Ecological welfare performance serves as a novel indicator for gauging regional green development, and is pivotal for scrutinizing the spatial distribution and variability characteristics of urban ecological welfare performance to facilitate zoning planning and management of urban ecological resources. Drawing upon input-output theory and incorporating undesired outputs of environmental pollution, we assessed the ecological welfare performance of cities within the Yangtze River Economic Belt utilizing the super-efficient SBM model. Subsequently, we analyzed its spatial distribution characteristics and conducted modeling analysis on the spatial variability. Our findings revealed that : (1)The ecological welfare performance of cities within the Yangtze River Economic Belt witnessed a significant increase of 33.3% since the inception of the development plan in 2016. (2)There existed a pronounced spatial clustering trend in ecological welfare performance among the cities, and is particularly notable in the marked enhancement in overall performance observed in the Yangtze River Delta region. (3)The spatial correlation range of urban ecological welfare performance gradually diminished over time, while the degree of variability remained relatively stable. Hence, it is imperative to reinforce ecological environmental governance to sustain the upward trajectory of performance. Drawing from the aforementioned conclusions, we propose countermeasures that focus on ecological environmental governance, ecological resource allocation and mechanism construction, and inter-city cooperation.

In the face of the challenges of rapid urbanization, the innovation-oriented urban construction plays a crucial role in the promotion of sustainable development, and the improvement of residents' quality of life. This article constructed an index system to measure the progress of innovative urban construction in Hubei Province and used the method of Mean Observation OLS (MO-OLS) regression to study the temporal and spatial effects of environmental factors on innovative urban construction from 1990 to 2019. This study aimed to overcome the shortcomings of traditional statistical methods that adopted fixed coefficients. The study found that, the entrepreneurial environment and venture capital showed a synergistic growth trend in promoting the innovative urban construction in Hubei Province. The impact coefficient of the entrepreneurial environment fluctuated less and had a relatively stable pushing effect. In contrast, the impact coefficient of venture capital was distributed in a wider range, with larger fluctuations. The impact coefficient of foreign investment showed a decreasing trend, while the impact coefficient of environmental regulation and its quadratic term remained relatively stable. Environmental governance contributed the least to the major innovative urban construction in Hubei Province. Specifically, the effects of the entrepreneurial environment, environmental governance, and venture capital in Wuhan City were leading other cities, while the contributions of foreign investment and venture capital to innovative construction varied significantly among different cities in Hubei Province. The use of the Mean Observation OLS method and the application of the environmental factors in the process of innovative urban construction in Hubei Province broadened the analytical paradigm of regional innovation research technically, and also provided a new perspective for understanding the spatiotemporal heterogeneity and complexity of innovation impact theoretically.

With the continuous acceleration of urbanization in China, urban agglomerations, as a new form of spatial agglomeration for urban development, have gradually become a new driving force for promoting high-quality urban development. Therefore, scientific evaluation of the resilience level of urban agglomerations can provide references for the decision-making process. By comprehensively applying the super-efficient SBM model, spatial vector model and barrel theory, this study established an analytical model for the resilience level of urban agglomerations. Subsequently, the Dagum's Gini coefficient, Kernel's density estimation and Markov's chain method were used to analyze the regional differences and spatial and temporal evolution trends of the resilience level of urban agglomeration. Finally, five major urban agglomerations in China were selected as research cases for empirical study. The results showed that the resistance and resilience capacity of provincial capitals and municipalities directly under the central government presented a two-level differentiation trend, while the adaptation and comprehensive resilience construction were relatively good; The resilience level of the five major urban agglomerations showed a clear overall spatial pattern of high in the east and low in the west, with coastal areas higher than inland areas. Among them, the average resilience of the Beijing-Tianjin-Hebei urban agglomerations was the lowest, and the weak board effect within the agglomeration was the most obvious; Except for the Beijing-Tianjin urban agglomeration, the differences in Gini coefficients within other urban agglomerations had decreased, with the most significant differences in resilience levels between the Beijing-Tianjin-Hebei and Chengdu-Chongqing urban agglomerations; The overall resilience level of the five major urban agglomerations showed a decreasing trend in dispersion, but there was still a significant Matthew effect. By considering spatial factors, there existed a significant spatial spillover effect in the Beijing-Tianjin-Hebei urban agglomeration.

Territory is the basis of all economic and social activity. Exploring the spatial-temporal characteristics and influencing factors of eco-efficiency is of great significance to the sustainable utilization of territory resources, as well as to economic and social development. Based on the Three-Zone Space perspective and multi-source data, the Territory Use Eco-Efficiency (TUEE) measurement system was constructed. The Undesirable Super-SBM model, spatial autocorrelation analysis and multi-scale geographically weighted regression (MGWR) were used in this study to analyze TUEE levels, spatial-temporal differences, and the driving factors in 53 counties in Jiangsu Province from 2000 to 2020. The results showed that: (1) the TUEE level of Jiangsu Province generally showed a gradual upward trend during the surveyed period. The urban space and ecological space eco-efficiency were steadily improved, while the agricultural space eco-efficiency decreased at first but then increased; (2) Jiangsu Province was in the procedure of changing from a scattered distribution of counties with high TUEE levels, to a pattern of high-TUEE counties in the south and low-TUEE levels in the north. The TUEE in coastal counties had certain advantages over inland counties. During the study period, there was a significant spatial positive correlation, and the correlation was increasing. High-high agglomeration was distributed in southern Jiangsu counties, and the low-low agglomeration was distributed in northern counties. (3) There was spatial heterogeneity in the influencing factors of TUEE levels in the province. Temperature and level of openness to the outside world had a significant promoting effect, while elevation had a significant inhibitory effect. Population density and level of economic development also had a promoting effect, but it was not statistically significant. Based on these findings, in order to enhance the overall TUEE of Jiangsu Province, it is necessary to strengthen inter-county connections, carry out territory utilization activities according to local conditions, optimize industrial structures and government investment structures.

Efficient utilization of urban industrial land resources and reduced carbon emissions under the "dual-carbon" target have become the focus of research on urban-rural spatial development. Taking industrial land in 13 cities in Jiangsu Province as the research object, this study used the Super-SBM model to measure the efficiency of urban industrial land use under carbon emission constraints. The trend of carbon emissions and the spatiotemporal evolution characteristics were explored. Furthermore, spatial econometric models were employed to explore the influencing factors of changes in industrial land use efficiency. This study revealed that: (1) From 2011 to 2021, the carbon emissions of industrial enterprises above designated size in Jiangsu Province remained stable overall, while the scale of industrial land expanded and the intensity of carbon emissions per unit area showed a downward trend; (2) The overall trend of urban industrial land use efficiency in Jiangsu Province showed a fluctuating growth. The trend declined from 2011 to 2015, and then rapidly increased from 2016 to 2021. The spatial pattern of industrial land use efficiency evolved dramatically, with significant enhancement in spatial agglomeration in regions of medium-high efficiency and high efficiency, among which the Nanjing metropolitan area and the Suzhou-Wuxi-Changzhou metropolitan area became high-efficiency urban conurbations; (3) The level of urbanization demonstrated a significant positive spatial spillover effect on adjacent cities. The increase in the proportion of industry in the industrial structure of Jiangsu Province had a significant negative impact on the industrial land use efficiency, but a significant positive spatial spillover effect on adjacent areas. Industrial property structure had a significant positive impact on the efficiency of urban industrial land use, while land structure and industrial development level had significant negative impacts on the efficiency of urban industrial land use under carbon emission constraints.

This study analyzed the spatial and temporal evolution of vegetation cover in the middle and lower reaches of the Yangtze River Basin from 2000 to 2021. The data used included Normalised Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Gross Primary Productivity (GPP) and Global Orbiting Carbon Observatory-2 Solar-Induced Chlorophyll Fluorescence (GOSIF) products inverted from Solar Induced Chlorophyll Fluorescence (SIF). The response of vegetation cover under drought conditions was further analysed by combining with the Standardized Precipitation Evapotranspiration Index (SPEI). The main conclusions were as follows: (1) Temporally, the average annual NDVI, EVI, GOSIF and GPP in the study area showed an overall significant increasing trend, with the increasing rates of 0.002 9 a-1, 0.002 4 a-1, 0.001 8 W·m-2·μm-1·sr-1·a-1 and 8.327 4 gC·m-2 ·a-1 (P<0.05); The monthly NDVI, EVI, GOSIF and GPP showed obvious intra-annual variations, with their maximum values occurring in July or August each year. (2) Spatially, NDVI, EVI, GOSIF and GPP in the study area showed a similar spatial distribution pattern, with the high-value areas mainly distributed in the southwestern part of Hunan Province, the western part of Hubei Province and Jiangxi Province, and the low value areas mainly distributed in the eastern part of the basin, such as Shanghai, Jiangsu, and Zhejiang. The percentage of areas with significantly decreasing trends were only 3.00%, 3.25%, 2.19% and 1.00% (P<0.05). (3) As the severity of drought increases (from mild to severe drought), the average decrease in the change rates of NDVI, EVI, GOSIF, and GPP from April to September showed an increasing trend. NDVI, EVI, GOSIF and GPP decreased from -2.45%, -3.87%, -4.77% and 0.58% in mild drought to -7.26%, -8.57%, -12.59% and -7.87% in the severe drought, respectively. The average values of GOSIF rate of change from April to September under different drought levels demonstrated a greater decrease than those of NDVI, EVI and GPP, indicating that the response of GOSIF to drought events was more sensitive.

From the perspective of the main functional area, this paper took the counties in the Jianghan Plain as the research area, for the period 2000-2020. Based on carbon emission (absorption) calculation, the SOM-K-means clustering model and geographic detector were used to analyze and explore the spatiotemporal differentiation of carbon balance, carbon compensation zoning, and the associated influencing factors. The results indicated that: (1) The carbon balance was becoming increasingly imbalanced, with carbon emissions (absorption) showing a spatially uneven development trend. (2) The low-carbon development zone and carbon sink function zone in the carbon balance partition were mainly the agricultural production areas, while the high-carbon optimization zone was focused on developed areas, which aligned with the characteristics of agricultural regions. (3) Different influencing factors had a varying explanatory power for net carbon emissions and exhibited temporal and spatial differences, with agriculture production and urbanization being the main influencing factors. The characteristics of the agricultural region in the Jianghan Plain was significant, which was ideal for this case study to enrich our understanding of regional carbon balances, to summarize and extract geographical features of carbon balances, and to support the realization of "dual-carbon" goals. 

Multifunctionality of land use is not only an important means to alleviate the conflict between human activities and land, but also a crucial factor in achieving sustainable development. This study focused on the Han River Basin as the research area and aimed to define the interaction mechanism between land use functional networks and urban-rural integration. By employing comprehensive methods such as land use multifunctional evaluation, social network analysis, and spatial metrology modeling, a multifunctional land use network was constructed under the context of urban-rural integration. The evolution characteristics and driving mechanisms of this network were further explored. The findings indicated that: (1) with an increasing rural-urban integration, there existed an increase in node centrality, network density, and network reciprocity of both production function networks and living function networks in rural-urban areas. The spatial distribution followed a pattern of downstream > midstream > upstream. However, for ecological function networks, although node centrality decreased slightly with an increased integration level, there was little change in network density or reciprocity, showing a distribution patter of upstream > midstream > downstream. (2) Among the driving factors affecting production function networks, both rural-urban integration degree and its spatial lag term significantly inhibited node centrality, but positively promoted network density and reciprocity. （3）The analysis of living function network showed that the degree of urban-rural integration had a positive effect on the living function node centrality, network density and network reciprocity. （4）For ecological function networks, rural-urban integration did not have significant effects on node centrality, but had a significant positive impact on both network density and reciprocity. The results of this study are of great practical significance for realizing urban-rural integration and promoting regional sustainable development.

Accurate identification of conflicts between land uses is of great significance to optimize the spatial layout of land and promote regional development. Taking Poyang Lake Ecological Economic Zone as the research object, this paper adopted the ecological risk model and land use suitability evaluation model to construct the measurement systems of land use structural conflict and functional conflict. This paper overlaid the structural conflict with the functional conflict to identify the type of land use conflict, based on grid cells. The corresponding control countermeasures were put forward. The results showed as follows. 1) Structural conflicts were divided into four categories including heavy, moderate, general and light conflict areas. The moderate conflicts were found to be the largest, with a total of 1 324 grid cells. The area was mainly distributed in the high urbanization level where human activities were obvious. 2) The suitability scores for agricultural, ecological and construction land use ranged from 35.08 to 86.30, 47.80 to 92.80 and 22.51 to 93.46, respectively. The suitability of agricultural land showed a larger distribution in the south and a smaller distribution in the east and west. The suitability of ecological land showed a larger distribution in the east and west and a smaller distribution in the center. The suitability of construction land showed a larger distribution in the center and south and a smaller distribution in the west. The area of functional conflict occupied a total of 1 885 cells, which was dominated by strong conflict zones in the southern and central regions with a flat terrain. 3) By synthesizing the results of structural and functional conflicts, the land use conflicts in Poyang Lake Ecological Economic Zone were divided into four categories, namely, weak conflict controllable area, single structural out-of-control area, single functional out-of-control area and structural-functional double out-of-control area. With regard to the types of land use conflicts in the study area, control measures of optimizing the spatial layout of the land, controlling the increment of construction land, and establishing the transition zone of the protected area were proposed in order to provide scientific guidance for the socio-economic development and spatial planning of Poyang Lake Ecological Economic Zone.

The coupling and coordination between urbanization and ecological environment are of great significance for achieving high-quality development in the Yangtze River Economic Belt (YREB).Based on nighttime light data and vegetation index, this study employed the coupling coordination degree model and geographic detector method to analyze the spatiotemporal changes and influencing factors of the coupling coordination between urbanization and ecological environment in the YREB from 2000 to 2019. This research showed: (1) The coupling coordination degree between urbanization and ecological environment in the YREB exhibited an increasing trend, showing a transition from a state of high disarray to a state of moderate coordination. Spatially, the coupling coordination exhibited a spatial distribution of east-high-west-low, with the provinces and cities in the downstream of the Yangtze River having higher levels compared to those in the middle and upstream areas. Additionally, the coupling coordination generally radiated outward from the provincial capital centers, with a gradual transition from stripes to clusters. (2) The primary driving factors of the coupling coordination in the YREB were the degree of openness, education investment, and economic development level. The key driving factors for the coupling coordination in the middle and upper reaches of the Yangtze River were the economic development level and industrial structure, while education investment, degree of openness, and innovation investment were the primary driving factors in the downstream provinces and cities of the Yangtze River. (3) The interaction among various influencing factors promoted the coupled coordination development of urbanization and ecological environment in the YREB and its provinces and cities. The coupling coordination between urbanization and ecological environment in the YREB was mainly influenced by the interactive synergy between industrial structure and innovation investment. Additionally, spatial disparities existed in the interaction of influencing factors across different regions. Overall, the coupling coordination of urbanization and ecological environment in the YREB should adopt differentiated regulatory strategies based on the interaction of different factors.

In order to explore the pollution level and potential ecological risk of surface sediments of heavy metals in Zhanghe Reservoir, Hubei Province, 20 sediment samples were collected from the surface sediments of Zhanghe Reservoir and its outlet. The content and distribution characteristics of eight heavy metals, including As, Hg, Cr, Ni, Cd, Cu, Pb, and Zn, were analyzed. The potential ecological risk index method and the geo-cumulative index method were used to analyze and evaluate the pollution of surface sediments in Zhanghe Reservoir. The results showed that the average enrichment coefficient of surface sediments of heavy metals in Zhanghe Reservoir was Cd(3.37) > Pb(1.29) > Ni(1.21) > Zn(1.11) > As(0.99) > Cu(0.98) > Cr(0.95) > Hg(0.88). The elements that exceeded the background value were Cd, Pb, Ni, and Zn. The accumulation of Cd content exceeded the standard value seriously. The high value area was located along the line from Guanyinsi Dam to Mahe Town and from Jigongjian Dam to Zhanghe Town. The potential ecological risk index of surface sediments of heavy metals in Zhanghe Reservoir was 91.85-233.88, and 45% of the sampling points were classified as slight and 55% as medium. The results of the geo-cumulative index evaluation showed that the main cause of sediment pollution in Zhanghe Reservoir was excessive Cd. The average geo-cumulative index of Cd was 1.09, and 11 sampling points were classified as mild and medium pollution, and 9 sampling points were classified as mild pollution. It was concluded that the main cause of Cd pollution in sediments of the northern reservoir area of Zhanghe Reservoir was coal mining and combustion, while the Cd pollution in sediments of the southern reservoir area was more closely related to the combustion of petroleum products.

Implementing ecological restoration is an important initiative to improve the vulnerability of natural ecosystems. This study aimed to reveal the characteristics of natural ecosystem vulnerability and the sustainability of future changes in the southwest karst region of China. Based on the habitat-structure-function quantitative framework, a system of indicators reflecting the vulnerability of natural ecosystems was selected to assess the vulnerability of natural ecosystems in China's southwestern karst region from 2001 to 2022. The results showed that: (1) In general, the natural ecosystem vulnerability index (nEVI) of China's southwestern karst region was high in the central and northern parts and low in the southern and eastern parts, with a decreasing trend in the inter-annual average nEVI (R2=0.17, P<0.05); (2) In terms of different geomorphological zones, the multi-year average nEVI of karst middle and high mountainous areas was the largest (0.73) and the decreasing trend was the least significant; (3) In terms of different vegetation types, the multi-year average nEVI of alpine vegetation was the largest (0.79) and the decreasing trend was the least significant; (4) The principal component analysis indicated that the habitat indicators of NDRI and SM, the structural indicators of LAI and SHDI, and the functional indicator of GPP were the dominant factors for the vulnerability change; (5) The Hurst index and the trend analysis of Sen indicated that a total of 46.36% of the nEVI showed a weak persistent decrease. There existed a certain risk of ecological imbalance. In the future, attention should be paid to the protection of natural forests in karst middle and high mountainous areas and the sustainable management of plantation forests in other areas. The adaptive management of ecosystems should also be encouraged.

In order to assist in implementing polices of carbon emission reduction and sink enhancement, the predictions of carbon emission peak and carbon neutrality at the provincial scale is essential. Taking the provincial administrative regions of China as the study cases, this paper calculated the carbon budget from 2005 to 2019. The STIRPAT model was utilized to investigate the variables affecting carbon emissions. Carbon emissions from 2020 to 2060 was forecasted. The results in terms of the peak time and value of carbon emission and the degree of carbon neutrality were compared for different scenarios including the Inertial Development Scenario, Planning Control Scenario, Peaking Constraint Scenario, and Green Development Scenario. The conclusions were as follows: (1) Carbon emission at the provincial scale in China showed a spatial pattern of high in the north and low in the south, high in the east and low in the west, with a fluctuating upward trend over time. Carbon sequestration was relatively stable and growing slowly, with a spatial pattern of high in the west and low in the east. (2) Population, urbanization rate, and per capita GDP were the main factors affecting carbon emissions, followed by industrial structure and energy intensity, while with energy structure and carbon intensity did not play a significant role. (3) The Green Development Scenario was the optimal scenario, under which all provinces could reach the carbon emission peak from 2020 to 2023 and achieve carbon neutrality at the national level in 2060. It was suggested that in the future, differentiated carbon emission reduction policies should be formulated in the light of the economic development level and the actual situation of different provinces. The tailored pathways to achieve carbon emission peak and carbon neutrality should be explored to promote the realization of the targets of “carbon emission peak and carbon neutrality” based on regionally coordinated emission reduction and equitable development.

The control measures of pollution need to be upgraded from the end treatment to the source treatment, based on the adjustment of industrial structure and energy structure. The energy-consuming right trading system is an important policy tool for pollution source control. Therefore, the energy-consuming right trading system can deeply integrate air pollution prevention and with greenhouse gas emission control measures. This study constructed a system dynamics model for evaluating the synergistic effect of pollution reduction and carbon reduction in China's industrial energy use right trading system. The impact of changes in policy factors on industrial pollution reduction and carbon reduction was examined, and the design of the system was optimized. The results showed: (1)The energy trading system could reduce the emission of industrial carbon dioxide and industrial pollutants on the basis of energy saving and consumption reduction. Among them, the change range of industrial wastewater emission reduction rate was the largest, from 21.07 % of the benchmark scenario to 23.88 % of the classic scenario;(2)The strict energy trading system had a more significant synergistic effect on pollution reduction and carbon reduction. Specific policy tools included those of increasing the price of energy trading, increasing the proportion of quotas reserved for energy use rights, and reducing the proportion of free quotas for energy use rights;(3)The energy trading system could reduce the emission of environmental pollutants such as industrial carbon dioxide and industrial solid waste by increasing the energy cost of enterprises and increasing the investment in industrial science and technology innovation.(4) The energy trading system would have a negative impact on the development of the industrial economy，among which the increase of the price of energy-consuming right trading demonstrated the greatest negative impact. When the transaction price of energy rights was reduced from 100 yuan / ton of standard coal under the classic scenario to 50 yuan / ton of standard coal, the actual industrial added value increased by about 1.07 %, and when the transaction price was increased to 300 yuan / ton of standard coal, the actual industrial growth value reduced by about 5.01 %. In order to maximize the synergistic effect of using the energy trading system to reduce pollution and reduce carbon, it is recommended to set the energy trading price, the proportion of free quotas, and the proportion of reserved quotas to 300 yuan / ton of standard coal, 0.8 and 0.4, respectively.

The Jianghuai Region is situated at the boundary of the north and south rainfall belts in China. This region experiences frequent extreme precipitation events. Nevertheless, research on the characteristics, trends, and mechanisms of extreme precipitation in the context of urbanization is still insufficient. Based on the daily precipitation data from 305 stations in the study area from 1960 to 2018, this study analyzed the temporal and spatial characteristics of extreme precipitation, and compared the differences in extreme precipitation between urban and suburban stations to investigate the relative impacts of urbanization. To further explore the mechanisms behind the influence of urbanization, this study also compared the Clausius-Clapeyron scaling of urban and suburban stations. In addition, the differences in atmospheric stability and water vapor conditions between urban and suburban stations during typical extreme precipitation events were also analyzed by computing physical parameters. Land use types and nighttime lights data were used to rigorously differentiate urban stations from suburban stations. The results showed that: (1) Extreme precipitation in the study area exhibited distinct spatial variations. The area with a significant increasing trend in the extreme precipitation indices was concentrated in southern Jiangsu, northern Zhejiang, and Shanghai. (2) With the development of urbanization, there was a trend of shifting from negative to positive in the urban-suburban difference in extreme precipitation. Contribution of urbanization was positive for all the extreme precipitation indices, with a rate exceeding 35% for all cases.The data in urban stations exhibited a more sensitive response to temperature. (3) The analysis of physical parameters indicated that the influence of urbanization on extreme precipitation might be attributed to the warming effect of the urban heat islands. These heat islands triggered upward motion of air, increased atmospheric instability, and enhanced water vapor content, which facilitated convective processes and the occurrence of extreme precipitation.

The study of urbanization's role in extreme temperature events can help to understand the evolution of these events and to reduce their damage. Based on daily meteorological observation data and land use/ cover change data from urban and rural sites in urban agglomeration in the middle reaches of the Yangtze River during 2000~2020, this study analyzed the temporal trends of extreme temperature events. Sen's slope estimation and the Mann-Kendall significance test were adopted in this study. The impact of urbanization and changes in landscape patterns on extreme temperature events was also discussed, in terms of the contribution rate. The results showed: (1) From 2000 to 2020, the overall trend of extreme temperature events at urban and rural sites in the study area was in the same direction, with an increasing trend in extreme high temperatures and a decreasing trend in extreme low temperatures. (2) Urbanization intensified the frequency of extreme temperature events at night. Impact of urbanization on the number of hot nights (TR) and cold nights (TN10p) was calculated as 0.19 days per decade and 0.27 days per decade, respectively, with the corresponding contribution rates of 49.79% and 74.08%. (3) The increase in the proportion of construction land patch area, patch density, and total edge length, as well as the overall increase in landscape fragmentation, diversity, and shape complexity, demonstrated the strongest correlation with the number of hot nights (TR) and the minimum extreme low temperature (TNn). The total edge length of construction land (TE_C) had the largest correlation coefficient with TR (0.25). Overall, urbanization noticeably affected the frequency and intensity of extreme temperature events in urban agglomeration in the middle reaches of the Yangtze River.

Flood disasters pose a significant threat to urban economic development and the safety of residents’ life and properties. Quantifying the resilience index of urban flood disasters can accelerate the construction of resilient cities and provide strong support for the high-quality development of cities. This study took Nanchang city in Jiangxi province as an example. The study area was discretized into 100m x 100m grid units. Multi-source data were used to construct an urban flood disaster resilience evaluation index system, based on PSR model, from four dimensions: nature, economy, society, and infrastructure. The AHP-entropy weight method was employed to explore the spatial distribution of flood disaster resilience at the pixel scale. Additionally, the main driving factors were identified using the geographical detector. The results revealed that the areas of extremely low and low levels of flood disaster resilience accounted for 5.9% and 5.7% of the total area, respectively. These areas were primarily located in Xihu District, Qingyunpu District, and Qingshan Lake District of Nanchang city. The primary contributing factors were identified as the large proportion of impervious surfaces and low vegetation coverage. The geographical detector analysis indicated that the main driving factors of flood disaster resilience in Nanchang City were the proportion of impervious surfaces, terrain humidity index, and the density of buildings. These findings provided a valuable basis for decision making regarding effective responses to prevent and reduce urban flood disasters.

In recent years, global warming led to frequent occurrence of extreme hydrological events, which caused severe disasters in terms of aggravated soil erosion. Therefore, studying the impact of extreme precipitation on sediment transport is of significant importance towards a better understanding of the influencing mechanism to minimize the impacts of extreme precipitation events. Based on the daily precipitation data of 20 meteorological stations in Jialing River basin and the surrounding areas, this paper selected 7 extreme precipitation indexes, and calculated each index by RClimDex model. The trend change and spatial distribution characteristics of extreme precipitation were explored by using linear tendency estimation method and Kriging interpolation method. Mann-Kendall catastrophe test and Lee-Heghinian catastrophe test were adopted to determine the catastrophe point. Finally, the double cumulative curve method was used to quantitatively analyze the contribution rate of extreme precipitation change and the contribution of human activities to the change of sediment discharge. The results showed that: (1) The intensity and frequency of extreme precipitation events tended to increase, while the duration of extreme precipitation events tended to decrease. In terms of spatial distribution, most of the indexes showed a decreasing trend from southeast to northwest. (2) The sediment discharge showed a significant downward trend in the past 45 years, with an abrupt change in 1984. (3) Extreme precipitation and human activities jointly led to the decrease of sediment discharge. Human activities were the main factor, contributing up over 90% of the changes. Compared to the contribution rate of annual precipitation, extreme precipitation demonstrated a greater contribution to the reduction of sediment discharge. This study provided a theoretical basis for improving the ability of disaster prevention and management of water and sediment transport in the area.