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In this study, we propose to assess climate impact on forest cover (represented by EVI) at multiple scales in areas undergoing substantial land cover change, using Landsat imagery with human-induced land cover change effect excluded. Taking the Qingliu River catchment located in a subtropical humid monsoon area in China as a case study, the results indicate that EVI increases significantly (p < 0.01) during 1989-2014 with a magnitude of 0.026/decade. Spatial distribution of EVI is distinct in summer and growing season. Temperature and precipitation show high partial correlations with EVI, with better partial correlation found between EVI and temperature. Their partial correlations with EVI on monthly scale are higher than those on annual scale. Besides, precipitation and pan evaporation show accumulative lag effects (4 months) on forest EVI, while temperature has no lag effect. Finally, an empirical formula is established to quantify the relationship among EVI and its main driving factors (temperature and precipitation) by considering the precipitation threshold (200 mm). The findings should provide scientific supports for local forest management and ecosystem services, and should also support the hydrological effect assessment of vegetation cover change under climate change for the study area., (Copyright © 2019. Published by Elsevier B.V.)

It is increasingly recognized that climate change could impose both direct and indirect impacts on the quality of the water environment. Previous studies have mostly concentrated on evaluating the impacts of climate change on non-point source pollution in agricultural watersheds. Few studies have assessed the impacts of climate change on the water quality of river basins with complex point and non-point pollution sources. In view of the gap, this paper aims to establish a framework for stochastic assessment of the sensitivity of water quality to future climate change in a river basin with complex pollution sources. A sub-daily soil and water assessment tool (SWAT) model was developed to simulate the discharge, transport, and transformation of nitrogen from multiple point and non-point pollution sources in the upper Huai River basin of China. A weather generator was used to produce 50 years of synthetic daily weather data series for all 25 combinations of precipitation (changes by - 10, 0, 10, 20, and 30%) and temperature change (increases by 0, 1, 2, 3, and 4 °C) scenarios. The generated daily rainfall series was disaggregated into the hourly scale and then used to drive the sub-daily SWAT model to simulate the nitrogen cycle under different climate change scenarios. Our results in the study region have indicated that (1) both total nitrogen (TN) loads and concentrations are insensitive to temperature change; (2) TN loads are highly sensitive to precipitation change, while TN concentrations are moderately sensitive; (3) the impacts of climate change on TN concentrations are more spatiotemporally variable than its impacts on TN loads; and (4) wide distributions of TN loads and TN concentrations under individual climate change scenario illustrate the important role of climatic variability in affecting water quality conditions. In summary, the large variability in SWAT simulation results within and between each climate change scenario highlights the uncertainty of the impacts of climate change and the need to incorporate extreme conditions in managing water environment and developing climate change adaptation and mitigation strategies.

Extreme events occur frequently in China against the background of global warming. Understanding the spatiotemporal variation of extreme events and predicting their future trends can provide a theoretical basis for formulating regional strategies that adapt to climate change. Using the CN05.1 grid meteorological data and eleven global climate models based on Coupled Model Intercomparison Project Phase 6 (CMIP6), we analyzed the evolution characteristics of extreme precipitation and high temperature events in China from 1975 to 2014, predicted the evolution of extreme events from 2015 to 2054, and proposes policy suggestions for dealing with these events. The results indicate that, from 1975 to 2014, the heavy precipitation exhibited an increasing-decreasing-increasing pattern from the northwest to southeast region of China, and the risk and catastrophability of extreme precipitation in regions located to the east of the Hu Line were great. Under SSP1-2.6 and SSP5-8.5 climate change scenarios, extreme precipitation in China will generally increase and become stronger by 2054, with a significant increase in North and Northeast China and a further increase in Northwest China. From 1975 to 2014, the number of warm nights and warm days in China increased significantly, and the increase in warm nights was higher than that of warm days. Under the SSP1-2.6 and SSP5-8.5 climate change scenarios, extreme heat events in China will increase significantly by 2054, with the greatest increase in Northwest, Southwest, and South China. To mitigate the impact of climate change and cope with the risk of extreme events in the future, China should further improve its response and emergency management capacities for dealing with flood and extreme heat risks, strengthen international cooperation, and formulate strategies adapted to local conditions.

Plastic products in plant production and protection help farmers increase crop production, enhance food quality, and reduce global water use and their environmental footprint. Simultaneously, plastic has emerged as a critical ecological issue in recent years, and its pollution has significantly impacted soil, water, and plants. Thus, this review examines the multifaceted problems of plastic pollution in agriculture as a risk to food security, the ecosystem, and the environment. The study's objective was to review and present the most recent information on using different plastic products in agriculture, the sources of plastic pollution, the advantages and drawbacks of using plastic products, and the strategies for mitigating plastic pollution in agriculture. Furthermore, after examining current plastic applications, benefits, adverse effects, and risks to soil, plants, and the environment, we addressed the requirements for technological advancements, regulations, and social processes that could contribute to mitigating plastic pollution in our ecosystems. We identified different pathways toward more sustainable use of plastics in agriculture and discussed future research directions. [ABSTRACT FROM AUTHOR]

Global climate change has affected vegetation cover in alpine areas. In this paper, we analyzed the correlation between Leaf Area Index (LAI) and climate factors of the Yarlung Tsangpo River basin, and identified their contributions using the quantitative analysis method. The results show that the vegetation cover in the study area generally exhibited an increasing trend. Grassland in the middle- and high-altitude areas was the main contributing area. Temperature is the dominant climatic factor affecting the change, the effect of which increases with the rise in elevation. The influences of precipitation and radiation had obvious seasonality and regionality. The vegetation illustrated a lag response to climate drivers. With the change in the elevation band, the response time to precipitation was significantly less than that to air temperature in the low-elevation area, while the opposite trend was observed in the high-elevation area. In the future, the LAI of the watershed will show different characteristics at different time points, with the increases in the LAI in autumn and winter becoming the main factors for the future increase in the LAI. This provides a crucial basis upon which to explore hydrological and ecological processes as important components of the Third Pole region. [ABSTRACT FROM AUTHOR]

The streamflow on the Tibetan Plateau (TP) plays an important role in the water supply of Asia's main river basins. To enhance understanding of hydrologic cycle under the pronounced warming over the TP, this study comprehensively investigates the streamflow changes at the upstream of six major rivers (Yellow River, Yalong River, Jinsha River, Lancang River, Nu River, and Yarlung Zangbo River) originating from the TP, and then diagnoses their possible causes by analysing the impacts of climate variability and human activities. Results indicate that these six major rivers studied have generally insignificant increasing trends in annual streamflow during the last half century, except for two stations. The significant increase appears at the Tuotuohe station in the headwater area of Jinsha River, while the dramatic decrease occurs at the Yunjinghong station in the downstream of Lancang River. In terms of climate factors, the six river basins show a distinct warming trend, along with a noticeable increase in precipitation over the central and northern regions. Pan evaporation, wind speed, sunshine duration, and relative humidity have been found to gradually decrease in most areas. As for the Tuotuohe station, both warming‐induced meltwater and increasing precipitation might jointly contribute to the increasing streamflow. But for the Yunjinghong station, the results simulated by the Variable Infiltration Capacity (VIC) model indicate that human activities, especially for the impoundment processes of Xiaowan and Nuozhadu dams, significantly influenced the streamflow, contributing to approximately 69% of the streamflow reduction during 2009–2013. In the context of accelerated global warming, greater attention should be paid to hydrometeorological changes on the TP to offer further insights for the water resources management of the 'Asian Water Tower'. [ABSTRACT FROM AUTHOR]

The Lancang–Mekong River Basin (LMRB) is the largest international river in Southeast Asia, supporting a population of about 70 million people. Precipitation is the main source of water resources in the basin, with significant impacts on ecology, production, and livelihoods in the basin. In this study, future precipitation was projected using the Coupled Model Intercomparison Project Phase 6 (CMIP6) climate models. The initial bias of each model was corrected using the daily bias-correction (DBC) method, and then the models were ensembled using the Bayesian model-averaging (BMA) method. The evaluation, based on metrics such as climatology bias, root-mean-square error (RMSE), mean absolute error (MAE), and correlation coefficient (COR), showed that the ensemble precipitation performs better than the individual models. Precipitation under four future Shared Socioeconomic Pathway scenarios (SSP126, SSP245, SSP370, SSP585) displayed an increasing trend throughout the LMRB. The anomalies in annual precipitation in 2061–2090 under each scenario are 136 mm, 142 mm, 114 mm, and 227 mm, in that order. Precipitation in spring and winter shows a trend of increasing in the northern LMRB and decreasing in the southern LMRB, and precipitation in summer and autumn shows a significant trend of increasing in almost the whole basin (significance level 0.05). Spring precipitation in the Mekong Delta decreases in all scenarios. The ratio of wet-season precipitation to dry-season precipitation shows an increasing trend for all scenarios, indicating that the difference between wet-season precipitation and dry-season precipitation will increase in the future. For daily precipitation, the Lancang River Basin (LRB) is dominated by a 3–5% increase in the number of days with 5–10 mm/d of precipitation and the Mekong River Basin (MRB) by a 3–5% increase in the number of days with 10–20 mm/d of precipitation under four SSP scenarios in 2061–2090. There are important changes in the spatial distribution of future precipitation, with the 2500 mm isohyet expanding outwards in a circular pattern and the center of the 1500 mm isohyet moving westwards; i.e., areas with annual precipitation exceeding 2500 mm and 1500 mm will expand. For dry-season precipitation, the 500 mm isohyet shrinks, mainly in a circular pattern towards the center, while the 300 mm isohyet moves mainly towards the east, indicating that areas of dry-season precipitation below 500 mm and 300 mm will expand. In the future, the LMRB will generally become wetter in the wet season and drier in the dry season. [ABSTRACT FROM AUTHOR]

In recent years, global climate change causes more extreme precipitation events in Lancang-Mekong River Basin (Lancang-Mekong Basin). It leads to the increase of rainstorm and flood risk, which poses a threat to the flood control safety of Lancang-Mekong Basin. Based on the precipitation data of four global climate models of CMIP6, this paper selected six indexes, including PRCPTOT and R10, to study the change characteristics of the extreme precipitation indexes in the Lancang-Mekong Basin during 1980–2020 and predicted the development trend of the extreme precipitation indexes in the Lancang-Mekong Basin during 2021–2050. The results show that from 1980 to 2020, the extreme precipitation events in regions I and IV showed an increasing trend, while those in regions II and III showed a decreasing trend. From 2021 to 2050, the extreme precipitation events in all regions of the Lancang-Mekong River show an upward trend, and most indexes increased compared with the historical period. The extreme precipitation indexes in most regions increases the most under the scenario of SSP5-8.5, while the increase is small under the scenario of SSP2-4.5; The six extreme precipitation indexes selected in the paper can better reflect the trend of extreme precipitation events and floods. The trend of extreme precipitation indexes in the Lancang-Mekong River basin in the future is more significant, which indicates that it may be affected more frequently by extreme precipitation events and floods. [ABSTRACT FROM AUTHOR]

Terrestrial water storage (TWS) is of great importance to the global water and energy budget, which modulates the hydrological cycle and then determines the spatiotemporal distributions of water resources availability. The Tibetan Plateau is the birthplace of the Yangtze, Yellow, and Lancang–Mekong River, where the water resources are directly related to the life of the Eastern and Southeastern Asian people. Based on multi-source datasets during the period 1981–2015, the long-term spatiotemporal variabilities of the TWS over the Tibetan Plateau were investigated by the Sen's slope and Mann–Kendall test trend analysis methods; the changing mechanisms were explored from two perspectives of components analysis and the hydrological cycle. The water conservation capacity of vegetation in the alpine mountainous areas was also discussed by geostatistical methods such as correlation analysis, extracted by attributes and zonal statistics. The results show that the TWS of the Tibetan Plateau increased with the speed of 0.7 mm/yr as the precipitation accumulated and the glaciers melted during the period 1981–2015. The TWS values were low and generally present a trend of obvious accumulation over the northern Tibetan Plateau, while the high and decreasing values were distributed in the south of Tibetan Plateau. The results of the components analysis indicate that the TWS mainly consisted of soil moisture at one-fourth layers, which are 0–200 cm underground in most areas of the Tibetan Plateau. The precipitation is mainly lost through evapotranspiration over the northern Tibetan Plateau, while in the northwestern corner of the Tibetan Plateau, the Himalayas, and northeastern Yarlung Zangbo River basin, the runoff coefficients were larger than 1.0 due to the influence of snow melting. In the alpine mountains, different climate and vegetation conditions have complex effects on water resources. The results are helpful for understanding the changing mechanism of water storage over the Tibetan Plateau and have scientific meaning for the development, utilization, and protection of regional water resources. [ABSTRACT FROM AUTHOR]

Hydrological simulations are a main method of quantifying the contribution rate (CR) of climate change (CC) and human activities (HAs) to watershed streamflow changes. However, the uncertainty of hydrological simulations is rarely considered in current research. To fill this research gap, based on the Soil and Water Assessment Tool (SWAT) model, in this study, we propose a new framework to quantify the CR of CC and HAs based on the posterior histogram distribution of hydrological simulations. In our new quantitative framework, the uncertainty of hydrological simulations is first considered to quantify the impact of "equifinality for different parameters", which is common in hydrological simulations. The Lancang River (LR) basin in China, which has been greatly affected by HAs in the past 2 decades, is then selected as the study area. The global gridded monthly sectoral water use data set (GMSWU), coupled with the dead capacity data of the large reservoirs within the LR basin and the Budyko hypothesis framework, is used to compare the calculation result of the novel framework. The results show that (1) the annual streamflow at Yunjinghong station in the Lancang River basin changed abruptly in 2005, which was mainly due to the construction of the Xiaowan hydropower station that started in October 2004. The annual streamflow and annual mean temperature time series from 1961 to 2015 in the LR basin showed significant decreasing and increasing trends at the α= 0.01 significance level, respectively. The annual precipitation showed an insignificant decreasing trend. (2) The results of quantitative analysis using the new framework showed that the reason for the decrease in the streamflow at Yunjinghong station was 42.6 % due to CC, and the remaining 57.4 % was due to HAs, such as the construction of hydropower stations within the study area. (3) The comparison with the other two methods showed that the CR of CC calculated by the Budyko framework and the GMSWU data was 37.2 % and 42.5 %, respectively, and the errors of the calculations of the new framework proposed in this study were within 5 %. Therefore, the newly proposed framework, which considers the uncertainty of hydrological simulations, can accurately quantify the CR of CC and HAs to streamflow changes. (4) The quantitative results calculated by using the simulation results with the largest Nash–Sutcliffe efficiency coefficient (NSE) indicated that CC was the dominant factor in streamflow reduction, which was in opposition to the calculation results of our new framework. In other words, our novel framework could effectively solve the calculation errors caused by the "equifinality for different parameters" of hydrological simulations. (5) The results of this case study also showed that the reduction in the streamflow in June and November was mainly caused by decreased precipitation and increased evapotranspiration, while the changes in the streamflow in other months were mainly due to HAs such as the regulation of the constructed reservoirs. In general, the novel quantitative framework that considers the uncertainty of hydrological simulations presented in this study has validated an efficient alternative for quantifying the CR of CC and HAs to streamflow changes. [ABSTRACT FROM AUTHOR]

Documenting year-to-year variations in carbon storage potential in terrestrial ecosystems is crucial for the determination of carbon dioxide (CO 2) emissions. However, the magnitude, pattern, and inner biomass partitioning of carbon storage potential and the effect of the changes in climate and CO 2 on inner carbon stocks remain poorly quantified. Herein, we use a spatially explicit individual-based dynamic global vegetation model to investigate the influences of the changes in climate and CO 2 on the enhanced carbon storage potential of vegetation. The modelling included a series of factorial simulations using the Climatic Research Unit (CRU) dataset from 1916 to 2015. The results show that CO 2 predominantly leads to a persistent and widespread increase in light-gathering vegetation biomass carbon stocks (LVBC) and water-gathering vegetation biomass carbon stocks (WVBC). Climate change appears to play a secondary role in carbon storage potential. Importantly, with the intensification of water stress, the magnitude of the light- and water-gathering responses in vegetation carbon stocks gradually decreases. Plants adjust carbon allocation to decrease the ratio between LVBC and WVBC for capturing more water. Changes in the pattern of vegetation carbon storage were linked to zonal limitations in water, which directly weaken and indirectly regulate the response of potential vegetation carbon stocks to a changing environment. Our findings differ from previous modelling evaluations of vegetation that ignored inner carbon dynamics and demonstrate that the long-term trend in increased vegetation biomass carbon stocks is driven by CO 2 fertilization and temperature effects that are controlled by water limitations. [ABSTRACT FROM AUTHOR]

Water resources severely constrain high-quality development in the Yellow River basin (YRB). Predicting the trend of precipitation on the basis of satisfying precision has important guiding significance for future regional development. Using the projected precipitation in 12 CMIP6 models, this study applied the most appropriate correction method for each model from four quantile-mapping methods and projected future changes of annual precipitation in the YRB and three key regions. The projection uncertainty was quantitatively assessed by addressing model spread (MS) and range. The precipitation anomaly under all four scenarios would increase for the YRB and key regions. The increasing rates (the linear coefficient) from Shared Socioeconomic Pathway 126 (SSP126) to SSP585 were 30–62, 60–103, 84–122, and 134–204 mm (100 yr)−1, respectively. The largest increase was the sediment-yielding region, which reached about 40–60 mm in 2031–60 and 70–125 mm in 2061–90. The 400-mm isohyet was projected to move continuously to the northwest in the future. The uncertainty quantified by MS was reduced by 85.9%–94.6%, and projection ranges were less than 50 mm (about 10% of climatology) in most parts of YRB. From the increasing trend of future precipitation in the YRB, it can be inferred that the arid region will shrink. It may be a good opportunity to implement ecological conservation and high-quality development of the YRB successfully. Significance Statement: We want to understand the spatial–temporal evolution pattern of future precipitation in the Yellow River basin (YRB) under climate change scenarios. In the future, the precipitation in the YRB and the three key regions will increase, with the sediment-yielding region increasing the most, and the arid region will shrink. Our findings confirm that the spatial–temporal patterns of precipitation in the YRB will change significantly under climate change scenarios. These findings will guide ecological protection and regional social and economic development in the YRB. Future research should focus on adaptation strategies of agricultural production patterns to climate change. [ABSTRACT FROM AUTHOR]

Water resources are essential for human beings. It is of significance to project future water resources carrying capacity for water resources planning and management. In this study, the Huang-Huai-Hai River Basin (HHHRB), where the contradiction between humans and water is prominent in China, is selected as the study area. The fuzzy comprehensive evaluation model of regional water resources carrying capacity is constructed, the variation characteristics of water resources affected by climate change are analyzed based on the Budyko-Fu model, and considering the influence of transit water resources and water diversion projects, the future water resources carrying capacity in HHHRB under four future climate scenarios in CMIP6 is projected. The results indicate that: (1) On the whole, the carrying capacity of water resources in HHHRB is weak, and the spatial difference is great. (2) Under the background of climate change in the future, precipitation, temperature, and water resources in HHHRB all show increasing trends with changes of 0.90–12.59%, 1.22–1.80 °C, and 13.12–34.29%. (3) Under the background of global change, the water resources carrying capacity of most prefecture-level cities in HHHRB will be greatly improved in the future, and the spatial distributions of change rates among different climate scenarios are relatively consistent. (4) The construction of water diversion projects such as the South-to-North Water Diversion Project has played an obvious role in improving the carrying capacity of water resources. The research results can provide important scientific and technological support for the rational allocation of water resources in the basin under the background of global change. [ABSTRACT FROM AUTHOR]

Research on precipitation regularity in the past 120 years is an important link in analyzing the precipitation characteristics of watersheds. This paper systematically analyzes the characteristic changes of centennial precipitation data in the Haihe River basin with the help of CRU data, PCI, SPI, and the Pearson type III curve. The results show that the spatial and temporal distribution of precipitation in the Haihe River basin has a more obvious inconsistency. The temporal distribution shows the characteristics of relatively stable in the early period and increasing fluctuation in the later period, the concentration of precipitation gradually decreases, and the overall drought level decreases. The spatial distribution shows a general pattern of gradually decreasing from southwest to northeast, the overall trend of summer precipitation changes from stable to north–south extremes, and the distribution probability of extreme precipitation events in the basin decreases from southeast to northwest, while the drought-prone area transitions from the northeast to the west and southwest of the basin. Under the influence of both climate change and human activities, the seasonal distribution of precipitation tends to be average, the area affected by extreme precipitation rises, and the arid area shifts to the inland area. [ABSTRACT FROM AUTHOR]

The source regions of the Yangtze River (SRYZ) and the Yellow River (SRYR) are sensitive areas of global climate change. Hence, determining the variation characteristics of the runoff and the main influencing factors in this region would be of great significance. In this study, different methods were used to quantify the contributions of climate change and other environmental factors to the runoff variation in the two regions, and the similarities and differences in the driving mechanisms of runoff change in the two regions were explored further. First, the change characteristics of precipitation, potential evapotranspiration, and runoff were analyzed through the observational data of the basin. Then, considering the non-linearity and non-stationarity of the runoff series, a heuristic segmentation algorithm method was used to divide the entire study period into natural and impacted periods. Finally, the effects of climate change and other environmental factors on runoff variation in two regions were evaluated comprehensively using three methods, including the improved double mass curve (IDMC), the slope change ratio of cumulative quantity (SCRCQ), and the Budyko-based elasticity (BBE). Results indicated that the annual precipitation and potential evapotranspiration increased during the study period in the two regions. However, the runoff increased in the SRYZ and decreased in the SRYR. The intra-annual distribution of the runoff in the SRYZ was unimodal during the natural period and bimodal in the SRYR. The mutation test indicated that the change points of annual runoff series in the SRYZ and SRYR occurred in 2004 and 1989, respectively. The attribution analysis methods yielded similar results that climate change had the greatest effect on the runoff variation in the SRYZ, with a contribution of 59.6%~104.6%, and precipitation contributed 65.3%~109.6% of the increase in runoff. In contrast, the runoff variation in the SRYR was mainly controlled by other environmental factors such as permafrost degradation, land desertification, and human water consumption, which contributed 83.7%~96.5% of the decrease in the runoff. The results are meaningful for improving the efficiency of water resources utilization in the SRYZ and SRYR. [ABSTRACT FROM AUTHOR]

The Yellow River Basin is an important economic belt and key ecological reservation area in China. In the context of global warming, it is of great significance to project the drought disaster risk for ensuring water security and improving water resources management measures in practice. Based on the five Global Climate Models (GCMs) projections under three scenarios of the Shared Socioeconomic Pathways (SSP) (SSP126, SSP245, SSP585) released in the Sixth Coupled Model Intercomparison Project (CMIP6), this study analyzed the characteristics of meteorological drought in the Yellow River Basin in combination with SPEI indicators over 2015–2100. The result indicated that: (1) The GCMs from CMIP6 after bias correction performed better in reproducing the spatial and temporal variation of precipitation. The precipitation in the Yellow River Basin may exhibit increase trends from 2015 to 2100, especially under the SSP585 scenario. (2) The characteristics of meteorological drought in the Yellow River Basin varied from different combination scenarios. Under the SSP126 scenario, the meteorological drought will gradually intensify from 2040 to 2099, while the drought intensity under SSP245 and SSP585 scenarios will likely be higher than SSP126. (3) The spatial variation of meteorological drought in the Yellow River Basin is heterogeneous and uncertain in different combination scenarios and periods. The drought tendency in the Loess Plateau will increase significantly in the future, and the drought frequency and duration in the main water conservation areas of the Yellow River Basin was projected to increase. [ABSTRACT FROM AUTHOR]

In order to systematically analyze the impacts of climate change and human activities on runoff, this paper takes the Zhanghe River Basin, which is greatly affected by human activities, as the research object, constructs an attribution analysis model of runoff changes based on historical data and the SWAT (Soil and Water Assessment Tool) model. The results show that the runoff of the watershed has significantly decreased in the past 60 years, in which the contribution rate of climate change is 36.2% and that of human activities is 63.8%. Among the climate change factors, precipitation is the main contributing factor and canal diversion is the main contributing factor among human activities. In addition, with the decrease in precipitation during the flood season and the increase in the crop planting area in the catchment, the distribution of canal water diversion has also changed, and the water consumption of summer crops has gradually become the main factor affecting canal water diversion. [ABSTRACT FROM AUTHOR]

In addition to agriculture, the water–land nexus (WLN) also profoundly affects the sustainable development of industry and residents' lives. However, little research has been designed to assess the water–land nexus from the perspective of industry development and people's quality of life. In the current paper, Wi, a regional industrial water–land nexus matching index, and Wd, a matching index of the domestic water–land nexus, were proposed for evaluating the water–land nexus from the industry development and quality of life perspectives separately in the current paper. Furthermore, climate change and human activities have significant impacts on the water–land nexus. The WLNs were assessed spatially and temporally for the first time based on these two indexes in 128 municipalities in the Huang-Huai-Hai River Basin of China from 1951 to 2017 to analyze the impacts of the changing environment on them. The impact of changing environment was explored based on changes of some climate factors and land use. The value of Wi are higher in the eastern and southern cities than the western and northern cities, while Zhenjiang city in Jiangsu Province has the highest Wi. For Wd, there are two low Wd zones across the basin, while the minimum values occurred in Linxia Hui Autonomous Region (Wd = 35.34 mm). Wi and Wd in most cities in the basin showed a significant downward trend, and some cities in the southwest of the basin have the fastest-decreasing of Wd. Wt and Wa were also calculated to assess the total and agricultural water–land nexus separately based on existing research. The Wt for the Huang-Huai-Hai River Basin gradually increases from northwest to southeast, and its spatial distribution characteristics are similar to precipitation in the river basin. In addition, the government should simultaneously implement water transfer plans to reduce the agricultural water pressure in Ningxia and Gansu provinces. Dynamic driving factors of change of the four assessment indexes (Wt, Wa, Wi, Wd) are briefly analyzed in the end of the paper. [ABSTRACT FROM AUTHOR]

This paper looks at regional water security in eastern China in the context of global climate change. The response of runoff to climate change in the Qinhuai River Basin, a typical river in eastern China, was quantitatively investigated by using the Soil and Water Assessment Tool (SWAT) model and the ensemble projection of multiple general circulation models (GCMs) under three different shared socioeconomic pathways (SSPs) emission scenarios. The results show that the calibrated SWAT model is applicable to the Qinhuai River Basin and can accurately characterize the runoff process at daily and monthly scales with the Nash–Sutcliffe efficiency coefficients (NSE), correlation coefficients (R), and the Kling–Gupta efficiency (KGE) in calibration and validation periods being above 0.75 and relative errors (RE) are ±3.5%. In comparison to the baseline of 1980–2015, the mean annual precipitation in the future period (2025–2060) under the three emission scenarios of SSP1-2.6, SSP2-4.5, and SSP5-8.5 will probably increase by 5.64%, 2.60%, and 6.68% respectively. Correspondingly, the multiple-year average of daily maximum and minimum air temperatures are projected to rise by 1.6–2.1 °C and 1.4–2.0 °C, respectively, in 2025–2060. As a result of climate change, the average annual runoff will increase by 16.24%, 8.84%, and 17.96%, respectively, in the period of 2025–2060 under the three SSPs scenarios. The increase in runoff in the future will provide sufficient water supply to support socioeconomic development. However, increases in both rainfall and runoff also imply an increased risk of flooding due to climate change. Therefore, the impact of climate change on flooding in the Qinhuai River Basin should be fully considered in the planning of flood control and the basin's development. [ABSTRACT FROM AUTHOR]

The South-to-North Water Diversion Project (SNWDP) is a national strategic project for water shortages in northern China. Climate change will affect the availability of water resources in both source and receiving areas. A grid-based RCCC-WBM model based on climate projections from nine Global Climate Models under SSP2-4.5 was used for analyzing the changes in temperature, precipitation, and streamflow in the near future (2025–2045, NF) and far future (2040–2060, FF) relative to the baseline (1956–2000). The results showed that: (1) the temperature of the western route will increase significantly in the NF and FF with an extent of 1.6 °C and 2.0 °C, respectively, (2) precipitation will very likely increase even though Global Climate Model (GCM) projections are quite dispersed and uncertain, and (3) over half of the GCMs projected that streamflow of receiving area will slightly increase with a rate of 1.68% [−8.67%, 12.3%] and 2.78% [−3.30%, 11.0%] in the NF and FF, respectively. Climate change will support the planning of the western route to a certain extent. However, water supply risk induced by the extreme situation of climate change should be paid adequate consideration when the project operates in practice due to the large dispersion and uncertainty of GCM projections. [ABSTRACT FROM AUTHOR]

Documenting year-to-year variations in carbon-sequestration potential in terrestrial ecosystems is crucial for the determination of carbon dioxide (CO2) emissions. However, the magnitude, pattern and inner biomass partitioning of carbon-sequestration potential, and the effect of the changes in climate and CO2 on inner carbon stocks, remain poorly quantified. Herein, we use a spatially explicit individual based-dynamic global vegetation model to investigate the influences of the changes in climate and CO2 on the enhanced carbon-sequestration potential of vegetation. The modelling included a series of factorial simulations using the CRU dataset from 1916 to 2015. The results show that CO2 predominantly leads to a persistent and widespread increase in above-ground vegetation biomass carbon-stocks (AVBC) and below-ground vegetation biomass carbon-stocks (BVBC). Climate change appears to play a secondary role in carbon-sequestration potential. Importantly, with the mitigation of water stress, the magnitude of the above- and below-ground responses in vegetation carbon-stocks gradually increases, and the ratio between AVBC and BVBC increases to capture CO2 and sunlight. Changes in the pattern of vegetation carbon storage was linked to regional limitations in water, which directly weakens and indirectly regulates the response of potential vegetation carbon-stocks to a changing environment. Our findings differ from previous modelling evaluations of vegetation that ignored inner carbon dynamics and demonstrates that the long-term trend in increased vegetation biomass carbon-stocks is driven by CO2 fertilization and temperature effects that are controlled by water limitations. [ABSTRACT FROM AUTHOR]

Climate change and local human activities are regarded as the two main factors influencing runoff. Using observed runoff, there is a statistically significant decreasing trend for annual and monthly runoff detected by the Mann-Kendall's test, in the upper reaches of Luanhe River basin (URLRB), 1954–2000. With the break point analysis, the whole time series are divided into two sub periods: "natural period (1954–1970) and "impact period" (1971–2000). "Natural runoff" from 1954 to 2000, is reconstructed by the variable infiltration capacity (VIC) model, in which the model parameters are calibrated in "natural period" representing the natural watershed characteristics without the impact of local human activities. By comparing the difference between observed runoff and "natural runoff" in "impact period", the contributions of climate change and local human activities are quantitatively separated. The results indicate that climate change and local human activities account for 49% and 51%, respectively, on the annual runoff decrease in the URLRB. That means the effects of climate change on runoff are roughly the same as the effects of local human activities. Climate change results in decrease in monthly runoff; and local human activities mainly affect flood season runoff. The results could be a reference for water resources projection and management in the URLRB and other catchments in northern China. [ABSTRACT FROM AUTHOR]

The streamflows in many rivers have been detected to be declining recently due to environmental changes, which are dominating water management strategies and affecting water security. The decline was usually ended up with attribution to climate change and underlying surface changes, without further exploring the effects of natural and anthropogenic components in climate. It might lead to overestimation for human-induced climate change impacts and inappropriate adaptation. The identification of the anthropogenic elements in streamflow change is very crucial and increasingly required by water management planning, climate mitigation and adaptation actions. A novel framework is proposed for streamflow change attribution in terms of three sources of natural climate variability (NCV), anthropogenic climate change (ACC) and the underlying surface changes in basins. The results suggest that the role of the underlying surface changes in basins overwhelms that of climate change in the recent historical period. However, the natural climate variability could not be neglected since it may play the dominant role in streamflow change, compared with that of the anthropogenic climate change. The results also highlight that we need to clarify the effects of human-induced climate change and the underlying surface changes, which are the goals of climate change adaptation and mitigation. The uncertainties of the attribution are analyzed in contrast with other attribution work in the same study case, and the sources are presented explicitly. The conclusion could facilitate a better understanding of the hydrological processes as a result of environmental changes and provide an efficient reference for administrators and decision makers. [ABSTRACT FROM AUTHOR]

ABSTRACT Drought episode identification and its severity characterization are crucial to evaluate and reduce the risk of drought disaster. The Standardized Precipitation Evapotranspiration Index ( SPEI) with two different potential evapotranspiration formulations, i.e. the Thornthwaite and Penman-Monteith equations, (denoted as SPEI-Th and SPEI-Pm, respectively) are two popular drought indices used today. These two SPEI versions have the limitations of overestimation of drought (as a response to global warming) and high data requirements, respectively. A new SPEI variant was developed with precipitation and pan evaporation ( Epan) as its inputs (denoted as SPEI-Pe), which overcomes the shortcomings of SPEI-Pm and SPEI-Th. Climatic data at ground stations in the Yunnan Province ( YP) of China were collected to validate this new SPEI variant with SPEI-Pm as the standard measure. Month-by-month comparison of SPEIs suggested that SPEI-Pe had a better agreement with the SPEI-Pm standard than SPEI-Th, with the criterion measures of mean absolute error and refined index of agreement ( dr). The sensitivity analysis showed that two energy variables, net and global radiation are the most influential factors for evapotranspiration, and for SPEI-Pm and differences between SPEI-Pm and other two variants too. The validity of SPEI-Pe was also tested against the historical drought records in YP. Results demonstrated that SPEI-Pe generally agreed with historical drought events at different durations with only several exceptions, and thus it had a comparable performance to identify drought episodes with the other two SPEI variants in YP. The results suggest that SPEI-Pe has a better agreement with SPEI-Pm than SPEI-Th, and that it provides a good replacement for the standard measure when underlying climatic data (especially the energy variables) are not available. [ABSTRACT FROM AUTHOR]

Global warming brings a huge challenge to society and human being. Understanding historic and future potential climate change will be beneficial to regional crop, forest, and water management. This study aims to analyze the precipitation and temperature changes in the historic period and future period 2021-2050 in the Xiangjiang River Basin, China. The Mann-Kendall rank test for trend and change point analysis was used to analyze the changes in trend and magnitude based on historic precipitation and temperature time series. Four global climate models (GCMs) and a statistical downscaling approach, LARS-WG, were used to estimate future precipitation and temperature under RCP4.5. The results show that annual precipitation in the basin is increasing, although not significant, and will probably continue to increase in the future on the basis of ensemble projections of four GCMs. Temperature is increasing in a significant way and all GCMs projected continuous temperature increase in the future. There will be more extreme events in the future, including both extreme precipitation and temperature. [ABSTRACT FROM AUTHOR]

This study presents models for predicting hourly canopy resistance ( r) and evapotranspiration (ET) based on Penman-Monteith approach. The micrometeorological data and ET were observed during maize and buckwheat growing seasons in 2006 and 2009 in China and Japan, respectively. The proposed models of r were developed by a climatic resistance ( r) that depends on climatic variables. Non-linear relationships between r and r were applied. The measured ET using Bowen ratio energy balance method was applied for model validation. The statistical analysis showed that there were no significant differences between predicted ET by proposed models and measured ET for both maize and buckwheat crops. The model for predicting ET at maize field showed better performance than predicting ET at buckwheat field, the coefficients of determination were 0.92 and 0.84, respectively. The study provided an easy way for the application of Penman-Monteith equation with only general available meteorological database. [ABSTRACT FROM AUTHOR]

Water resource assessment on climate change is crucial in water resource planning and management. This issue is becoming more urgent with climate change intensifying. In the current research of climate change impact, climate natural variability (fluctuation) has seldom been studied separately. Many studies keep attributing all changes (e.g. runoff) to climate change, which may lead to wrong understanding of climate change impact assessment. Because of lack of long enough historical series, impacts of climate variability have been always avoided deliberately. Based on Latin hypercube sampling technique, a block sampling approach was proposed for climate variability simulation in this study. The widely used time horizon (1961-1991) was defined as baseline period, and the runoff variation probability affected by climate natural variability was analysed. Allowing for seven future climate projections in total of three GCMs (CSIRO, NCAR, and MPI) and three emission scenarios (A1B, A2, and B1), the impact of future climate change on water resources was estimated in terms of separating the contribution from climate natural variability. Based on the analysis of baseline period, for the future period from 2021 to 2051, the impact of climate natural variability may play a major part, whereas for the period from 2061 to 2091, climate change attributed to greenhouse gases may dominate the changing process. The results show that changes from climate variability possess a comparable magnitude, which highlights the importance to separate impacts of climate variability in assessing climate change, instead of attributing all changes to climate change solely. Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Using the defined sensitivity index, the sensitivity of streamflow, evapotranspiration and soil moisture to climate change was investigated in four catchments in the Haihe River basin. Climate change contained three parts: annual precipitation and temperature change and the change of the percentage of precipitation in the flood season ( Pf). With satisfying monthly streamflow simulation using the variable infiltration capacity model, the sensitivity was estimated by the change of simulated hydrological variables with hypothetical climatic scenarios and observed climatic data. The results indicated that (i) the sensitivity of streamflow would increase as precipitation or Pf increased but would decrease as temperature increased; (ii) the sensitivity of evapotranspiration and soil moisture would decrease as precipitation or temperature increased, but it to Pf varied in different catchments; and (iii) hydrological variables were more sensitive to precipitation, followed by Pf, and then temperature. The nonlinear response of streamflow, evapotranspiration and soil moisture to climate change could provide a reference for water resources planning and management under future climate change scenarios in the Haihe River basin. Copyright © 2011 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Abstract: Recently, runoff in many river basins in China has been decreasing. Therefore, the role that climate change and human activities are playing in this decrease is currently of interest. In this study, we evaluated an assessment method that was designed to quantitatively separate the effects of climate change and human activities on runoff in river basins. Specifically, we calibrated the SIMHYD rainfall runoff model using naturally recorded hydro-meteorologic data pertaining to the Sanchuanhe River basin and then determined the effects of climate change and human activities on runoff by comparing the estimated natural runoff that occurred during the period in which humans disturbed the basin to the runoff that occurred during the period prior to disturbance by humans. The results of this study revealed that the SIMHYD rainfall runoff model performs well for estimating monthly discharge. In addition, we found that absolute runoff reductions have increased in response to human activities and climate change, with average reductions of 70.1% and 29.9% in total runoff being caused by human activities and climate change, respectively. Taken together, the results of this study indicate that human activities are the primary cause of runoff reduction in the Sanchuanhe River basin. [ABSTRACT FROM AUTHOR]

Vegetation is seen as a sensitive indicator of global change because of its crucial role in connecting the atmosphere, soil, and water. Fractional vegetation cover (FVC), in turn, is an important indicator of vegetation status. Qingyang is a typically ecologically sensitive region, with a range of changes in vegetation in the last decade as a result of climatic and non-climatic factors. However, the exact impact of climate change and human activities remains unclear. Satellite observations can help to clarify that impact, allowing us to assess trends in vegetation change in the last two decades (2000–2019). In this study, daily and composite time series vegetation variations were derived from moderate resolution imaging spectroradiometer (MODIS) data and the impact of climate and human activity factors was examined for different administrative districts. By deploying multiple regression models, the research revealed that human activity has contributed 46% to the FVC variation, while the remaining 54% was led by climate factors. In areas where FVC was increasing, human activity contributed 55.89% while climate factors contributed 44.11%. In areas where FVC was decreasing, human activity and climate factors contributed 24.58% and 75.42%, respectively. The study also looks at the impacts of El Nino/IOD events in FVC dynamics in the study site. The FVC inversion result from MODIS proved capable of capturing long-term and seasonal vegetation patterns and thus provide a valuable archive for decadal-scale vegetation dynamics in the study area. Moreover, the improvement in FVC was a dual effect of climatic and human activities, while the latter owns a higher contribution especially for the implementation of ecological construction projects. [ABSTRACT FROM AUTHOR]

The global water cycle is becoming more intense in a warming climate, leading to extreme rainstorms and floods. In addition, the delicate balance of precipitation, evapotranspiration, and runoff affects the variations in soil moisture, which is of vital importance to agriculture. A systematic examination of climate change impacts on these variables may help provide scientific foundations for the design of relevant adaptation and mitigation measures. In this study, long-term variations in the water cycle over China are explored using the Regional Climate Model system (RegCM) developed by the International Centre for Theoretical Physics. Model performance is validated through comparing the simulation results with remote sensing data and gridded observations. The results show that RegCM can reasonably capture the spatial and seasonal variations in three dominant variables for the water cycle (i.e., precipitation, evapotranspiration, and runoff). Long-term projections of these three variables are developed by driving RegCM with boundary conditions of the Geophysical Fluid Dynamics Laboratory Earth System Model under the Representative Concentration Pathways (RCPs). The results show that increased annual average precipitation and evapotranspiration can be found in most parts of the domain, while a smaller part of the domain is projected with increased runoff. Statistically significant increasing trends (at a significant level of 0.05) can be detected for annual precipitation and evapotranspiration, which are 0.02 and 0.01 mm/day per decade, respectively, under RCP4.5 and are both 0.03 mm/day per decade under RCP8.5. There is no significant trend in future annual runoff anomalies. The variations in the three variables mainly occur in the wet season, in which precipitation and evapotranspiration increase and runoff decreases. The projected changes in precipitation minus evapotranspiration are larger than those in runoff, implying a possible decrease in soil moisture. [ABSTRACT FROM AUTHOR]

Conducting water resource assessment and forecasting at a basin scale requires effective and accurate simulation of the hydrological process. However, intensive, complex human activities and environmental changes are constraining and challenging the hydrological modeling development and application by complicating the hydrological cycle within its local contexts. Six sub-catchments of the Yellow River basin, the second-largest river in China, situated in a semi-arid climate zone, have been selected for this study, considering hydrological processes under a natural period (before 1970) and under intensive human disturbance (2000–2013). The study aims to assess the capacity and performance of the hydrological models in simulating the discharge under a changing environment. Four well-documented and applied hydrological models, i.e., the Xin'anjiang (XAJ) model, GR4J model, SIMHYD model, and RCCC-WBM (Water Balance Model developed by Research Center for Climate Change) model, were selected for this assessment. The results show that (1) the annual areal temperature of all sub-catchments presented a significant rising trend, and annual precipitation exhibited insignificant decline trend; (2) as a result of climate change and intensive human activities, the annual runoff series showed a declining trend with abrupt changes mostly occurring in the 1980s with the exception of the Tangnaihai station; (3) the four hydrological models generally performed well for runoff simulation for all sub-catchments under the natural period. In terms of Nash–Sutcliffe efficiency coefficient, the XAJ model worked better in comparison to other hydrological models due to its detailed representations and complicated mechanism in runoff generation and flow-routing scheme; (4) environmental changes have impacted the performance of the four hydrological models under all sub-catchments, in particularly the Pianguan River catchment, which is could be attributed to the various human activities that in turn represent more complexity for the regional hydrological cycle to some extent, and reduce the ability to predict the runoff series; (5) the RCCC-WBM model, well known for its simple structure and principles, is considered to be acceptable for runoff simulation for both natural and human disturbance periods, and is recommended for water resource assessment under changing environments for semi-arid regions. [ABSTRACT FROM AUTHOR]

Attributing runoff change to different drivers is vital in order to better understand how and why runoff varies, and to further support decision makers on water resources planning and management. Most previous works attributed runoff change in the arid or semi-arid areas to climate variability and human activity on an annual scale. However, attribution results may differ greatly according to different climatic zones, decades, temporal scales, and different contributors. This study aims to quantitatively attribute runoff change in a humid subtropical basin (the Qingliu River basin, East China) to climate variability, land-use change, and human activity on multiple scales over different periods by using the Soil and Water Assessment Tool (SWAT) model. The results show that runoff increased during 1960–2012 with an abrupt change occurring in 1984. Annual runoff in the post-change period (1985–2012) increased by 16.05% (38.05 mm) relative to the pre-change period (1960–1984), most of which occurred in the winter and early spring (March). On the annual scale, climate variability, human activity, and land-use change (mainly for forest cover decrease) contributed 95.36%, 4.64%, and 12.23% to runoff increase during 1985–2012, respectively. On the seasonal scale, human activity dominated runoff change (accounting for 72.11%) in the dry season during 1985–2012, while climate variability contributed the most to runoff change in the wet season. On the monthly scale, human activity was the dominant contributor to runoff variation in all of the months except for January, May, July, and August during 1985–2012. Impacts of climate variability and human activity on runoff during 2001–2012 both became stronger than those during 1985–2000, but counteracted each other. The findings should help understandings of runoff behavior in the Qingliu River and provide scientific support for local water resources management. [ABSTRACT FROM AUTHOR]

Abstract In this study, we introduce a data stream method for dynamic runoff simulation, which allows capturing the evolving relationship between runoff and its impact factors (e.g., temperature, rainfall). The basic idea is to view continuously arriving data of runoff and its impact factors as a data stream, and dynamically learn its relationship. To validate the effectiveness of the proposed method, we compare its performance with that of three data driven models (ANN, SVR, Random Forest) and six representative hydrological models (SWAT, AWBM, SimHyd, SMAR, Sacramento, and Tank) in simulating monthly runoff. The proposed method performs well with the best NSE of 0.88, being superior to comparable models. Furthermore, the data stream model also shows its advantage in the flexibility of combing various impact factors of runoff into the model. The findings demonstrate that the data stream method provides a promising way to dynamically simulate runoff in a changing environment. Graphical abstract Image Highlights • An instance-based data stream method is introduced for dynamic runoff simulation. • The proposed method outperforms comparable data-driven and hydrological models. • It provides a useful tool for runoff simulation in a changing environment. • It is flexible to integrate various impact factors of runoff into runoff simulation. [ABSTRACT FROM AUTHOR]

• Reveal spatial and upstream–downstream patterns of runoff change drivers in eastern Tibetan Plateau for the first time. • Climate change dominant runoff trend and change in eastern Qinghai-Tibetan Plateau. • Quantitatively explained climatic and underlying surface conditions change contributed to runoff change. • Both hydrological model and Budyko framework were employed for robust results. Quantitatively identifying the impact of climatic and underlying surface condition changes on runoff is crucial for the efficient utilization of water resources and understanding hydroclimatic variability processes. This study aims to employ both Grid-RCCC-WBM model and Fu's equation based on Budyko hypothesis to quantitatively analyze the spatial patterns of runoff changes, driving forces, and upstream–downstream relationships in ten typical basins across the eastern Qinghai-Tibet Plateau (QTP) for the first time. Breaks for Additive Season and Trend method was used to detect breakpoints in runoff series and both hydrological model and Budyko equation categorized driving forces of runoff change into change in climatic (including precipitation and potential evaporation) and underlying surface conditions. The results indicated (i) significant abrupt changes in the runoff time series around 1998, with runoff increasing in all basins except for the source region of the Yellow River. (ii) significant upstream–downstream differences in the trend and magnitude of runoff changes between breakpoints in the Yangtze and Lancang Rivers over the past 20 years, and (iii) significant runoff response to climate variability after the breakpoints in the source region of the Yangtze and Yellow river. Our findings revealed that, contrary to the backdrop of decreasing precipitation, the upstream basins maintained increasing runoff relying on permafrost and glacier meltwater, while the downstream basins exhibited decreasing trend. The differences in runoff changes after the detected breakpoints were dominated by changes in underlying surface conditions, with the highest contribution rates observed in the Dajin (494 %), Lanzhou (398%), and Tangnaihai (197%) basins. This study involved both spatial pattern and upstream–downstream relationship of runoff change that can be widely applied to other large-scale regions and especially holds important implications for the scientific and rational utilization of water resources in the QTP. [ABSTRACT FROM AUTHOR]

Considering the impact of climate change and human activity, hydrological projection in the Miyun Reservoir basin (MYRB) was estimated by the Variable Infiltration Capacity (VIC) model with the output from NCAR-CCSM3 under A1B, A2, and B1 scenarios in 2010–2099. Climate change was the change of temperature and precipitation; and human activity included water withdrawal from river, hydraulic projects, land use/covers change, etc. The VIC model parameters were calibrated in “natural period” without the impact of human activity, i.e., before the breakpoint of the precipitation-runoff double cumulative curve. In order to consider the impact of human activity, the Hydrological Projection Revision Formula was constructed to revise the hydrological projection in two catchments (Xiakuai and Zhangjiafen catchment) covering most parts of the MYRB. Based on the output from NCAR-CCSM3, the MYRB would become warmer and wetter in future climate change scenarios. The results indicated that there might be a slight decreasing trend for runoff in 2020s (2010–2039), but the runoff would increase in 2050s (2040–2069) and 2080s (2070–2099) in MYRB under three climate change scenarios. For example, in 2050s the runoff might increase by 35.2–90.4% and 14.3–51.6% in Xiakuai and Zhangjiafen catchment, respectively, compared to the baseline period (1961–1999). Meantime, a high uncertainty for hydrological projection in MYRB should be focused, because only one GCM was used in this study. [ABSTRACT FROM AUTHOR]

Climate change impact assessment on runoff plays a key role for catchment-scale water resources planning and adaptation. Quantification of impacts on water resources modeling at the catchment-scale is characterized by uncertainties of hydrological model parameters, emission scenarios, and global climate model outputs (including the downscaling techniques). The hydrological parameter uncertainty may show the different magnitude with that of Global Climate Models (GCMs). Much less systematic work has been done to estimate climatic uncertainty and to assess the climatic and hydrologic model outputs within an uncertainty perspective. In this study, based on the Generalized Likelihood Uncertainty Estimation (GLUE) methodology, a systematic uncertainty analysis framework is proposed in terms of a comparable variable. Climatic uncertainty was involved in an ensemble manner through combination of the results from emission scenarios A1B, A2 and B1 and global climate models (CSIRO, NCAR, MPI). The biases of downscaled temperature and precipitation simulations from GCMs were processed by a delta change approach method. Addressing into TOPMODEL, it was analyzed for the future runoff variation and uncertainties impact by climate change. The results indicate uncertainties introduced by different sources lie in different magnitudes, which highlights the new challenges to cope with the multi-scales uncertainty in decision-making process. [ABSTRACT FROM AUTHOR]

Summary: Climate variability and human activities are regarded as the two driving factors for the hydrological cycle change. In the last several decades, there were statistically significant decreasing trends for streamflow and precipitation, but an increasing trend for mean temperature in the Haihe River basin (HRB). The attribution of climate variability and human activities for streamflow decrease was quantitatively assessed in three catchments located in different parts of the HRB. They are the Taolinkou catchment in the Luanhe River, Zhangjiafen catchment in the north of Haihe River, and Guantai catchment in the south of Haihe River. Based on the break point of streamflow, the whole period was divided into two periods: “natural period” (before the break point) and “impacted period” (after the break point). Using the Variable Infiltration Capacity (VIC) model calibrated in the “natural period”, the “natural streamflow” without the impact of human activities was reconstructed for the whole period. The differences of the “natural streamflow” between the “natural period” and “impacted period” indicated the impact of climate variability on streamflow decrease. The remaining contribution to streamflow decrease was made by human activities. The results indicated that the decrease of streamflow between the two periods could be attributed to 58.5% (41.5%), 40.1% (59.9%), and 26.1% (73.9%) from climate variability (human activities) in the Taolinkou, Zhangjiafen and Guantai catchment, respectively. That was to say, climate variability was the major driving factor for the streamflow decrease in the Taolinkou catchment; on the other hand, human activities was the main driving factor for the streamflow decrease in the Zhangjiafen and Guantai catchment. [Copyright &y& Elsevier]

• The NDVI is simulated based on ensemble modelling using climatic factors and landuse. • The NDVI increases by 3.03%–5.79% as an one °C increase in temperature in the YHHRB. • The NDVI increase by 3.35%–4.80% as a 10% increase in precipitation in the YHHRB. • Landuse has a pronounced effect on the sensitivity of NDVI to climate change. As a critical factor of earth's ecosystem, vegetation is sensitive to climate change and its feedback has a pronounced effect on climate, hydrology, and ecology, etc. The quantitative sensitivity of Normalized Difference Vegetation Index (NDVI) to climate change has been investigated in the Yellow-Huai-Hai River Basin (YHHRB) covering multiple climatic zones. Based on multicollinearity test using the Variance Inflation Factor, four climatic factors and six landuse types were used as independent variables for NDVI simulation. The calibrated and validated statistical vegetation models denoted good performance using four machine learning algorithms. The ensemble results from the four machine learning modelling were used to assess the sensitivity of NDVI to temperature and precipitation change on annual and monthly scale. Based on historical climatic variability and future scenarios, eight hypothetical climatic scenarios for the changes in temperature and precipitation were used in this study. The results indicated that there were positive responses of NDVI to temperature and precipitation change. As an one °C increase in temperature, the NDVI was going to increase by 3.03%–5.79%, and it would increase by 3.35%–4.80% when the precipitation increased 10% in the YHHRB. Relatively, the NDVI was more sensitive to precipitation decrease than increase. The sensitivity of NDVI to temperature or precipitation was non-linear as temperature or precipitation changing for a specified climatic zone. Monthly, the sensitivity of NDVI to temperature change varied among the four climatic zones, but as precipitation increasing, the higher and lower sensitivity of NDVI were investigated in wetter and drier months, respectively. Spatially, the NDVI was more sensitive to temperature and precipitation in colder and drier areas, respectively. Landuse also has a significant impact on the sensitivity of NDVI to climate change. The results might be useful for understanding the climate-vegetation dynamics and landuse management under future climate change. [ABSTRACT FROM AUTHOR]

This study investigates Holocene sedimentary evolution and hypoxia development using borehole cores CJK06 and CJK09, in combination with other published core data. Based on lithology and microfossil (benthic foraminifera) characteristics, seven types of sedimentary facies were identified from the base upward: river, tidal flat, tide-influenced river, transgressive lag, estuary, inner-shelf, and prodelta. Isochronous correlation among the cores was established relying on accelerator mass spectrometry 14C dates. Facies succession indicates that a weak progradation occurred in coastal environments (12–10 ka BP) due to the Younger Dryas-induced deceleration of sea-level rise; rapid deposition locally occurred in the southern marginal area of tide-dominated estuary environments (10–8 ka BP), likely due to the junction of the Yangtze and Qiantangjiang River currents; and marine current-induced fluid mudflows prevailed in the shallow marine environments (8–1 ka BP), with the cooling climates of 5–1 ka BP. Furthermore, prodelta and shallow marine environments co-occurred with an uneven progradation of the delta within the last 1 ka, while deposition occurred just inside the more southern, delta-influenced area. The occurrence of euryhaline benthic foraminifera suggests that an enhanced freshwater discharge of the mid-Holocene (8–5 ka BP) was followed by a sharp decline in the late Holocene (5–1 ka BP) with climate change. The occurrence of cold-water benthic foraminifera indicates a severe cold-water condition during the mid-Holocene due to the intrusion of upwelling currents triggered by the propelling force of warm currents and summer monsoon winds. In addition, the occurrence of low-oxygen foraminiferal assemblages reveals that hypoxia has developed since 10 ka BP in stages consistent with the sedimentary evolution: localized hypoxia formation coincident with the southern depocenter during the early Holocene (10–8 ka BP); severe hypoxia with enhanced freshwater discharge and upwelling current intrusion during the mid-Holocene; and weakened hypoxia of the late Holocene, mainly due to the sharp decline in freshwater discharge. Within 1 ka BP, freshwater discharge from the approaching river mouth and increased nutrient inputs from enhanced human activities on land have contributed to the prevalence of hypoxia, especially in the southern deltaic area. Overall, it was revealed that the freshwater discharge modulated with climate variations and delta progradation plays a primary role in controlling the sedimentary evolution and hypoxia development during the mid-late Holocene. • Gravity flows (fluid mudflow) prevailed during the late Holocene (5–1 ka BP). • Holocene freshwater discharge was enhanced (8–5 ka BP) and then sharply declined. • Severe upwelling current intrusion occurred during the mid-Holocene (8–5 ka BP). • Hypoxia boomed during the mid-Holocene (8–5 ka BP). [ABSTRACT FROM AUTHOR]

• Based on 26 GCMs and the calibrated VIC hydrological model, the impact of global warming 1.5℃ and 2.0℃ on China's hydroclimate status is projected. • Using the quadrantal classification of flood and drought changes, the future changes in China's water cycle state are analyzed. • Floods and droughts in China are expected to further intensify under global warming. Global warming has been shown to have a profound impact on hydrological process, especially on hydrological extremes. To avoid the potential risk of extreme hazards, it is essential to project changes in hydroclimatic extremes under the 1.5℃ and 2.0℃ targets of the Paris Agreement, especially in China, which is geographically, climatologically, economically, and socially complex. Here, this study projects future changes in hydroclimatic extremes in China under 1.5℃ and 2.0℃ warming targets based on a distributed hydrological model driven by an ensemble of downscaled general circulation models. The study shows that global warming of 1.5℃ and 2.0℃ would perceptibly affect the spatial patterns of extreme rainfall and extreme heat in China. The intensification of events such as extreme rainfall, meteorological drought, and extreme heat would intensify the hydrological extremes, including floods and hydrological droughts. The risk of future extreme floods and hydrological droughts will increase simultaneously, with a 34.6% (38.0%) probability of acceleration (more severe floods and droughts) in a 1.5℃ (2.0℃) warming world. Correspondingly, global warming tends to exacerbate the water cycle, with a 92.5% (94.2%) probability that at least one extreme event will exhibit intensification characteristics in the 1.5℃ (2.0℃) warming scenario. The acceleration of the water cycle and the intensification of the hydrological extremes may have adverse impacts on the balanced development of China's ecological and economic society. [ABSTRACT FROM AUTHOR]

The Lancang-Mekong River is the most important international river in Southeast Asia, and its water resources are invaluable for the survival of the inhabitants of the basin, while the climatic conditions have a significant impact on the production and livelihoods of the riparian countries. In this study, future climate change in the Lancang-Mekong River Basin (LMRB) was projected based on precipitation and temperature from CMIP6. First, a bias processing procedure was established to correct the initial bias of climate models using the Daily Bias Correction (DBC) method, and the performance of equal weighted averaging (EW) and Bayesian mode averaging (BMA) of multi-model ensembles was compared. The characteristics of future precipitation and temperature changes were projected in terms of mean climatology, seasonal variation and extreme events, respectively, from which the future trends of the four weather extremes (dry-cold, dry-hot, wet-cold and wet-hot) were projected. Evaluation based on mean climatology, daily frequency distribution, temporal change and its bias showed that the climate bias correction procedure has good performance. It was found that future precipitation in the LMRB will increase by 50–120 mm in the near future (2031–2050) and 150–400 mm in the far future (2061–2090), with higher increases in the upper Mekong River Basin (MRB), Lower MRB and Mekong Delta than in the Lancang River Basin (LRB) and middle MRB. Future increase in precipitation will occur mainly from June to October, while April and May will see a decrease by 10–30 mm, and the number of heavy precipitation days (R25, daily precipitation exceeding 25 mm) will increase by about 5 days in the eastern part of the lower and middle MRB. The mean temperature will increase by 1–3 °C in most parts of the LMRB, with the LRB experiencing an increase of about 3 °C higher than in the MRB. Future maximum and minimum daily temperatures will increase by 1–2 °C in the near future and by 2–5 °C in the far future. Dry-hot days will increase by about 20 days in the lower and middle MRB, and wet-hot days will increase significantly in the MRB, by 30–80 days in the near future and by 50–100 days in the far future. • Comprehensive projection of future climate changes in the Lancang-Mekong River Basin based on the CMIP6 model. • Future precipitation increase in the Lancang-Mekong River Basin will mainly occur in June–October. • The average temperature in most parts of the Lancang-Mekong River Basin will increase by 1–3 °C in the future. • The number of wet-hot days in the Mekong River Basin will increase by >100 days in 2061–2090. [ABSTRACT FROM AUTHOR]

• Understanding future change with the aspects of runoff and hydroclimatic conditions. • Source region of Yangtze River will be warmer and wetter in the future. • Runoff will increase by around 15% with highly spatial heterogeneity. Exploring the future hydroclimatic conditions of source region of Yangtze River (SRYaR), an alpine affected by climate change significantly, is essential for basin water resources management and development ss global climate change intensifies and the process of climate warming and humidification in Northwest China. This study proposed a practical framework for assessing water resource response to the context of climate changes in alpine catchments from the respective of both runoff and hydroclimatic conditions. Utilizing Grid-RCCC-WBM driven by corrected climatic forcing from the global climate models, this study estimate the prospective overall warmer and wetter pattern in the source region of Yangtze River. The key results indicated that: (1) Under all future scenarios, both temperature and precipitation within the catchment exhibit a significant upward trend. Projections from multi-model ensembles (MME) suggest that during the mid-term period (2041–2060, MT), temperatures are expected to rise by [0.74 °C, 3.08 °C] compared to the baseline period (1995–2014), with precipitation changes ranging from [4.8%, 21.4%]. (2) Future runoff within the catchment exhibits a consistent increase, with a linear trend rate of 1.1 mm/decade. runoff changes in MT compared to the baseline period vary from [−5.1%, 33.7%]. Runoff decreases in the northern part of the catchment, while notable increases occur in the southeastern and western regions. (3) In the future, the ratio of catchment evaporation capacity to precipitation decreases in comparison to the baseline period with an augmentation in soil moisture, enhancing its capacity for water retention and reducing the conversion of precipitation to evaporation, resulting a wetting trend of the catchment. (4) The future snowpack in the catchment continues to decrease, with a significant reduction in both the proportion of snowfall relative to total precipitation and the proportion of snowmelt runoff relative to total runoff, the risk of water resources crisis in the watershed is escalating. [ABSTRACT FROM AUTHOR]

The distribution of terrestrial soil organic carbon changes with climate and substrate conditions. This study investigated the spatial and temporal distribution of soil organic carbon and its influencing elements in the Yarlung Tsangpo River Basin using meteorological, subsurface, and remotely sensed data over the past 39 years, combined with random forests and geodetector. The results of the study showed that soil organic carbon has been increasing in the study area over the past 39 years, and this change has been concentrated in the central part of the watershed. Among the environmental factors, precipitation, temperature, and leaf area index were the main contributors to the soil organic carbon changes, and the effects of the three factors were more significant at higher altitudes, with a 33 % increase in the significance level. Notably, the interactions among the factors exceeded their individual effects, and the combination of climate and leaf area index showed a significant two-factor enhancement effect, with q-value enhancements generally ranging from 0.15 to 0.3. The two-factor enhancement effect was more pronounced below 3000 m above sea level, where the topography of the study area concentrates soil organic carbon in the gently sloping areas of the catchment. [ABSTRACT FROM AUTHOR]