluxes (i.e., water cycle intensification). We discuss how the changing AAA pathway orchestrates and impacts social-ecological systems. We conclude with four recommendations for the sustainability of the AAA pathway in ongoing research, management, conservation, and governance., Competing Interests: Competing interests statement:The authors declare no competing interest.

In 2023 Amazonia experienced both historical drought and warm conditions. On October 26th 2023 the water levels at the port of Manaus reached its lowest record since 1902 (12.70 m). In this region, October monthly maximum and minimum temperature anomalies also surpassed previous record values registered in 2015 (+ 3 °C above the normal considering the 1981-2020 average). Here we show that this historical dry and warm situation in Amazonia is associated with two main atmospheric mechanisms: (i) the November 2022-February 2023 southern anomaly of vertical integrated moisture flux (VIMF), related to VIMF divergence and extreme rainfall deficit over southwestern Amazonia, and (ii) the June-August 2023 downward motion over northern Amazonia related to extreme rainfall deficit and warm conditions over this region. Anomalies of both atmospheric mechanisms reached record values during this event. The first mechanism is significantly correlated to negative sea surface temperature (SST) anomalies in the equatorial Pacific (November-February La Niña events). The second mechanism is significantly correlated to positive SST anomalies in the equatorial Pacific, related to the impacts of June-September El Niño on the Walker Circulation. While previous extreme droughts were linked to El Niño (warmer North Tropical Atlantic SST) during the austral summer (winter and spring), the transition from La Niña 2022-23 to El Niño 2023 appears to be a key climatic driver in this record-breaking dry and warm situation, combined to a widespread anomalous warming over the worldwide ocean., (© 2024. The Author(s).)

Several large-scale drivers of both anthropogenic and natural environmental changes are interacting nonlinearly in the transition zone between eastern Amazonia and the adjacent Cerrado, considered to be another Brazilian agricultural frontier. Land-use change for agrobusiness expansion together with climate change in the transition zone between eastern Amazonia and the adjacent Cerrado may have induced a worsening of severe drought conditions over the last decade. Here we show that the largest warming and drying trends over tropical South America during the last four decades are observed to be precisely in the eastern Amazonia-Cerrado transition region, where they induce delayed wet-season and worsen severe drought conditions over the last decade. Our results evidence an increase in temperature, vapor pressure deficit, subsidence, dry-day frequency, and a decrease in precipitation, humidity, and evaporation, plus a delay in the onset of the wet season, inducing a higher risk of fire during the dry-to-wet transition season. These findings provide observational evidence of the increasing climatic pressure in this area, which is sensitive for global food security, and the need to reconcile agricultural expansion and protection of natural tropical biomes., (© 2022. The Author(s).)