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Understanding how drought is impacted by both natural and human influences is crucial to the sustainable utilization and protection of water resources. We established a drought severity index (DSI) based on the terrestrial water storage anomaly (TWSA) derived from the GRACE satellite to detect drought characteristics and trends over ten major river basins in China from 2002 to 2017. The influence of natural factors (terrestrial water storage components, precipitation, evapotranspiration, runoff, NDVI, and teleconnection factors (ENSO, PDO, NAO, and AO)) and a human factor (LULC) on drought were investigated and quantified from the perspective of water storage components based on the Theil–Sen trend and Mann–Kendall test method, the perspective of climate change based on cross wavelet transforms, and the perspective of water balance based on Random Forest. The results indicated that (1) almost all humid and arid basins experienced major drought periods during 2002–2006 and 2014–2017, respectively. The southern IRB and central YZRB regions exhibited notable declines in DSI trends, while the majority of the HLRB, IRB, LRB, YRB, HRB, and SWRB experienced significant increases in DSI trends; (2) abnormal groundwater decreases were the main cause of drought triggered by insufficient terrestrial water storage in most basins; (3) ENSO was the strongest teleconnection factor in most humid basins, and NAO, PDO, and AO were the strongest teleconnection factors in the arid basins and PRB. Most significant resonance cycles lasted 12–64 months in 2005–2014; and (4) the influence of an anthropogenic driver (LULC) has become as important as, or more important than, natural factors (runoff and teleconnection factors) on hydrological drought. [ABSTRACT FROM AUTHOR]

Ecological protection and high-quality development of the Yellow River Basin (YRB), China, aroused remarkable concerns from China's Central Government, and has been a major national strategy. The Inner Mongolia reach of the Yellow River Basin (IM-YRB) is a typical dryland with pervasive vegetation restoration through the actions of the ecological projects that have been conducted in recent years. However, how climate changes and human activities, such as land use and land cover (LULC) changes, jointly impact vegetation variations in this region remains poorly understood. Here, using an explainable machine learning technique, we evaluated linkages between the kernel normalized difference vegetation index (kNDVI) and air temperature, precipitation, soil moisture, and LULC changes, and relevant marginal contributions of these four drivers to the observed vegetation changes. The grassland fraction on a pixel level was selected as the quantitative LULC variable due to its key role in regional LULC. We found that interannual kNDVI changes in most areas of this study region were negatively sensitive to temperature, but positively sensitive to precipitation and soil moisture, with area fractions of 71.74%, 96.93%, and 89.33%, respectively. The area fraction of negative kNDVI sensitivity to LULC was roughly equivalent to that of positive kNDVI sensitivity. The contributions of air temperature, precipitation, soil moisture, and LULC to overall kNDVI changes were 21.54%, 33.32%, 32.19%, and 12.95%, respectively. Moisture conditions also play a critical role in vegetation changes, which was reflected by the fluctuating growth of kNDVI as interannual changes in precipitation. Nonetheless, kNDVI changes are also affected by LULC, and LULC became the dominant factor behind the kNDVI anomalies over the grassland restoration regions from barren over the IM-YRB. This research provides theoretical support for dryland vegetation restoration under the influence of climate change. [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]

This study quantifies the influences of climate variation and vegetation greening on the changes in evapotranspiration (ET) over 110 humid catchments of China from 1982 to 2016. A process‐based model considering climate and vegetation changes is employed to estimate ET. The simulated ET compared well with the observed values based on the flux measurements and water balance equation, with the coefficients of determination above 0.62. During the study period, environmental change of the study area was characterized by the increases in air temperature and leaf area index, that is, climate warming and vegetation greening. Annual ET increased at 104 catchments with the trends ranging from 0.01 to 6.2 mm yr−2. The numerical experiment approach and sensitivity method are used to attribute ET changes to climate variation and vegetation greening. The results show that the contributions of climate variation to ET changes estimated by the two methods are 90.6% and 91.3%, respectively, whereas the contributions of vegetation greening to ET changes are only 9.4% and 8.7%, indicating that climate variation controls ET changes in the study area. However, vegetation greening alters the proportions of ET components, which contributes 59.0%–62.0% to the increase in the ratio of transpiration to ET. This study quantifies the roles of climate and vegetation changes in the dynamics of ET, suggesting that more concerns should be paid on the interactions between ecological processes and hydrological cycle in humid regions. Key Points: Evapotranspiration changes are attributed to climate variation and vegetation greening over 110 humid catchments in ChinaClimate variation controls the dynamics of evapotranspiration over the humid regionVegetation greening has limited influences on evapotranspiration but mainly alters evapotranspiration partitioning [ABSTRACT FROM AUTHOR]

Intense anthropogenic climate changes are expected to increase atmospheric aridity in the 21st century. The aridity index (AI), defined as the ratio of annual precipitation (Pre) to atmospheric evaporation (potential evapotranspiration [PET]), represents an efficient indicator of climatic changes. However, the variations and underlying drivers of AI values have not been comprehensively compared in different climatic regions. Using the AI calculated on the basis of bias‐corrected precipitation and optimized PET over the period of 1999–2017 and two climate model projections for the coming century, we investigated the response of the AI to climate change and quantified the contributions of climatic factors to AI variations in eight climatic regions in China, that is, the northwest (NW), north‐centre (NC), northeast (NE), North China Plain (NCP), east (E), southeast (SE), southwest (SW) and Tibet Plateau (TP). The results indicated that the AI values in seven of the eight climate regions exhibited negative trends from 1999 to 2017, with mean values ranging from −0.0008 in SW to −0.0414 in NC, while the AI values in the TP region showed a significant positive trend, with a value of 0.0124. Pre was the dominant factor for the variations in AI values in all climate regions, with contribution rates from 65 to 308%, followed by decreasing solar radiation in the NW, NC, E, SE and SW regions; deceasing wind speed in NE and NCP; and deceasing actual vapour pressure in the TP. The effect of increasing temperature on the AI trend was offset by other climate factors. By the end of the 21st century, under the Representative Concentration Pathway 8.5 emission scenario, the AI will significantly increase in five of the eight regions to values approximately 16.5% higher than those during 1999–2017, and this increase in the AI will be dominated by increasing PET. Overall, the shift in the dominant AI factor from Pre in recent years to PET in the future indicates that more attention should be given to the response of the AI to global warming. Furthermore, regional differences in climate change and AI values during 2018–2,100 will inevitably influence water availability and urgently require the development of adaptation strategies for different climatic regions. [ABSTRACT FROM AUTHOR]

The distributions of bird species have changed over the past 50 years in China. To evaluate whether the changes can be attributed to the changing climate, we analyzed the distributions of 20 subspecies of resident birds in relation to climate change. Long-term records of bird distributions, gray relational analysis, fuzzy-set classification techniques, and attribution methods were used. Among the 20 subspecies of resident birds, the northern limits of over half of the subspecies have shifted northward since the 1960s, and most changes have been related to the thermal index. Driven by climate change over the past 50 years, the suitable range and latitude or longitude of the distribution centers of certain birds have exhibited increased fluctuations. The northern boundaries of over half of the subspecies have shifted northward compared with those in the 1960s. The consistency between the observed and predicted changes in the range limits was quite high for some subspecies. The changes in the northern boundaries or the latitudes of the centers of distribution of nearly half of the subspecies can be attributed to climate change. The results suggest that climate change has affected the distributions of particular birds. The method used to attribute changes in bird distributions to climate change may also be effective for other animals. [ABSTRACT FROM AUTHOR]

An overview of basic research on climate change in recent years in China is presented. In the past 100 years in China, average annual mean surface air temperature (SAT) has increased at a rate ranging from 0.03°C (10 yr) to 0.12°C (10 yr). This warming is more evident in northern China and is more significant in winter and spring. In the past 50 years in China, at least 27% of the average annual warming has been caused by urbanization. Overall, no significant trends have been detected in annual and/or summer precipitation in China on a whole for the past 100 years or 50 years. Both increases and decreases in frequencies of major extreme climate events have been observed for the past 50 years. The frequencies of extreme temperature events have generally displayed a consistent pattern of change across the country, while the frequencies of extreme precipitation events have shown only regionally and seasonally significant trends. The frequency of tropical cyclone landfall decreased slightly, but the frequency of sand/dust storms decreased significantly. Proxy records indicate that the annual mean SAT in the past a few decades is the highest in the past 400-500 years in China, but it may not have exceeded the highest level of the Medieval Warm Period (1000-1300 AD). Proxy records also indicate that droughts and floods in eastern China have been characterized by continuously abnormal rainfall periods, with the frequencies of extreme droughts and floods in the 20th century most likely being near the average levels of the past 2000 years. The attribution studies suggest that increasing greenhouse gas (GHG) concentrations in the atmosphere are likely to be a main factor for the observed surface warming nationwide. The Yangtze River and Huaihe River basins underwent a cooling trend in summer over the past 50 years, which might have been caused by increased aerosol concentrations and cloud cover. However, natural climate variability might have been a main driver for the mean and extreme precipitation variations observed over the past century. Climate models generally perform well in simulating the variations of annual mean SAT in China. They have also been used to project future changes in SAT under varied GHG emission scenarios. Large uncertainties have remained in these model-based projections, however, especially for the projected trends of regional precipitation and extreme climate events. [ABSTRACT FROM AUTHOR]

In recent decades, both observation and simulation data have demonstrated an obvious decrease in runoff and soil moisture, with increasing evapotranspiration, over the Loess Plateau. In this study, we employed a Variable Infiltration Capacity model coupled with scenario simulation to explore the impact of change in climate and land cover on four hydrological variables (HVs) over the Loess Plateau, i.e., evapotranspiration (ET), runoff (Runoff), shallow soil moisture (SM1), and deep soil moisture (SM2). Results showed precipitation, rather than temperature, had the closest relationship with the four HVs, with r ranging from 0.76 to 0.97 (p < 0.01), and this was therefore presumed to be the dominant climate-based driving factor in the variation of hydrological regimes. Vegetation conversion, from cropland and grassland to woodland, significantly reduced runoff and increased soil moisture consumption, to sustain an increased ET, and, assuming that the reduction of SM2 is entirely evaporated, we can attribute 71.28% ± 18.64%, 65.89% ± 24.14% of the ET increase to the water loss of SM2 in the two conversion modes, respectively. The variation in HVs, induced by land cover change, were higher than the expected climate change with respect to SM1, while different factors were selected to determine HVs variation in six catchments, due to differences in the mode and intensity of vegetation conversion, and the degree of climate change. Our findings are critical for understanding and quantifying the impact of climate change and vegetation conversions, and provide a further basis for the design of water resources and land-use management strategies with respect to climate change, especially in the water-limited Loess Plateau. [ABSTRACT FROM AUTHOR]