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The unprecedented 2022 Yangtze River Basin (YRB) heatwave is a threat to human society and natural ecology, so the understanding of its underlying drivers is critical to regional climate adaptation and resilience. Here we conducted a multi‐method attribution analysis on the contribution of atmospheric circulation change and anthropogenic impacts to the occurrence probability and intensity of this extreme heatwave. Based on the nonstationary statistical analysis, the 2022 YRB heatwave is a 1‐in‐900‐year event and a 1‐in‐110‐year event with and without considering the 2022 YRB heatwave in the fitting, respectively. The large‐scale meteorological condition analysis shows that the 2022 YRB heatwave is featured with an anomalous high‐pressure system that favors a hot and dry atmospheric column, overlaid by anomalous subsidence and clear skies which leads to warming and greater solar heating. The ensemble constructed circulation analogue analyses show that the circulation anomaly fails to explain the observed 2022 YRB SAT anomalies fully. Specifically, 46% (0.132 ± 0.027°C decade−1) of the observed SAT trend during 1979–2022 (0.290 ± 0.048°C decade−1) is caused by anthropogenic warming and the associated thermodynamic feedback, while the remaining 54% (0.157 ± 0.038°C decade−1) of the trend is caused by changes in the large‐scale atmospheric circulation. Our findings on changes in atmospheric circulation patterns associated with YRB heatwave and anthropogenic contributions to YRB heatwave could provide valuable information for climate adaptation and mitigation strategies in the context of a warming climate. Plain Language Summary: Heatwaves are major climate extremes in the context of global warming, which have inverse effects on human health, food and energy production, and ecosystems. The 2022 heatwave in the Yangtze River Basin (YRB) sets a new record in observational history with its extreme intensity, long duration, and widespread affected areas. The 2022 YRB heatwave is too exceptional to be possible without anthropogenic warming, which is a 1‐in‐900‐year event and a 1‐in‐110‐year event, respectively, with and without considering it in the nonstationary statistical fitting. An anomalous and prolonged high‐pressure system predominated the evolution of the 2022 YRB heatwave, which favors anomalous subsidence and clear skies, leading to hot and dry atmospheric conditions. Next, we applied an ensemble circulation constructed analogue approach to separate the contributions of large‐scale circulation changes and anthropogenic warming in generating the 2022 heatwave. The results reveal that circulation dynamics can only partially explain the 2022 event. When historical changes are taken into account, the changes in large‐scale circulation and anthropogenic warming, respectively, can account for 54% and 46% of the observed summer surface air temperature anomalies in the YRB region. Key Points: The 2022 Yangtze River Basin (YRB) heatwave, linked to anomalous circulation backgrounds, set unprecedented records for surface air temperature (SAT)The atmospheric circulation anomalies alone cannot fully explain the SAT anomalies during the 2022 YRB heatwaveThe variation in atmospheric circulation and anthropogenic warming contributed nearly equally to the historical SAT trend of YRB [ABSTRACT FROM AUTHOR]

The phenomenon of sudden drought after pluvial (or heavy pluvial after drought) is known as the Dry–Wet Abrupt Alternation (DWAA). This kind of disaster has been evaluated globally based on various DWAA indices. However, few validations have been performed to compare the various DWAA indices. Given that directly validating the identified DWAA events remains difficult because of the limited historical records of DWAA events, in this study, we developed a simple weighting analysis method to cross‐validate the detected DWAA events using three widely‐used indices. The weighting analysis method can be used to estimate the effectiveness of the DWAA indices by calculating the ratio of the synchronous DWAA events (the DWAA events could be synchronously detected by different indices) to the total number of the detected DWAA events. Results suggest that the standard weighted average of precipitation (SWAP) index has better performance for detecting DWAA events in the Pearl River Basin (PRB) compared to other indices. The soil moisture synchronization, meteorological concentration and real DWAA records further testify that the SWAP is more capable of detecting the DWAA events in the PRB. Based on the validation, the SWAP‐derived DWAA events show that both dry–wet (D–W) events and wet–dry events are severe in the upstream sub‐basins in the PRB, while D–W events are more frequent in the downstream PRB. Our study provides a simple but effective method to validate the detected DWAA. The finding underscores the need to validate DWAA detection generated from multiple indicators before further research, and it could help develop adaptation strategies to improve resilience to combined extremes under changing climate. [ABSTRACT FROM AUTHOR]

The frequency of large-scale anomalous precipitation events over China has increased during 1961–2018. However, it remains challenging to understand the mechanisms associated with these anomalous events showing different spatial patterns. Here, we applied an autoencoder technique to identify large-scale anomalous precipitation events for both observations and model simulations, which were then classified into several patterns through a self-organizing map method. The synoptic behavior and atmospheric circulation background of different anomalous patterns were also analyzed using simultaneous composite analyses. Results show that occurrences of different anomalous precipitation patterns have increased significantly, except those centered in North China, Northeast China, and the Yangtze River basin. The anomalous precipitation patterns manifest various intraseasonal distributions, which are linked to zonal oscillations of the western North Pacific subtropical high (WNPSH) and meridional displacements of East Asia westerly jet (EAJ). Accompanied by the westward movement of WNPSH, anticyclonic systems transport warm moist air from the Indian Ocean and the South China Sea to converge with the cold air caused by anomalous cyclones over the northwest flank of the WNPSH, leading to large-scale anomalous precipitation in these regions. Besides WNPSH, the northward and southward displacements of EAJ also favor the occurrence of anomalous precipitation events in northern and southern China, respectively. Our study also illustrates that the occurrence frequency of anomalous precipitation events is projected to increase remarkably under the Shared Socioeconomic Pathway 5–8.5 (SSP585) scenario by rates of twofold to fourfold. [ABSTRACT FROM AUTHOR]

Drought is one of the most frequent and devastating natural disasters. Based on future climate scenarios and land use/land cover (LULC) patterns, the copula framework was employed to calculate the probabilities of meteorological and hydrological drought risks for the next 30 years (2021–2050) in the Wanquan River Basin, meanwhile, the relationship between hydrological and meteorological droughts was revealed by correlation analysis and cross-wavelet transform (XWT). The results are as follows: (1) In the next 30 years, the risk of intra-seasonal meteorological drought (short-term drought) in the WRB is high at a probability of 40–70%, while the risk of inter-seasonal meteorological drought is relatively small at a probability of close to 30%; (2) compared with meteorological drought, the risk of intra-seasonal hydrological drought is small, but the probability of inter-seasonal hydrological drought (medium- or long-term drought) is 30–50%, and the risk of hydrological drought in the upstream is greater than that in the downstream; (3) the future meteorological and hydrological droughts in the WRB are significantly and positively correlated, and that hydrological drought lags behind meteorological drought. [ABSTRACT FROM AUTHOR]

Assessing the water budget closures and source of water budget imbalances is fundamental to improving the understanding of changes in the hydrological system and their associated impacts. We analyzed the long‐term (1982–2016) water budget for 1,561 watersheds by using various observed data sets for precipitation (P), evapotranspiration (ET), observed streamflow (Q), and total water storage change (∆TWS). The results show that 93%, 79%, 44%, and 20% of watersheds show water imbalances ratio less than 30%, 20%, 10%, and 5% of their corresponding precipitation. The average absolute water imbalance ratio for all watersheds is 14.2% of P. Watersheds showing large water imbalance ratio values are mostly located in biomes of Tropical and Subtropical Moist Broadleaf Forests, Boreal Forests/Taiga, and Tundra. Different P, ET, and Q data set combinations result in different degrees of water imbalance. The water budget imbalance ratio shows a significant negative relationship with humidity index and vegetation coverage, while a positive relationship with the proportions of irrigation area and watershed area. Showing small water imbalances for most watersheds, reanalysis precipitation data set (ERA5 and MSWEP), MTE evapotranspiration data set performed better than other data sets in water budget analyses in most biomes. The uncertainties of P, ET, Q, and ∆TWSGRACE contribute to 40.1%, 14.3%, 26.6%, and 19% of the water budget imbalance on average, respectively. Improving the accuracy of P and ET estimates, and streamflow measurements are critical to better understanding the water budget and improves modeling of hydrological processes. Key Points: Water budget imbalances are less than 30%, 20%, 10%, and 5% of precipitation for 93%, 79%, 44%, and 20% of all watershedsReanalysis precipitation (ERA5 and MSWEP) and MTE evapotranspiration perform better than other data sets in the water budget in most biomesMoist Broadleaf Forests, Boreal Forests/Taiga, and Tundra show the largest water imbalance ratio due to bias in hydroclimatic data sets [ABSTRACT FROM AUTHOR]

Vegetation interacts closely with water resources. Conventional field studies of plant–water relations are fundamental for understanding the mechanisms of how plants alter and adapt to environmental changes, while large-scale studies can be more practical for regional land use and water management towards mitigating climate change impacts. In this study, we investigated the changes in the total water storage (TWS), aridity index (AI) and vegetation greenness, productivity, and their interactions in the Pearl River basin since April 2002. Results show an overall increasing trend of vegetation greenness and productivity, especially in the middle reaches where TWS also increased. This region dominated by croplands was identified as the hot spot for changes and interactions between water and vegetation in the basin. Vegetation was more strongly affected by TWS than precipitation (P) at both the annual and monthly scales. Further examination showed that the influence of TWS on vegetation in dry years was stronger than wet years, while the impact of P was stronger in wet years than dry years; moreover, vegetation productivity responded slower but stronger to atmospheric dryness in dry years than wet years. The lag effects resulted in nonlinearity between water and vegetation dynamics. This study implies that vegetation in the basin uses rainwater prior to water storage until the soil becomes dry, and their dynamics indicate that vegetation development is subject to water availability, and that vegetation is not dominant in reducing water availability. [ABSTRACT FROM AUTHOR]

Extreme precipitation event is rare and mostly occurs on a relatively small local scale, which presents marked uncertainties when analyzing its characteristics. Using daily precipitation data covering 1959-2009 from 62 stations over the Pearl River Basin, the percentile method (PM) and the absolute critical value method (ACVM) are applied to define extreme precipitation thresholds (EPT), and their different impacts on the spatial-temporal distribution of extreme precipitation event were analyzed in this study. The findings of this study show: (1) Using the K-means clustering algorithm in terms of precipitation indices and the topography, longitude and latitude of each station, the whole basin is divided into eight precipitation zones. (2) The extreme indices, including extreme precipitation frequency, extreme precipitation proportion and proportion of extremely n-day precipitation, calculated by PM are markedly higher than those calculated by ACVM during five decades, which is particularly obvious in the low precipitation area such as the west-northern of the basin since more daily precipitation events are treated as extreme precipitation in this region if EPT is defined by PM. (3) The spatial distributions of extreme frequencies respectively calculated by these two methods are quite different across the basin. The spatial distribution of extreme frequencies calculated by ACVM shows a high-value center in the southeast coastal areas and a low-value center in the northwest mountain areas. However, the extreme frequencies calculated by PM distribute evenly over the basin, which is obviously inconsistent with the empirical results, an area with heavy precipitation usually has a high extreme precipitation frequency, and vice versa. [ABSTRACT FROM AUTHOR]

The change structures of precipitation and precipitation intensity and rainy days are analyzed for the Pearl River Basin (from 1959 to 2009) on the basis of a suite of 24 climatic indices derived from daily precipitation data at 62 meteorological stations with the help of the Mann-Kendall test. Contributions of seasonal precipitation and precipitation intensity class to the annual precipitation are also examined using the inverse distance weighted method. The following four conclusions can be drawn: (1) although the average annual precipitation of the entire basin does not show obvious variation, the number of annual rainy days has decreased significantly in 98.3 % of the stations. These two factors result in an obvious increase in precipitation intensity at 64.5 % of the stations. (2) No clear change trend has been found for seasonal precipitation over the entire area; however, the number of rainy days in each season has decreased significantly. In particular, the number of rainy days in the entire year and in the fall season has decreased in 98.3 and 100 % of the stations, respectively. (3) Although the number of rainy days in drizzle has decreased in 83.9 % of the stations, the number of rainy days where heavy rain and extremely heavy rain occurred increased in nearly 75.8 and 82.3 % of the stations, respectively. (4) The number of rainy days in fall and winter contributes more to the change in the number of annual rainy days than the number of rainy days in spring and summer. Heavy rain and extremely heavy rain contribute more to the change in total annual precipitation than drizzle; however, they contribute less to the change in the number of annual rainy days than drizzle. The findings in this study can provide important information for formulating water resource and eco-environment management strategies in the Pearl River Basin to policymakers and stakeholders. [ABSTRACT FROM AUTHOR]

Highlights: [•] The non-parametric absolute critical value method is not applicable to large scale river basin. [•] The non-parametric percentile method is sensitive to data series and dependent on percentile. [•] The parametric method depends on the probability distribution and size of data series. [•] The detrended fluctuation analysis method provides unique threshold and reasonable solution. [ABSTRACT FROM AUTHOR]

Analyzing the spatiotemporal characteristics and causes of landscape pattern changes in watersheds around big cities is essential for understanding the ecological consequence of urbanization and provides a basic reference for the watershed management. This study used a land-use transition matrix and landscape indices to explore the spatiotemporal change of land use and landscape pattern over Liuxihe River basin of Guangzhou in the southeast of China from 1980 to 2015 with multitemporal Landsat satellite data in response to the rapid urbanization process. Primary temporal and spatial influencing factors were first quantitatively identified through grey relation analysis (calculating correlation degree between land use changes and influencing factors) and Geodetector (detecting landscape spatial heterogeneity and its driving factors), respectively. Considerable spatial and temporal differences in land use and landscape pattern changes were observed herein, thus determining the influencing factors of these differences in the Liuxihe River basin. These changes were characterized by a large increase in construction land converted from cropland, particularly in the middle and lower reaches of the basin from 2000 to 2010, causing dramatic fragmentation and homogenization of the landscape pattern there. Meanwhile, the landscape pattern gradually transitioned from an agricultural land use dominant landscape to a construction land use dominant landscape in these regions. Furthermore, the rapid growth of a nonagricultural population and the transformation of industry primarily caused the temporal changes of landscape pattern, and the landscape spatial heterogeneity was mainly caused by the interaction of complicated geomorphology and anthropogenic activities in different spatial locations, particularly after 2000. This study not only provides an improved approach to quantifying the main spatiotemporal influencing factors of landscape pattern changes during different time periods, but also offers a reference for decision-makers to formulate optimal strategies on ecological protection and urban sustainable development of different regions in this study area. [ABSTRACT FROM AUTHOR]

• Responses of streamflow to changes in vegetation composition and climate variability were investigated considering changes in the terrestrial water storage. • The Budyko parameter is significantly related to vegetation composition and climate variability. • Streamflow changes were more (less) sensitive to tree coverage than non-tree coverage in humid (arid) regions. Vegetation and climate play critical roles in the hydrological cycle as vital components of the earth system. Understanding the impacts of changes in vegetation composition and climate on hydrological processes is essential for water balance and sustainable water resource management. We analyzed the effects of changes in vegetation composition and climate variability on streamflow changes in 3434 global watersheds from 2003 to 2016 using the Budyko framework. We found that ignoring changes in terrestrial water storage would result in large errors in the influence of landscape changes on streamflow changes. The sensitivity of streamflow changes to climate seasonality index (CSI), precipitation seasonality index (PSI), total vegetation coverage (M), tree coverage (MT), and non-tree coverage (MNT) varied in different regions. Effective precipitation (Pe), potential evapotranspiration (PET), CSI , PSI , M , MT , and MNT changes were the dominant factor in streamflow changes for 64.8%, 3.0%, 5.1%, 4.1%, 9.8%, 7.7%, 5.6% of global watersheds, respectively. Attributing streamflow changes showed that the effects of MT and MNT on streamflow changes were mutually reinforcing in most basins. The influence of vegetation composition on streamflow changes was greater in semi-humid and arid regions than in humid regions. This research quantified the impacts of vegetation composition changes and climate change on streamflow changes worldwide and could clarify the hydrological responses to changing environments. [ABSTRACT FROM AUTHOR]

Highlights • Natural/anthropogenic water connections among US watersheds were investigated. • Highly water-stressed areas may expand from 14% to 18% by 2070–2099. • Regional water connectivity could buffer the potential stress escalations. • Future changes may aggravate upstream-downstream water conflicts. Abstract Surface water supply for a watershed relies on local water generated from precipitation and water connections with other watersheds. These connections are confined by topography and infrastructure, and respond diversely to stressors such as climate change, population growth, increasing energy and water demands. This study presents an integrative simulation and evaluation framework that incorporates the natural and anthropogenic water connections (i.e., stream flows, inter-basin water transfers, water withdrawals and return flows) among the 2099 8-digit Hydrologic Unit Code (HUC-8) watersheds across the conterminous United States. The framework is then applied to investigate the potential impacts of changes in climate and water use on regional water availability and water stress (the ratio of demand to supply). Our projections suggest that highly water-stressed areas may expand from 14% to 18% and the stressed population would increase from 19% to 24% by 2070–2099. Climate-change mitigation practices (e.g., energy structure reform, technology innovation) could largely offset these trends by reducing demand and enhancing supply. At the watershed scale, the spatially inhomogeneous responses to future changes suggest that regional water connectivity could significantly buffer the potential stress escalations due to the redistribution of water resources and diverse changes in consumptive uses and water supplies in different source areas. However, the detrimental future changes (e.g., depleting river discharges, larger demands of water withdrawal) may aggravate conflicts over water rights among regions and challenge our current water infrastructure system. This study provides new insights into the critical role of regional water connectivity in water supply security, and highlights the increasing need for integrated monitoring and management of water resources at various spatial levels in a changing world. [ABSTRACT FROM AUTHOR]