River Basin Research Articles

Spatiotemporal variations in potential evapotranspiration in the Yellow River and Yangtze River Basins under changing environments: impacts on runoff and their causes

Spatiotemporal variations in potential evapotranspiration in the Yellow River and Yangtze River Basins under changing environments: impacts on runoff and their causes

A study on the quantification and impact mechanism of regional ecological compensation based on revised carbon accounts: evidence from the Yellow River Basin economic zone in China

A study on the quantification and impact mechanism of regional ecological compensation based on revised carbon accounts: evidence from the Yellow River Basin economic zone in China

Study on the Spatial–Temporal Variation of Groundwater Depth and Its Impact on Vegetation Coverage in Ejina Oasis

Ejina, a representative inland river basin situated in the arid region of northwest China, exhibits a delicate ecological environment and its vegetation coverage is intrinsically linked to regional ecological security. Based on MOD13Q1-NDVI data from 2018 to 2023 and groundwater depth monitoring data during the same period, this study analyzed the spatial–temporal variation characteristics of vegetation coverage and its relationship with groundwater depth in Ejina. It is found that the vegetation coverage in Ejina is generally low and mainly distributed along the riverbanks in the form of strips. During the study period, the overall trend of vegetation coverage showed a fluctuating pattern of first increasing and then decreasing, revealing the fragility of the regional ecology. The groundwater depth shows the characteristic of being higher in the east river than the west, and the trend of groundwater depth along the river flow is first increasing and then decreasing. The spatial groundwater depth indicates that the east river is higher than that of the west river, and the groundwater depth along the river flow first increases and then decreases. In terms of inter-annual changes, the groundwater depth experiences a process of first decreasing and then stabilizing. Further analysis indicates that vegetation growth and coverage in Ejina are significantly affected by water conditions, and areas with high Normalized Difference Vegetation Index (NDVI) values are mainly distributed along the riverbanks. In addition, there is a certain degree of correlation between groundwater depth and NDVI. When the depth of groundwater is too deep or too shallow, the positive correlation between NDVI and groundwater depth increases slightly and the negative correlation decreases slightly. The findings of this study are of great significance for understanding and predicting the response of vegetation coverage to groundwater changes in arid areas, and provide a scientific basis for water resources management and ecological protection in Ejina.

First data on concentrations and composition of polycyclic aromatic hydrocarbons in soil, bottom sediments and suspended matter of water throughout the whole Fatala River Basin (Republic of Guinea)

First data on concentrations and composition of polycyclic aromatic hydrocarbons in soil, bottom sediments and suspended matter of water throughout the whole Fatala River Basin (Republic of Guinea)

Integrative framework for analyzing ecosystem services multifunctionality in watershed planning: case study of the Coello River Basin, Colombia

Integrative framework for analyzing ecosystem services multifunctionality in watershed planning: case study of the Coello River Basin, Colombia

Baseflow: Potential Pathway Underlying a High Nitrogen Concentration in a Less-rainy Watershed—Taking Chaohe River Basin of China as an Example

Baseflow: Potential Pathway Underlying a High Nitrogen Concentration in a Less-rainy Watershed—Taking Chaohe River Basin of China as an Example

Appraising meteoric-surface-groundwater interaction through analyses of hydrochemical evolution of water resources in the Lower Niger River Basin, Nigeria

Appraising meteoric-surface-groundwater interaction through analyses of hydrochemical evolution of water resources in the Lower Niger River Basin, Nigeria

Extreme Precipitation Events During the Wet Season of the South America Monsoon: A Historical Analysis over Three Major Brazilian Watersheds

Most of South America, particularly the region between the southern Amazon and southeastern Brazil, as well as a large part of the La Plata Basin, has its climate regulated by the South American Monsoon System. Extreme weather and climate events in these areas have significant socioeconomic impacts. The Madeira, São Francisco, and Paraná river basins, three major watersheds in Brazil, are especially vulnerable to wet and drought periods due to their importance as freshwater ecosystems and sources of water for consumption, energy generation, and agriculture. The scarcity of surface meteorological stations in these basins makes meteorological studies challenging, often using reanalysis and satellite data. This study aims to identify extreme weather (wet) and climate (wet and drought) events during the extended wet season (October to March) from 1980 to 2022 and evaluate the performance of two gridded datasets (CPC and ERA5) to determine which best captures the observed patterns in the Madeira, São Francisco, and Paraná river basins. Wet weather events were identified using the 95th percentile, and wet and drought periods were identified using the Standardized Precipitation Index (SPI) on a 6-month scale. In general, CPC data showed slightly superior performance compared to ERA5 in reproducing statistical measures. For extreme day precipitation, both datasets captured the time series pattern, but CPC better reproduced extreme values and trends. The results also indicate a decrease in wet periods and an increase in drought events. Both datasets performed well, showing they can be used in the absence of station data.

Monitoring Dissolved Organic Carbon Concentration and Flux in the Qiantang Riverine System Using Sentinel-2 Satellite Images

Real-time monitoring of riverine-dissolved organic carbon (DOC) and its controlling factors is critical for formulating strategies regarding the river basin and marginal seas pollution prevention and control. In this study, we established a linear regression formulation that relates the permanganate index (CODMn) to the DOC concentration based on in situ measurements collected on five field surveys in 2023–2024. This regression formulation was used on a large number of data collected from automatic monitoring stations in the Qiantang River area to construct a daily quasi-in situ database of DOC concentration. By combining the quasi-in situ DOC data and Sentinel-2 measurements, an enhanced algorithm for empirical DOC estimation was developed (R2 = 0.66) using the extreme gradient boosting (XGBoost) method and its spatial and temporal variations in the Qiantang River were analyzed from 2016 to 2023. Spatially, the main stream of the Qiantang River exhibited an overall decreasing and increasing trend influenced by population density, economic development, and pollutant discharge in the basin area, and the temporal distribution of DOC was controlled by meteorological conditions. The DOC contents had the highest in summer, primarily due to high rainfall and leaching. The inter-annual variation in DOC concentration was influenced by the total annual runoff volumes, with a minimum level of 2.24 mg L−1 in 2023 and a maximum level of 2.45 mg L−1 in 2019. The monthly DOC fluxes ranged from 6.3 to 13.8 × 104 t, with the highest values coinciding with the maximum river discharge volumes in June and July. The DOC levels in the Qiantang River remained relatively high in recent years (2016–2023). This study enables the concerned stakeholders and researchers to better understand carbon transportation and its dynamics in the Qiantang River and its coastal areas.

An examination of the fluctuation and long-term persistence of drought regimes in the Jing River basin using the PDSI–SWAT model

An examination of the fluctuation and long-term persistence of drought regimes in the Jing River basin using the PDSI–SWAT model

Distribution of heavy metals in the sediments of Ganga River basin: source identification and risk assessment.

Sediment serves as a heavy metal store in the riverine system and provides information about the river's health. To understand the distribution of heavy metal content in the Ganga River basin (GRB), a total of 25-bed sediment and suspended particulate matter (SPM) samples were collected from 25 locations in December 2019. Bed sediment samples were analyzed for different physio-chemical parameters, along with heavy metals. Due to insufficient quantity of SPM, the samples were not analyzed for any physio-chemical parameter. The metal concentrations in bed sediments were found to be as follows: Co (6-20mg/kg), Cr (34-108mg/kg), Ni (6-46mg/kg), Cu (14-210mg/kg), and Zn (30-264mg/kg) and in SPM, the concentrations were Co (BDL-50mg/kg), Cr (10-168mg/kg), Ni (BDL-88mg/kg), Cu (26-80mg/kg), and Zn (44-1186mg/kg). In bed sediment, a strong correlation of 0.86 and 0.93 was found between Ni and Cr, and Cu and Zn respectively and no significant correlation exists between organic carbon and metals except Co. In SPM, a low to moderate correlation was found between all the metals except Zn. The risk indices show adverse effects at Pragayraj, Fulhar, and Banshberia. Two major clusters were formed in Hierarchal Cluster Analysis (HCA) among the sample points in SPM and bed sediment. This study concludes that the Ganga River at Prayagraj, Banshberia, and Fulhar River is predominately polluted with Cu and Zn, possibly posing an ecological risk. These results can help policymakers in implementing measures to control metal pollution in the Ganga River and its tributaries.

Garra ngopi sp. n., a new fish species (Cyprinidae: Labeoninae) from the Brahmaputra River basin, Arunachal Pradesh, North–Eastern India

Garra ngopi sp. n., a new fish species (Cyprinidae: Labeoninae) from the Brahmaputra River basin, Arunachal Pradesh, North–Eastern India

Flood risk zone mapping and future projections for the Thamirabarani river basin, Southern India: insights from decadal rainfall trends and GIS-based analytical hierarchy process technique

Flood risk zone mapping and future projections for the Thamirabarani river basin, Southern India: insights from decadal rainfall trends and GIS-based analytical hierarchy process technique

Multi-Criteria Analysis for Geospatialization of Potential Areas for Water Reuse in Irrigated Agriculture in Hydrographic Regions

As the climate crisis progresses, droughts and the seasonal availability of fresh water are becoming increasingly common in different regions of the world. One solution to tackle this problem is the reuse of treated wastewater in agriculture. This study was carried out in two significant hydrographic regions located in the southeast of Brazil (Mogi Guaçu River Water Management Unit—UGRHI-09 and Piracicaba River Basin—PRB) that have notable differences in terms of land use and land cover. The aim of this study was to carry out a multi-criteria analysis of a set of environmental attributes in order to classify the areas under study according to their levels of soil suitability and runoff potential. The integrated analysis made it possible to geospatialize prospective regions for reuse, under two specified conditions. In the UGRHI-09, condition 1 corresponds to 3373.24 km2, while condition 2 comprises 286.07 km2, located mainly in the north-western and central-eastern portions of the unit. In the PRB, condition 1 was also more expressive in occupational terms, corresponding to 1447.83 km2; and condition 2 was perceptible in 53.11 km2, predominantly in the central region of the basin. The physical characteristics of the areas studied were decisive in delimiting the areas suitable for the reuse of treated wastewater.

Spatiotemporal changes and driving factors of ecological environmental quality in the Yongding-Luan River Basin based on RSEI

The ecological environmental quality (EEQ) of the Yongding-Luan River Basin (YLRB) is pivotal to the ecological security of the Beijing-Tianjin-Hebei (JJJ) region's core area. Evaluating the EEQ and analyzing its changes are essential for regional ecological management. However, long-term ecological changes in the YLRB remain uncovered. In this study, we constructed a seamless Remote Sensing Ecological Index (RSEI) for the YLRB from 1986 to 2022 using time-series Landsat imagery on the Google Earth Engine (GEE) platform. The Sen + Mann-Kendall method was employed to analyze the spatiotemporal trends of EEQ, and the Geodetector was used to quantitatively assess the driving factors and their interactions. The results show that: 1) The mean RSEI of the YLRB increased from 0.486 in 1986 to 0.532 in 2022, marking a 9.5% rise and indicating a fluctuating upward trend. 2) The EEQ of the YLRB experienced three distinct phases: improvement, deterioration, and re-improvement. Improvements were predominantly in the western YLRB, while deterioration was mainly in the northern Xilinguole region and the southern urban expansion areas of Beijing, Langfang, Tianjin, and Tangshan. 3) The driving factor detection indicates that land use type and annual average precipitation are the primary driving factors of RSEI change in the YLRB. Furthermore, their interaction results in a significant effect on RSEI, with a maximum of 0.691. These findings align with the historical urban expansion in the YLRB and the environmental policies implemented by the Chinese government. The ecological evolution and driving factors identified in this study offer a scientific basis for regional ecological decision-making and management.

Spatial-Temporal Changes in Ecosystem Service Value and Its Overlap with Coal Mining Intensity in the Yellow River Basin, China, During 2000–2030

Understanding the ecosystem services and their interaction with coal resource development is crucial for formulating sustainable development policies. In this study, we focused on the Yellow River Basin, characterized by both rich coal resources and ecological fragility. The key findings are that (1) the ecosystem service value (ESV) in the Yellow River Basin exhibited significant spatial heterogeneity during 2000–2030, decreasing from the southeast to northwest, and decreasing the most notably in the southern part of the upper reaches of the river basin; (2) the high-high clustering area of the ESV shifted from the upper-middle reaches in 2000 to the middle-lower reaches in 2020, while the low-low clustering area remained within Inner Mongolia. By 2030, the high-high clustering area is expected to stabilize in southern Shaanxi Province, and the low-low area will potentially spread eastward; (3) the overall ESV is low, and it experienced a significant decline from 2000 to 2020, with water supply emerging as a major limiting factor, although some policy-supported counties had better ecological service values and trends. (4) From 2000 to 2020, the coal mining intensity (CMI) was concentrated in the upper and middle reaches, particularly at the junctions of Shanxi, Shaanxi, and Inner Mongolia, and the pattern remained stable, but local areas experienced increased mining intensity; (5) the overlap of the CMI and ESV primarily exhibited a low-high clustering pattern in the middle and upper reaches of the Yellow River Basin and eastern Ordos City, and a high-high clustering pattern in the middle reaches of the basin in Shanxi Province, which remained stable and slightly expanded from 2000 to 2030; (6) the trade-off between the ecosystem services in the overlap area intensified, especially between the provisioning and support services, and was significantly impacted by the coal mining activities. The findings indicate that the area that overlaps with the coal mining area in the Yellow River Basin has expanded and has had an increasing negative impact on the ESV. It is also essential to address the trade-offs between the provisioning and support services and to implement ecological restoration measures to mitigate the risk of ESV loss. Future efforts should focus on the regions where the CMI and ESV overlap and have poor coordination and the adverse effects of resource extraction on ecosystem services are becoming more pronounced. The results of this study demonstrate that spatial overlap analysis is effective in identifying the hotspots and provides a foundation for developing sustainable and high-quality policies for ecologically fragile basins.

Mummy of a juvenile sabre-toothed cat Homotherium latidens from the Upper Pleistocene of Siberia.

The frozen mummy of the large felid cub was found in the Upper Pleistocene permafrost on the Badyarikha River (Indigirka River basin) in the northeast of Yakutia, Russia. The study of the specimen appearance showed its significant differences from a modern lion cub of similar age (three weeks) in the unusual shape of the muzzle with a large mouth opening and small ears, the very massive neck region, the elongated forelimbs, and the dark coat color. Tomographic analysis of the mummy skull revealed the features characteristic of Machairodontinae and of the genus Homotherium. For the first time in the history of paleontology, the appearance of an extinct mammal that has no analogues in the modern fauna has been studied.

Spatiotemporal Changes and Influencing Factors of the Coupled Production–Living–Ecological Functions in the Yellow River Basin, China

The imbalance in the “production–living–ecology” function (PLEF) has become a major issue for global cities due to the rapid advancement of urbanization and industrialization worldwide. The realization of PLEF coupling and coordination is crucial for a region’s sustainable development. Existing research has defined the concept of PLEF from the perspective of land function and measured its coupling coordination level using relevant models. However, there is still room for improvement in the indicator system, research methods, and other aspects. This work builds a PLEF coupling coordination evaluation-index system based on the perspective of human habitat using multi-source data in order to examine the spatial differences in PLEF coupling coordination level and the influencing factors in the Yellow River Basin (YRB). Using the modified coupling coordination model, the Moran index, spatial Markov chain model, and geographically weighted random forest model were introduced to analyze its spatial and temporal differentiation and influencing factors. The results found that (a) the level of PLEF coupling coordination in the YRB from 2010 to 2022 has been improving, and the number of severely imbalanced cities has been reduced from 23 to 15, but the level of downstream cities’ coupling coordination is significantly higher than that of upstream cities. The probability of cities maintaining their own level is greater than 50%, and there is basically no cross-level transfer. (b) The Moran index of the PLEF coupling coordination level has risen from 0.137 to 0.229, which shows a significant positive clustering phenomenon and is continually strengthening. The intercity polarization effect is being continually enhanced as seen in the LISA clustering diagram. (c) There is significant heterogeneity between the influencing factors in time and space. In terms of importance level, the series is per capita disposable income (0.416) > nighttime lighting index (0.370) > local general public budget expenditure (0.332) > number of beds per 1000 people (0.191) > NO2 content in the air (0.110). This study systematically investigates the dynamic evolution of the coupled coordination level of PLEF in the YRB and its influencing mechanism, which is of great practical use.

Textiles from the Late Bronze Age and the Early Iron Age in the Vistula and Oder River Basin – Poland

Textiles from the Late Bronze Age and the Early Iron Age in the Vistula and Oder River Basin – Poland

The Dynamics of Air Pollution in the Southwestern Part of the Caspian Sea Basin (Based on the Analysis of Sentinel-5 Satellite Data Utilizing the Google Earth Engine Cloud-Computing Platform)

The Caspian region represents a complex and unique system of terrestrial, coastal, and aquatic environments, marked by an exceptional landscape and biological diversity. This diversity, however, is increasingly threatened by substantial anthropogenic pressures. One notable impact of this human influence is the rising concentration of pollutants atypical for the atmosphere. Advances in science and technology now make it possible to detect certain atmospheric pollutants using remote Earth observation techniques, specifically through data from the Sentinel-5 satellite, which provides continuous insights into atmospheric contamination. This article investigates the dynamics of atmospheric pollution in the southwestern part of the Caspian Sea basin using Sentinel-5P satellite data and the cloud-computing capabilities of the Google Earth Engine (GEE) platform. The study encompasses an analysis of concentrations of seven key pollutants: nitrogen dioxide (NO2), formaldehyde (HCHO), carbon monoxide (CO), ozone (O3), sulfur dioxide (SO2), methane (CH4), and the Aerosol Index (AI). Spatial and temporal variations in pollution fields were examined for the Caspian region and the basins of the seven rivers (key areas) flowing into the Caspian Sea: Sunzha, Sulak, Ulluchay, Karachay, Atachay, Haraz, and Gorgan. The research methodology is based on the use of data from the Sentinel-5 satellite, SRTM DEM data on absolute elevations, surface temperature data, and population density data. Data processing is performed using the Google Earth Engine cloud-computing platform and the ArcGIS software suite. The main aim of this study is to evaluate the spatiotemporal variability of pollutant concentration fields in these regions from 2018 to 2023 and to identify the primary factors influencing pollution distribution. The study’s findings reveal that the Heraz and Gorgan River basins have the highest concentrations of nitrogen dioxide and Aerosol Index levels, marking these basins as the most vulnerable to atmospheric pollution among those assessed. Additionally, the Gorgan basin exhibited elevated carbon monoxide levels, while the highest ozone concentrations were detected in the Sunzha basin. Our temporal analysis demonstrated a substantial influence of the COVID-19 pandemic on pollutant dispersion patterns. Our correlation analysis identified absolute elevation as a key factor affecting pollutant distribution, particularly for carbon monoxide, ozone, and aerosol indices. Population density showed the strongest correlation with nitrogen dioxide distribution. Other pollutants exhibited more complex distribution patterns, influenced by diverse mechanisms associated with local emission sources and atmospheric dynamics.