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• The extent of flooding in China is greater than in any other country. • Nearly 66% of China's landmass is submerged by flooding. • Financial toll of flooding accounts for approximately 1.42% of the annual GDP. • Various forms of climatic change contribute to flooding. The extent of flooding in China is more significant than in any other country. Our research reveals that approximately 66 % of China's landmass is submerged by flooding, affecting about 50 % of the population. Furthermore, the financial toll of flooding now accounts for approximately 1.42 % of the annual gross domestic product (GDP), which is almost 40 times higher than the corresponding figure for the United States. We have observed that Zhengzhou city in Henan province, which faced a devastating flood in 2021, received a significant amount of rainfall, specifically a total of 552.5 mm within a 24-hour period. The floods in Henan province in 2021 caused considerable damage, including impacting nearly 15 million people, resulting in almost 400 deaths, damaging over 10,000 square kilometers of agricultural land, causing almost $19 billion in economic losses, and leading to the collapse of over 35,000 households and damage to various properties. In a similar manner, the significant flooding that occurred in southern China in 2020 impacted approximately 7.1 million individuals across eight provinces and resulted in 54 fatalities, the collapse of 6,700 houses, and incurred a direct economic loss of US$3.33 billion. We found that rainstorms have significantly increased to 10 % in the last 60 years in China. In this paper, we delved into exploring the existing published articles, reports, and government and authoritative legal texts to analyze the causes and impacts of flooding in China's flood-prone regions and potential mitigation strategies to reduce the repercussions of distressing flood events. We believe this study will help policymakers by providing new insights while formulating policy to reduce the loss caused by high-level flooding. [ABSTRACT FROM AUTHOR]

[Display omitted] • We develop a framework to estimate future Flood Regulation Service (FRS) dynamics. • The framework considers the joint impacts of both climate change and urbanization. • Future FRS supply–demand imbalance will continue to intensify. • Future impacts of climate change in Baiyangdian Lake Basin cannot be ignored. • Cities should actively adapt to climate change to reduce flood risks in the future. Estimating the supply–demand relationship's future dynamics and trend of Flood Regulation Service (FRS) is important for preventing flood risks and choose an appropriate future development path. Less attention has been given to assessing the future trends in this relationship under the joint influence of climate change and urbanization. This paper aims to quantify future trends in the FRS supply–demand relationship under the joint impacts of climate change and urbanization. To this end, we took the Baiyangdian Lake Basin as an example and developed a "Climate Change-Urbanization-FRS supply and demand" framework by combining future climate scenarios from the ScenarioMIP (Scenario Model Intercomparison Project) dataset and socioeconomic data from the SSPs (Shared Socioeconomic Pathways) to estimate the FRS supply and demand dynamics during the period from 2020 to 2050. The results show that the framework has a reasonable ability to estimate the FRS supply–demand relationship. The correlation coefficients between estimated supply–demand ratios and the historical values exceeded 0.9. The average FRS supply–demand ratio among the four scenarios shows a significantly downward trend between 2020 and 2050. The FRS is expected to decrease by 0.159 (36.6 %), resulting in the imbalanced area increasing from 38.3 km2 (4.1 % of the whole basin) to 11049.7 km2 (36.2 %). We believe that although urbanization is the dominant factor contributing to the intensified imbalance trend (with a contribution of 71.2 %), influences from climate change also cannot be ignored (with a contribution of 28.8 %). Therefore, adaptation actions to climate change should be actively taken to reduce urban flood risks in the future. [ABSTRACT FROM AUTHOR]

• Tree ring is an ideal indicator of annual total grain production parameters. • Tree growth synchronized with grain production, and concurrent response to climate. • Reconstruction of total grain productivity based on dendrochronology. • To explore the relationship between total grain sown area and climate change. Climate change affects the growth of regional vegetation; both trees and grain crops often change concurrently, such that the annual radial growth of trees shows consistent inter-annual variations with the total grain crop productivity. However, it remains unclear whether they exhibit concurrent responses to climate factors, and that there lacks of the study on long-term high-resolution variations of grain crops productivity. This paper employs a Pinus massoniana tree-ring series from the Tongbai Mountains to analyze the correlations between tree-ring chronology, local climate data and grain productivity indicators (i.e., total sown grain areas (TSA), total grain outputs (TGO), and average grain yield per hectare (YPH)) of Henan Province in central China. The results indicate that temperature in March and August was the main limiting factor on tree growth, and the best concurrent relationship with tree growth was TSA, which has a correlation of 0.747 (p < 0.001) during 1959–2020. Therefore, a 124-year TSA series in Henan Province was reconstructed using tree-ring data from the Tongbai Mountains, which reveals there were two distinct low periods of total grain sown area in the 1920 s-1930 s and 1980 s-2000 s. There are significant cycles of about 2.57a (p < 0.01), 2.89a (p < 0.05), and 10.95a (p < 0.1), indicating that vegetation growth might be affected by large-scale climate forcing, such as ENSO (2-7a cycle) and sunspot activity (11a cycle). Overall, this study outlines a new approach to understand long-term changes in grain production, which is conducive to grain management and socioeconomic sustainability. [ABSTRACT FROM AUTHOR]

• We calculated carbon sequestration/emissions in agroecosystems in Hebei, China. • We measured agricultural production efficiency considering an undesirable output. • The annual average low-carbon agriculture production efficiency increased by 3.03%. • There were disparities of efficiency among cities owing to increased carbon emission. • Climate change had complex effects on low-carbon agricultural production. With the increase of greenhouse gas (GHG) emissions in the atmosphere, global greenhouse effects have intensified, thereby contributing to climate change. Agriculture contributes to climate change by increasing GHG emissions, and climate change in turn affects agricultural production. In this paper, we calculated carbon emissions and sequestration of agriculture in the 142 counties of Hebei Province, China, and analyzed their spatiotemporal distributions during 2000–2010. Considering net carbon emissions as an undesirable output, we then measured low-carbon agricultural production efficiency using a stochastic directional distance function. We further explored the impacts of climate change on low-carbon agricultural production. We found that carbon emissions in agriculture increased by 15.85% (650 million tons) during 2000–2010, while carbon sequestration in agroecosystems increased by 33.82% (13.8 million tons). The annual average low-carbon agricultural production efficiency increased by 3.03%. There were distinct disparities of efficiency among cities, with the highest efficiency in Chengde and Shijiazhuang. The efficiency in southeastern areas was lower than that in the northwest, owing to the increased carbon emissions. Temperature and precipitation had a positive effect on efficiency in Hebei, whereas extreme weather events caused lower efficiency. The results provide valuable references for developing sustainable, climate-resilient and adaptive agriculture under changing climatic conditions. [ABSTRACT FROM AUTHOR]

[Display omitted] • A new repeatable batch processing method is developed for regional SUHI assessment. • A framework is proposed to explain the formation of SUHI effect. • The impacts of most driving factors on SUHI effect are spatial heterogeneous. • More attention should be paid to small cities. The urban heat island (UHI) effect has become a hot topic worldwide because of the double stress of global climate change and rapid urbanization. However, the deficiencies of existing methods hinder the monitoring and assessment of the surface urban heat island (SUHI) effect at the regional scale. This paper presented a new method to assess SUHI intensity, and then applied it in China. The results indicated that: (1) compared with other methods, this new method has some merits like higher accuracy, fewer operational steps, and higher portability. It enables accurate, semi-automated assessment of SUHI intensity at the regional scale. (2) SUHI effect exists in 81.02% of the cities in China. These cities were mainly concentrated in southeastern China, which presented the significant characteristic of spatial agglomeration. (3) Urban-rural differences in relative humidity, vegetation coverage, evapotranspiration, waterbody coverage, and the number of industrial enterprises are the main driving factors for the SUHI effect in China. Furthermore, there are significant interactions among these driving factors. (4) The spatial heterogeneity of the influence directions and intensities of many driving factors is obvious. Therefore, traditional regression models should be utilized more cautiously because they cannot capture the spatial heterogeneity of variables. (5) The hypothesis of "the larger the city size, the higher the SUHI intensity" is not valid, so more attention should be paid to small cities in the future. [ABSTRACT FROM AUTHOR]

Rapid urbanization has exerted substantial pressure on China’s energy system and contributed to climate change. To find the key drivers of urban residential energy consumption and CO 2 emissions, this paper uses an extended Stochastic Impacts by Regression on Population, Affluence and Technology (STIRPAT) model that employs city-level data to examine the influences of population scale, income level, population compactness and price on house-based residential energy consumption, energy-related CO 2 emissions and private vehicle ownership. The empirical results indicate that factors such as population scale, affluence, and population compactness can lead to increases in residential energy consumption and CO 2 emissions. In terms of transportation, income and population scale positively drive the growth of private vehicle ownership, while the fuel price negatively influences private vehicle ownership. Moreover, population scale is the most important factor in residential energy consumption and CO 2 emissions. Finally, policy recommendations are suggested for China’s urban development strategy and urban design and to encourage technology innovations that reduce residential energy consumption and CO 2 emissions. [ABSTRACT FROM AUTHOR]

[Display omitted] • Past LULC changes can be divided into two stages: (I) accelerated evolution stage (1980–2010), and (II) stable evolution stage (2010–2020). • Carbon storage presented a high-low-high distribution pattern from north to south. • Areas with a rapid urbanization process exhibited more obvious changes in carbon storage dynamics. • Rapid LULC dynamics have reduced the carbon sequestration capacity of the ecosystem. • The implementation of ecological conservation could increase the carbon fixation in ecosystems. Land use/land cover (LULC) change has greatly altered ecosystem carbon storage capacity and can eventually profoundly impact global climate change. Characterizing the LULC change and its impact on ecosystem carbon storage in coastal areas is greatly significant to comprehensively understanding the influences of human activities on ecosystems. Based on LULC data, this paper combined CA-Markov and InVEST models to evaluate the past, present, and future LULC change and its impact on ecosystem carbon storage in coastal areas of China. The results showed that past LULC change in coastal areas can be divided into two stages: (I) accelerated evolution stage (1980–2010), and (II) stable evolution stage (2010–2020). Changes in LULC types have led to a downward trend in ecosystem carbon storage, with a cumulative loss of 0.39 Pg and 0.15 Pg during the two stages, respectively. Spatially, carbon storage presented a high-low-high spatial distribution pattern from north to south. Temporally, areas with a rapid urbanization process exhibited more obvious changes in carbon storage dynamics. Compared with the natural change scenario, the areas with LULC types conversion under the ecological conservation scenario in 2050 will be lower due to the limitation of ecological protection, and it caused carbon storage reduction will slow down. Rapid LULC dynamics, that a large area of farmland, unused land and, water have been converted into construction land, reduced the carbon sequestration capacity of the ecosystem. This study will provide reliable references and precise data support for coastal management and decision-making. [ABSTRACT FROM AUTHOR]

• The relationship between the groundwater depth and grassland ecology was analysed; • Groundwater depth affected the composition and diversity of vegetation species; • A reasonable groundwater depth can buffer the impact of climate change on the vegetation to maintain grassland ecological stability; • The control of grassland degradation should include the potential exploitation of groundwater. Grassland degradation in the semiarid area of China is often attributed to overgrazing and expansion of irrigated agriculture without the consideration of groundwater. However, falling groundwater levels in the region have caused many problems for grassland ecology. In this paper,the typical sandy grassland- the Tongliao part of Horqin grassland was selected as the study area to study the spatial distribution of normalized difference vegetation index (NDVI) and the relationship between the NDVI and groundwater depth (GD) of each grassland pixel was studied. The temporal variation of the NDVI and its correlations with precipitation were investigated. The relationship between GD and vegetation species diversity in grassland was analyzed based on the vegetation survey. The results of the relation between GD and NDVI and vegetation species showed that GD can buffer the impact of increase in drought events on the vegetation because GD affected the composition and diversity of vegetation species. As the GD increases, the mean NDVI showed a trend of increasing first and then decreasing, and basically remained unchanged when the GD was greater than 3.5 m. The species diversity of grassland decreased with increasing GD and was not related to GD when GD was greater than 3.5 ∼ 4 m. Falling groundwater levels will cause great changes in the structure of grassland; specifically, azonal vegetation will gradually die and 3.5 m may be the critical GD needed to maintain the incomplete extinction of grassland azonal vegetation in the aeolian sandy soil. Correlation analysis proved that the correlation between NDVI and precipitation was significantly enhanced when GD increased sharply from 3 m to 6 m after 1999. This research indicates that the control of grassland degradation should pay attention to controlling the groundwater exploitation to recover a reasonable groundwater level, which was found to be necessary in the support of diverse and climate resilient of vegetation. [ABSTRACT FROM AUTHOR]

• Dynamic analysis of mixed forest species. • Potential suitable range of simulated species. • Dominant factors of species distribution. • P. tabuliformis and O. davidiana are mixed tree species. • R's ENMeval language package to optimize Maxent model. The outstanding self-regulation ability of mixed forest plays an important role in maintaining ecosystem stability. However, in recent years, climate change has caused geographical changes of species. This paper studies the potential geographical location of mixed species for the first time, so as to formulate the planting plan of mixed species in suitable areas. Therefore, we use the species distribution model based on Maxent to predict the potential suitable area of Chinese Pinus tabuliformis and Ostryopsis davidiana mixed forest under the climate change scenario, and provide a scientific basis for expanding the construction of P. tabuliformis and O. davidiana mixed forest in the future under three greenhouse gas emission scenarios (RCP2.6, RCP4.5 and RCP8.5) of current and future climate (2041–2060 and 2081–2100). The simulation accuracy of Maxent model is verified by the area under receiver operating characteristic curve (AUC). The results show that the distribution range of P. tabuliformis is much larger than that of O. davidiana in China. Under the current climate conditions, the overlapping area of medium to highly suitable growing areas of P. tabuliformis and O. davidiana is 64.40 × 104 km2, accounting for 6.71% of China's land area, mainly distributed in most areas of North China, Northeast China (Western Liaoning), Northwest China (Shaanxi, Ningxia, the Southernmost part of Inner Mongolia and Eastern Gansu) and Central China (Northern Hubei). Under the future high concentration emission scenario (RCP8.5), the overlapping area of medium to highly suitable growing areas of P. tabuliformis and O. davidiana will be reduced. Under the scenario of medium concentration climate emission (RCP 4.5), the centroids of P. tabuliformis and O. davidiana tend to migrate from west to north. The annual mean temperature (bio1) has a significant effect on the geographical distribution of P. tabuliformis and O. davidiana. In addition, the mean temperature of the driest quarter (bio9) and annual precipitation (bio12) also have a significant impact on the geographical distribution of P. tabuliformis. Similarly, there are obvious factors on the geographical distribution of O. davidiana , as well as isothermality (bio3) and precipitation of the wettest quarter (bio16), indicating that the important climate factors affecting the geographical distribution of P. tabuliformis and O. davidiana are not completely consistent. We believe that mixed forests play a positive role in coping with climate change. The research results can help decision-makers to formulate adaptation countermeasures based on climate change. [ABSTRACT FROM AUTHOR]

• Nonlinearity and interaction of drivers of runoff and nitrate were identified. • Agricultural expansion and climate change offset positive effect of forest restoration. • Landscape configuration determined surface runoff and nitrate load in wet season. • Cropland fragmentation is crucial to alleviate nitrate load. Climate variability and landscape modifications directly influence watershed hydrology and processes of nonpoint source pollution, while remedial action requires distinguishing their effects. However, nonlinearity and multiple causality limit our ability to diagnose causes. Therefore, this study developed an approach that integrates hydrological modeling, random forests, regression trees, and variation partitioning analysis, to identify the effects of climate and landscape pattern changes upon runoff and nitrate loading in two typical watersheds in the Three Gorges Reservoir area of China. The Soil and Water Assessment Tool (SWAT) was used to track the spatiotemporal dynamics of runoff and nitrate loading (2000–2015). The findings showed that drylands and orchards were the dominant sources of nitrate and baseflow was the key mode of nitrate transport. Water yield and baseflow were mainly influenced by precipitation change, while the surface runoff and nitrate load were affected primarily by landscape pattern changes, especially in the wet season. Although ecological restoration programs have improved forest cover and forest fragmentation, the effects of forest restoration on the reduction of surface runoff and nitrate at the watershed scale have been offset by increased precipitation and agricultural expansion. Nevertheless, the role of landscape configuration is so dramatic that it can override variation in nitrate losses driven by changes in land cover and precipitation. Effective control of nitrate loss under intensive ecological restoration can be achieved by using a mosaic of "sink" patches to divide larger areas of cropland into smaller patches, maintaining cropland fragmentation, and limiting the increase in edge density of cropland. This paper's proposed and implemented approach provides a new understanding of the interactions and nonlinear relationship between hydrological processes and environmental change, providing explicit ideas and useful insights for landscape planners and managers for improving eco-hydrological functions of watershed at the practical level. We emphasize that the impact of land use change cannot be assumed to be linear in restoration strategies, instead nonlinear impacts, clear details of landscape configuration, and seasonal climatic characteristics should be explicitly considered. [ABSTRACT FROM AUTHOR]

Abstract: Lichen epiphytes are applied as excellent environmental indicators worldwide. However, very little is known about epiphytic lichen communities and their response to forest dynamics in subtropical China. This paper proposes the applications of the cover, diversity, and functional traits of epiphytic lichens to assess environmental changes associated with succession in subtropical forests of southwest China. Bole lichens were sampled from 120 plots of eight representative forest types in the Ailao Mountains. Total cover, species richness, diversity and community structure of bole lichens differed significantly among forest types, and the highest cover and diversity occurred in the Populus bonatii secondary forest (PBSF). Sixty-one indicator species were associated with particular forest types and more than 50% occurred in the PBSF. Both cover and diversity of most lichen functional groups varied regularly during forest succession. Lichen pioneer species were not displaced by competitively superior species as succession proceeds and cyanolichens were more prevalent in secondary forests. The results also highlight the importance of habitat variables such as canopy openness, host diversity, forest age, tree size, the size of the largest tree, tree density, and basal area on the lichen community. Consequently, our findings support the notion that epiphytic lichens, in terms of cover, diversity, species composition and functional traits can be used as effective indicators for large-scale and long-term forest monitoring. More importantly, the narrowly lobed foliose group was the best candidate indicator of environmental conditions in this region. The combined application of lichen indicator species and functional groups seemed to be a more reliable and more powerful method for monitoring forest dynamics in subtropical montane ecosystems. [Copyright &y& Elsevier]

[Display omitted] • Grassland degradation is the main reason for the decline in carbon storage. • The carbon storage of farmland has increased significantly. • The risk of carbon storage reduction in the future is still high. The carbon storage of terrestrial ecosystems is closely related to global climate change. Therefore, assessing the impact of land-use changes on carbon storage is instructive to reduce global carbon emissions. Taking an arid region in northwest China as an example, this paper analyzed the land-use changes in arid region from 1980 to 2015. It used the CA-Markov model to predict the land-use pattern from 2020 to 2050, the carbon storage and sequestration module in Integrated Valuation of Ecosystem Services and Tradeoffs (Invest) mode to assess and predict ecosystem carbon storage over the past 35 years and in the next 30 years and discusses the impact of land-use changes on the carbon storage of terrestrial ecosystems. The results showed that: (1) The high-value areas of carbon storage in arid region were primarily concentrated in grassland, forests and farmland, and the low-value areas of carbon storage were mainly in desert areas. (2) The carbon storage in arid region showed a downward trend. From 1980 to 2015, the carbon reserves of terrestrial ecosystems in arid region decreased by 90.95 Tg, and the net loss of carbon reserves from 2020 to 2050 was 14.72 Tg. Grassland degradation was the main reason for the reduction of carbon storage in arid region. (3) The carbon storage of farmland had increased significantly, but the expansion of farmland dominated by high carbon density grassland, wetland and forest, had reduced the overall carbon storage of the arid region. [ABSTRACT FROM AUTHOR]

• China's water use efficiency showed an increasing trend from 2001 to 2017. • The water use efficiency of forest land is higher than that of low vegetation. • Human activities have a greater contribution to the increase in water use efficiency. • China has more areas with positive correlation between water use efficiency and meteorology. In the context of increasing global carbon emissions, and the relative shortage of water resources, research on the relationships between climate change, human activities and the carbon–water coupling response of China's ecosystems is crucial. Water use efficiency (WUE) is an important indicator reflecting the coupling of ecosystem carbon and water cycles. Based on trend analysis, correlation analysis and multiple regression residual analysis, this paper analyzes the spatiotemporal distributions, change trends, correlations with meteorological factors, changes in different vegetation coverage types, and relative contributions of the main driving factors of China's vegetation WUE from 2001 to 2017. The results show the following: (1) For the past 17 years, the multiyear average value of vegetation WUE in China is 1.08 g C m - 2 mm - 1 , the average annual growth rate is 0.003 g C m - 2 mm - 1 a - 1 . The area with increasing trend of WUE accounts for 59.09% of the total area. (2) The seasonal WUE is highest in autumn, followed by summer, spring and winter. (3) The areas in which vegetation WUE is positively correlated with temperature and precipitation account for approximately 50.21% and 66.16% of the total area, respectively. (4) In terms of the relative annual average value of the WUE, the different vegetation cover types, in descending order, are mixed forests > needleleaf forests > broadleaf forests > shrublands > grasslands > croplands > wetlands > barren lands. (5) Human activities and climate change contributed 66.75% and 33.25%, respectively, to the increase in vegetation WUE in China in the past 17 years. The research results have important scientific significance for clarifying the impacts of climate change and human activities on the carbon–water cycle of the terrestrial ecosystems of China and assessing regional differences in the potential of terrestrial ecosystems to increase carbon sinks. [ABSTRACT FROM AUTHOR]

• The crop yield deviations are more susceptible to change in temperature. • The level of climate change induced risk amounts to 1.3-5.3% of the average yields. • The risk leads to a considerable change in cropland use in Chinese farms. • Changing cropland use structure is an effective strategy of mitigating the risk. This paper estimates the climate change induced risk for 14 crops measured by the yield deviation using the panel data from seven counties in Jiangsu province in China from 1998 to 2017, and then investigates the risk effect on cropland use in a representative farm using the survey data and the MOTAD model. The results show that the crop yield deviation are more susceptible to change in temperature than that in sunlight and precipitation. The crop-specific risk level amounts to 1.3–5.3% of the average yields. The risk leads to reducing the cultivated areas by 6% and also causes a significant change in cropland use. As an effective adaptation strategy of mitigating the climate change induced risk, the farms should reduce the total cultivated area by about 15% in comparison with the observed situation while the cropland use structure should be adjusted accordingly. More cropland should be allocated to wheat, peanut and cotton but the other crop areas should be reduced or maintained. [ABSTRACT FROM AUTHOR]

• Combining emergy with factor analysis can reduce the singleness and subjectivity of evaluation. • From the ecological, economic, engineering and social aspects to evaluate regional resilience. • Provide a good practical case for studying the regional resilience of developing countries. • Provide a good basis for government decision making. With the aggravation of global climate change, the frequency of global natural disasters is increasing year by year. How to actively respond to natural disasters has become the key to ensure the sustainable development of the region. Since urbanization in developing countries is much lower than that in developed countries, most scholars in the past focused on the regional resilience of developed countries rather than developing countries. China is the largest developing country in the world, choosing China as the research area has practical guiding significance. To assess the current state of China's regional resilience capacity, this paper establishes an evaluation system of resilience capacity index of 28 indicators based on China's actual situation. The comprehensive emergy and factor analysis method are used to evaluate the resilience capacity index of 26 regions (provinces) in China from four aspects: ecology, economy, engineering, and society. The results show that economy and ecology are the critical factors affecting regional resilience capacity index. China's regional resilience index has apparent characteristics of agglomeration, distribution, and imbalance in space. China's coastal resilience index is generally higher than China's inland region, showing gradient differentiation in spatial change. These characteristics are influenced by China's policy, which is consistent with the expected early effect of China's reform and opening-up policy. [ABSTRACT FROM AUTHOR]

• The rainfall-runoff relationship has changed under climate change and human activities in the TRH region. • The impacts climate indicators of rainfall-runoff ratio in the sub-basins of TRH region were different. • The contribution rates of human activity in the YRB were a little higher than that in the YARB. Identifying the impact of climate change and human activities on rainfall-runoff relationship in the Three-River Headwaters (TRH) region is essential for water source conservation, ecological security, and biodiversity maintenance of China and East Asia. In this paper, the runoff-rainfall ratio was used as the index of rainfall-runoff relationship. Different methods were employed to identify the impact indicators and quantitative assessment of rainfall-runoff relationship from 1957 to 2016. The results are the following: (1) the rainfall-runoff relationship has changed in the source regions of Yangtze River basin (YARB) and Yellow River (YRB), and runoff-rainfall ratio has increased by 2.9% and decreased by 3.2%, respectively; (2) the main climate indicators of runoff-rainfall ratio were rainfall, potential evaporation and sunshine hours in the YARB, and rainfall, potential evaporation and temperature in the YRB; (3) the contribution rates of human activity in the YRB were a little higher than that in the YARB, and the contribution rates of climate change and human activity were 90.9% and 9.1% in the YARB and 42.9% and 57.1% in the YRB. The results can provide invaluable information for managing water resources and taking ecological protection measures. [ABSTRACT FROM AUTHOR]