Search Results (55)

Climate-driven hydrological extremes and anthropogenic interventions are increasingly altering streamflow regimes worldwide. While prior studies have explored climate or regulation effects separately, few have integrated multiple teleconnection indices and reservoir chronologies within a cross-basin comparative framework. This study addresses this gap by assessing long-term streamflow nonstationarity and its drivers at two key stations—Khabarovsk on the Amur River and Datong on the Yangtze River—representing distinct hydroclimatic settings. We utilized monthly discharge records, meteorological data, and large-scale climate indices to apply trend analysis, wavelet transform, percentile-based extreme diagnostics, lagged random forest regression, and slope-based attribution. The results show that Khabarovsk experienced an increase in winter baseflow from 513 to 1335 m³/s and a notable reduction in seasonal discharge contrast, primarily driven by temperature and cold-region reservoir regulation. In contrast, Datong displayed increased discharge extremes, with flood discharges increasing by +71.9 m³/s/year, equivalent to approximately 0.12% of the mean flood discharge annually, and low discharges by +24.2 m³/s/year in recent decades, shaped by both climate variability and large-scale hydropower infrastructure. Random forest models identified temperature and precipitation as short-term drivers, with ENSO-related indices showing lagged impacts on streamflow variability. Attribution analysis indicated that Khabarovsk is primarily shaped by cold-region reservoir operations in conjunction with temperature-driven snowmelt dynamics, while Datong reflects a combined influence of both climate variability and regulation. These insights may provide guidance for climate-responsive reservoir scheduling and basin-specific regulation strategies, supporting the development of integrated frameworks for adaptive water management under climate change. Full article

Drought impacts agricultural production and regional sustainable development. Accordingly, timely and accurate drought monitoring is essential for ensuring food security in rain-fed agricultural regions. Alternating drought and flood events frequently occur in the Heilongjiang River Basin, the largest grain-producing area in Far East Asia. However, spatiotemporal variability in drought is not well understood, in part owing to the limitations of the traditional Temperature Vegetation Dryness Index (TVDI). In this study, an Improved Temperature Vegetation Dryness Index (ITVDI) was developed by incorporating Digital Elevation Model data to correct land surface temperatures and introducing a constraint line method to replace the traditional linear regression for fitting dry–wet boundaries. Based on MODIS (Moderate-resolution Imaging Spectroradiometer) normalized vegetation index and land surface temperature products, the Heilongjiang River Basin, a cross-border basin between China, Mongolia, and Russia, exhibited pronounced spatiotemporal variability in drought conditions of the growing season from 2001 to 2023. Drought severity demonstrated clear geographical zonation, with a higher intensity in the western region and lower intensity in the eastern region. The Mongolian Plateau and grasslands were identified as drought hotspots. The Far East Asia forest belt was relatively humid, with an overall lower drought risk. The central region exhibited variation in drought characteristics. From the perspective of cross-national differences, the drought severity distribution in Northeast China and Inner Mongolia exhibits marked spatial heterogeneity. In Mongolia, regional drought levels exhibited a notable trend toward homogenization, with a higher proportion of extreme drought than in other areas. The overall drought risk in the Russian part of the basin was relatively low. A trend analysis indicated a general pattern of drought alleviation in western regions and intensification in eastern areas. Most regions showed relatively stable patterns, with few areas exhibiting significant changes, mainly surrounding cities such as Qiqihar, Daqing, Harbin, Changchun, and Amur Oblast. Regions with aggravation accounted for 52.29% of the total study area, while regions showing slight alleviation account for 35.58%. This study provides a scientific basis and data infrastructure for drought monitoring in transboundary watersheds and for ensuring agricultural production security. Full article

Research on fish skin artefacts’ dyeing practices among the Nivkh, Nanai, Ulchi, Udegei, Oroch, and Negidal Indigenous Peoples of the Amur River basin remains scarce. These fishing communities traditionally crafted fish skin garments, essential to their subsistence and spiritual life, adorning them with protective motifs. While artistic and cultural aspects of these belongings have been explored, their dyeing techniques remain understudied. This multidisciplinary research examines natural colourants in fish skin artefacts from international museum collections, using historical textual research, ethnographic records, Native Traditional Knowledge, and previous dye analysis by museum conservators. Findings reveal a restricted but meaningful palette of red, blue, yellow, and black colourants, sourced from plants, minerals, and organic materials. Early dyers extracted blue from indigotin-rich plants such as Polygonum tinctorium, or from Commelina communis petals. Red hues were obtained from Carthamus tinctorius petals, introduced through Silk Route trade networks, or from minerals like red ochre. Black was derived from carbon black, while riverine minerals were ground with dry fish roe diluted with water to create additional colour variations. This study first reviews fish skin use in Amur River Indigenous cultures, explores nineteenth-century dyeing materials and techniques, and finally considers broader implications for Indigenous material heritage. Full article

Rapid climate warming and intensified human activities are causing profound alterations in terrestrial hydrological systems. Understanding shifts in hydrological regimes and the underlying mechanisms driving these changes is crucial for effective water resource management, watershed planning, and flood disaster mitigation. This study examines the hydrological regimes of the Heilongjiang-Amur River Basin, a transboundary river basin characterized by extensive permafrost distribution in northeastern Asia, by analyzing long-term daily meteorological (temperature, precipitation, evaporation) and hydrological data from the Komsomolsk, Khabarovsk, and Bogorodskoye stations. Missing daily runoff data were reconstructed using three machine learning methods: Convolutional Neural Networks (CNN), Long Short-Term Memory Networks (LSTM), and Convolutional Long Short-Term Memory Networks (CNN-LSTM). Trend analysis, abrupt change detection, and regression techniques revealed significant warming and increased actual evapotranspiration in the basin from 1950 to 2022, whereas precipitation and snow water equivalent showed no significant trends. Climate warming is significantly altering hydrological regimes by changing precipitation patterns and accelerating permafrost thaw. At the Komsomolsk station, an increase of 1 mm in annual precipitation resulted in a 0.48 mm rise in annual runoff depth, while a 1 °C rise in temperature led to an increase of 1.65 mm in annual runoff depth. Although annual runoff exhibited no significant long-term trend, low-flow runoff demonstrated substantial increases, primarily driven by temperature and precipitation. These findings provide critical insights into the hydrological responses of permafrost-dominated river basins to climate change, offering a scientific basis for sustainable water resource management and strategies to mitigate climate-induced hydrological risks. Full article

This study investigated the fish species composition and environment of the Emur River, a tributary of the Upper Heilongjiang (Amur) River system, which is a typical extreme-cold region of China. From 2022 to 2024, 28 native species (27 species of fish and 1 species of lamprey), including 4 endangered species, were monitored from 14 sampling sites. When grouped according to the main stream vs. tributaries and summer vs. autumn, we found significant differences (p < 0.05) in the composition of the fish communities. In autumn, the main stream fish assemblage was dominated by common species that prefer a slow current, including Phoxinus phoxinus (33.7%), Lota lota (25.2%), and Phoxinus lagowskii (19.8%). The tributary fish assemblage was primarily composed of typical coldwater fish species, such as L. lota (48.9%), Cottus poecilopus (20.2%), and Thymallus grubii (18.1%). However, in summer, there was no significant difference between the main course and tributaries. Canonical correspondence analysis showed environmental factors, including water temperature, elevation, and dissolved oxygen, to have significant impacts on the fish distribution to an extent that varied with species. This study may contribute to the management of coldwater fish diversity in mountain rivers and the protection of aquatic species habitats in regions of extreme cold. Full article

The study of river backwater points (bpts) is pivotal for understanding the interactions between riverine and coastal systems, including brackish water dynamics, coastal flooding, and ecosystem processes. Despite extensive research, the global spatio-temporal dynamics of bpts, particularly in rivers with minimal human intervention, remains underexplored. This study investigates backwater lengths and shifts in 18 major global rivers (discharge > 5000 m³/s) from 2000 to 2020, uncovering significant hydrological and geographical patterns. In 2000, backwater lengths ranged from 113.16 km (Salween) to 828.75 km (Amur), with bpts consistently positioned upstream of apex points. By 2020, all rivers exhibited upstream retreats of their bpts, ranging from 10.43 km (Salween) to 132.51 km (Amazon), and retreat ratios typically falling between 0% and 20%. The Salween, Niger (60%), and Irrawaddy (38%) demonstrated the most significant proportional shifts. Geographical transitions of bpts varied widely: rivers such as the Ganges and Amur shifted toward urbanized areas, while the Amazon and Orinoco remained in remote regions, reflecting the differential impact of human activity and natural processes. There was a general correlation between backwater length and river discharge, with exceptions like the Amur indicating the influence of other factors such as geomorphic settings and sediment dynamics. While sea-level rise (0.019–0.115 m) affected estuarine conditions, it showed no consistent relationship with bpt retreat at the global scale, but a regional-scale analysis indicates that sea-level rise can lead to the retreat of bpts for those rivers with macro-tidal environments and high sediment yields with less human intervention, suggesting localized interactions dominate backwater dynamics. These findings highlight the complex interplay of environmental and anthropogenic pressures on global river systems. They provide a critical foundation for advancing hydrological modeling, improving river management strategies, and understanding the broader implications of spatio-temporal bpt dynamics under changing climatic and human influences. Full article

In spring, the river ice melts to a certain extent and cracks to form drift ice and impact force on the bridge abutments; the river ice, due to the impact of ablation, has an internal formation of different porosities, and the level of porosity affects the mechanical properties of the river ice, so that the impact force generated by the river ice is also different. In this paper, the Heihe–Blagoveshchensk Amur River Bridge abutment is the object of river ice impact, and the discrete element method (DEM) is employed to analyze the impact process and impact force on the abutment by numerical simulation of the melting river ice. The damage characteristics of the ice rows with different ice speeds, ice thicknesses, and porosity, and the time curve of the impact force are obtained. It is found that the maximum impact force of river ice on the abutment decreases nonlinearly with the increase in river ice porosity; the peak contact force occurs with a lag time, and the damage is gradually concentrated in the vicinity of the area in direct contact with the abutment. In this paper, according to the simulation results, the relationship between river ice porosity and the maximum impact force on the bridge abutment, as well as the time parameters, is obtained by fitting, and the power loading model of the bridge abutment impacted by the river ice is established, which provides a basis for the reasonable calculation of the impact force of the ablated river ice at bridge abutments. Full article

Freshwater turtle species preservation relies on understanding their population dynamics and geographical distribution. Amur softshell turtles (ASTs [Pelodiscus maackii]) are poorly protected due to insufficient awareness and the population in Northeastern China has experienced a steep decline compared to previous years. This study aims to investigate the population density and structure of ASTs in the Jewellery Island area of the Ussuri River in Northeast China using continuous-time capture–recapture methods in closed populations. A three-month mark–recapture study was conducted in 2022, resulting in 35 juvenile captures, including 12 recaptures from 23 marked individuals. The estimated population size in the study area was 40.79 ± 9.75 (95% confidence interval, 95% CI = 27–65), translating to 0.663 ± 0.158 turtles/ha (95% CI = 0.44–1.06 individuals/ha). Approximately 35.4–85.2% of the estimated population was marked. Additionally, we explored the influence of environmental variables on turtle distribution by dividing the surveyed sites into seven sections based on their natural characteristics. The ASTs distribution inferred from trapping successes was considerably different among sections, with most turtles (91%) captured at the vegetated shoreline and in water channel 2. This research offers essential baseline data to support future assessments of ASTs population on a larger scale and to inform the development of conservation strategies. Full article

Acquiring the spatiotemporal patterns of cropland disturbance is of great significance for regional sustainable agricultural development and environmental protection. However, effective monitoring of cropland disturbances remains a challenge owing to the complexity of the terrain landscape and the reliability of the training samples. This study integrated automatic training sample generation, random forest classification, and the LandTrendr time-series segmentation algorithm to propose an efficient and reliable medium-resolution cropland disturbance monitoring scheme. Taking the Amur state of Russia in the Amur river basin, a transboundary region between Russia and China in east Asia with rich agriculture resources as research area, this approach was conducted on the Google Earth Engine cloud-computing platform using extensive remote-sensing image data. A high-confidence sample dataset was then created and a random forest classification algorithm was applied to generate the cropland classification probabilities. LandTrendr time-series segmentation was performed on the interannual cropland classification probabilities. Finally, the identification, spatial mapping, and analysis of cropland disturbances in Amur state were completed. Further cross-validation comparisons of the accuracy assessment and spatiotemporal distribution details demonstrated the high accuracy of the dataset, and the results indicated the applicability of the method. The study revealed that 2815.52 km² of cropland was disturbed between 1990 and 2021, primarily focusing on the southern edge of the Amur state. The most significant disturbance occurred in 1991, affecting 1431.48 km² and accounting for 50.84% of the total disturbed area. On average, 87.98 km² of croplands are disturbed annually. Additionally, 2495.4 km² of cropland was identified as having been disturbed at least once during the past 32 years, representing 83% of the total disturbed area. This study introduced a novel approach for identifying cropland disturbance information from long time-series probabilistic images. This methodology can also be extended to monitor the spatial and temporal dynamics of other land disturbances caused by natural and human activities. Full article

Information about the population structure, including the age and sex composition, growth characteristics, and diet of fish, is essential for the conservation and sustainable exploitation of fish stock. The burbot, Lota lota, is the only freshwater species of the family Lotidae in the Amur (Heilongjiang) River catchment located in northeastern China. Information on the biological characteristics and data on the population structure of this fish from the Amur River are scarce. To study these factors in burbot, Lota lota, in the Amur River of China, 749 specimens from four sampling areas were taken and analyzed in October 2022, January 2023, and May 2023. The ages of the sampled fish ranged from 1+ to 7+ years. The female/male ratio was 1.04:1, and body length and mass varied from 175 to 595 mm and 73.5 to 1958.7 g, respectively. The length–weight regression parameter b value was estimated as 2.80. The parameters of the von Bertalanffy growth model were L_∞ = 596, K = 0.221, and t₀ = −0.771 for all sampled fish; L_∞ = 625, K = 0.208, and t₀ = −0.756 for females; and L_∞ = 584, K = 0.219, and t₀ = −0.980 for males. The analysis of the stomach contents showed fish to be the major source of nutrition across all areas and sampling periods. In January, the secondary prey of burbots in the Huma reach of the upper Amur River was aquatic insect larvae, while, in the Tongjiang and Fuyuan reaches of the middle Amur River, the secondary prey was shrimp. The mean stomach fullness index and rate of empty stomachs differed with the sampling area, with the greatest proportion of empty stomachs observed in the Luobei reach of the middle Amur River, and the lowest in the Tongjiang and Fuyuan reaches. The mean stomach fullness index showed the opposite trend. In the Huma reach, the contributions of fish to the diet and the mean stomach fullness index were significantly higher in May than in October and January. The study provides the first detailed information on the population age and sex structure, growth patterns, and feeding ecology of burbots from the Amur River, China. The results will aid in formulating management strategies and regulations for local populations of burbots in the Amur River, China. Full article

The Acorus calamus group, or sweet flag, includes important medicinal plants and is classified into three species: A. americanus (diploid), A. verus (tetraploid), and A. calamus (sterile triploid of hybrid origin). Members of the group are famous as components of traditional Indian medicine, and early researchers suggested the origin of the sweet flag in tropical Asia. Subsequent research led to an idea of the origin of the triploid A. calamus in the Amur River basin in temperate Asia, because this was the only region where both diploids and tetraploids were known to co-occur and be capable of sexual reproduction. Contrary to this hypothesis, triploids are currently very rare in the Amur basin. Here, we provide the first evidence that all three species occur in Kazakhstan. The new records extend earlier data on the range of A. verus for c. 1800 km. Along the valley of the Irtysh River in Kazakhstan and the adjacent Omsk Oblast of Russia, A. verus is recorded in the south, A. americanus in the north, and A. calamus is common in between. We propose the Irtysh River valley as another candidate for a cradle of the triploid species A. calamus. It is possible that the range of at least one parent species (A. americanus) has contracted through competition with its triploid derivative species, for which the Irtysh River floods provide a tool for downstream range expansion. We refine our earlier data and show that the two parent species have non-overlapping ranges of variation in a quantitative metric of leaf aerenchyma structure. Full article

Comprehensively understanding the spatial ecology and habitat preferences of endangered species is essential for population restoration and conservation. We investigated the home range and movement of the endangered Amur soft-shell turtle (Pelodiscus maackii) in the Ussuri River, Heilongjiang Province, Northeastern China. The study involved tracking 19 Amur soft-shell turtles from late June to mid-October, 2022, resulting in complete and partial home range size data for eight subadults and two adults, respectively. The primary analysis focused on eight subadults, and the models that best described daily movement were identified. We also explored the potential factors influencing home range size. The mean movement rate ranged from 39.18 ± 20.04 m/day to 72.45 ± 29.36 m/day and was positively correlated with the linear home range and water temperature. The most enlightening estimation of home range was derived from a 95% kernel density estimate, utilizing likelihood cross-validation smoothing while adhering to constraints delineated by the river boundaries. The average size of the home range was determined to be 1.02 hectares and displayed no correlation with body size. Subadults tended to establish well-defined home ranges over time, whereas defining home ranges for adults proved challenging. This research addresses a gap regarding the ecology of the Amur soft-shell turtle and provides a foundation for future conservation plans. Full article

Since the early 1950s, the development of human settlements and over-exploitation of agriculture in the China side of the Amur River Basin (CARB) have had a major impact on the water environment of the surrounding lakes, resulting in a decrease of aquatic vegetation. According to the United Nations Sustainable Development Goals, a comprehensive understanding of the extent and variability of aquatic vegetation is crucial for preserving the structure and functionality of stable aquatic ecosystems. Currently, there is a deficiency in the CARB long-sequence dataset of aquatic vegetation distribution in China. This shortage hampers effective support for actual management. Therefore, the development of a fast, robust, and automatic method for accurate extraction of aquatic vegetation becomes crucial for large-scale applications. Our objective is to gather information on the spatial and temporal distribution as well as changes in aquatic vegetation within the CARB. Utilizing a hybrid approach that combines the maximum spectral index composite and Otsu algorithm, along with the integration of convolutional neural networks (CNN) and random forest, we applied this methodology to obtain an annual dataset of aquatic vegetation spanning from 1985 to 2020 using Landsat series imagery. The accuracy of this method was validated through both field investigations and Google Images. Upon assessing the confusion matrix spanning from 1985 to 2020, the producer accuracy for aquatic vegetation classification consistently exceeded 87%. Further quantitative analysis unveiled a discernible decreasing trend in both the water and vegetation areas of lakes larger than 20 km² within the CARB over the past 36 years. Specifically, the total water area decreased from 3575 km² to 3412 km², while the vegetation area decreased from 745 km² to 687 km². These changes may be attributed to a combination of climate change and human activities. These quantitative data hold significant practical implications for establishing a scientific restoration path for lake aquatic vegetation. They are particularly valuable for constructing the historical background and reference indices of aquatic vegetation. Full article

Located in the Heilongjiang (Amur) River in north-east Asia, spanning four countries, plays a crucial role as an international border river, and its meteorological changes significantly impact the variation in water resources in the basin. This study utilizes daily average temperature and precipitation data from 282 meteorological stations in the Heilongjiang (Amur) River Basin and its surrounding areas for the period 1980–2022. The analysis employs spatial interpolation, change point testing, and model construction prediction methods. The results indicate a significant increasing trend in both overall temperature and precipitation changes within the Heilongjiang (Amur) River Basin. At the spatial scale, the annual warming rate increases gradually from the southeastern coastal region to the northwestern plateau region, while the rate of precipitation increase decreases from the southern area towards its surroundings. Temporally, the warming amplitude during the growing season decreases gradually from east to west, and the trend in precipitation changes during the growing season aligns with the overall annual precipitation trend. During the non-growing season, the warming trend shows a decrease in the plains and an increase in the plateau, while precipitation increase concentrates in the central and southern plains, and precipitation decrease predominantly occurs in the northwestern plateau region. Temperature and precipitation change points occurred in the years 2001 and 2012, respectively. In precipitation prediction, the Long Short-Term Memory (LSTM) model exhibits higher accuracy, with R (Pearson correlation coefficient) and NSE (Nash-Sutcliffe efficiency coefficient) values approaching 1 and lower NRSME values. This study provides a research foundation for the rational development and utilization of water resources in the Heilongjiang (Amur) River Basin and offers valuable insights for research on climate change characteristics in large transboundary river systems. Full article

The interconnected forest regions along the lower Tumen River, at the Sino-North Korean border, provide critical habitats and corridors for the critically endangered Amur Leopard (Panthera pardus orientalis). In this region, there are two promising corridors for leopard movement between China and North Korea: the Jingxin–Dapanling (JD) and Mijiang (MJ) corridors. Past studies have confirmed the functionality of the JD corridor, but leopards’ utilization of the MJ corridor has not yet been established or confirmed. In this study, we assessed the functionality of the MJ corridor. The study area was monitored using camera traps between May 2019 and July 2021. We also analyzed 33 environmental and vegetation factors affecting leopard survival and analyzed leopard movement. In the Mijiang area, the Amur leopard was mainly active in the region adjacent to the Northeast China Tiger and Leopard National Park and did not venture into area near the North Korean border. The complex forest structure allowed leopards to move into the Mijiang area. However, the high intensity of human disturbance and manufactured physical barriers restricted further southward movement. Therefore, human-induced disturbances such as grazing, mining, farming, logging, and infrastructure development must be halted and reversed to make the Mijiang region a functional corridor for the Amur leopard to reach the North Korean forest. This necessitates inter-governmental and international cooperation and is essential for the long-term survival of the Amur leopard. Full article