Search Results (5)

The Ucayali River is one of the most dynamic large rivers in the world, with high rates of channel migration regularly producing cutoffs. In the lower portion of the Ucayali River, before its confluence to the Marañon River where the Amazon River is born, the increase in water and sediment discharge triggers bends with secondary channels (transitional stage from purely meandering to anabranching), which influence the planform migration rates and patterns of the sinuous channels. Based on remote sensing analysis, a comparison of planform dynamics of bends with and without secondary channels is presented. For the case of a bend with secondary channels (Jenaro Herrera, JH), detailed field measurements for bed morphology, hydrodynamics, bed and suspended load are performed for low-, transitional- and high-flow conditions (August, February and May, respectively). Additionally, a two-dimensional depth average hydraulic model is utilized to correlate observed migrating patterns with the hydrodynamics. Results indicate that the secondary channels have disrupted typical planform migration rates of the main meandering channel. However, at high amplitudes, these secondary channels reduce their capacity to capture flow and start a narrowing process, which in turn increases migration rates of the main channels (meandering reactivation process), suggesting that an imminent cutoff along the JH bend is underway by pure lateral migration or by the collapse into the existing paleochannels. Full article

We describe a new minimum extent, persistent surface water classification for reaches of four major rivers in the Peruvian Amazon (i.e., Amazon, Napo, Pastaza, Ucayali). These data were generated by the Peruvian Amazon Rural Livelihoods and Poverty (PARLAP) Project which aims to better understand the nexus between livelihoods (e.g., fishing, agriculture, forest use, trade), poverty, and conservation in the Peruvian Amazon over a 35,000 km river network. Previous surface water datasets do not adequately capture the temporal changes in the course of the rivers, nor discriminate between primary main channel and non-main channel (e.g., oxbow lakes) water. We generated the surface water classifications in Google Earth Engine from Landsat TM 5, 7 ETM+, and 8 OLI satellite imagery for time periods from circa 1989, 2000, and 2015 using a hierarchical logical binary classification predominantly based on a modified Normalized Difference Water Index (mNDWI) and shortwave infrared surface reflectance. We included surface reflectance in the blue band and brightness temperature to minimize misclassification. High accuracies were achieved for all time periods (>90%). Full article

The Amazon River Basin (ARB) plays an important role in the hydrological cycle at the regional and global scales. According to the Intergovernmental Panel on Climate Change (IPCC), the incidence and severity of droughts could increase in this basin due to human-induced climate change. Therefore, the assessment of the impacts of extreme droughts in the ARB is of vital importance to develop appropriate drought mitigation strategies. The purpose of this study is to provide a comprehensive characterization of dry spells and extreme drought events in terms of occurrence, persistence, spatial extent, severity, and impacts on streamflow and vegetation in the ARB during the period 1901–2018. The Standardized Precipitation-Evapotranspiration Index (SPEI) at multiple time scales (i.e., 3, 6, and 12 months) was used as a drought index. A weak basin-wide drying trend was observed, but there was no evidence of a trend in extreme drought events in terms of spatial coverage, intensity, and duration for the period 1901–2018. Nevertheless, a progressive transition to drier-than-normal conditions was evident since the 1970s, coinciding with different patterns of coupling between the El Niño/Southern Oscillation (ENSO) phenomenon and the Pacific Decadal Oscillation (PDO), Atlantic Multidecadal Oscillation (AMO), and Madden–Julian Oscillation (MJO) as well as an increasing incidence of higher-than-normal surface air temperatures over the basin. Furthermore, a high recurrence of short-term drought events with high level of exposure to long-term drought conditions on the sub-basins Ucayali, Japurá-Caquetá, Jari, Jutaí, Marañón, and Xingu was observed in recent years. These results could be useful to guide social, economic, and water resource policy decision-making processes in the Amazon basin countries. Full article

The Amazon River Basin is the largest rainforest in the world. Long-term changes in precipitation trends in the basin can affect the continental water balance and the world’s climate. The precipitation trends in the basin are not spatially uniform; estimating these trends only at locations where station data are available has an inherent bias. In the present research, the spatially distributed annual precipitation trends were studied in the Amazon River Basin from the year 1981 to 2017 using the Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) product. The precipitation trends were also cross-validated at locations where station data were available. The research also identifies clusters within the basin where trends showed a larger increase (nine clusters) or decrease in precipitation (10 clusters). The overall precipitation trend in the Amazon River Basin over 37 years showed a 2.8 mm/year increase, with a maximum of 45.1 mm/year and minimum of −37.9 mm/year. The highest positive cluster was in Cuzco in the Ucayali River basin, and the lowest negative was in Santa Cruz de la Sierra, in the upstream Madeira River basin. The total volume of the incoming precipitation was 340,885.1 km³, with a withdrawal of −244,337.1 km³. Cross-validation was performed using 98 in situ stations with more than 20 years of recorded data, obtaining an R² of 0.981, a slope of 1.027, and a root mean square error (RMSE) of 363.6 mm/year. The homogeneous, standardized, and continuous long-term time series provided by CHIRPS is a valuable product for basins with a low-density network of stations such as the Amazon Basin. Full article

The Neotropical freshwater ichthyofauna has among the highest species richness and density of any vertebrate fauna on Earth, with more than 5,600 species compressed into less than 12% of the world’s land surface area, and less than 0.002% of the world’s total liquid water supply. How have so many species come to co-exist in such a small amount of total habitat space? Here we report results of an aquatic faunal survey of the Fitzcarrald region in southeastern Peru, an area of low-elevation upland (200–500 m above sea level) rainforest in the Western Amazon, that straddles the headwaters of four large Amazonian tributaries; the Juruá (Yurúa), Ucayali, Purús, and Madre de Dios rivers. All measures of fish species diversity in this region are high; there is high alpha diversity with many species coexisting in the same locality, high beta diversity with high turnover between habitats, and high gamma diversity with high turnover between adjacent tributary basins. Current data show little species endemism, and no known examples of sympatric sister species, within the Fitzcarrald region, suggesting a lack of localized or recent adaptive divergences. These results support the hypothesis that the fish species of the Fitzcarrald region are relatively ancient, predating the Late Miocene-Pliocene (c. 4 Ma) uplift that isolated its several headwater basins. The results also suggest that habitat specialization (phylogenetic niche conservatism) and geographic isolation (dispersal limitation) have contributed to the maintenance of high species richness in this region of the Amazon Basin. Full article