Hanjiang River Research Articles

A novel structural equation modelling-based framework for identifying hydrometeorological multi-factor interaction

Study regionThe Hanjiang River Basin, China. Study focusIn this study, we proposed a new integrated framework based on structural equation models to identify hydrometeorological multi-factor interaction relationship. The spatiotemporal distribution and interaction relationship of hydrological, meteorological, and vegetation indicators in the Hanjiang River Basin were analyzed based on the national long-series monitoring data. New hydrological insights for the regionThe findings reveal that: (1) The rainfall is the maximum in the lower reaches (968.87 mm), and the runoff depth fluctuated the most in the lower reaches (1181.70 mm to 2934.88 mm). (2) Dew point temperature is an important influencing factor of rainfall in the upper and middle reaches, and relative humidity is an important influencing factor of rainfall in the lower reaches. High vegetation cover is an important influencing factor for runoff depth. (3) Rainfall and runoff depth are significantly negatively affected by meteorological characteristics, with effect values ranging from −0.24 to −0.68. However, runoff depth is positively affected by rainfall, relative humidity, vegetation characteristics, and canopy interception, with effect values ranging from 0.02 to 0.58. The size and mode of influence have significant regional differences.

Quantifying the Effect of Land Use and Land Cover Changes on Spatial-Temporal Dynamics of Water in Hanjiang River Basin

As a vital part of the geo-environment and water cycle, ecosystem health and human development are dependent on water resources. Water supply and demand are influenced significantly by land use and cover change (LUCC) which shapes the surface ecosystems by altering their structure and function. Under future climate change scenarios, LUCC may greatly impact regional water balance, yet the impact is still not well understood. Therefore, examining the spatial relationship between LUCC and water yield services is crucial for optimizing land resources and informing sustainable development policies. In this study, we focused on the Hanjiang River Basin and used the patch-generating land use simulation (PLUS) model, coupled with the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model, to assess water yield services under three Shared Socioeconomic Pathway and Representative Concentration Pathway (SSP-RCP) scenarios. For the first time, we considered the impact of future changes in socio-economic and water use indicators on water demand using correction factors and ARIMA projections. The relationship between water supply and demand was explored using this approach, and LUCC’s effects on this balance are also discussed. Results indicate that: (1) The patterns of LUCC are similar for the three scenarios from 2030 to 2050, with varying levels of decrease for cropland and significant growth of built-up areas, with increases of 6.77% to 19.65% (SSP119), 7.66% to 22.65% (SSP245), and 15.88% to 46.69% (SSP585), respectively, in the three scenarios relative to 2020; (2) The future supply and demand trends for the three scenarios of produced water services are similar, and the overall supply and demand risks are all on a downward trend. Water demand continues to decline, and by 2050, the water demand of the 3 scenarios will decrease by 96.275×108t, 81.210×108t, and 84.13×108t relative to 2020, respectively; while supply decreases from 2030 to 2040 and rises from 2040 to 2050; (3) Both water supply and demand distributions exhibit spatial correlation, and the distribution of hotspots is similar. The water supply and demand are well-matched, with an overall supply-demand ratio greater than 1.5; (4) LUCC can either increase or decrease water yield. Built-up land provides more water supply compared to other land types, while forest land has the lowest average water supply. Limiting land use type conversions can enhance the water supply.

Hydrological response to future changes in climate and land use/land cover in the Hanjiang River Basin

Hydrological response to future changes in climate and land use/land cover in the Hanjiang River Basin

Chemical Characteristics and Water Quality Assessment of Groundwater in the Dongjiang-Hanjiang River Basin, China

Groundwater plays an important role in the rapid economic development of the Dongjiang-Hanjiang River Basin. This paper uses the Gibbs model, ionic ratio coefficient analysis, factor analysis, water quality index method and human health risk assessment model to estimate the chemical properties and quality of groundwater in the Dongjiang-Hanjiang Basin. The ion concentration and proportion of SO42- water in the Hanjiang River Basin are higher than those in the Dongjiang River Basin. The groundwater ions come mainly from the dissolution of carbonate rocks, silicate rocks and saline rocks, some of which come from human activities such as industry and mining. Groundwater composition is controlled by rock dissolution, alternating cation adsorption, and human activities. The proportion of rock dissolution is the greatest, but the influence of human activities is obvious. The intensity of human activities such as industry, mining and agriculture is greater in the Hanjiang River Basin than in the Dongjiang River Basin. The overall groundwater quality is poor, and the Dongjiang River Basin is better than the Hanjiang River Basin. The above-standard factors are mainly pH, I−, NO3−, NH4+, As and Pb2+. Nitrate pollution in groundwater is harmful to health and the health risk of children from nitrate is higher than that of adults. The health risk in the Hanjiang River Basin is higher than that in the Dongjiang River Basin. This can serve as a vital reference for similar areas worldwide, offering guidance for groundwater management, pollution prevention and control.

Exploring Spatio-Temporal Dynamics of Future Extreme Precipitation, Runoff, and Flood Risk in the Hanjiang River Basin, China

The hydrological cycle is altered by climate change and human activities, amplifying extreme precipitation and heightening the flood risk regionally and globally. It is imperative to explore the future possible alterations in flood risk at the regional scale. Focusing on the Hanjiang river basin (HRB), this study develops a framework for establishing a scientific assessment of spatio-temporal dynamics of future flood risks under multiple future scenarios. In this framework, a GCMs statistical downscaling method based on machine learning is used to project future precipitation, the PLUS model is used to project future land use, the digitwining watershed model (DWM) is used to project future runoff, and the entropy weight method is used to calculate risk. Six extreme precipitation indices are calculated to project the spatio-temporal patterns of future precipitation extremes in the HRB. The results of this study show that the intensity (Rx1day, Rx5day, PRCPTOT, SDII), frequency (R20m), and duration (CWD) of future precipitation extremes will be consistently increasing over the HRB during the 21st century. The high values of extreme precipitation indices in the HRB are primarily located in the southeast and southwest. The future annual average runoff in the upper HRB during the near-term (2023–2042) and mid-term (2043–2062) is projected to decrease in comparison to the baseline period (1995–2014), with the exception of that during the mid-term under the SSP5-8.5 scenario. The high flood risk center in the future will be distributed in the southwestern region of the upper HRB. The proportions of areas with high and medium–high flood risk in the upper HRB will increase significantly. Under the SSP5-8.5 scenario, the area percentage with high flood risk during the future mid-term will reach 24.02%. The findings of this study will facilitate local governments in formulating effective strategic plans for future flood control management.

Territorial Spatial Evolution and Driving Mechanisms in Economically Developed Watershed Areas: A Case Study of Hanjiang River Basin in China

Territorial Spatial Evolution and Driving Mechanisms in Economically Developed Watershed Areas: A Case Study of Hanjiang River Basin in China

Understanding future water-carbon-land coupled systems in the era of COP 27: The case of the Hanjiang river Basin, China

The 27th Conference of the Parties (COP 27) emphasized addressing this century's interconnected challenges of food, water, and energy. This study proposes a coupled ecosystem service and multi-scenario land-use change simulation model designed to investigate the future dynamics of water-carbon-land coupled systems in the Hanjiang River Basin (HJRB), the primary objective is to provide valuable insights that can inform strategic spatial management decisions, aligning with the ambitious objectives outlined in COP 27. Specifically, this study utilized the PLUS model, InVEST model, and redundancy analysis to comprehensively analyze the interplay between ecosystem services and land-use changes, with a specific focus on water, carbon, and land dynamics. The results showed that regardless of the simulated scenarios, there was a consistent pattern observed in the changes of land use types within the HJRB, with a decrease in farmland and an increase in forest. However, the water area showed an increasing trend in all scenarios, especially in the ecological land protection (ELP) and sustainable development scenarios. Furthermore, the ELP scenario effectively suppressed the expansion of building land and the erosion of ecological land. Ecosystem services under different scenarios showed similar spatial distribution patterns but presented varying degrees of change related to the impact of future land use and urban development on ecosystem services. The water yield (WY), carbon storage, and soil conservation in the upstream areas increased to varying degrees, while those in the downstream areas decreased. In conclusion, precipitation, land use/land cover change, DEM (Digital Elevation Model), and NDVI (Normalized Difference Vegetation Index) were the main driving factors affecting ecosystem services, with precipitation having the most significant and enduring impact on WY. This study supports the adoption of targeted spatial management measures to promote sustainable development and enhance human well-being.

A Multivariate Model and Correlation Study on the Impact of Typical Residential Spatial Forms in the Middle Reaches of the Hanjiang River on the Thermal Environment and Thermal Comfort

Different spatial forms affect the indoor thermal environment and human thermal comfort. A good living environment largely depends on the flexibility of spatial forms, and spatial scale and proportion are the key factors affecting these forms. We selected typical residential houses in the middle reaches of the Hanjiang River in the hot summer and cold winter climate area as an example. Through on-site measurements and questionnaire surveys, we studied the impact of residential form indicators on the thermal environment and thermal comfort. We also established a multivariate model to explore the correlation among various parameters. The results showed that the spatial-real ratio of the residential spatial form index in the middle reaches of Hanjiang River was 5–58%. The height from the ground was 2.23–6.92 m. The open-space ratio was 0.04–4.55. The explanatory power of the spatial form index to indoor air temperature was 57.5%, with a strong correlation (R2 = 0.675). The explanatory power for humidity was 38.2%, with a weak correlation (R2 = 0.525). The explanatory power of SET was 30.6–50.1%, with a weak correlation (R2 = 0.466). The explanatory power of PMV was 6.5–31.7%, and PMV1.0 was weakly correlated (R2 = 0.474). The explanatory power for PPD was 15.5%, where PPD 1.0 was close to a weak correlation (R2 = 0.508). The results of this study provide reference values for the design methods of and decision-making process for green and energy-saving regional buildings.

Water Ecological Security Pattern Based on Hydrological Regulation Service: A Case Study of the Upper Hanjiang River

Water ecological problems involve flood, drought, water pollution, destruction of water habitat and the tense relationship between humans and water. Water ecological problems are the main problems in the development of countries all over the world. In terms of ecological protection, China has put forward the ecological red line policy. Water ecology is an important component of the ecosystem, and the delineation of the water ecological red line is an important basis for ecological protection. Based on ecosystem services, this paper tries to determine the red line of the water ecology space and tries to solve various water problems comprehensively. Based on the ecosystem services accounting method, the SWAT (soil and water assessment tool) model was used to simulate the spatial–temporal dynamic quantities of water purification and rainwater infiltration services in the upper reaches of the Hanjiang River. The basin was divided into 106 sub-basins and 1790 HRUs (hydrological response units). Water quality data taken from 8 sites were used to verify the simulation results, and the verification results have high reliability. The grid scale spatialization of water quality and rainwater infiltration is realized based on HRU. The seasonal characteristics of hydrological regulation and control services were analyzed, the red line of hydrological regulation and control in the upper reaches of the Hanjiang River was defined, and the dynamic characteristics of water ecological red line were analyzed. According to the research results, the water ecological protection strategy of the basin is proposed. The prevention and control of water pollution should be emphasized in spring and summer, the prevention and control of rain flood infiltration in autumn and winter, and the normal monitoring and management should be adopted in the regulation and storage. The results of this study can provide scientific reference for water resources management and conservation policy making.

A Numerical Simulation-Based Adaptation of the Pedestrian-Level Wind Environment in Village Streets: A Case Study on the Chuan Dao Area of the Hanjiang River in Southern Shaanxi

Village streets are indispensable spaces for people to perform outdoor activities, and they also directly affect the outdoor wind environment in villages. At present, people are paying more attention to the wind environment comfort of urban residential areas and urban commercial streets, but there is a lack of attention and research on the wind environment comfort of village and town streets. By summarizing the field research and meteorological data of Lefeng Village, we propose the outdoor wind environment evaluation requirements applicable to the Hanjiang River’s Chuan Dao area in the winter and summer seasons. We found that more than 80% of the outdoor wind environment in the summer is less than 1 m/s. Based on the numerical simulation method of computational fluid dynamics, and on the basis of the characteristics of the streets and lanes in the Hanjiang River’s Chuan Dao area, we found that the wind environment is poor in the winter and summer seasons; regarding streets and lanes, we propose three appropriate values, namely building density, building height, and street width. It is suggested that it is appropriate for the building density of the area to be less than 36%, the height of the building to be less than 15 m, and the width of the street to be 6–11 m when the street is open to traffic and 3–6 m when only pedestrians are passing through the area.

Two-dimensional distribution of arsenic species in the riparian zone regulated by As-Fe co-transformation under varying river water proportions and bicarbonate concentrations

Arsenic (As) contamination of groundwater is a major issue in global environmental health. In the riparian zone, mixing river water and groundwater with different substances is proposed to affect arsenic transformation and distribution. However, the distribution of arsenic species in the riparian zone and its co-transformation with iron under varying river water proportions and bicarbonate (HCO3–) concentrations remain unclear. The two-dimensional distributions of arsenic species, including exchangeable (Ex-As), carbonates-bounded (Carb-As), FeMn(hydr)oxide-bounded (Ox-As), organic-bounded (Om-As) and residual arsenic (Res-As), were investigated in three typical profiles of the riparian zone near the lower reaches of the Hanjiang River, China. The apparent enrichment of arsenic in the pore water, either As(III) and As(V), and in the sediment, mainly Carb-As and Ox-As, were observed in the profiles. The correlation analysis showed that the distributions of arsenic species in the riparian zone were primarily related to dissolved or total organic matter (DOC or TOC), Fe, HCO3–, dissolved oxygen (DO) and oxidation–reduction potential (Eh). Further batch experiments mixing simulated river water and groundwater with different proportions and HCO3– concentrations demonstrated that the forming of the arsenic-rich area in the riparian sediment was derived from the oxidation of Fe(II) and As(III) from groundwater, controlled by the varying DO from river water and HCO3– from organics degradation. These results provide more knowledge of the transforming process of arsenic in the riparian zone and a better understanding of the role of the riparian zone in arsenic restraint.

Hydro-morphology and water quality jointly shape the structure and network stability of the plankton community in multi-tributary river basins

Revealing the spatial variation in phytoplankton and zooplankton communities, along with their responses to water flow, climate, and water quality from headwaters to downstream, is crucial for grasping their evolutionary dynamics and crafting ecological preservation strategies. Here, the spatial distribution, assembly processes, and stability changes of phytoplankton and zooplankton in the tributaries from headwaters to downstream reaches of the Danjiang River and the upper Hanjiang River (China) were analyzed using environmental DNA (eDNA) technology. Geographic factors accounted for over 60% of the variation in the distribution of phytoplankton and zooplankton, although environmental factors also played a significant role. From upstream to downstream, the proportion of phytoplankton Bacillariophyta decreased from 37.12% to 33.07% in March and from 27.68% to 25.36% in August. Euglenophyta decreased from 1.04% to 0.53% in March and 10.48% to 2.16% in August. The proportion of zooplankton Ciliophora increased from 67.17% to 85.04%, while Amoebozoa decreased by approximately 9.83% in August. Phytoplankton and zooplankton richness initially increased, then declined from upstream to downstream. The assembly of zooplankton and phytoplankton communities was mainly driven by deterministic processes, with values ranging from 0.2 to 0.5. Furthermore, the upstream community showed a stronger dominance of deterministic processes, while the mainstream community exhibited weaker determinism than the tributaries. In both March and August, zooplankton were more influenced by deterministic processes than phytoplankton. From upstream to downstream, the stability and complexity of phytoplankton and zooplankton networks decreased, significantly influenced by river width, flow velocity, agricultural land proportion, and nutrient concentration. Maintaining diverse phytoplankton was crucial for sustaining zooplankton diversity and ensuring network stability. Furthermore, the growth duration of phytoplankton and zooplankton was influenced by the spatial distribution of sampling points in the river, contributing to complex interactions with environmental factors. The complexity of these interactions necessitates careful consideration in future studies on spatial patterns in riverine plankton communities.

Effects of the Water Diversion Project from the Three Gorges Reservoir to the Hanjiang River on diatom blooms in Middle and Lower reaches of the Hanjiang River

ABSTRACT The algal blooms in the Middle and Lower reaches of the Hanjiang River (MLHR) have become a great aquatic eco-environmental problem over recent years. The planned implementation of the Water Diversion Project from the Three Gorges Reservoir to the Hanjiang River (WDP-TH) would influence the growth and propagation of diatoms and the development of algal blooms. In this paper, a dynamic model of diatom growth is developed that considers factors such as light exposure, water temperature, total phosphorus, and flow velocity. The effects of the WDP-TH on algal density and blooms in the MLHR were predicted for a typical median year, a typical dry year, and an extremely dry year. The results showed that following the water recharge in a typical median year, the propagation of diatoms in the MLHR was significantly promoted because of an increase in total phosphorus concentration. However, following the water recharge in typical dry and extremely dry years, increased flow rate and improved hydrodynamic conditions significantly inhibited diatom growth and accelerated the transport process. The results of the hypothetical simulation showed that after the initiation of the WDP-TH, inhibition effects of improved hydrodynamic force on algae were more apparent than promotion effects of increased total phosphorus concentration in the MLHR.

Assessment of dynamic hydrological drought risk from a non‐stationary perspective

AbstractThe stationarity hypothesis of hydrometeorological elements has been questioned in the context of global warming and intense human disturbance. The conventional drought index and methods of frequency analysis may no longer be applicable for hydrological drought risk evaluation under a changing environment. In this study, a new dynamic hydrological drought risk evaluation framework is proposed for application to the Hanjiang River basin (HRB), which simultaneously considers the non‐stationarity in the construction of drought index as well as in the frequency analysis. First, a non‐stationary standardized runoff index (NSRI) is developed using a generalized additive model for location, scale and shape (GAMLSS) framework. Then, hydrological drought characteristics including duration and severity are identified, and their marginal distributions are established. Finally, based on the dynamic copula, considering the non‐stationarity of the dependence structure, the dynamic joint probability distribution, conditional probability distribution and return period of the bivariate hydrological drought properties are analysed. Results showed that NSRI, which integrates the impacts of climate change and anthropogenic activities on the non‐stationarity of runoff series, had a better ability to capture runoff extremes than had SRI. In addition, it is indispensable to consider the non‐stationarity of the dependence structure between variables when discussing the multivariate joint risk of hydrological drought. The risk of hydrological drought in the study area has shown an increasing trend in the past 65 years, and the drought conditions from upstream to downstream have been alleviated first and then intensified. This study provides valuable information for regional drought risk estimation and water resources management from a non‐stationary perspective.

Predicted Climate Change will Increase Landslide Risk in Hanjiang River Basin, China

Predicted Climate Change will Increase Landslide Risk in Hanjiang River Basin, China

Environmental implication identification on water quality variation and human health risk assessment in the middle and lower reaches of the Hanjiang River, China

As the longest tributary of the Yangtze River, the Hanjiang River has been a “lifeline” for the “Yangtze River Economic Belt of China”. The water quality of the middle and lower reaches of the Hanjiang River (MLHR) has received considerable attention due to environmental degradation, increasing population, and water diversion project operations during the past decade. In this study, 16 water quality parameters from 14 national water quality monitoring stations along the MLHR were collected monthly from January 2021 to December 2022. Water quality index (WQI) methods coupling multivariate statistical techniques, e.g., seasonal Mann-Kendall test (SKT) and Mantel’s test, were applied to analyze and evaluate the spatiotemporal variations of water quality under different environmental and hydrological conditions. The Hazard Quotients (HQs) were used to assess the non-carcinogenic and carcinogenic risk for adults and children via ingestion and dermal pathways. The results showed that the overall water quality in the MLHR was classified as “excellent”, with the average WQI higher than “91”, and each single water quality indicator met Class I or Class II surface water quality standards of China. Ammonia (NH3-N), Total phosphorus (TP), Permanganate (CODMn), pH, and Arsenic (As) were significantly correlated with water level variations. CODMn and TP were decisive in explaining the WQI variations of the MLHR. NH3-N, water temperature, pH, and dissolved oxygen were key parameters for explaining WQI variations in most regions of the MLHR. As, Cadmium (Cd), and Chromium (Cr) presented potential health risks in the MLHR and should warrant close monitoring due to their significant health implications. Due to the continuous construction and operation of cascade hydro-projects, the synchronous monitoring of water quality and hydrological data of the MLHR should be conducted in the future. This study provides a scientific reference for managing water quality in the MLHR and similar natural riverine water bodies.

Evaluation of daily precipitation modeling performance from different CMIP6 datasets: A case study in the Hanjiang River basin

To effectively compare and analyze daily precipitation modeling capabilities across different CMIP6 datasets, our study introduces a novel method to compare daily precipitation models across CMIP6 datasets in the Hanjiang River Basin (HRB). We quantify indicators such as precipitation distribution, temporal correlation, wet-dry detection, extreme value error, and spatio-temporal variability, enabling a comprehensive rating of precipitation accuracy. It has been found that while both CMIP6(CP6) and NEX-GDDP-CMIP6 (GCP6) models show similar simulation accuracy, GCP6 excels in several aspects like distribution, temporal correlation, extreme value simulation, and spatial variability, yet lags in wet-dry detection and temporal change. Notably, using the comprehensive rating score (CRS) analysis, significant differences in precipitation simulation accuracy exist between models, particularly CP6, with variations of up to 0.22 (51.2%) between the highest and lowest scores. Among the top ten models, GCP6 occupies four positions such as MRI-ESM2-0, GFDL-CM4, MPI-ESM1-2-HR, and TaiESM1, while CP6 holds the remaining six like CanESM5, EC-Earth3-Veg, MPI-ESM1-2-HR, GFDL-CM4, MRI-ESM2-0, and IPSL-CM6A-LR. These findings not only offer a clear understanding of the simulation performance of CMIP6 datasets across various precipitation characteristics, but also quantitatively compare the modeling capabilities of different models for watershed precipitation through CRS. This aids climate adaptation research, hydrological forecasting, and flood management in the basin.

Role of Pacific Ocean climate in regulating runoff in the source areas of water transfer projects on the Pacific Rim

Over the past two decades, more frequent and intense climate events have seriously threatened the operation of water transfer projects in the Pacific Rim region. However, the role of climatic change in driving runoff variations in the water source areas of these projects is unclear. We used tree-ring data to reconstruct changes in the runoff of the Hanjiang River since 1580 CE representing an important water source area for China’s south-north water transfer project. Comparisons with hydroclimatic reconstructions for the southwestern United States and central Chile indicated that the Pacific Rim region has experienced multiple coinciding droughts related to ENSO activity. Climate simulations indicate an increased likelihood of drought occurrence in the Pacific Rim region in the coming decades. The combination of warming-induced drought stresses with dynamic El Niño (warming ENSO) patterns is a thread to urban agglomerations and agricultural regions that rely on water transfer projects along the Pacific Rim.

Comprehensive evaluation of extreme hydrometeorological events coincidence and their interrelationships in the Hanjiang River Basin, China

Extreme hydrometeorological events are often highly destructive and can cause huge damage to the natural environment and social economy. As climate change and human activities intensify, the frequency and intensity of such extreme events continue to increase. This phenomenon is also shown in the Hanjiang River Basin (HRB) in recent decades. In this study, we focus on the coincidence occurrence patterns of extreme hydrometeorological events. First, we used the standardized index method to extract the annual maximum and minimum values of runoff, precipitation, maximum and minimum temperatures from 1961 to 2019 in the control area of the Baihe (BH) hydrological station, with time scales from 1 month to 12 months. Then through the Copula and nested structure Copula functions, the joint occurrence probability of bivariate and multivariate were analyzed. The results show that too high a maximum temperature will inhibit runoff, while an increase in minimum temperature will promote an increase in runoff to a certain extent. Both the maximum and minimum temperatures in the basin shown a significant increasing trend, and the intensity of hydrological drought also shows an increasing trend. An increase in maximum temperature will aggravate hydrological drought, as the combined joint occurrence probability of them is the greatest. Analysis through the nested structure Copula functions show that when extreme hydrometeorological events both occurred at the median of their intervals, their coincidence occurrence probability is the maximum, and when the time scale is eight months, their coincidence occurrence probability is the highest. This study can provide a reference for joint probability analysis of extreme hydrometeorological events.

A data mining-then-predict method for proactive maritime traffic management by machine learning

Proactive traffic management is increasingly critical in maritime intelligent transportation systems. Central to this is maritime traffic forecasting, which leverages specific structures and properties of the problem. This study focuses on the traffic dynamics within convergent areas of inland waterways and proposes a method based on data mining followed by prediction using Automatic Identification System (AIS) data. This approach addresses uncertainties in ship voyage destinations and optimizes predictions for temporary stops in inland waterways. AIS data is processed to depict complete ship motion trajectories, grouping them into trajectory sets based on shared origin, destination, and route. These groups help represent maritime traffic patterns using the entrance and exit points of channels and the boundaries of the study area. Additionally, a stop detection model is applied to these trajectories to identify nodes within maritime traffic networks. A decision tree algorithm is then employed to train a classifier for predicting traffic patterns. The method was validated in the convergent area of the Yangtze River and the Hanjiang River, demonstrating effective pattern extraction from inland maritime traffic and high accuracy in predicting single ship trajectories, achieving a 96.7% accuracy rate and 80.9% precision. The findings suggest that the proposed method (1) effectively extracts and predicts traffic patterns, (2) identifies congestion in convergent waters, and (3) supports traffic management strategies.