As a strategic emerging industry, digital industry is an important driving force to promote the high-quality development of the Yangtze River Economic Belt (YREB) and construct a new advantage in regional competition. Exploring the evolution of the spatio-temporal pattern and driving factors of digital industry in the YREB is of great practical significance for optimizing the layout of digital industry. Based on the data of more than 300 000 digital enterprises from 2000 to 2020, this study used the descriptive statistics, standard deviational ellipse and multi-scale geographically weighted regression modelling methods to conduct a research. The results showed that: (1) The number of digital enterprises increased significantly during. The spatial distribution of the digital industry showed that “the core of the downstream cities was prominent, and the middle and upper reaches of the cities were gradually expanding”. （2）In terms of sub-industry, the digital product production industry showed a trend of “prominent downstream agglomeration core, and gradual expansion of the middle and upper reaches with the provincial capital city as the core”. The digital product service industry showed the characteristics of “close connection between the middle and lower reaches of the city, and continuous agglomeration in the lower reaches”. The digital factor support and technology emerging industry showed a trend of “the provincial capital city being the core, and a multi-core piecewise distribution”.（3）The spatial distribution of digital industries was generally affected by a variety of factors such as location, market, technology and institutions. The role of each driver was spatially heterogeneous. In addition, there existed differences in the impact of different types of digital industry drivers, i.e. digital production enterprises focused more on location factors and were path-dependent. The digital product service industries relied mainly on consumers and markets and were more path-creative. The digital support and technology emerging industries were found to be both path-dependent and path-creative in the location selection.

Leveraging the first-mover advantage of the green finance pilots in the Yangtze River Economic Belt is of positive significance for promoting green innovation and high-quality development. Based on the panel data of 108 cities from 2006 to 2022, this study found that green finance had a significant and continuous role in promoting the quality of green innovation in the Yangtze River Economic Belt. The role was more prominent in the upstream basin, non-innovative pilot cities, low-carbon pilot cities and digital economic development pilot areas. Optimizing capital allocation, leveraging environmental subsidies and diversifying innovation risks were the potential mechanisms of affecting the quality of green innovation. Further analysis showed that financial technology, government environmental attention and intellectual property protection played a positive regulatory role. Moreover, under the conditions of moderate environmental regulation and higher education investment, green finance played a greater role in improving the quality of green innovation. These findings were helpful to further understand the unique value and function process of green finance. This study provided objective evidence and policy basis for promoting the quality of green innovation in the Yangtze River Economic Belt.

Based on the panel data of cities in urban agglomeration in the middle reaches of the Yangtze River from 2010 to 2022, this study explored the characteristics of spatio-temporal distribution and influencing factors of green technology innovation. The methods of Kernel density estimation, Dagum’s Gini coefficient, spatial autocorrelation analysis, social network analysis and spatial Durbin model were used in this study. The results showed that: (1) The levels of green technology innovation in urban agglomeration in the middle reaches of the Yangtze River and the three regions showed a decreasing growth rate. There was heterogeneity in their levels of change in absolute differences and polarization characteristics. (2) The overall differences maintained at a high level, with hypervariable density and inter-regional differences being the main sources. (3) The spatial distribution was uneven, and most cities were concentrated in low-value or lower-value regions, and the core-edge characteristic was obvious. The type of spatial agglomeration was primarily characterized by low-low agglomeration, with a relatively stable trend of agglomeration. (4) The scale of cooperation network had developed significantly, and the accessibility and connectivity had increased significantly. A leading rise was indicated in the core cities of Wuhan and Changsha, and a rise in Nanchang and Zhuzhou cities, which formed a situation of “multi-core leading + multi-point support”. (5) The level of economic development, environmental regulation, innovation support and financial level promoted green technology innovation in local cities, while the dependence on foreign investment and the degree of opening up to the outside world showed an inhibiting effect. The industrial structure based on the tertiary industry promoted the neighboring cities, while the degree of opening up to the outside world had an inhibiting effect.

Carbon emissions in China is of significant attention. Improvement of carbon emission efficiency in cities is crucial to balancing economic growth and environmental protection. This study employed the super-efficiency SBM model to assess the energy carbon emission efficiency of the Chengdu-Chongqing urban agglomeration from 2005 to 2022. The spatial and temporal evolution characteristics were also analyzed. A number of 16 cities in the study area were categorized based on the constructed influencing indicator system of energy carbon emission efficiency. A spatial panel model was used to investigate the drivers of energy carbon emission efficiency in different types of cities. The results showed that, from 2005 to 2022, the total carbon emissions of the study area increased at an average annual growth rate of 3.92%. The annual energy carbon emission efficiency showed a trend of decreasing and then fluctuating upward. The efficiency of Mianyang, Yibin, and Nanchong was not coordinated with the level of economic development. The efficiency of the Chengdu-Chongqing urban agglomeration exhibited a differentiated distribution pattern with high core and low periphery, and there was a multipolar phenomenon manifested by the fact that Chengdu and Chongqing were the high-value regions and the surrounding cities were the low-value regions. Economic development, industrial structure, energy intensity, and population distribution were identified as the factors affecting the improvement of carbon emission efficiency. However, the impact of investment scale, spatial layout, and urban planning on energy carbon emission efficiency differed according to the city type and the development stage. This study provided technical support for urban carbon emission reduction and policy recommendations for low-carbon development in the Chengdu-Chongqing urban agglomeration and other urban agglomerations.

Taking red culture as the guide to realize the high-quality development of cultural and tourism integration is an important channel for the old revolutionary base areas to actively cultivate and develop new productive forces. This is also of great significance to the revitalization and development of the old revolutionary base areas in the new era. Taking 108 administrative units at county level in the Central Soviet Area of Jiangxi, Fujian and Guangdong as the research units, this study analyzed the spatial and temporal development pattern and future evolution trend of high-quality development of red cultural tourism from 2018 to 2022. The mathematical models such as kernel density, Markov matrix, NICH index and Hurst index were used. The obstacle degree model was further adopted to identify the shortcomings of integration development. The research showed that :①The high-quality development of the integration of red culture and tourism in the study area was stable and. The trend of club convergence and integration was significant, with significant internal circulation dependence and self-adaptability; ②The fusion level presented a semi-enclosed structure of ' core-periphery ' and an increasing trend of ' northwest-southeast ' in space. Based on the core growth point, an extended and radiant growth mechanism was formed, which had strong spatial stability and continuity. ③During the study period, the comprehensive sound quantity heat of the network and the total factor productivity of economic development were the most important shortcomings that restricted the development of high-quality integration, followed by supporting supply, passenger source abundance and environmental regulation, and the short-board factors.

Spartina alterniflora is the most harmful invasive plant in coastal wetlands in China. It is of great significance to use remote sensing technology to clarify its spatial distribution and monitor its clearance dynamics for coastal Spartina alterniflora control and wetland resource protection. This study proposed a dynamic monitoring framework for Spartina alterniflora that integrated multi-source time-series remote sensing data to address the issues of severe cloud interference, vegetation spectral confusion, and feature redundancy in coastal wetland vegetation classification. Based on Sentinel-1, Sentinel-2, and Landsat8 data from Yancheng,Jiangsu Province,covering the period from 2022-2023, the optimal time window for extracting Spartina alterniflora was determined through NDVI temporal phenology analysis. Combined with Random Forest, a highly discriminative feature set was selected from multiple sources of features (spectrum, texture, radar, terrain). Finally, a U-Net deep learning model was used to achieve high-precision extraction and dynamic monitoring of Spartina alterniflora. The results showed that the mid growth season (June to August) was the optimal time window for extracting Spartina alterniflora. Using images from this period to extract the wetland in Yancheng in 2022, the overall classification accuracy was 94.34%, with a Kappa coefficient of 0.873 4. The total invasive area of Spartina alterniflora was 119.08 km2, mainly distributed in Dafeng, Dongtai, Sheyang. During the process of Spartina alterniflora management in 2023, a total area of 80.49 km2 was cleared. Among them, Dafeng had the widest cleared area, with a total of 46.46 km2. This research provided a feasible plan for long-term and large-scale monitoring of the spread of Spartina alterniflora in coastal wetlands, and provided important reference for large-scale invasive plant control and wetland protection.

Research on the spatiotemporal evolution and coupling effects of soil and water resource carrying capacities is crucial for regional sustainable development. Taking the YiShuSi river basin as the object, this study used the DPSIR framework to construct an evaluation index system of water and soil resources carrying capacity. The Super-SBM-DEA, coupling coordination, and geodetector model were employed to explore the spatiotemporal evolution characteristics and the major influencing factors of water and soil resources carrying capacity, coordinated utilization efficiency, and coupling coordination from 2013 to 2022. This study aimed to provide data support for the sustainable development of the region. This study showed that: (1) The change of water and soil resources carrying capacity was mainly affected by the response layer (0.271 4) and the driving force layer (0.268 6). The pressure layer (0.083 4) had the least influence. (2) The water and soil resources coordinated utilization efficiency in the eight prefecture-level cities was in a good state, with an average efficiency value of greater than 1. However, unfavorable weather conditions had an impact on Xuzhou, Zaozhuang, Jining, and Rizhao, leading to lower efficiency ratings in some of the years. (3) The water and soil resources coupling coordination was rising, while the disparities across prefecture-level cities were progressively narrowing. With a general spatial distribution that was "high in the east and low in the west, high in the north and low in the south," Linyi had the strongest coupling coordination among them. The north-south direction had a "U"-shaped curve change between 2014 and 2018. (4) The main factors affecting the coupling coordination were per capita GDP (48.58%), residential water consumption (94.96%), and per capita grain output (86.54%). The interaction between each factor had a greater influence on the evolution of the coupling coordination than a single factor. Based on the above outcomes, policy recommendations were put forth to optimize the allocation of these resources, encourage industrial restructuring, improve ecological environment restoration, and strengthen regional coordination and cooperation.

The cross-basin water diversion of the Middle Route of the South-to-North Water Diversion Project (SNWDP) is an extremely complex system that involves multiple stakeholders. It is difficult to balance the conflicts in water quantity and water quality among the water source area, the middle and lower reaches area, and the water receiving area involved in the Project. In order to ensure the sustainable exertion of the project’s benefits and the long-term development of the economy and society, a tripartite evolutionary game model was established in this study. Under the constraint and incentive mechanism of the central government, the evolutionary equilibrium strategies of the water source area, the middle and lower reaches area, and the water receiving area were analyzed. The opportunity cost of losses in the water source area, the water resource value of the middle and lower reaches area, and the ecological compensation amounts from the water receiving area to the water source area were calculated, based on the opportunity cost method, the water resource value model, and the cost-sharing model. The sensitivities of cost and fine parameters were analyzed. The results showed that: (1) If a stable strategic equilibrium of the water source area was to be achieved, the fine imposed by the central government on the water source area should be greater than 18.147 billion yuan. If the unit water resource value of the middle and lower reaches area was greater than the unit cost of purchasing water rights, the evolutionary stable strategy could be achieved. The horizontal ecological compensations from the water-receiving area to the water source area and the middle and lower reaches area were 6.091 billion yuan and 1.08 billion yuan, respectively. If a stable strategic equilibrium of the water receiving area was to be achieved, the fine imposed by the central government on the water receiving area should be greater than 7.171 billion yuan. (2) The punishment measures of the central government had a positive incentive effect on the water source area and the water receiving area, and the water receiving area was more sensitive to fines than the water source area. The game system became more difficult to reach an equilibrium state for the higher relevant cost parameters of the water source area and the middle and lower reaches area.

The coordinated development of ecotourism and resource and environmental carrying capacity is of significant importance for implementing the national ecological civilization construction and achieving local sustainable development. The study of the symbiotic relationship between the two can provide a scientific basis for promoting a high-quality ecotourism. In this article, the entropy weight method was used to determine the weights of indicators. An evaluation system was constructed for the coupling and coordination of eco-tourism and resource and environmental carrying capacity. A total of 24 counties in Hunan Province from 2014 to 2022 were calculated. The spatiotemporal evolution characteristics of the coupling and coordination were analyzed. The results indicated that: (1) The quality level and the coupling coordination in the Dongting Lake area within Hunan Province exhibited an upward trend, yet significant disparities existed for different counties. (2) The level of coupling coordination presented a spatial distribution pattern of "high in the center and low on the periphery", and the level of ecological tourism development positively correlated with the carrying capacity of resource and environment. (3) According to the results, the 24 counties could be classified into three development types: coordinated and balanced type, well-running type, and uncoordinated and lagging type. Optimizing the development path of ecological tourism and facilitating the complementary advantages and resource sharing among counties would be conducive to the high-quality development of the entire rural area and to promote rural revitalization in the Dongting Lake area.

This paper aimed to explore the characteristics of land use change under multiple scenarios in the Danjiangkou Reservoir Area, and to grasp the resulting ecological and environmental effects. This study was expected to provide a scientific basis for the optimization of territorial space and ecological environmental construction in the reservoir area. Based on land use data from 2000, 2010, and 2020, the PLUS model was used to predict the spatial pattern of land use in 2030 under scenarios of natural development, farmland protection, and ecological conservation. Additionally, methods such as the ecological environment quality index and ecological contribution rate were employed to analyze the ecological and environmental effects of land use changes in different periods. The results showed that: (1) From 2000 to 2020, forest land was the dominant land use type, with a notable shift from farmland to forest land. The forest land area demonstrated the largest increase of 762.07 km2, accounting for 3.82% of the total area. (2) Under scenarios of natural development and ecological conservation in 2030, the farmland area would decrease while the forest land area would increase. In contrast, under the farmland protection scenario, the farmland area would increase, and the expansion of forest land was somewhat restricted. (3) From 2000 to 2030, the ecological environment quality index was as high as 0.61. The spatial distribution pattern of ecological environment quality remained basically stable. (4) From 2000 to 2030, the conversion of farmland to forest land played a dominant role in improving the ecological environment, accounting for more than 74% of the total contribution rate. Conversely, the conversion of forest land to farmland was the leading factor causing ecological environment degradation, which explained 53% of the total contribution rate. The overall ecological environment quality in the Danjiangkou Reservoir Area was high. The changes were mainly influenced by the conversion among farmland, grassland, and forest land. In the future, various land use indicators should be considered comprehensively in conjunction with the development goals of the reservoir area to achieve high-quality development.

The lower Jinsha River region holds significant ecological importance and is home to the world’s largest hydropower base. Understanding the spatiotemporal dynamics of vegetation coverage in this area can provide valuable insights for ecological conservation and sustainable development in the basin. This study analyzed vegetation coverage changes and associated influencing factors across different stages of hydropower development (2000–2022), using MODIS NDVI (Normalized Difference Vegetation Index) data. We employed methods of Theil-Sen Median trend analysis, BEAST (Bayesian Estimator of Abrupt change, Seasonality, and Trend), and the Geographical Detector model. The results revealed that: (i) Over the past 23 years, vegetation NDVI around the lower Jinsha River region exhibited a fluctuating increase. NDVI increased from 0.460 to 0.515 in the Xiluodu-Xiangjiaba segment (Xi-Xiang section) and from 0.432 to 0.476 in the Wudongde-Baihetan segment (Wu-Bai section). Following the completion of the hydropower station, vegetation improvement predominated, with the areas of significant and slight improvement accounting for 85.25% and 66.93% of the study region, respectively. (ii) Trend components of NDVI in the Xi-Xiang and Wu-Bai sections experienced five abrupt changes, and the decline consistently coincided with reservoir impoundment periods. Nonlinear NDVI change pattern, such as monotonic increases, interrupted increases, and shifts from decline to increase, were observed. (iii) Elevation, temperature, slope, and precipitation were the key drivers of NDVI changes in the Xi-Xiang section, while elevation, evapotranspiration, temperature, and precipitation significantly influenced the Wu-Bai section. Socioeconomic factors, including land use, night-time light, and population, showed an increased influence after reservoir construction. Significant interactions between elevation, climatic, and socioeconomic factors were observed, which exhibited dual-factor enhancement and nonlinear effects.

Controlling ozone pollution is a crucial component of the pollution prevention initiatives outlined in China's 14th Five-Year Plan. This study utilized monitoring data (2015 to 2022) of near-surface nighttime O3during the warm seasons, and explored the spatial-temporal variations of the O3 concentrations across the Yangtze River Economic Belt (YREB), with a particular focus on the areas of the Yangtze River Delta, the middle reaches of the Yangtze River, and the Chengdu-Chongqing urban agglomerations. Furthermore, the exposure-response model was applied to evaluate the health risks associated with nighttime O3 exposure from 2015 to 2021. The results showed that: (1) The concentration of nighttime O3 during the warm seasons in the YREB exhibited a fluctuating upward trend, with an annual increasing rate of 0.81 μg簚(m3簚a)-1. Notably, the Yangtze River Delta urban agglomeration experienced the most significant annual increase in nighttime O3 concentration, at a rate of 17.6%. In contrast, the Chengdu-Chongqing and middle reaches of the Yangtze River urban agglomerations demonstrated more modest growth rates, with an increase of 8.3% and 7.8%, respectively. (2) The spatial distribution of nighttime O3 concentration in the YREB revealed a distinct pattern, with elevated levels observed in the northeast and reduced levels in the southwest. Additionally, the number of cities experiencing high nighttime O3 concentrations increased from 33 in 2015 to 44 in 2022. (3) The number of premature deaths that was attributed to nighttime O3 exposure peaked in 2018, and the number subsequently declined, and then experienced a rebound in 2021. By 2021, the mortality rate due to nighttime O3 exposure had decreased by 5% compared to that in 2015. Among the three urban agglomerations, the Yangtze River Delta exhibited the highest number of premature deaths from nighttime O3 exposure, followed by the Yangtze River Midstream city cluster, of which the Chengdu-Chongqing city cluster demonstrated the fewest. Deaths attributed to nighttime O3 exposure in the three urban agglomerations showed a downward trend. This study provided important references for future ozone pollution prevention and control, which was related to policy formulation and public health protection in the Yangtze River Economic Zone.

The study of the spatial-temporal distribution and driving factors of atmospheric PM2.5 in Jiangsu Province is of great significance for formulating effective prevention and control policies. Using various statistical methods, geographical detector, and a multi-scale geographically weighted regression (MGWR) model, this research explored the spatiotemporal distribution characteristics of PM2.5 in Jiangsu Province and its influencing factors. The results indicated that: (1) The annual average PM2.5 concentration ranged from 33.93 to 70.65 μg·m-3, showing an upward trend in 2000, a decline after 2013, and an overall downward trend. Seasonally, PM2.5 concentrations were highest in winter, followed by spring and autumn, and lowest in summer. The multi-year average spatial distribution of PM2.5 showed higher concentrations in the northwest and lower concentrations in the southeast. (2) Factor detection results indicated that humidity and wind speed were the primary driving factors influencing the spatial differentiation of PM2.5. Furthermore, the explanatory power of all driving factors was greater than that of any single factor, suggesting that spatial differentiation of PM2.5 was the result of a combination of multiple driving factors. (3) The scale and intensity of the effects of each driving factor on PM2.5 showed significant differences. Sunshine duration had the smallest effect scale and the greatest spatial heterogeneity. Elevation and annual average relative humidity had the largest effect scales, showing a relatively consistent influence on PM2.5 concentration across the study area. PM2.5 concentration was positively correlated with elevation and annual average temperature, and generally negatively correlated with annual average relative humidity, wind speed, precipitation, and sunshine duration.

The upper reaches of the Han River basin serve as a crucial water source for the middle route of the South-to-North Water Diversion Project. Understanding the hydrochemical characteristics and major ion sources of the surface water is of great significance for ensuring the water supply safety. This study quantitatively analyzed the hydrochemical composition characteristics and the main control factors of surface water in the Shaanxi section of the Han River basin. A total of 46 sets of surface water hydrochemical data were collected. The methods used included mathematical statistics, ion ratio analysis, graphical methods, and the Absolute Principal Component Scores-Multiple Linear Regression (APCS-MLR) receptor model. The results showed that the dominant cations in the surface water were Ca2+, with HCO3- and SO42-as the dominant anions. The pH values ranged from 7.53 to 8.81, with an average of 8.18. The TDS values ranged from 107 to 451 mg/L, with an average value of 187 mg/L. In terms of spatial distribution, the average mass concentrations of TDS and pH in tributaries were higher than those in the mainstream. The average mass concentrations of major ions and TDS values in the three prefecture-level cities followed the order: Shangluo City > Hanzhong City > Ankang City. The main hydrochemical type of surface water in the study area was HCO3-Ca. The hydrochemical components of surface water were mainly influenced by rock weathering and human activities, with weak cation exchange. Rock weathering was dominated by the dissolution of carbonate and silicate rocks. The impact of human activities on the hydrochemical evolution was mainly reflected in changes in ion components such as SO42-, Cl-, NO3-, and Na+, which were primarily influenced by mining activities and agriculture activities. The APCS-MLR receptor model revealed that the main sources of surface water hydrochemical components were silicate rock dissolution and mining activities, evaporative salt rock dissolution and domestic sewage, carbonate rock dissolution and agricultural activities, and other sources, which contributed 33.75%, 13.67%, 30.87%, and 21.71%, respectively to the surface water of the study area.

As a critical wetland ecosystem in the Yangtze River Basin, the Dongting Lake region has undergone substantial ecological reorganization under land use transitions. This study quantified the spatiotemporal coupling relationships between ecosystem service value (ESV) and landscape ecological risk (LER) in response to land use/cover change (LUCC) during 1996-2020 through multi-temporal remote sensing analysis. The results revealed that the cropland consistently expanded, while grassland and unused land decreased. Water bodies experienced a fluctuating decline, whereas forested areas and built-up land increased.ESV initially declined before rebounding, ultimately resulting in a net reduction of 21.247 billion RMB (8.33%), while LER showed a slight but consistent downward trend, with an average decline from 0.7814 to 0.7332. Water bodies were identified as both high-value ESV providers and high-risk LER areas, with stable ESV hotspots in lake water bodies and cold spots primarily in surrounding forested and grassland areas. Meanwhile, LER hotspots showed a shrinking trend within water bodies, with an increasing spatial aggregation, whereas cold spots remained in forested and grassland areas. The coupling coordination degree between ESV and LER followed a “decline–increase” pattern, with water bodies exhibiting a higher coupling degree than other land use types, indicating a state of “moderately coordinated development.” Spatially, the coordination degree was higher in central areas and lower in peripheral regions, reflecting “relatively imbalanced” and “barely balanced” development outside water bodies, while areas with high coupling coordination showed an expanding trend. These results elucidated complex LUCC-ESV-LER interdependencies in watershed ecosystems, and provided critical insights for optimizing ecological security frameworks and enhancing value realization mechanisms in major river basins.

Investigating the spatiotemporal relationship between carbon emissions and ecosystem service values (ESV) from a land use change perspective is crucial for deepening our understanding of human-land system interactions, formulating effective environmental protection policies, and fostering green economic development. This study focused on Sichuan Province's land use changes from 2000 to 2022. The energy consumption data were integrated through grid analysis, combined with spatial autocorrelation models. The objective was to dissect the spatiotemporal patterns of carbon emissions and ESV as well as their interplay mechanisms. The results demonstrated that: (1)Over the past two decades, there had been an expansion in forested areas and built-up zones at the expense of arable lands, grasslands, and unused terrains, while water bodies remained relatively unchanged.(2)Net carbon emissions due to land use had shown a steady increase over time, escalating from 198.44 million tons in 2000 to 398.11 million tons by 2022. High emission intensity clusters were predominantly found within urban centers of the Sichuan Basin and Panxi city cluster,whereas low emission regions were mostly situated in mountainous western parts and periurban areas, experiencing a general decrease in size. (3)ESV witnessed a slow yet continuous rise from 1.707 trillion yuan in 2000 to 1.728 trillion yuan in 2022, with the largest contributions from forests and grasslands. Significant spatial disparities existed in ESV distributions. (4)A clear negative correlation existed between carbon emission intensity and ESV intensity, which indicated that heightened carbon emissions corresponded with reduced ecological service capabilities. The above outcomes elucidated the intricate dynamics between economic growth and environmental health in Sichuan, and offered scientific foundations for crafting sustainable strategies to balance land planning and conservation efforts.

Understanding the characteristics of rainy seasons in the Jinsha River was significant for the development of regional water resources, as well as for the prevention and mitigation of flood and drought disasters. Based on daily precipitation data from 1961 to 2023 in the middle-to-lower reaches of the Jinsha River, the onset date, termination date, length, and total precipitation of the rainy seasons were defined, using the established criteria. The spatiotemporal characteristics, changing trends, and atmospheric circulation features during transitional periods were also analyzed. The results showed that, the onset of the rainy seasons had progressed from the northeast towards the west, while the end of the rainy seasons was relatively uniform across the region. The duration of the rainy seasons was longer in the eastern part, compared to the western. The total rainfall during the rainy seasons was higher in the central area than on either side. The onset of the rainy seasons was associated with the northward shift of the South Asian High, coupled with enhanced warm and moist vapor transport from the Bay of Bengal with cold air activity from the west. Conversely, when the wind direction over the Bay of Bengal shifted from southwest to easterly, weakened the warm and moist vapor transport, and westerly winds strengthened over the basin, the rainy seasons came to an end. Climatologically, the rainy seasons lasted for 152 days from May 25th to October 23rd. The average total amount of precipitation during the rainy seasons was 785.2 mm. There were no significant long-term trends in the characteristics of the rainy seasons, however, inter-decadal fluctuations were evident. After the 21st century, there was a delay in the onset date of the rainy seasons. It was also found that the length of the rainy seasons was shortened, and the total precipitation was reduced.