Search Results (36)

Atmospheric warming results in increase in temperatures for the mean, the coldest, and the hottest day of the year, season, or month. Global warming leads to a large increase in the atmospheric water vapor content and to changes in the hydrological cycle, which include an intensification of precipitation extremes. Using the GISS-E2.1 climate model, we present the future changes in the coldest and hottest daily temperatures as well as in extreme precipitation indices (under four main Shared Socioeconomic Pathways (SSPs)). The increase in the wet-day precipitation ranges between 6% and 15% per 1 °C global surface temperature warming. Scaling of the 95th percentile versus the total precipitation showed that the sensitivity for the extreme precipitation to the warming is about 10 times stronger than that for the mean total precipitation. For six precipitation extreme indices (Total Precipitation, R95p, RX5day, R10mm, SDII, and CDD), the histograms of probability density functions become flatter, with reduced peaks and increased spread for the global mean compared to the historical period of 1850–2014. The mean values shift to the right end (toward larger precipitation and intensity). The higher the GHG emission of the SSP scenario, the more significant the increase in the index change. We found an intensification of precipitation over the globe but large uncertainties remained regionally and at different scales, especially for extremes. Over land, there is a strong increase in precipitation for the wettest day in all seasons over the mid and high latitudes of the Northern Hemisphere. There is an enlargement of the drying patterns in the subtropics including over large regions around Mediterranean, southern Africa, and western Eurasia. For the continental averages, the reduction in total precipitation was found for South America, Europe, Africa, and Australia, and there is an increase in total precipitation over North America, Asia, and the continental Russian Arctic. Over the continental Russian Arctic, there is an increase in all precipitation extremes and a consistent decrease in CDD for all SSP scenarios, with the maximum increase of more than 90% for R95p and R10 mm observed under SSP5–8.5. Full article

Global vegetation growth is dynamically influenced and regulated by hydrological processes. Understanding vegetation responses to terrestrial water storage (TWS) dynamics is crucial for predicting ecosystem resilience and guiding water resource management under climate change. This study investigated global vegetation responses to a terrestrial water storage anomaly (TWSA) using NDVI and TWSA datasets from January 2004 to December 2023. We proposed a Pearson-ACF time lag analysis method that combined dynamic windowing and enhanced accuracy to capture spatial correlations and temporal lag effects in vegetation responses to TWS changes. The results showed the following: (1) Positive NDVI-TWSA correlations were prominent in low-latitude tropical regions, whereas negative responses occurred mainly north of 30°N and in South American rainforest, covering 38.96% of the global vegetated land. (2) Response patterns varied by vegetation type: shrubland, grassland, and cropland exhibited short lags (1–4 months), while tree cover, herbaceous wetland, mangroves, and moss and lichen typically presented delayed responses (8–9 months). (3) Significant bidirectional Granger causality was identified in 16.39% of vegetated regions, mainly in eastern Asia, central North America, and central South America. These findings underscored the vital role of vegetation in the global water cycle, providing support for vegetation prediction, water resource planning, and adaptive water management in water-scarce regions. Full article

The coypu (Myocastor coypus), a semi-aquatic rodent native to South America, has established invasive populations across North America, Asia, and Europe. In Greece, since its initial recording in 1965, the species has been rapidly expanding, forming sizable populations in northern continental regions. However, the extent of its invasion and the environmental drivers shaping its distribution and spatial patterns in western–central Greece remain poorly understood. Here, we address this knowledge gap, aiming to identify and map new coypu records, investigate the relationship between coypu presence and habitat characteristics, and analyze its spatial distribution. Between 2020 and 2023, we conducted 50 field surveys across the study area, documenting direct and indirect evidence of coypu presence. We integrated kernel density estimation, Getis-Ord Gi*, and Anselin local Moran’s I to identify spatial distribution patterns and hotspots of the coypu. Additionally, we analyzed environmental factors including land cover type, total productivity, and geomorphological features to determine their influence on habitat selection. Our findings reveal significant spatial clustering of coypus, with 12 identified hotspots primarily located in protected areas, and highlight tree cover density and productivity variability as key predictors of coypu presence. The suitability of western–central Greece for the coypu appears to be driven by extensive wetlands and interconnected hydrological systems, with hotspots concentrated in lowland agricultural landscapes, providing essential data to guide targeted management strategies for mitigating the ecological risks posed by this invasive species. Full article

The integrated multi-satellite retrievals for the global precipitation measurement (IMERG) data, which is the latest generation of multi-satellite fusion inversion precipitation product provided by the Global Precipitation Measurement (GPM) mission, has been widely applied in hydrological research and applications. However, the quality of IMERG data needs to be validated, as this technology is essentially an indirect way to obtain precipitation information. This study evaluated the performance of IMERG final run (version 6.0) products from 2001 to 2020, using three sets of gauge-derived precipitation data obtained from the Integrated Surface Database, China Meteorological Administration, and U.S. Climate Reference Network. The results showed a basic consistency in the spatial pattern of annual precipitation total between IMERG data and gauge observations. The highest and lowest correlations between IMERG data and gauge observations were obtained in North Asia (0.373, p < 0.05) and Europe (0.308, p < 0.05), respectively. IMERG data could capture the bimodal structure of diurnal precipitation in South Asia but overestimates a small variation in North Asia. The disparity was attributed to the frequency overestimation but intensity underestimation in satellite inversion, since small raindrops may evaporate before arriving at the ground but can be identified by remote sensors. IMERG data also showed similar patterns of interannual precipitation variability to gauge observation, while overestimating the proportion of annual precipitation hours by 2.5% in North America, and 2.0% in North Asia. These findings deepen our understanding of the capabilities of the IMERG product to estimate precipitation at the hourly scale, and can be further applied to improve satellite precipitation retrieval. Full article

Chemical and physical denudation rates have been assessed in areas with different lithologies. Surprisingly, there are no studies that attempt to document these rates in the Poços de Caldas Alkaline Massif (PC), the largest alkaline magmatism in South America and an important Al supergene deposit in Brazil. Therefore, the chemical and physical denudation rates were assessed and explained in the PC. Surface water and rainwater samples were collected at the Amoras Stream basin, covering one complete hydrological cycle (2016). All samples were analyzed for dissolved cations, silica, anions, total dissolved solids (TDS), and total suspended solids (TSS). The results reflected the seasonal variation on discharge, water temperature, and electrical conductivity in the Amoras Stream, with most of the cations, anions, silica TDS, and TSS being carried in the wet season. Partial hydrolysis and silicate incongruent dissolution are the main water/rock interactions in the PC, with an atmospheric/soil CO₂ consumption rate of 1.6 × 10⁵ mol/km²/a. The annual fluxes of Cl⁻, PO₄³⁻, NO₃⁻, and Al³⁺ were significantly influenced from rainwater. Chemical and physical weathering rates were 4 ± 0.8 and 3.0 ± 0.6 m/Ma in the PC, respectively, indicating that under the current climatic condition, the weathering profile is in dynamic equilibrium. Full article

The Amazon biome plays a crucial role in the hydrological cycle, supplying water vapor for the atmosphere and contributing to evapotranspiration (ET) that influences regional humidity across Brazil and South America. Remote sensing (RS) has emerged as a valuable tool for measuring and estimating ET, particularly in the data-scarce Amazon region. A scientometric analysis was conducted to identify the most used RS-based ET product or model in Brazil and its potential application in the Amazon. Scientometrics allows for the quantitative analysis of scientific output; this study identified the most widely used RS product in the Amazon biome. Articles published in Web of Science, Scielo, and Scopus databases up to 2022 were searched using the keywords “Evapotranspiration”, “Remote Sensing”, and “Brazil”. After initial screening, 140 relevant articles were subjected to scientometric analysis using the Bibliometrix library in RStudio 2023.06.1+524. These articles, published between 2001 and 2022, reveal a collaborative research landscape involving 600 authors and co-authors from 245 institutions, with most studies originating from Brazil’s Southeast and North (Amazon) regions. Notably, within the 12 studies focusing on ET by RS in the Amazon biome, applications were diverse, encompassing river basins, climate change, El Niño, and deforestation, with the MOD16 product being the most frequently employed. Full article

In recent years, a new discipline known as Explainable Artificial Intelligence (XAI) has emerged, which has followed the growing trend experienced by Artificial Intelligence over the last decades. There are, however, important gaps in the adoption of XAI in hydrology research, in terms of application studies in the southern hemisphere, or in studies associated with snowmelt-driven streamflow prediction in arid regions, to mention a few. This paper seeks to contribute to filling these knowledge gaps through the application of XAI techniques in snowmelt-driven streamflow prediction in a basin located in the arid region of north-central Chile in South America. For this, two prediction models were built using the Random Forest algorithm, for one and four months in advance. The models show good prediction performance in the training set for one (RMSE:1.33, R²: 0.94, MAE:0.55) and four (RMSE: 5.67, R²:0.94, MAE: 1.51) months in advance. The selected interpretation techniques (importance of the variable, partial dependence plot, accumulated local effects plot, Shapley values and local interpretable model-agnostic explanations) show that hydrometeorological variables in the vicinity of the basin are more important than climate variables and this occurs both for the dataset level and for the months with the lowest streamflow records. The importance of the XAI approach adopted in this study is discussed in terms of its contribution to the understanding of hydrological processes, as well as its role in high-stakes decision-making. Full article

Drought events are critical environmental threats that yield several socioeconomic impacts. Such effects are even more relevant for South America (SA) since different activities essential for the continent, such as agriculture and energy generation, depend highly on water resources. Thus, this study aimed to evaluate future changes in precipitation and hydrological drought occurrence in SA through climate projections from eight global climate models (GCMs) of CMIP6. To this end, statistical downscaling was applied to the projections obtained using the quantile delta mapping technique, and the method proved to be efficient in reducing systematic biases and preserving GCMs’ trends. For the following decades, the results show considerable and statistically significant reductions in precipitation over most of SA, especially during the austral spring, with the most intense signal under the SSP5-8.5 forcing scenario. Furthermore, GCMs showed mixed signals about projections of the frequency and intensity of drought events. Still, they indicated agreement regarding the increased duration and severity of events over the continent and a substantial proportion of moderate and severe events over most of Brazil during the 21st century. These results can be helpful for better management of water resources by decision-makers and energy planners. Full article

SWAT+ is a revised version of the SWAT model that has the capability to route flow across landscape units in the catchment, which is expected to improve the spatial representation of processes in watersheds. We applied the SWAT+ model in the Uruguay River Basin, an international river basin in South America with a total surface area of 370,000 km², in order to (1) assess the water balance components, (2) represent their spatial distribution, and (3) examine their changes over time. The catchment was divided into uplands and floodplains and a decision table rule was developed based on streamflow data. The SPOTPY Python library was linked to SWAT+ and used as a tool to perform sensitivity analyses and calibration. The model represented the fluctuations of discharge well, although there was a general tendency to underestimate peak flows. Blue (precipitation and runoff) and green (evapotranspiration and soil water content) hydrological components were spatially plotted. Overall, SWAT+ simulated a realistic spatial distribution of the water cycle components. A seasonal Mann–Kendall test suggests a positive increasing trend in the average temperature (p-value = 0.007; Sen’s slope = 0.09), the soil water content (p-value = 0.02; Sen’s slope = 1.29), and evapotranspiration (p-value: 0.03; Sen’s slope = 1.97), indicating that the ecosystem experienced a changing climate during the simulation period. The findings presented in this study are of significant value for the impacts of sustainable management and the evaluation of climate change on water resources in the Uruguay River Basin. Full article

Wetlands are crucial hydrological features that provide benefits, including ecosystem services and habitat conservation, protection from flooding associated with sea level rise and extreme events, water storage and treatment, recreation, and aesthetics, among others. Peru is one of the few countries in Latin America that has not developed a national wetland inventory. While this can in part be attributed to the limited availability of peer-reviewed publications in the English literature, a larger quantity of Peruvian wetland-related publications are available in Spanish, and are less accessible to the global population. In this paper, we developed an extensive review and synthesis of the Spanish literature, including university theses, peer-reviewed articles, and government reports. Our report focuses on evaluating the state of the art of Peruvian wetlands in terms of temporal evolution, geographical distribution, vested institutions, research topics (e.g., water quality, fauna, flora, microorganisms, etc.), and advances toward the conservation of wetlands. The analysis identified 274 wetland-related publications in Spanish (188 theses, 83 peer-reviewed, and 6 government reports) and a temporal increase in dissemination over the past two decades. The reports encompassed 161 distinct wetlands distributed nationwide; however, most of the investigations focused on only a few wetland bodies with a disproportionate concentration in just three administrative regions. This reveals that wetland-related research is unevenly distributed in Peru, and highlights a need to extend this knowledge to underrepresented systems and regions. Although Peru ranks third in South America for protected (Ramsar) wetland areas, case studies have revealed that wetlands in the country are vulnerable to human activities. Recent national legislation established in 2021 should help to address this challenge, as before this time, there was a more decentralized approach, whereby each administrative region held responsibility for the protection of their own wetlands. Collective findings indicate that research activity should be increased nationally in order to better understand the function and benefits of wetlands throughout Peru, in addition to the continued development and enforcement of regulations designed to protect these valuable ecosystems. Finally, since a national Peruvian wetland inventory is urgently needed, this analysis provides a baseline for this development of, as well as identifying gaps in, knowledge needed for appropriate national representation. Full article

Plant communities in North American prairie pothole wetlands vary depending on hydrology, salinity, and anthropogenic disturbance in and around the wetland. We assessed prairie pothole conditions on United States Fish and Wildlife Service fee-title lands in North Dakota and South Dakota to improve our understanding of current conditions and plant community composition. Species-level data were collected at 200 randomly chosen temporary and seasonal wetland sites located on native prairie remnants (n = 48) and previously cultivated lands that were reseeded into perennial grassland (n = 152). The majority of species surveyed appeared infrequently and were low in relative cover. The four most frequently observed species were introduced invasive species common to the Prairie Pothole Region of North America. Our results suggested relative cover of a few invasive species (i.e., Bromus inermis Leyss., Phalaris arundinacea L., and Typha ×glauca Godr. (pro sp.) [angustifolia or domingensis × latifolia]) affect patterns of plant community composition. Wetlands in native and reseeded grasslands possessed distinct plant community composition related to invasive species’ relative cover. Invasive species continue to be prevalent throughout the region and pose a major threat to biological diversity, even in protected native prairie remnants. Despite efforts to convert past agricultural land into biologically diverse, productive ecosystems, invasive species continue to dominate these landscapes and are becoming prominent in prairie potholes located in native areas. Full article

Regionalization schemes reflect different macroscale distribution patterns and show large areas characterized by a common natural history, resulting in similar associations of biotic and abiotic features. Freshwater biota and terrestrial biota do not respond in the same way to environmental variables. The Iberá Depression, one of the largest wetlands in South America, is recognized in many schemes either as a functional unit or as an area with an ecotonal character. We used the distributional data of 128 species of Odonata, from a total of 103 collection sites from Corrientes and Misiones provinces, to test if Iberá functions as an ecological and functional unit, based on the Odonata distribution patterns. In addition, we tested if their distribution patterns fit into the most widespread regionalization schemes (hydrological basins, biogeographical provinces and ecoregions) used in Argentina. The Iberá Depression was not recovered as a functional unit; its sub-basins are more related to external basins than to each other. Neither the ecoregion nor the biogeographical schemes are suitable to explain the distribution patterns of the Odonata. The Odonata seem to respond to the availability of particular wetlands (e.g., ponds, streams, rivers, swamps, etc.), or to specific physical characteristics, such as the type of sediment, the availability of oxygen, etc., instead of to biogeographical or ecoregional schemes. Full article

We evaluated the coupled dynamics of vegetation dynamics (NDVI) and soil moisture (SMOS) at monthly resolution over different regions of tropical South America and the effects of the Eastern Pacific (EP) and the Central Pacific (CP) El Niño–Southern Oscillation (ENSO) events. We used linear Pearson cross-correlation, wavelet and cross wavelet analysis (CWA) and three nonlinear causality methods: ParrCorr, GPDC and PCMCIplus. Results showed that NDVI peaks when SMOS is transitioning from maximum to minimum monthly values, which confirms the role of SMOS in the hydrological dynamics of the Amazonian greening up during the dry season. Linear correlations showed significant positive values when SMOS leads NDVI by 1–3 months. Wavelet analysis evidenced strong 12- and 64-month frequency bands throughout the entire record length, in particular for SMOS, whereas the CWA analyses indicated that both variables exhibit a strong coherency at a wide range of frequency bands from 2 to 32 months. Linear and nonlinear causality measures also showed that ENSO effects are greater on SMOS. Lagged cross-correlations displayed that western (eastern) regions are more associated with the CP (EP), and that the effects of ENSO manifest as a travelling wave over time, from northwest (earlier) to southeast (later) over tropical South America and the Amazon River basin. The ParrCorr and PCMCIplus methods produced the most coherent results, and allowed us to conclude that: (1) the nonlinear temporal persistence (memory) of soil moisture is stronger than that of NDVI; (2) the existence of two-way nonlinear causalities between NDVI and SMOS; (3) diverse causal links between both variables and the ENSO indices: CP (7/12 with ParrCorr; 6/12 with PCMCIplus), and less with EP (5/12 with ParrCorr; 3/12 with PCMCIplus). Full article

The synoptic mode of variability (SMV) refers to changes in atmospheric conditions over periods ranging from 2 to 10 days. In tropical regions, this variability is driven by tropical waves that have a clear signal on the wavenumber–frequency power spectra of precipitation. This study uses the ensemble empirical mode decomposition (EEMD) method to identify the SMV in daily precipitation and streamflows in 47 river basins over northern South America. We found the presence of the frequency bands with periods of 3–12 days and 6–18 days, which agrees with the SMV associated with tropical waves that modulate precipitation over the region. Furthermore, our results reveal that variance explained by the SMV in rainfall over each catchment is greater than the variance explained by those SMV in streamflows, which suggests that catchments efficiently filter out this variability. We found that SMV explains from 5% to 20% of streamflow variability for catchments ranging from 1000 km${}^2$ to 5000 km${}^2$. Additionally, the variance explained by SMV decreases as a power fit with the catchment area. Thus, this study characterizes the SMV for potential applications on regional hydrology, diagnosis, modeling, short-time forecasting, prediction, and management of water resources. Full article

The precipitation phase (i.e., rain and snow) is important for the global hydrologic cycle and climate system. The objective of this study is to evaluate the precipitation-phase partitioning capabilities of remote sensing and reanalysis modeling methods on the global scale. Specifically, observation data from the National Centers for Environmental Prediction (NCEP) Automated Data Processing (ADP), from 2000 to 2007, are used to evaluate the rain–snow discrimination accuracy of the Integrated Multi-Satellite Retrievals for Global Precipitation Measurement (IMERG) and the fifth-generation reanalysis product of the European Centre for Medium Range Weather Forecasts (ERA5). The results show that: (1) the ERA5 performs better than the IMERG at distinguishing rainfall and snowfall events, overall. (2) The ERA5 has high accuracy in all continents except for South America, while the IMERG performs well only in Antarctica and North America. (3) Compared with the IMERG, the ERA5 can more effectively capture snowfall events at high latitudes but shows worse performance at mid-low latitude regions. Both the IMERG and ERA5 have lower accuracy for rain–snow partitioning under heavy precipitation. Overall, the results of this study provide references for the application and improvement of global rain–snow partitioning products. Full article