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In the context of global warming, snow cover changes have an extremely important impact on the hydrological cycle and the redistribution of water resources in arid and semi-arid regions. In this paper, based on the daily cloud-free snow area remote sensing product data in the source region of Yangtze River (SRYR) from 2000 to 2019, the snow phenology variables such as the snow cover day (SCD), snow onset date (SOD), snow end date (SED), and snow duration day (SDD) were extracted separately for each hydrological year, and the vertical distribution of snow cover area (SCA) in the SRYR was analyzed by combining with the digital elevation model (DEM). In addition, we also combined climate factors and land cover types to further explore the spatiotemporal variation characteristics of snow phenology in response to different influencing factors, in order to reveal the spatiotemporal variation patterns of snow cover in the SRYR. The results showed that: (1) The SCA in the SRYR has a more obvious vertical distribution, with the maximum SCA reaching 61.58% at high elevation, while at low elevation, the SCA is mostly below 20%. The distribution of SCD in the study area showed a significant exponential correlation with DEM (R2 = 0.87). (2) The area of SOD in the SRYR showed an advanced trend of about 63.37%, while the area of SED showed a delayed trend of about 69.59%, and the area which showed significant trends is 4.29% and 4.36%, respectively. Therefore, the trends of both SOD and SED showed insignificant changes. (3) Temperature change is the main factor affecting the change of snow cover in the SRYR. Among them, 90.9% of the regions showed a significant positive correlation between temperature and SCD, while precipitation showed a significant negative correlation with SCD in about 75.3% of the total area of SRYR. Under the stable snow area (SCD > 60), the land cover type is glacial or permanent snow about 1.5 × 103 km2, which covers almost the entire glacial or permanent snow of the SRYR. [ABSTRACT FROM AUTHOR]

Variability in soil moisture has implications for regional terrestrial environments under a warming climate. This paper focuses on the spatiotemporal variability in the intra-annual persistence of soil moisture in China using the fifthgeneration reanalysis dataset by the European Centre for Medium-Range Weather Forecasts for the period 1979-2018. The results show that in China, the mean intra-annual persistence in the humid to arid zones increased from 60 to 115 days in the lower layer but decreased from 19 to 13 days and from 25 to 14 days in the upper and root layers, respectively. However, these changes were strongly attenuated in extremely dry and wet regions due to the scarcity of soil moisture anomalies. Large changes in persistence occurred in the lower soil layer in dryland areas, with a mean difference of up to 40 days between the 2010s and the 1980s. Overall increasing trends dominated the large-scale spatial features, despite regional decreases in the eastern arid zone and the North and Northeast China plains. In the root layer, the two plains experienced an expanded decrease while on the Tibetan Plateau it was dominated by decadal variability. These contrasting changes between the lower and root layers along the periphery of the transition zone was a reflection of the enhanced soil hydrological cycle in the root layer. The enhanced persistence in drylands lower layer is an indication of the intensified impacts of soil moisture anomalies (e.g., droughts) on terrestrial water cycle. These findings may help the understanding of climate change impacts on terrestrial environments. [ABSTRACT FROM AUTHOR]

Over a long multi-year period, flood events can be classified according to their effectiveness in moving sediments. Efficiency depends both on the magnitude and frequency with which events occur. The effective (or dominant) discharge is the water discharge which corresponds to the maximum sediment supply. If its calculation is well documented in temperate or humid climates and large basins, it is much more difficult in small and semi-arid basins in which short floods with high sediment supplies occur. Using the example of 31 years of measurements in the Wadi Sebdou (north-west Algeria), this paper compares the two main statistical approaches to calculate the effective discharge (the empirical method based on histograms of sediment supply by discharge classes and an analytical calculation based on a hydrological probability distribution and on a sediment rating curve) to a very simple proxy: the half-load discharge, i.e. the flow rate corresponding to 50 % of the cumulative sediment yield. Three types of discharge subdivisions were tested. In the empirical approach, two subdivisions provided effective discharge close to the half-load discharge. Analytical solutions based on log-normal and log-Gumbel probability distributions were assessed but they highly underestimated the effective discharge, whatever the subdivision used to adjust the flow frequency distribution. Furthermore, annual series of maximum discharge and half-load discharge enabled the return period of hydrological years with discharge higher than the effective discharge (around 2 years) to be inferred and showed that more than half of the yearly sediment supply is carried by flows higher than the effective discharge only every 7 hydrological years. This study was the first to adapt the analytical approach in a semi-arid basin and to show the potentiality and limits of each method in a such climate. [ABSTRACT FROM AUTHOR]

Persistent precipitation deficits are among the most impactful consequences of global warming. Here we focus on changes in the annual number of dry days (NDD) and in the annual maximum length of dry spells due to a quadrupling of atmospheric CO2. We use atmosphere‐only simulations to decompose the projected changes into additive contributions. A fast adjustment leads to a global increase in NDD despite notable regional exceptions (e.g., South Asia and Sahel). The effect of the uniform component of the surface ocean warming is model‐dependent but shapes the regional distribution of the NDD response in each model. Finally, the ocean warming pattern also contributes to large uncertainties, likely through contrasting changes in large‐scale circulation. Our results thus highlight the complexity of the NDD response, with policy‐relevant practical implications for mitigation and adaptation strategies. Plain Language Summary: Global warming is expected to intensify the global water cycle, including the intensity and frequency of precipitation extremes. Yet, the response of the dry side of the daily precipitation distribution to increased atmospheric CO2 has received so far less attention. Here we show that this response remains highly model‐dependent across the latest generation of global climate models. Furthermore, we use atmosphere‐only simulations to isolate different drivers of the precipitation response. A fast radiative and vegetation adjustment to increased CO2 leads to an overall increase in the mean annual number of dry days (NDD) despite some regional exceptions. The effect of the ocean surface warming is highly model‐dependent, only partly due to the diversity of the simulated patterns of sea surface temperature anomalies. The regional response of NDD and of the maximum length of dry spells thus does not simply scale with global warming across the different models. Key Points: AGCM simulations are used to split the dry day response to increased CO2 into fast adjustment versus slower uniform and patterned SST effectsNone of the three components consistently dominates the global land response of dry days across the selected CMIP6 modelsThe uniform SST warming dominates the regional anomalies, which however do not scale with global warming across the multi‐model ensemble [ABSTRACT FROM AUTHOR]

This study develops a convolutional recurrent deep learning model to accurately predict fine‐resolution spatiotemporal changes in grass coverage in arid regions. Applying the model to the Gobi Desert reveals that ecological flow regulation contributes to 61.8% of the total increase in grass cover (130.6 km2) in the study area (40,423 km2) over 2005–2015, nearly triple the contribution of local climate change (+23.0%). The transboundary hydrological impact (+32.4%) and interactions between drivers (−17.2%) are also significant. In an intermediate future climate change scenario, we found no statistically significant trend for the total grass‐covered area due to the counteracting effects among different drivers. The study findings suggest that timely, adaptive and spatially heterogeneous ecological flow management is crucial for addressing grassland degradation in arid regions. This study provides a promising approach to land surface modeling under climate change and human disturbance and expands the existing understanding of the global greening process. Plain Language Summary: The Earth's recent greening (i.e., vegetation increase) has boosted the terrestrial carbon sink, intensified the hydrologic cycle, and contributed to mitigating global warming. CO2 fertilization has been identified as the primary cause at the global scale, while climate change, land use changes, and nitrogen deposition also contribute. However, there are still many gaps in our understanding of how grasslands in arid areas are being affected. Studies in Central Asia identified precipitation as the dominant factor affecting grassland change and grazing as the main influence from humans. Based on satellite data, we employ a novel deep learning (DL) approach to emulate spatiotemporal changes in grass coverage at a 1‐km resolution over an area of 40,423 km2 in the Gobi Desert in northwestern China. Our study identified previously overlooked mechanisms contributing to the increase in grass coverage, including ecological flow management and transboundary hydrological impact. Ecological flow management was found to be responsible for almost three times the increase in grass coverage over 2005–2015 than that of local climate changes. Our findings suggest that timely, adaptive, and spatially targeted ecological flow management is urgently needed to prevent further grassland degradation in arid regions, and DL‐based artificial intelligence can offer valuable management suggestions. Key Points: Deep learning (DL) precisely emulates spatiotemporal changes in grass coverage at a 1‐km resolution over an area of 40,423 km2DL interprets ecological flow regulation (EFR) as the leading cause of grassland greening in the Gobi DesertTimely, adaptive and spatially heterogeneous ecological flow management is desired to prevent grassland degradation in arid regions [ABSTRACT FROM AUTHOR]

The forecasted increased frequency and intensity of extreme climatic events may strongly affect ecosystem structure and function in the future. It is unclear how ecosystems will function in the long run over a large spatial scale under a new extreme water cycle. This open question calls for a conceptual framework as a fundamental basis for theoretical and experimental exploration of ecosystem function on a large scale driven by an extreme climate envelope. To assess the problem on a large scale, we investigated hyper‐arid ecosystems (HAEs) as natural tangible models that already function under an extreme climatic envelope. Our new assertion is that if extreme climate change drives arid lands to function under alternate extreme conditions, then arid land ecosystems will function like an HAE as an alternative state, rather than progress to desertification. To support our assertion, we developed a conceptual framework of HAEs that includes a geo‐hydrological "abiotic engine" that drives HAE function by soil moisture diversity and plant functional groups. Based on this conceptual framework, we suggest incorporating two new hypotheses in climate change studies to advance our understanding of responses of large‐scale, water‐limited ecosystems: (1) Hydro‐climatic extremes in water‐limited ecosystems will reduce the degree of resource conservation by slope ecosystems due to reduction in plant cover and soil. The decreased ecosystem function on the slope will be compensated for by increasing the effect of the abiotic engine on the ephemeral stream, thus enhancing meta‐ecosystem functioning in the ephemeral stream. (2) In water‐limited ecosystems, climate change toward hydro‐climatic extremes will rescale the dominant hydro‐ecological processes of pulse–reserve, source–sink, and connectivity along the semiarid, arid, and HA gradients in two ways: (i) shrinking of both spatial and temporal dimensions; and (ii) shrinking in the temporal dimension and expanding in the spatial dimensions. The first rescaling trajectory is related to biodiversity–ecosystem function and the second to the abiotic engine processes. [ABSTRACT FROM AUTHOR]

Precipitation events have been predicted and observed to become fewer, but larger, as the atmosphere warms. Water-limited ecosystems are especially sensitive to changes in water cycling, yet evidence suggests that productivity may either increase or decrease in response to precipitation intensification. Interactions among climate, soil properties, and vegetation type may explain different responses, but this is difficult to experimentally test over large spatial scales. Simulation modeling may reveal the mechanisms through which climate, soils, and vegetation interact to affect plant growth. We use an individual-based plant ecohydrological model to simulate the effects of 25%, 50%, and 100% increases in precipitation event sizes on water cycling and shrub, grass, and forb biomass in 200 shrub-steppe sites spanning 651,000 km2 of the Intermountain West, USA. Simulations did not change annual precipitation amounts and were performed for 0, 3, and 5 °C warming. Larger precipitation events decreased evaporation and 'pushed' water into shrub root zones in arid and semi-arid sites, but 'pushed' water below shrub root zones in mesic sites resulting in increased shrub biomass in arid and semi-arid, but not mesic, sites. Positive effects of precipitation intensification on shrub growth partially counteracted negative effects of warming. Grasses and forbs showed no consistent response to precipitation intensification. Results indicate that increased precipitation intensity creates a competitive advantage for shrubs in arid and semi-arid sites. This advantage results in greater shrub relative abundance and suggests that precipitation intensification contributes to woody plant encroachment observed globally in arid and semi-arid ecosystems. [ABSTRACT FROM AUTHOR]

The "dry gets drier, and wet gets wetter" (DDWW) paradigm has been widely used to summarize the expected trends of the global hydrologic cycle under climate change. However, the paradigm is largely conditioned by choice of different metrics and datasets used and is still comprehensively unexplored from the perspective of terrestrial water storage anomalies (TWSAs). Considering the essential role of TWSAs in wetting and drying of the land system, here we built upon a large ensemble of TWSA datasets, including satellite-based products, global hydrological models, land surface models, and global climate models to evaluate the DDWW hypothesis during the historical (1985–2014) and future (2071–2100) periods under various scenarios with a 0.05 significance level (for trend estimates). We find that 11.01 %–40.84 % (range by various datasets) of global land confirms the DDWW paradigm, while 10.21 %–35.43 % of the area shows the opposite pattern during the historical period. In the future, the DDWW paradigm is still challenged, with the percentage supporting the pattern lower than 18 % and both the DDWW-validated and DDWW-opposed proportion increasing along with the intensification of emission scenarios. We show that the different choices of data sources can reasonably influence the test results up to a 4-fold difference. Our findings will provide insights and implications for global wetting and drying trends from the perspective of TWSA under climate change. [ABSTRACT FROM AUTHOR]

The arid region of Northwest China, located in the central Asia, responds sensitively to global climate change. Based on the newest research results, this paper analyzes the impacts of climate change on hydrology and the water cycle in the arid region of Northwest China. The analysis results show that: (1) In the northwest arid region, temperature and precipitation experienced “sharply” increasing in the past 50 years. The precipitation trend changed in 1987, and since then has been in a state of high volatility, during the 21st century, the increasing rate of precipitation was diminished. Temperature experienced a “sharply” increase in 1997; however, this sharp increasing trend has turned to an apparent hiatus since the 21st century. The dramatic rise in winter temperatures in the northwest arid region is an important reason for the rise in the average annual temperature, and substantial increases in extreme winter minimum temperature play an important role in the rising average winter temperature; (2) There was a significant turning point in the change of pan evaporation in the northwest arid area in 1993, i.e., in which a significant decline reversed to a significant upward trend. In the 21st century, the negative effects of global warming and increasing levels of evaporation on the ecology of the northwest arid region have been highlighted; (3) Glacier change has a significant impact on hydrology in the northwest arid area, and glacier inflection points have appeared in some rivers. The melting water supply of the Tarim River Basin possesses a large portion of water supplies (about 50%). In the future, the amount of surface water will probably remain at a high state of fluctuation. [ABSTRACT FROM AUTHOR]

Using tree-ring data of Pinus sylvestris var. mongolica from the Hulun Buir region in northeast China, 12 annual runoff series of the Hailar River spanning the past 202-216 years were established for the first time; these included 11 branches and one for the entire basin. These reconstructions, which could explain 29.4%-52.7% of the total variance for the measured runoffs during 1956-2006, performed well in statistical verification tests. In the whole basin's reconstruction of 212 years, 34 extreme drought years (16.0%) and 41 extreme pluvial years (19.3%) were identified; 4 of the 10 most extreme years occurred after 1980. The consistent cycle and correlation revealed that the Hailar runoff had a teleconnection with the El Niño-Southern Oscillation (ENSO). The sharply increasing variance at the end of the reconstruction, accompanied by the increasing intensity of short cycles (4-8 years), indicated that runoff variability in the Hailar River basin has enhanced in the late twentieth century. This is verified by the drastic fluctuations in water level and area of rivers and lakes, and the frequent shift of natural land cover types in the Hulun Buir area in recent decades. The intensified runoff variability can be connected with the concurrently enhanced ENSO activity. Our study is the first to identify the intensification of recent runoff variability in the semiarid to arid region in northeast China from a long-term perspective. With projected enhancement of ENSO activity, the Hailar River basin will face the increased risk of extreme hydrological events. [ABSTRACT FROM AUTHOR]

Changes in climatic characteristics such as seasonal and inter-annual variability may affect ecosystem structure and function, hence alter carbon and water budgets of ecosystems. Studies of modelling combined with field experiments can provide essential information to investigate interactions between carbon and water cycles and climate. Here we present a first attempt to investigate the long-term climate controls on seasonal patterns and inter-annual variations in water and carbon exchanges in an arid-zone savanna-woodland ecosystem using a detailed mechanistic soil-plant-atmosphere model (SPA), driven by leaf area index (LAI) simulated by an ecohydrological model (WAVES) and observed climate data during 1981-2012. The SPA was tested against almost 3 years of eddy covariance flux measurements in terms of gross primary productivity (GPP) and evapotranspiration (ET). The model was able to explain 80 and 71% of the variability of observed daily GPP and ET, respectively. Long-term simulations showed that carbon accumulation rates and ET ranged from 20.6 g C m mon in the late dry season to 45.8 g C m mon in the late wet season, respectively, primarily driven by seasonal variations in LAI and soil moisture. Large climate variations resulted in large seasonal variation in ecosystem water-use efficiency (eWUE). Simulated annual GPP varied between 146.4 and 604.7 g C m y. Variations in annual ET coincided with that of GPP, ranging from 110.2 to 625.8 mm y. Annual variations in GPP and ET were driven by the annual variations in precipitation and vapour pressure deficit (VPD) but not temperature. The linear coupling of simulated annual GPP and ET resulted in eWUE having relatively small year-to-year variation. [ABSTRACT FROM AUTHOR]

We present an observational analysis examining soil moisture control on surface energy dynamics and planetary boundary layer characteristics. Understanding soil moisture control on land-atmosphere interactions will become increasingly important as climate change continues to alter water availability. In this study, we analyzed 4 years of data from the Santa Rita Creosote Ameriflux site. We categorized our data independently in two ways: (1) wet or dry seasons and (2) one of the four cases within a two-layer soil moisture framework for the root zone based on the presence or absence of moisture in shallow (0-20 cm) and deep (20-60 cm) soil layers. Using these categorizations, we quantified the soil moisture control on surface energy dynamics and planetary boundary layer characteristics using both average responses and linear regression. Our results highlight the importance of deep soil moisture in land-atmosphere interactions. The presence of deep soil moisture decreased albedo by about 10%, and significant differences were observed in evaporative fraction even in the absence of shallow moisture. The planetary boundary layer height ( PBLh) was largest when the whole soil profile was dry, decreasing by about 1 km when the whole profile was wet. Even when shallow moisture was absent but deep moisture was present the PBLh was significantly lower than when the entire profile was dry. The importance of deep moisture is likely site-specific and modulated through vegetation. Therefore, understanding these relationships also provides important insights into feedbacks between vegetation and the hydrologic cycle and their consequent influence on the climate system. [ABSTRACT FROM AUTHOR]

Substantial evidence exists for wetter-than-modern continental conditions in North America during the pre-Quaternary warm climate intervals. This is in apparent conflict with the robust global prediction for future climate change of a northward expansion of the subtropical dry zones that should drive aridification of many semiarid regions. Indeed, areas of expected future aridification include much of western North America, where extensive paleo-environmental records are documented to have been much wetter before the onset of Quaternary ice ages. It has also been proposed that climates previous to the Quaternary may have been characterized as being in a state with warmer-than-modern eastern equatorial sea surface temperatures (SSTs). Because equatorial Pacific SSTs exert strong controls on midlatitude atmospheric circulation and the global hydrologic cycle, the teleconnected response from this permanent El Niño-like mean state has been proposed as a useful analogue model, or "blueprint", for understanding global climatological anomalies in the past. The present study quantitatively explores the implications of this blueprint for past climates with a specific focus on the Miocene and Pliocene, using a global climate model (CAM3.0) and a nested high-resolution climate model (RegCM3) to study the hydrologic impacts on global and North American climate of a change in mean SSTs resembling that which occurs during modern El Niño events. We find that the global circulation response to a permanent El Niño resembles a large, long El Niño event. This state also exhibits equatorial super-rotation, which would represent a fundamental change to the tropical circulations. We also find a southward shift in winter storm tracks in the Pacific and Atlantic, which affects precipitation and temperature over the mid-latitudes. In addition, summertime precipitation increases over the majority of the continental United States. These increases in precipitation are controlled by shifts in the subtropical jet and secondary atmospheric feedbacks. Based on these results and the data proxy comparison, we conclude that a permanent El Niño like state is one potential explanation of wetter-than-modern conditions observed in paleoclimate-proxy records, particularly over the western United States. [ABSTRACT FROM AUTHOR]

Global climate change not only affects the processes within the water cycle but also leads to the frequent occurrences of local and regional extreme drought events. In China, spatial and temporal characterizations of drought events and their future changing trends are of great importance in water resources planning and management. In this study, we employed self-calibrating Palmer drought severity index (SC-PDSI), cluster algorithm, and severity-area-duration (SAD) methods to identify drought events and analyze the spatial and temporal distributions of various drought characteristics in China using observed data and CMIP5 model outputs. Results showed that during the historical period (1961–2000), the drought event of September 1965 was the most severe, affecting 47.07% of the entire land area of China, and shorter duration drought centers (lasting less than 6 months) were distributed all over the country. In the future (2021–2060), under both representative concentration pathway (RCP) 4.5 and RCP 8.5 scenarios, drought is projected to occur less frequently, but the duration of the most severe drought event is expected to be longer than that in the historical period. Furthermore, drought centers with shorter duration are expected to occur throughout China, but the long-duration drought centers (lasting more than 24 months) are expected to mostly occur in the west of the arid region and in the northeast of the semi-arid region. [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]