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Accurate simulation and reliable projection of temperature and precipitation over China under climate change is important for proposing adaptation measures for future natural ecosystems. This study proposes a novel method to construct an optimal reliability ensemble averaging (REA) subset from the Coupled Model Intercomparison Project Phase 6 (CMIP6) based on their historical performance in simulating temperature and precipitation across different subregions. The optimal REA ensemble outperforms the multi‐model ensemble mean (MMEM) and single optimal model in reproducing the spatial patterns of historical annual mean temperature and precipitation over China from 1985 to 2014. Under the examined Shared Socioeconomic Pathway scenarios (SSP1‐2.6, SSP2‐4.5 and SSP5‐8.5), the REA projects persistent warming and increased precipitation towards the end of the 21st century, intensifying under higher emissions. Nationwide mean temperature rises of 1.39, 2.69 and 5.05°C, and precipitation increases of 9%, 10% and 20% are projected in the long‐term (2081–2100) relative to 1995–2014 under SSP1‐2.6, SSP2‐4.5 and SSP5‐8.5 scenarios, respectively. Northwestern China and the Tibetan Plateau are expected to experience amplified warming and precipitation increases, respectively. Compared to the MMEM, the REA generally indicates reduced warming but larger precipitation increases, especially over the Tibetan Plateau under higher‐emissions scenarios. The REA exhibits lower projection uncertainty than the MMEM for both temperature and precipitation, primarily attributed to reduced internal variability. The novel optimal framework for REA shows the potential for extracting robust regional climate information applicable to different subregions of China. This study may contribute to new comprehension of future climate change over China. [ABSTRACT FROM AUTHOR]

• Quantified future thaw trends of frozen carbon on the TP based on 15 GCMs. • Compared frozen carbon thaw under two schemes with and without permafrost area shrinkage. • Underscored the pivotal role of permafrost area shrinkage in quantifying frozen carbon thaw. • Emphasized the tremendous potential for future carbon emissions from the TP permafrost area. Permafrost degradation on the Tibetan Plateau (TP) is anticipated to result in the thaw of permafrost carbon. Existing studies have been conducted to assess the future thaw of frozen carbon on the TP, primarily focusing on the deepening of the active layer while neglecting the impact of permafrost area shrinkage. This oversight may lead to a significant underestimation of the potential thaw of frozen carbon. Our research underscores the pivotal role of permafrost area shrinkage in estimating the future thaw of frozen carbon. Our findings reveal that when the combined effects of permafrost area shrinkage and active layer deepening are considered, the thaw rates of frozen carbon in various radiative forcing scenarios are nearly four times those based on active layer deepening alone. Notably, our results demonstrate substantial thaw of frozen organic carbon in the TP permafrost area under all four future scenarios: In the low radiative forcing scenario SSP1-2.6, it is predicted that 55.4 % of the organic carbon in the permafrost area 0–10 m soils will be in a state of thaw by 2100, and more than 90 % in the high radiative forcing scenario SSP5-8.5. This substantial thaw is poised to diminish the TP's current carbon sink function significantly. Our study emphasizes that as global warming persists, frozen carbon in permafrost areas will play a more active role in global carbon cycle processes in the future. Furthermore, we stress the importance of considering permafrost area shrinkage in understanding the thaw of frozen carbon, providing valuable insights for carbon balance studies on the TP. [ABSTRACT FROM AUTHOR]

Interactions among different large-scale ocean-atmosphere coupled modes are exceptionally complex. Diverse scale modes interact through oceanic circulations, ocean-atmosphere heat fluxes, and atmospheric bridges, thus affecting both the global weather system and long-term climate changes. This paper presents a review of the interaction mechanisms among six ocean-atmosphere coupled modes (ENSO, PDO, IOD, AO, NAO, and AMO) and their impacts on the South and East Asian Monsoon. Identifying the changes in the dynamics and energy budgets caused by the spatial structure evolution and amplitude change of various ocean-atmosphere coupled modes can yield a better understanding of their forcing effects on climate change. These effects are not only restricted to surrounding regions, but also significant interaction is found between the distant equator and the polar region. Interactions between various ocean-atmosphere coupled modes occur through Rossby wave activity, westerly airflow, cyclone circulation, and pressure gradients. However, because of the complexity of the relationship between multiple factors, it remains difficult to clarify the driving mechanism of each coupled mode change. More importantly, predictions based on long-term observation data are still a weak link in climate change research. This review summarizes the current knowledge on the interaction among the six ocean-atmosphere coupled modes, thus uncovering their impacts on South and East Asian Monsoon from a global perspective. • None of the ocean-atmosphere coupled modes exist independently. • Atmospheric bridges and ocean heat transfer exert an important impact on climate. • Circulation anomalies are triggered through waveguide in the mid-latitude region. • The equatorial region promotes vortex to affect the middle–high latitude regions. [ABSTRACT FROM AUTHOR]

[Display omitted] • From spatiotemporal dimension to analyze drought propagation of SPEI to SSMI on the TP. • There is a lag time of 2–3 months from SPEI to SSMI and increases from summer to winter. • Climate, vegetation and permafrost type have an impact on drought propagation. • In winter, drought duration decreases in 45% of the TP after drought propagation, and drought severity decreases in 52%, particularly in the Inner TP. • The direction of propagation from SPEI to SSMI is predominantly northwest. Meteorological drought signals trigger different types of droughts by propagating in the water and energy cycle processes. The understanding of the propagation process from meteorological to soil moisture drought is not clear on the Tibetan Plateau (TP). We used the standardized precipitation index (SPEI) and the standardized soil moisture index (SSMI) to represent meteorological and soil moisture drought. By using Mann-Kendall (MK) trend test, wavelet analysis, run theory, Moran's I and drought migration model, we evaluated the trend of SPEI and SSMI on the TP from 1980 to 2018, analyzed the response relationship, explored the temporal (lag time (LT), propagation rate, duration (DD) and severity (DS)) and spatial (spatial autocorrelation, trajectory, direction and distance) properties of drought propagation, and discussed the potential factors. The result indicated that SPEI intensified at winter and annual scales, SSMI mitigated at all time scales. Both of them showed a consistent dry trend in the southeastern TP. In the time dimension, SSMI usually lagged behind SPEI by about 2–3 months, and the LT increased from summer to winter. The LT tended to be shorter in summer in regions characterized by humid and semi-humid climates, meadows and shrublands, and seasonally frozen ground. Propagation rates were greater in the southeast than northwest. After propagation, DD and DS became weaker in winter (45 % and 52 % of regions decreased, respectively) and stronger in summer (80 % and 76 % of regions increased, respectively). In the spatial dimension, the LT of adjacent regions is closely related, dominated by High - High values and Low-Low values. SSMI had shorter migration trajectories and slower migration rates than SPEI. In addition, the direction of drought propagation was predominantly northwest. For the first time, this study has provided insights into the spatial and temporal propagation of meteorological drought to soil moisture drought on the TP and provides a theoretical basis for understanding drought propagation and predicting soil moisture drought. [ABSTRACT FROM AUTHOR]

There are various empirical models used in the estimation of global solar radiation; however, knowledge of direct and diffuse solar radiation is insufficient. Global solar radiation is the sum of direct and diffuse solar radiation, and a method that calculates global solar radiation from the estimated direct and diffuse solar radiation was further proposed in this study. The observed daily solar radiation and meteorological data from 97 stations during 1993–2016 were used for the analysis, and the results indicated that the concave-shaped relationship with relative sunshine duration was more obvious for direct solar radiation than for global solar radiation, while an inverted u-shaped relationship was found for diffuse solar radiation. Generally, the performances of empirical models in estimating direct and diffuse solar radiation were worse than the estimation of global solar radiation. However, because the bias of estimated direct and diffuse solar radiation was partially offset, the results in this study indicated that global solar radiation can be better calculated from the estimated direct and diffuse solar radiation when compared with the best performed empirical model, especially in data-scarce regions. The results of this study will aid in better estimations and understanding of the variations in global solar radiation, as well as direct and diffuse solar radiation. [ABSTRACT FROM AUTHOR]

This study provides the first comprehensive assessment of Regional Climate Model version 4.6.1 (RegCM4) for the Tibetan Plateau (TP) region. A wide range of model configurations were analyzed with different parameterizations employed to represent cumulus convection (Kuo, Grell, Emanuel, Kain, and Tiedtke), land surface processes (BATS and CLM), planetary boundary layer turbulence (Holtslag and UW PBL), and radiation (CCM3 and RRTM). In addition to the above experiments at a 30-km horizontal resolution, another experiment was conducted based upon the use of a double-nested dynamic downscaling method to construct a simulation at a 10-km resolution to study the sensitivity to the model resolution. We evaluated a 20-year simulation for precipitation, cloud cover, surface radiation budget, 2-m air temperature, and the surface atmospheric circulation against ground and satellite-based observations during the period 1989–2008. Among the factors analyzed regarding sensitivity, precipitation was unsurprisingly found to be sensitive to the cumulus parameterization scheme, and the CLM is found to reduce rainfall compared with BATS, which is satisfactory for both the Emanuel and Tiedtke schemes. Compared with the cumulus convection schemes, the cloud cover and surface radiation budget are sensitive to the land surface, PBL, and radiation schemes. Generally, the CLM is characterized by reduced mean cloud cover and enhanced surface longwave and shortwave radiation compared with BATS. Conversely, the UW PBL and RRTM radiation schemes result in increased cloud cover and less surface radiation compared with the default options in RegCM4. All experiments, except those employing the Kuo scheme, represent the mean 2-m air temperature and regional circulation patterns reasonably well. At the basin scale, the seasonal cycle and interannual variations of precipitation are found to be not well depicted by most model configurations, although the temperature field was well reproduced. Considering all the analyzed variables collectively, the Tiedtke scheme combined with the CLM land surface model is demonstrated to provide the best performance over the TP. However, the higher-resolution version of the model improves the precipitation simulation significantly, particularly in the Brahmaputra river basin, which is located in the north of the Himalayas. [ABSTRACT FROM AUTHOR]

This paper focuses on the first work face under a thick loose layer of sediment and thin bedrock in the No. 8 Mining District of the Baodian Coal Mine in the Yanzhou mining area of China. Due to mining, the hydrogeological conditions in the aquifers at the bottom of the thick, loose sediment layers have been greatly changed in the shallow areas in this area. The main problem is a low-pressure, water-rich aquifer. However, this problem could be remedied by modifying the coal pillars to prevent sand flow instead of water seepage. To do so, measurements of the first work face were obtained from drilling data, and the stress distribution and plastic zone were determined by examining the mining of the upper part of the no. 3 coal seam using FLAC3D numerical analysis software. The simulated results were also compared with the empirically calculated results. Comprehensive analysis indicates that modifying the coal pillars from preventing water seepage or inrush to preventing sand flow appears feasible, and provides an important reference for increasing mining areas and recovery of coal resources. [ABSTRACT FROM AUTHOR]

Droughts are regional phenomena that dynamic varied along the time; however, the spatiotemporal dynamic processes of drought were usually ignored in the drought identification methods. To better understand the space-time structure of drought, a space-time continuum drought identification method was used to identify drought intensity, duration, and area in Huai River basin, and their multiple dependences were modeled by copulas. The Intensity-Area-Frequency (IAF) curves were used to model the regional variation of drought in this study. Without identified space-time structure of drought, the construction of IAF curves is usually focusing on the decreasing drought intensity with increasing areal extent. However, stronger drought intensity was found to be followed by larger areal extent when considering the space-time structure of drought, and a copula-based method was introduced to better constructive IAF curves. Conditional probabilities of several drought characteristics taking extreme values were further analyzed. Compared to probabilities estimated by univariate frequency analysis, results indicate that occurrence frequency of drought was underestimated when neglecting any natural characteristic of drought, and underestimation was more serious for the more extreme situations of drought. Furthermore, owing to stronger dependences of drought characteristics from short-term to long-term, more serious underestimations of occurrence frequency of drought were found for the drought from short-term to long-term when neglecting any natural characteristic of drought. [ABSTRACT FROM AUTHOR]

The Asian Summer Monsoons (ASM) represent the main source of precipitation in China and East Asia with about one third of the world population and a region of widespread civilizations. Identifying the temporal and spatial patterns (pathways) of these monsoonal events during the Late Holocene to today has been a matter of debate amongst the scientific community. Here we show that the distribution patterns of the cosmogenic isotope 10Be and oceanic 127I in the topsoil across China exhibit imprints of the main ASM pathways. Our results indicate the monsoon pathway pattern persisted for several millennia or more and suggest a strong bond between 10Be and water vapor transport patterns. Our data also reveal a127I distribution pattern controlled by the ASM pathways, rather than proximity to the sea or bedrock weathering. The persistent pathway of the ASM during the late Holocene, together with higher than average global soil iodine concentration, may have further strengthened the development of civilizations in this region of the world through reduction of iodine deficiency related diseases. • The distribution of 10Be and 127I concentratioins in topsoil is presented. • The relationship model of 10Be concentration and annual precipitation rate is established. • The relative stability of the Asian Summer Monsoon during the late Holocene is found. [ABSTRACT FROM AUTHOR]

Highlights • Reduction of wind speed was the major driving force for decreasing trends in ET 0. • Actual and potential evapotranspiration exhibited an asymmetric complementary relationship. • Vegetation greening was mediated by elevation. • Non-uniform climate warming imposed opposite impacts on vegetation growth. Abstract This study comprehensively analyzed long-term (1960–2014) variations of potential and actual evapotranspiration (ET) and quantified their inter-annual and seasonal sensitivity and attribution to climate and vegetation growth changes in the upper reaches of the Yellow River Basin (UYRB). Satellite-derived vegetation greenness and in situ measured hydrometeorological datasets were used. Average annual reference evapotranspiration (ET 0) showed significant decreasing trend (p < 0.05) by 0.32 mm year−1 over the past 55 years. Results obtained from recovered stationary series and sensitivity analyses showed that reduction of wind speed was the major driving force for decreasing trends in annual and seasonal ET 0. Water budget-derived actual evapotranspiration (ET a) increased dramatically during the study period, whereas potential evapotranspiration (ET p) calculated from Penman equation and pan evaporation (ET pan) decreased significantly, suggesting the existence of evaporation paradox over the UYRB. ET a and ET p or ET pan exhibited complementary behavior, while the complementary relationship was asymmetric. During the period 1982–2014, vegetation greening occurred in most areas (65.6%) of the UYRB and was mediated by elevation. Interestingly, non-uniform climate warming imposed opposite impacts on vegetation growth, namely inter-annual and seasonal NDVI was stimulated by daytime temperature but suppressed by nighttime temperature. Furthermore, the positive impacts imposed by daytime temperature on NDVI was much larger in spring than in autumn and summer. Large-scale coherent vegetation greening would be the primary factor affecting inter-annual ET a in comparison with climate factors. These results help in deep understanding the hydrological response to climate change in cold mountain regions. [ABSTRACT FROM AUTHOR]

• Seasonal positive SM-P and negative SM-T2m feedback detected at TP. • Positive SM-runoff feedback dominated at TP, especially in summer and autumn. • ET linked in the SM-P-T2m feedback, but the nexus of SM-ET-ROF is complex. • Inner TP, Sources of Yellow-Yangtze-Mekong-Salween river basin as SM-hydroclimate interacting hotspot. • Common compound aggregation method is efficient to recognize hotspot among multi-data. Land-atmosphere energy and moisture exchanges exert great impacts on local and regional climate. However, high uncertainties exist in the recent land–atmosphere interactions due to scarce observations and difficulties in modeling at high elevations and cold regions. This study applied multiple high-resolution reanalysis products (ERA5-land, GLDAS Noah and CLSM products) and one regional climate model, RegCM4, to diagnose the interaction pattern and strength of seasonal soil moisture and hydroclimate on the Tibetan Plateau (TP) using a conditional correlation coefficient method and the global land–atmosphere coupling experimental modeling approach. A compound aggregation method is applied to recognize hot spots with strong soil moisture-hydroclimate interactions among multiple data. As a result, the Changtang Plateau in the inner TP, the sources of the Yellow, Yangtze, Mekong, Salween, and Lancang Rivers and part of the Brahmaputra River basin in the south-southeastern TP are diagnosed with strong land–atmosphere interactions in most seasons. In summer, the coupling strength is stronger, and the covered area is much wider and spatially continuous as the climate turns warm. All applied data indicate a positive dominant soil moisture-precipitation feedback, and a negative soil moisture-temperature feedback at the hot spots. Meanwhile, the soil moisture-runoff feedback is strong and positive at most parts of the TP, especially at the hot spots and in summer. Evapotranspiration acts as a positive linkage in the soil moisture-precipitation-temperature interactions, while the nexus of soil moisture, evapotranspiration and runoff is complicated. This study contributes to understanding local land-hydroclimate interactions in the high elevation and cold climate of the TP. Additionally, the found the proposed compound aggregation method efficient for compound studies. [ABSTRACT FROM AUTHOR]

Glaciers, lakes, rivers, and vegetation are particularly sensitive to the change of precipitation in the transition zone between arid and humid regions of the Tibetan Plateau. This study analyzed the spatiotemporal evolution of precipitation and its mechanisms under dynamic and thermodynamic processes based on in situ and satellite precipitation data of the Tibetan Plateau. The results indicate that the proportion of areas with annual precipitation <400 mm or >2000 mm decreases, while the proportion of areas with annual precipitation between 400 and 2000 mm increases from 1998 to 2018. This shows that precipitation in arid, semi-arid, and semi-humid regions exhibits an increasing trend, while that in southeastern humid regions exhibits a decreasing trend. Moreover, the dynamic process has a stronger effect on the change of precipitation than the thermodynamic one. In particular, the former is twice as strong as the latter, indicating that the atmospheric circulation wind has a more significant impact on the precipitation change. Although the arid, semi-arid, and semi-humid regions show a wetting trend, their physical mechanisms are different. The decrease of negative contribution of the advection and the increase of positive contribution of the convergence lead to the increase of precipitation in northwestern arid and semi-arid regions, while the convergence and advection show a slight decrease in the eastern semi-humid and humid regions. • The precipitation of arid, semi-arid and semi-humid regions tends to increase. • The precipitation in the southeastern humid climate region tends to decrease. • The mechanisms of precipitation change in the northwest and east are different. • The changes of dynamic and thermodynamic in the northwest and east are different. [ABSTRACT FROM AUTHOR]

Accurate estimates of canopy conductance ( g c ) are essential for quantifying the carbon, water and energy fluxes of ecosystem and understanding the patterns of water utilization of vegetation in arid regions. To this end, g c of Haloxylon ammodendron community, dominated by three desert shrub species, was calculated using the inversed Penman-Monteith equation from measurements of sap flow and concurrent microclimate over two main growing seasons (2014–2015). Then, it was used to examine the Jarvis-Stewart (JS) models which comprised different response functions and the simplified process-based model (BTA) to select the best one for our study species and climate. Photosynthetically active radiation and vapor pressure deficit typically covary throughout the day and are known have opposite effects on g c . When this effects was taken into account, both the JS model and the BTA model produced better g c fittings. Selection of proper vapor pressure deficit function and air temperature function significantly improved the performance of the JS model. The best JS model given a correlation coefficient of 0.89, RMSE of 1.99 mm s −1 and average percent error of 19% in comparison with the PM-calculated g c , while the best BTA model outperformed this model, reflected by higher correlation coefficient (0.90), and lower RMSE (1.93 mm s −1 ) and average percent error (9%). The average decoupling coefficient was 0.28, indicating canopies of H. ammodendron community were well coupled from the atmosphere. These findings addressed the importance of selection of stress function and consideration of air temperature for improving g c estimation in arid region, and gain new knowledge on the environmental control on canopy conductance. [ABSTRACT FROM AUTHOR]

The hydrological response to the potential future climate change in Yangtze River Basin (YRB), China, was assessed by using an ensemble of 54 climate change simulations. The Coupled Model Intercomparison Project 5 simulations under two new Representative Concentration Pathways (RCP) 4.5 and 8.5 emission scenarios were downscaled and used to drive the Variable Infiltration Capacity hydrological model. This study found that the range of temperature changes is homogeneous for almost the entire region, with an average annual increase of more than 2 °C under RCP4.5 and even more than 4 °C under RCP8.5 in the end of the twenty first century. The warmest period (June-July-August) of the year would experience lower changes than the colder ones (December-January-February). Overall, mean precipitation was projected to increase slightly in YRB, with large dispersion among different global climate models, especially during the dry season months. These phenomena lead to changes in future streamflow for three mainstream hydrological stations (Cuntan, Yichang, and Datong), with slightly increasing annual average streamflows, especially at the end of twenty first century. Compared with the percentage change of mean flow, the high flow shows (90th percentile on the probability of no exceedance) a higher increasing trend and the low flow (10th percentile) shows a decreasing trend or lower increasing trend. The maximum daily discharges with 5, 10, 15, and 30-year return periods show an increasing trend in most sub-basins in the future. Therefore, extreme hydrological events (e.g., floods and droughts) will increase significantly, although the annual mean streamflow shows insignificant change. The findings of this study would provide scientific supports to implement the integrated adaptive water resource management for climate change at regional scales in the YRB. [ABSTRACT FROM AUTHOR]

ABSTRACT The soil moisture-precipitation (SM-P) feedback process can affect the water and energy cycles at local to regional scale, subsequently affecting the water distribution in space and time. This study investigates SM-P feedback at different time scales over Asia during boreal summer season based on the covariation between SM and P. In this article the positive (negative) feedback means positive (negative) statistical correlations between SM-P. This is based on the statistical relationship and do not reflect physical process associated between SM and P. The Global Land Data Assimilation System (GLDAS) data, Climate Forecast System Reanalysis (CFSR) data and regional climate model, version 4 (RegCM4) simulations are adopted for analysis in this study. The results indicate a negative SM-P relationship at a seasonal time scale over mid-high latitudes of the study area whereas a positive but weak and spatial scattered correlation pattern is observed at the interannual time scale. A positive relationship is diagnosed over India, Indochina, and southeast China regions at seasonal (though weak) and interannual time scales. The positive and/or negative SM-P correlation patterns observed at different time scales depends on the memory associated with seasonal precipitation and soil moisture. The strength of the SM-P relationship seems to be influenced by the threshold behaviour of soil moisture, especially at the interannual time scale. This indicates that beyond a certain threshold in soil moisture anomalies likely to have significant influence on precipitation. [ABSTRACT FROM AUTHOR]

The role of environmental variables in controlling transpiration ( E c ) is an important, but not well-understood, aspect of transpiration modeling in arid desert regions. Taking three dominant desert shrubs, Haloxylon ammodendron , Nitraria tangutorum , and Calligonum mongolicum , as examples, we aim to evaluate the applicability of three transpiration models, i.e. the modified Jarvis-Stewart model (MJS), the simplified process-based model (BTA), and the artificial neural network model (ANN) at different temporal scales. The stem sap flow of each species was monitored using the stem heat balance approach over both the 2014 and 2015 main growing seasons. Concurrent environmental variables were also measured with an automatic weather station. The ANN model generally produced better simulations of E c than the MJS and BTA models at both hourly and daily scales, indicating its advantage in solving complicated, nonlinear problems between transpiration rate and environmental driving forces. The solar radiation and vapor pressure deficit were crucial variables in modeling E c for all three species. The performance of the MJS and ANN models was significantly improved by incorporating root-zone soil moisture. We also found that the difference between hourly and daily fitted parameter values was considerable for the MJS and BTA models. Therefore, these models need to be recalibrated when applied at different temporal scales. This study provides insights regarding the application and performance of current transpiration models in arid desert regions, and thus provides a deeper understanding of eco-hydrological processes and sustainable ecosystem management at the study site. [ABSTRACT FROM AUTHOR]

[Display omitted] • An integrated approach involving HGS modeling and isotope analysis is developed. • The contribution of the subsurface water to the stream is 32% for one rainfall event. • Rainfall infiltration-mixing-exfiltration process is vital to runoff generation. • Exfiltration-induced overland flow is the dominant water source for a rainfall event. The majority of runoff studies to date have reported a similar pattern of rapid rain-to-runoff conversion via overland flow and shallow subsurface water flow, as well as the ubiquity of thresholds and hysteresis in rainfall-runoff response. But each of those approaches has limitations in terms of inference and process description. Processes of water transport and mixing and how they influence runoff generation are still not well understood or quantified. In this study, HydroGeoSphere, a fully-integrated surface/subsurface flow model, was used together with stable isotopes for disentangling runoff generation mechanisms in a headwater catchment. The study area (0.21 km2) is the first-level tributary of the Xin'an Jiang River located in a humid climate region of eastern China. Water flow simulation elucidated the spatial water transport process, and isotope tracing quantified the complex water mixing process between the shallow soil and hillslope surface. This study provides insights into the rapid transformation of rainfall infiltration and mixing in soil and exfiltration to a hillslope. Results show that the stream runoff was separated into rainfall-induced overland flow (9 %), exfiltration-induced overland flow (including the 53 % of mixed water from rainfall infiltration and 6 % of the stored soil water), and subsurface flow (32 %). Exfiltration-induced overland flow was the dominant water source in the headwater catchment during a rainfall-runoff event. The mutual influence of rainfall infiltration and soil water exfiltration caused the shallow soil to rapidly become saturated, thus forming saturation excess overland flow. The consistence of estimated soil water velocity based on the integrated isotope and numerical modeling approach, at about 0.4 m/d nearby the stream channel, improved the reliability of model visualizations. Further analysis indicates that water flow paths and velocities responding to the rainfall event were attributed to the soil moisture conditions and topography. This study demonstrates that identifying the rapid mixing processes between the rain and the soil water was crucial for understanding hillslope overland flow and runoff generation in headwater catchments. [ABSTRACT FROM AUTHOR]

Changes in climate are likely to induce changes in precipitation characteristics including intensity, frequency, duration and patterns of events. In this paper, we evaluate the performance of multiple regional climate models (RCMs) in the North American Regional Climate Change Assessment Program (NARCCAP) to simulate storm properties including storm duration, inter-storm period, storm intensity, and within-storm patterns at eight locations in the continental US. We also investigate the future projections of them based on precipitation from NARCCAP historic runs and future runs. Results illustrate that NARCCAP RCMs are consistent with observed precipitation in the seasonal variation of storm duration and inter-storm period, but fail to simulate the magnitude. The ability to simulate the seasonal trend of average storm intensity varies among locations. Within-storm patterns from RCMs exhibit greater variability than from observed records. Comparisons between RCM-historic simulations and RCM projections indicate that there is a large variation in the future changes in storm properties. However, multi-model ensembles of the storm properties suggest that most regions of the United States will experience future changes in storm properties that includes shorter storm duration, longer inter-storm period, and larger average storm intensity. [ABSTRACT FROM AUTHOR]

This paper compares the historical simulations and future projections of surface air temperature over the Tibetan Plateau of the updated Coupled Model Intercomparison Project phase (CMIP6) and the precedent phase of the project (CMIP5) to quantify differences in the projections under different scenarios. Model evaluation for the historical period (1961–2005) indicates that the multi-model ensemble (MME) mean of CMIP6 outperforms CMIP5 MME in simulating spatial–temporal characteristics of surface air temperature. The temperature changes relative to 1986–2005 are projected in the near-term (2021–2040), mid-term (2041–2060), and long-term (2081–2100) future under Shared Socio-economic Pathway (SSP)2-4.5 and SSP5-8.5 of CMIP6 and Representative Concentration Pathway (RCP)4.5 and RCP8.5 of CMIP5. The projected temperature shows larger increases in the long-term projection compared with the near- and mid-term projection under both SSPs and RCPs. CMIP6 MME projects higher temperature changes and accelerated warming trends relative to CMIP5 MME. Additionally, the projected temperature increases and warming rates show a significant elevation dependency, especially in the long-term projection. The uncertainty for future projections is quantified by the square root of error variance (SREV) method. The results record a clear reduction in the uncertainty of CMIP6 temperature relative to CMIP5 primarily concentrated at the elevation zones of over 5000 m. The analysis of the projected temperature over the Tibetan Plateau is of great significance for policy-makers to make socio-economic adjustments for the future warming. This study is conducive to the credibility of future temperature projections for CMIP6 and enhances our comprehension of the uncertainty of SSP and RCP scenarios. [ABSTRACT FROM AUTHOR]

• Spatial difference of runoff evolution attribution was quantitatively analyzed. • The runoff was more sensitive to precipitation and underlying surface change than potential evaporation. • The increase of climate aridity index directly led to the decrease of the sensitivity coefficients. • Climate change increased upstream runoff and decreased midstream and downstream runoff. • Underlying surface change was the dominant factor leading to runoff reduction. Attribution analysis of runoff evolution under changing environmental conditions is currently a hot yet challenging topic in hydrology research. In this study, the Budyko method was used to quantitatively identify the effects of climate conditions and the underlying surface such as topography, land use and vegetation cover on the runoff changes in the Yellow River Basin during 1961–2018, and to clarify the spatial differences in the sensitivity and attribution of the runoff evolution by dividing the entire basin into sub-basins. The results show that the runoff was more sensitive to the underlying surface and precipitation changes than to the potential evaporation. The sensitivity coefficients decreased from upstream to downstream and the aridity index increased. The contribution rates of the climatic and the underlying surface changes to the runoff changes were 10.3–36.8% and 62.9–88.7%, respectively, and the underlying surface changes were the dominant factor causing the decrease in the runoff. Climate change led to increased runoff in the upper reaches and decreased runoff in the middle and lower reaches; while the underlying surface changes led to decreased runoff throughout the entire basin, especially in the middle reaches of the Yellow River. The quantified spatial differences in the runoff evolution attribution can help improve regional water resource management and provide theoretical support for studying the water cycle evolution mechanism in the Yellow River Basin. [ABSTRACT FROM AUTHOR]

Basin-scale runoff changes reflect the comprehensive impact of various environmental variables including climate and vegetation. Among them, vegetation plays an important role in the process of runoff generation and is one of the key links affecting the hydrological cycle. However, the contribution of vegetation to runoff changes is still unclear. In order to analyze the main driving factors of runoff changes in the Yanhe River Basin, this research builds a BPG model based on the Budyko framework, Porporato model, and Guswa model to evaluate the sensitivity coefficient of runoff to vegetation change, and quantitatively reveals the contribution of vegetation to runoff change. The results showed that, the runoff in the Yanhe River Basin decreased significantly from 1982 to 2018, and a mutation point occurred in 1999. After that, the runoff decreased by 29.88% and the NDVI increased by 15.30%. In terms of the sensitivity to runoff changes, runoff is more sensitive to changes in basin characteristics including vegetation than the climate change. According to the concepts of relative contribution and absolute contribution proposed in this research, the relative contribution rate and absolute contribution rate of climate change and basin characteristic changes were − 18.13%, 117.67% and 43.22%, 56.78%, respectively. Changes in basin characteristics such as vegetation, terraces and check dams caused by human activities are the main causes for runoff changes. The relative contribution rate and absolute contribution rate of vegetation change to runoff change were 34.98% and 16.88%, respectively, which is one of the dominant factors for basin characteristics change. And basin characteristic factors such as artificial water withdrawal, terraces and silt dams are the other main contributors to runoff changes. The research results can provide a theoretical basis for guiding future ecological restoration projects and water resources planning in the basin. • BPG model was built to evaluate the sensitivity and quantitatively reveal the contribution of vegetation to runoff change. • Proposed the concepts of relative contribution and absolute contribution of runoff change. • The runoff was more sensitive to basin characteristics change than climate change. • Climate change led to runoff increase while basin characteristics change led to runoff reduction in Yanhe River. • Changes in basin characteristics such as vegetation are the dominant factors of runoff changes. [ABSTRACT FROM AUTHOR]

The regional drought predictability is strongly influenced by teleconnections factors. Among them, El Niño-Southern Oscillation (ENSO) is important to drought occurrence. However, it is still not fully understood how the probability of regional droughts corresponding to different ENSO regimes varies with time lags. In this study, the event-based coincidence analysis (ECA) is employed to statistically derive the relationships regarding time information and magnitude between conventional ENSO (c-ENSO)/ENSO Modoki (ENSO_M) episodes and drought events. The standardized precipitation evapotranspiration index (SPEI) based on station-records is used to determine meteorological droughts. Our study focuses on the largest freshwater lake of China, Poyang Lake basin (PLB), as severe droughts have occurred there frequently. Results indicate that the summer-autumn continuous drought dominates the severe droughts, with a frequent onset in August/September, and a cessation in October/November. The likelihood of drought occurrence is highest during cool phases of c-ENSO (CEN), followed by warm ENSO_M (WEM), warm c-ENSO (WEN), and cool ENSO_M (CEM). The influence of WEN/WEM on droughts is statistically significant mostly for a time lag of 10 months, whereas CEN/CEM shows no lagged influence. Furthermore, the variability of the 850 hPa wind anomalies during different ENSO episodes at various time lags is corresponding to the lagged influence of ENSO on droughts. The development and persistence of droughts is resulting from strengthened northeasterly wind anomalies over the PLB. Our findings demonstrate that the ENSO anomalies are early warning signals of droughts and hence can be beneficial for increasing the drought predictivity • A novel statistical framework to quantify the probability of droughts responding to ENSO with varied time lags is developed. • The influence of WEN/WEM on the droughts in the PLB is statistically significant mostly for a time lag of 10 months. • The strengthened northeasterly wind anomalies over the PLB likely results in the development of ENSO-induced droughts. [ABSTRACT FROM AUTHOR]

With a booming development characterized by new urbanization in current China, urban water consumption attracts growing concerns. An efficient and probabilistic prediction of urban water consumption plays a vital role for urban planning toward sustainable development, especially in megacities limited by water resources. However, the data insufficiency issue commonly exists nowadays and seriously restricts further development of urban water simulation. In this article, we proposed a consolidated framework for probabilistic prediction of water consumption under an incompletely informational circumstance to deal with the challenge. The model was constructed based on a state-of-the-art Bayesian neural networks (BNNs) technique. Three dominated influencing factors were identified and included into the BNN model. Future impact factors were generated by using a variety of methods including a quadratic polynomial model, a regression and auto-regressive moving average combination model and a Grey Verhulst model. Thereafter, water consumption projection (2013-2020) and uncertainty estimates was done. Results showed that the model matched well with observations. Through reducing the dependence on large amount of information and constructing a probabilistic means incorporating uncertainty estimation, the new approach can work better than conventional means in support of water resources planning and management under an incompletely informational circumstance. [ABSTRACT FROM AUTHOR]

This study aims to investigate the soil temperature atmosphere (ST Atm) coupling strength and their influence on the subsequent climate anomalies over Asia based on a regional climate model RegCM4 with both statistical analysis method and numerical experiments. The major findings are as follows: (1) The soil temperature precipitation (ST P) coupling is quite weak and spatially scattered from both RegCM4 output and GLDAS data in each season with the only obvious signals existing over the north India region in summer season according to the RegCM4 output; the soil temperature 2m air temperature (ST T2m) coupling is strong and spatially continuous with the India (in spring, summer and autumn seasons), South Indochina (in spring and summer seasons) and part of North China (in summer season) standing out as hotspots. (2) The soil temperature evapotranspiration (ST ET) and soil temperature evaporative fraction (ST EF) coupling almost resembles the same spatial patterns and magnitude in each season. Both the ET and EF play an important role in linking ST P coupling in each season, but not in the ST T2m coupling. The hotspots of ST T2m coupling outweigh the areas with strong ST ET and ST EF coupling. Only the India and Indochina in each season are recognized by the RegCM4 while the Indochina and west Asia in spring, north India, Indochina and part of mid-high latitudes in summer season pinpointed by GLDAS data show consistent strong ST T2m coupling with significant ST ET and ST EF coupling. This finding demonstrates the complicated ST Atm coupling. (3) The ST anomalies prescribed at the first step of each season can only persist a short time (within 5 days) over most part of the study area while the fixed one-month anomalies can last longer (approximately 2 months with colder anomalies and 45 days with warmer anomalies in tropical regions). (4) The impact of ST anomalies on subsequent precipitation is quite weak and can be ignored over most part of the study area, while the impact on subsequent T2m is obvious and spatially continuous. The spatial patterns for the changes of climate variables (e.g., latent heat flux (LH), sensible heat flux (SH), ET, T2m) are almost consistent with the changes of ST over most part of the study area (except India and Indochina in spring and autumn seasons) where warmer (colder) ST anomalies lead to increase (decrease) of LH, SH, ET and T2m, demonstrating the important role of land atmosphere interactions in the locale climate. Over the India and Indochina, the large-scale circulation dominates the local climate in spring and autumn seasons. (5) The impact of colder ST anomalies can last longer than the warmer ones. Among the spring, summer and autumn seasons, the impact persists shortest in summer and longest in autumn, especially over the India region. [ABSTRACT FROM AUTHOR]

ABSTRACT Given the availability of a new generation of general circulation model simulations from the Coupled Model Intercomparison Project Phase 5 ( CMIP5) archive, we attempt to evaluate the model output by using three variants of the transformed Mielke measure to assess (1) the performance of the models in simulating historical surface temperature and precipitation, (2) the climate change response of the models to future greenhouse gases ( GHGs) scenarios, and (3) the consistency of the projected change of each model with that of the multi-model ensemble ( MME) mean. Most models exhibited varying degrees of skills, depending on the region and season, whereas a few models were identified as performing well globally, including the CMCC models, IPSL-CM5A-MR, and BCC-CSM1.1M. Models with the highest and lowest climate sensitivities, as well as those that project future climate changes most resembling the MME mean, were identified. The future precipitation and temperature changes projected by the MPI models and NCAR-CESM1 models were found to best resemble the overall MME. Finer resolution was found to improve model performance in simulating historical climate in most regions and seasons, particularly for temperature; however, it does not have a significant effect on the response of model climates to future GHGs scenarios. We found that no model can simultaneously exhibits good performance in simulating historical climate and in projecting a future climate that is close to the MME mean. Determining the 'best' overall model is difficult because 'best' is dependent on the specific applications for which a model will be used. Evaluating climate models is an important step to build confidence in their application for impact assessment. Our study provides a basis for concerned groups choosing climate models for their subsequent studies. [ABSTRACT FROM AUTHOR]

Rice is one of most important crops in China, accounting for approximately 18% of total cultivated area. Rice productivity is significantly affected by undergoing climate change and vulnerable with water stress. Therefore, investigating the responses of rice growth and water resources utilization to more pronounced climate change is of great importance for water resources planning and management in terms of maintaining the ecosystem integrity and ensuring the food security. In this study, the changes of rice yield, water consumption (ET), irrigation water requirement (IWR), water use efficiency (WUE) and irrigation water use efficiency (IWUE) from 1961 to 2010 in three typical sites (Kunshan and Nanjing in the Yangtze River Basin, and Kaifeng in the Yellow River Basin) in rice plantation region of China were evaluated by means of validated rice crop model ORYZA2000. Their responses to future climate scenarios of 21 century were investigated by driving ORYZA2000 with downscaling climatic data from HadCM3 (Hadley Centre Coupled Model version 3) under A2 and B2 emission scenarios with the help of a statistical downscaling method (SDSM). The results exhibit a significant decline in rice yield was identified by 49.3 kg ha −1 , 32.0 kg ha −1 and 45.8 kg ha −1 for Kunshan station, Nanjing station and Kaifeng station, respectively, in the past 50 years due to obviously shortened rice growth duration (0.20 day a −1 , 0.15 day a −1 and 0.27 day a −1 , respectively). While changes of ET and IWE were different for three stations representing by significant increase of ET and IWE in Kunshan, non-significant increase in Nanjing and significant decrease in Kaifeng. Whereas accompanying production reduction, simulated WUE and IWUE for three stations all presented significant deceasing trends ranging from 0.06 kg ha −1 mm −1 to 0.16 kg ha −1 mm −1 . The future projection results under IPCC SRES A2 and B2 emission scenarios indicated the generally negative effect of climate warming to rice yield (maximum by −18.9% decline in 2090s in Kunshan) during the 21 century due to remarkable shortened growth period, resulting in generally depressed WUE and IWUE, although there would be the distinct response of the ET and IWR to future climate change for the three stations. Meanwhile, the increase of CO 2 concentration under future climate is beneficial to raise the rice yield, alleviate crop water consumption and irrigation water requirements and improve the water use efficiencies of rice in a certain degree. Further works should be carried out to capture simulation uncertainties in climate change impact assessment with consideration of interactions among anthropogenic activities, environmental and biological factors. [ABSTRACT FROM AUTHOR]

Abstract: Hydrologic cycles of most high altitude glacierized watersheds in the Tibetan Plateau are not closely monitored due to their inaccessibility. Understanding the hydrologic cycle in such a basin may provide insight into the role climate plays on changes in glacier mass. Thus, hydrologic simulations with a physical perspective in the Tibetan glacierized watershed are of great significance. A high altitude glacierized basin in the central Tibetan Plateau, Qugaqie basin, was investigated with an energy-balance based glacier-melt model and the Gridded Surface Subsurface Hydrologic Analysis (GSSHA) model. With these two models, glacier mass balance was estimated and basin runoff from glaciers was simulated at a daily time step. Results from the simulation period (October 1, 2006–September 30, 2011) demonstrated that the glaciers experienced a large negative surface mass balance with the cumulative value of −300cmw.e.. In other words, up to 13.93×106 m3 water volume was melting out from the glaciers during these five years. In the 2007/08year, however, the glaciers experienced a surplus mass balance because of the low air temperature and increased precipitation in the summer season. Infiltration, evapotranspiration (ET), and overland flow were also calculated using the GSSHA model. Results showed that precipitation, the main water source, contributed roughly 95% to the total mass gain of the annual water balance in the Qugaqie basin during the study period, while the glacial runoff (snow/ice melting) contributed 5% water balance. In the water loss, 17% of annual water volume was consumed by the ET process. As a result, the remaining water volume (83%) converted to the basin river flow to the Lake Nam Co. In the summertime, the glacial runoff accounted for 15% of the total basin runoff volume, while this contribution increased in the upstream portion to 46% due to a large percentage of glacierized area. The analysis showed that the glacial runoff contributions to the total river flow decrease significantly due to the decreased air temperature in the summer of 2008. In general, the integrated model produced acceptable estimations of hydrologic response in this high altitude glacierized basin, which is jointly fed by precipitation and glacial runoff. This study suggests that, a process-based model for glacierized basins can provide a reasonable simulation of hydrologic response and further enhance our understanding of this high altitude region in the Tibetan Plateau. [Copyright &y& Elsevier]

Accurate soil moisture information is useful in agricultural practice, weather forecasting, and various hydrological applications. Although land surface modeling provides a viable approach to simulating soil moisture, many factors such as errors in the precipitation can affect the accuracy of soil moisture simulations. This paper examined how precipitation rate and evapotranspiration rate affect the accuracy of soil moisture simulation using simple biosphere model with and without data assimilation through ensemble Kalman filter (EnKF). For each of the two variables, seven levels of relative errors (−20, −10, −5, 0, 5, 10 and 20 %) were introduced independently, thus a total of 49 combined cases were investigated. Observations from Wudaogou Hydrology Experimental site in the Huaihe River basin, China, were used to drive and verify the simulations. Results indicate that when the error of precipitation rate is within 10 % of the observations, the resulting error in soil moisture simulations is less significant and manageable, thus the simulated precipitation can be used to drive hydrological models in poorly gauged catchments when observations are not available. When the error of evapotranspiration rate is within 20 % of the observations, which is partly caused by model structural and parameterization errors, its impact on soil moisture simulation is less significant and can be acceptable. This study also demonstrated that the EnKF can perform consistently well to improve soil moisture simulation with less sensitivity to precipitation errors. [ABSTRACT FROM AUTHOR]

The transport of bromide (Br) under matric heads of 0, −2, −5, and −10 cm using undisturbed soil columns was investigated for understanding the solute transport in arid soils. Undisturbed soil cores were collected at ground surface, directly below where tension infiltrometer measurements were made in the Amargosa Desert, Nevada, United States. Laboratory experiments were conducted by introducing water containing Br tracer into a soil column maintained at steady-state conditions. The observed data of breakthrough curves ( BTC) were well fitted to an one-region model, except for the cores at saturation, and a core at the matric head of −5 cm, from which the observed data were better fitted to a two-region model. Fitted pore water velocities with the one-region model ranged from 1.2 to 56.6 cm/h, and fitted dispersion coefficients ( D) ranged from 2.2 to 100 cm2/h. Results for the core analyzed with the two-region model indicated that D ranged from 27.6 to 70.9 cm2/h at saturation, and 25.7 cm2/h at the matric head of −5 cm; fraction of mobile water ( β) ranged from 0.18 to 0.65, and mass transfer coefficient ( ω) ranged from 0.006 to 0.03. In summary, the water fluxes and Br dispersion coefficients at investigated matric heads were very high due to the coarseness of the soils and possibly due to preferential flow pathways. These high water fluxes and Br dispersion coefficients would lead to a higher risk of deeper leaching accumulating nitrate nitrogen to the groundwater, and have significant effects on the desert ecosystem. [ABSTRACT FROM AUTHOR]

Abstract: In this study, we test our hypothesis that no single index such as El Niño-Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), Atlantic Multi-decadal Oscillation (AMO) or North Atlantic Oscillation (NAO) derived from the Pacific and Atlantic Oceans can explain the multi-scale temporal variability and spatial distribution of heavy precipitation in the western United States. Instead, it may be possible to utilize a characterization of their integrated effect or some other unidentified factors which reflects the combined physical oceanic–atmospheric processes that occur. For this purpose, Empirical orthogonal function (EOF) analysis is performed on summer (April–September) and winter (October–March) heavy precipitation expressed as total precipitation when daily precipitation is larger than 95th percentile (R95) to indentify the leading modes of variability during the period 1948–2009. The correlation between the principle components (PCs) of each EOF mode with Sea Surface Temperature (SST) anomalies is evaluated. The analysis has shown that the leading modes of R95 variability and the connections between local R95 and SST over western United States are seasonally dependent. The first EOF mode of summer R95 is associated with AMO. The first two EOF modes of winter R95 are related to an integrated effects of ENSO, PDO, and NAO which explain nearly half (49%) of the spatial and temporal variance in R95 in this region. Additionally, the coupled effects of these three oceanic–atmospheric oscillations on winter R95 are evaluated by investigating the ENSO-R95 responses modulated by a combination of different PDO and NAO phases. Based on our analyses and predicted future states of these oceanic–atmospheric oscillations, we suggest possible heavy precipitation scenarios for upcoming decades which may be useful to forecasters and water managers. [Copyright &y& Elsevier]

• Spatial consistency is considered to define extreme precipitation. • Regional extreme precipitation has increased in both frequency and spatial coverage. • PDO-/ENSO phases increase regional extreme precipitation at various scales in summer. • PDO+/ENSO phases increase the regional extreme precipitation in winter. • Features in the pressure field significantly respond to PDO and ENSO. The frequency of extreme precipitation is increasing globally and poses a significant threat to human and natural systems. At the regional scale, these changes are becoming increasingly uncertain. Therefore, it is critical to understand the spatiotemporal evolution of extreme precipitation on a regional scale. In this study, we applied the connected component labelling algorithm to define regional extreme precipitation events (REPEs). This approach considers spatial coverage and its correlation with precipitation. We further investigated the spatiotemporal changes in extreme precipitation in the Yangtze River basin using the empirical orthogonal function and examined their potential relationships with large-scale climate indices, including the El Niño-Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO). The results show that REPEs in the study area exhibited an increasing trend in both frequency and spatial coverage since 1970. In addition, the integrated effects of PDO and ENSO have a significant impact on REPEs at various scales in summer and at large scales in winter. We also analysed the differences in these events between the current year and the following year for PDO and ENSO combinations and found that the position of REPEs change with different PDO and ENSO combinations in both summer and winter season. The spatiotemporal characteristics of REPEs in the study area reveal the corresponding connections with the East Asian continent–ocean 500-hPa pressure field. Based on our analysis and current predictions of these ocean–atmospheric oscillations, we suggest creating more REPE scenarios for upcoming decades, which may benefit forecasting and water resource management. [ABSTRACT FROM AUTHOR]

With the firm demonstration of the in vivo presence and biological functions of many non- B DNA structures, it is of great significance to understand their physiological roles from the perspective of structural conformation, stability, and transition kinetics. Although relatively simple in primary sequences compared to proteins, non- B DNA species show rather versatile conformations and dynamic transitions. As the most-studied non- B DNA species, the G-quadruplex displays a myriad of conformations that can interconvert between each other in different solutions. These features impose challenges for ensemble-average techniques, such as X-ray crystallography, NMR spectroscopy, and circular dichroism ( CD), but leave room for single-molecular approaches to illustrate the structure, stability, and transition kinetics of individual non- B DNA species in a solution mixture. Deconvolution of the mixture can be further facilitated by statistical data treatment, such as iPoDNano ( integrated population deconvolution with nanometer resolution), which resolves populations with subnanometer size differences. This Personal Account summarizes current mechanical unfolding and refolding methods to interrogate single non- B DNA species, with an emphasis on DNA G-quadruplexes and i-motifs. These single-molecule studies start to demonstrate that structures and transitions in non- B DNA species can approach the complexity of those in RNA or proteins, which provides solid justification for the biological functions carried out by non- B DNA species. [ABSTRACT FROM AUTHOR]

Summary: Hybrid data assimilation (DA) is greatly used in recent hydrology and water resources research. In this study, one newly introduced technique, the ensemble particle filter (EnPF), formed by coupling ensemble Kalman filter (EnKF) with particle filter (PF), is applied for a multi-layer soil moisture prediction in the Meilin watershed based on the support vector machines (SVMs). The data used in this paper includes six-layer soil moisture: 0–5cm, 30cm, 50cm, 100cm, 200cm and 300cm and five meteorological parameters: soil temperature at 5cm and 20cm, air temperature, relative humidity and solar radiation in the study area. In order to investigate this EnPF approach, another two filters, EnKF and PF are applied as another two data assimilation methods to conduct a comparison. In addition, the SVM model simulated data without updating with data assimilation technique is discussed as well to evaluate the data assimilation technique. Two experimental cases are explored here, one with 200 initial training ensemble members in the SVM training phase while the other with 1000 initial training ensemble members. Three main findings are obtained in this study: (1) the SVMs machine is a statistically sound and robust model for soil moisture prediction in both the surface and root zone layers, and the larger the initial training data ensemble, the more effective the operator derived; (2) data assimilation technique does improve the performance of SVM modeling; (3) EnPF outweighs the performance of other two filters as well as the SVM model; Moreover, the ability of EnPF and PF is not positively related to the resampling ensemble size, when the resampling size exceeds a certain amount, the performance of EnPF and PF would be degraded. Because the EnPF still performs well than EnKF, it can be used as a powerful data assimilation tool in the soil moisture prediction. [Copyright &y& Elsevier]

The Yangtze Economic Belt (hereafter, the Belt) is one of the most dynamic regions in China in terms of population growth, economic progress, industrialization, and urbanization. It faces many resource constraints (land, food, energy) and environmental challenges (pollution, biodiversity loss) under rapid population growth and economic development. Interactions between human and natural systems are at the heart of the challenges facing the sustainable development of the Belt. By adopting systematic thinking and the methodology of system dynamics simulation, an integrated system-dynamics-based simulation model for the Belt, named ANEMI_Yangtze, has been developed based on the third version of ANEMI3. The nine sectors of population, economy, land, food, energy, water, carbon, nutrients, and fish are currently included in ANEMI_Yangtze. This paper presents the ANEMI_Yangtze model description, which includes (i) the identification of the cross-sectoral interactions and feedbacks involved in shaping the Belt's system behavior over time; (ii) the identification of the feedbacks within each sector that drive the state variables in that sector; and (iii) the description of a new fish sector and modifications to the population, food, energy, and water sectors, including the underlying theoretical basis for model equations. The validation and robustness tests confirm that the ANEMI_Yangtze model can be used to support scenario development, policy assessment, and decision-making. This study aims to improve the understanding of the complex interactions among coupled human–natural systems in the Belt to provide the foundation for science-based policies for the sustainable development of the Belt. [ABSTRACT FROM AUTHOR]

Abstract: With well-determined hydraulic parameters in a hydrologic model, a traditional data assimilation method (such as the Kalman filter and its extensions) can be used to retrieve root zone soil moisture under uncertain initial state variables (e.g., initial soil moisture content) and good simulated results can be achieved. However, when the key soil hydraulic parameters are incorrect, the error is non-Gaussian, as the Kalman filter will produce a persistent bias in its predictions. In this paper, we propose a method coupling optimal parameters and extended Kalman filter data assimilation (OP-EKF) by combining optimal parameter estimation, the extended Kalman filter (EKF) assimilation method, a particle swarm optimization (PSO) algorithm, and Richards’ equation. We examine the accuracy of estimating root zone soil moisture through the optimal parameters and extended Kalman filter data assimilation method by using observed in situ data at the Meiling experimental station, China. Results indicate that merely using EKF for assimilating surface soil moisture content to obtain soil moisture content in the root zone will produce a persistent bias between simulated and observed values. Using the OP-EKF assimilation method, estimates were clearly improved. If the soil profile is heterogeneous, soil moisture retrieval is accurate in the 0–50cm soil profile and is inaccurate at 100cm depth. Results indicate that the method is useful for retrieving root zone soil moisture over large areas and long timescales even when available soil moisture data are limited to the surface layer, and soil moisture content are uncertain and soil hydraulic parameters are incorrect. [Copyright &y& Elsevier]

Abstract: The application of artificial neural network (ANN) to rainfall-runoff simulations has provided promising results in recent years. However, it is difficult to obtain satisfying results by using raw data for the direct prediction of the time series of streamflows. To improve simulating daily streamflow with back-propagation (BP) neural networks, the whole data set in this study is divided into two independent groups, flood period and non-flood period. The approaches and techniques of applying the division-based BP (DBP) in runoff simulation are presented in this paper. A comparison of the DBP model to the primitive BP model and the Xinanjiang model was also conducted to evaluate the effectiveness of the improvement. The numerical experimental results indicate that DBP model still overestimated flow peak, but improved considerably the streamflow simulation in the non-flood period. [Copyright &y& Elsevier]

Summary: A new method of coupling coarse-grid regional or global climate models with a much finer-grid hydrologic model is described, that is designed for interactive climate-hydrologic simulations with explicit changes in individual rivers, lakes, wetlands and water tables. Six vertical land-surface solutions with prescribed near-surface soil moistures or standing water depths within each coarse meteorological cell are obtained to disaggregate the relevant quantities (infiltration, runoff) to the finer hydrologic grid based on current near-surface soil moisture in the hydrologic model. Feedbacks on the climate (evaporation, surface heat flux) can be aggregated on the climate grid in the same way. The method is applied for the simulation over the North American continent using (i) NCEP/NCAR reanalyzed meteorologic data and Higgins precipitation data for recent decades, (ii) a vertical column land-surface model on the same coarse grid, and (iii) a new hydrologic model of river, lake and groundwater flow on a 20×20km grid. The predicted routing of major rivers and most lake extents are realistic, reflecting the hydrologic consistency of the 20-km topography. The modeled continental patterns of water-table depths, vadose-zone soil moisture and recharge rates are reasonable. The predicted seasonal discharges at the outlets of four major US river basins are in fair to good agreement with those observed, except for the Colorado where human influences drastically reduce the natural flow. [Copyright &y& Elsevier]

Significant soil water variation has often been found in top few meters of arid soils. Understanding soil water variation in these soils is crucial to groundwater recharge estimation, rainfall runoff process, risk assessment, and water resource management. A soil hydrologic model (SHM) was developed for simulating soil water movement in the vertical direction using time steps of minutes to days. To account for the dual processes of matrix and macropore flow, a parameterization scheme of dual processes has been adopted to derive effective hydraulic conductivity used in the SHM simulation. The integral-balance model based on water flux at different degrees of water saturation used to calculate the macropore conductivity is more useful in quantitatively integrating the macropore contribution to the dynamic soil water fluxes. The SHM, successfully applied to humid and semi-arid regions and validated at the Nevada Test Site (NTS) in this study, was used to evaluate soil water variation in an arid region, the NTS. Soil texture effects on soil water content have been evaluated; results indicate that higher hydraulic conductivity soils have less soil water content. A representative vegetation type at the NTS—Larrea tridentate is included to simulate the effects of vegetative cover on the soil water content. The simulations show that the bare soils have higher soil water content than the vegetated soils, which is consistent with observations and other modeled results. Due to low precipitation at the NTS for much of the year, effects of the macropore flow on soil water content are insignificant. However, the macropore flow could be an important factor influencing the soil water content during high precipitation events. [Copyright &y& Elsevier]

Intense precipitation events frequently occur in the Hanjiang River Basin (HRB) in China, causing major economic losses and affecting human security. Accurate precipitation simulations are sensitive to the choice of physical schemes in numerical weather prediction models. Therefore, in this study the performance of the different combinations of physical schemes in the Weather Research and Forecasting (WRF) model was investigated for the HRB. Five intense precipitation events in summer during the period 2008–2011 were selected. For simulating each intense precipitation event, an 18-member multi-physics ensemble was designed by using three cumulus (CU) schemes and four microphysics (MP) schemes. The temporal dynamics and spatial patterns of the simulated precipitation were evaluated systematically by a comparison to the China precipitation analysis reference data. A quantitative analysis using the Euclidean distance metric to synthesize the evaluation results was performed. The performed uncertainty analysis suggests that the skill of precipitation simulation is more sensitive to the choice of the CU scheme and less sensitive to the choice of the MP scheme. Our analysis shows that a suitable WRF physical configuration consists of Kain-Fritsch and WRF Single-Moment 6-class, which reaches a performance similar to that of the ensemble mean method. To our knowledge, this multi-physics ensemble study is the first effort to comprehensively evaluate the applicability of the WRF model to intense precipitation simulations over the HRB. Therefore, this study potentially contributes to the improvement of climate simulations for central China. • Cumulus schemes have primary impact on intense precipitation simulation while microphysics schemes have secondary impact. • A suitable WRF physical configuration is the combinations of the KF and WSM6 schemes. • This study potentially contributes to the improvement of climate simulations for central China. [ABSTRACT FROM AUTHOR]

The topography of the Tibetan Plateau (TP) plays an important role in the formation of the Asian monsoon as well as global climate change. In particular, the water vapor transport patters shows redistribution under the influence of high mountains, which profoundly impacts the landscape of the local and surrounding areas. Based on satellite precipitation data of global precipitation measurements from 2015 to 2018, the influence of the topography on the spatial and temporal distributions of the precipitation in the TP was evaluated. The results show that the precipitation distribution is clearly affected by the topography, and decreases from southeast to northwest. Precipitation mainly concentrates in the southern foothills of the Himalayas. In the hinterland of the TP, the gradient distance increases from southeast to northwest, with value changes from 100 mm / 60 km to 100 mm / 150 km. The maximum annual precipitation height in the windward side of the TP (west of Tianshan Mountains, south of Himalayas, and southwest of Hengduan Mountains) is below 2000 m, while in the northern and inner areas, it exceeds 4000 m. The precipitation isoline in the south and northwest of the TP is consistent with the elevation contour. However, in the northeastern and interior areas, the precipitation isoline is consistent with the orientation of the mountain structural belt. • The effect of topography on precipitation distribution is discussed in the Tibetan Plateau based on IMERG. • The vertical profile of topography and precipitation of the seven main mountains in the Tibetan Plateau is studied. • The horizontal distribution of precipitation and topography reveals the influence of topography on precipitation. • The maximum precipitation height and spatial-temporal distribution of the seven main mountains are obtained. • The influence of water vapor transport in the Westerlies and monsoon climate of the Tibetan Plateau is discussed. [ABSTRACT FROM AUTHOR]

Comprehensive Summary: Protein‐protein interactions (PPIs) play a crucial role in drug discovery and disease treatment. However, the development of effective drugs targeting PPIs remains challenging due to limited methodologies for probing their spatiotemporal anisotropy. Here, we propose a single‐molecule approach using a unique force circuit to investigate PPI dynamics and anisotropy under mechanical forces. Unlike conventional techniques, this approach enables the manipulation and real‐time monitoring of individual proteins at specific amino acids with defined geometry, offering insights into molecular mechanisms at the single‐molecule level. The DNA force circuit was constructed using click chemistry conjugation methods and genetic code expansion techniques, facilitating orthogonal conjugation between proteins and nucleic acids. The SET domain of the MLL1 protein and the tail of histone H3 were used as a model system to demonstrate the application of the DNA force circuit. With the use of atomic force microscopy and magnetic tweezers, optimized assembly procedures were developed. The DNA force circuit provides an exceptional platform for studying the anisotropy of PPIs and holds promise for advancing drug discovery research targeted at PPIs. [ABSTRACT FROM AUTHOR]

The impact on the hydrologic cycle of permafrost degradation under the influence of climate change has caused an inestimable threat to sustainable regulation of the ecosystem. This study quantified the responses of main hydrological elements, including soil moisture, groundwater, runoff components and discharge to totally degraded permafrost in eastern High Asia by establishing cases with and without thermodynamics using a cold region model combining hydrological processes and thermodynamics. The results showed that the model successfully simulated discharge in cold region basins. Totally degraded permafrost decreased soil moisture in the vadose zone (SMV) and increased the absolute depth to ground water (ADGW). In the daily scale, total permafrost degradation decreased the direct flow in autumn, slightly increased direct flow in spring and decreased interflow in summer. Total permafrost degradation also increased daily baseflow all year round and by >50% in spring, decreased daily discharge during autumn and increased daily discharge during spring. In the annual scale, total permafrost degradation increased direct flow, baseflow, and discharge, and decreased interflow. The magnitudes of these changes were positively related to the ratios of permafrost to the subbasin area. The responses of daily runoff components and discharge to totally degraded permafrost were significantly larger than the annual value. The groundwater level, direct flow and baseflow were far more sensitive to permafrost degradation than SMV, interflow and discharge. The responses of annual individual hydrological elements were more obvious than the annual discharge. These quantified results can be extensively used in lumped hydrology simulations, water resource assessments and eco-system management for partial permafrost degradation. Unlabelled Image • Responses of hydrologic elements to permafrost degradation are still un-quantified. • Two cases with and without thermodynamics using a fully coupled hydro-thermal model • Permafrost degradation decreases autumn and increases winter/spring discharge. • Smaller annual discharge increase in permafrost degradation than hydrologic elements [ABSTRACT FROM AUTHOR]

• Developed a new filter method – unscented weighted ensemble Kalman filter (UWEnKF). • UWEnKF is a highly effective and practical assimilation technique. • UWEnKF has better performance than EnKF. A new data assimilation technique, unscented weighted ensemble Kalman filter (UWEnKF) was developed based on the scaled unscented transformation and ensemble Kalman filter (EnKF). In UWEnKF, the individual members selected are unequally weighted and symmetric about the expectation. To investigate the performance of UWEnKF, nine assimilation experiments with different ensemble sizes (161, 1601, 16001) and different assimilation frequencies (every 6 h, every 12 h, every 24 h) were designed to assimilate soil surface (5 cm) moisture data observed at station HY in the upper reaches of the Yellow River, in the northeastern of Tibetan plateau, China into the Richards equation. The results showed that the performance of the filter was greatly affected by random noise, and the filter was sensitive to ensemble size and assimilation frequency. Increasing the ensemble size reduced the effects of random noise on filter performance in several independent assimilation runs (i.e., it decreased the differences between the results of the several independent assimilation runs). Reducing the assimilation frequency also reduced the effects of random noise on filter performance. UWEnKF gave more accurate soil moisture model results than EnKF for all ensemble sizes and assimilation frequencies at all soil depths. Additionally, EnKF may have different performances according to different initial conditions, but not for UWEnKF. Precipitation and soil properties uncertainties had some impact on filter performance. Thus, UWEnKF is a better choice than EnKF, while it is more computationally demanding, for improving soil moisture predictions by assimilating data from many sources, such as satellite-observed soil moisture data, at a low assimilation frequency (e.g., every 24 h). [ABSTRACT FROM AUTHOR]

• A high-density reservoir network is integrated into a distributed hydrologic model. • Despite the mitigation by reservoirs, climate impacts call on adaptation measures. • The framework can provide implications for regional water resources management. The Poyang Lake Basin (PLB) is expected to see more precipitation and higher temperature by 2050. Due to climate change, it is advisable to identify the vulnerable area and to investigate if the local reservoir network of hundreds of larger reservoirs and thousands of smaller reservoirs can effectively mitigate the climate-induced hydrologic variation. Therefore, the local high-density reservoir network is integrated into a distributed hydrologic model (HMS) through a fully coupled reservoir module. We then apply the extended HMS in a one-way coupled mode to the bias corrected Coordinated Regional Downscaling Experiment in East Asia (CORDEX-EA) regional climate simulations under two Representative Concentration Pathways – RCP4.5 and RCP8.5. Results indicate that climate change poses new challenges to water resources management for the PLB, with a likely decrease of water availability in the dry season but an increase of water availability, flood magnitude and flood frequency in the flood season till 2049. The local reservoir network can mitigate climate impacts by displacing excessive water resources in the flood season to the dry season and mitigating floods across the basin. Despite that, much of the southern basin is likely to see a higher risk of water shortage in the dry season, while most of the northern basin is expected to see a higher flood risk. The approach and findings are expected to improve the understanding of the role of reservoirs in the context of climate change, and provide implications for water resources management and climate change adaptation strategies on a regional scale. [ABSTRACT FROM AUTHOR]

In this paper, we applied the Empirical Orthogonal Function (EOF) analysis on a drought index expressed as consecutive dry days (CDD) to identify the drought variability in western United States. Based on the EOF analysis, correlation maps were generated between the leading principle component (PC) of seasonal CDD and sea surface temperature (SST) anomalies to explore the dynamic context of the leading modes in CDD. The EOF analysis indicates that the spatiotemporal pattern of winter CDD is related to an integrated impact from El Niño–Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), and Atlantic Multi-decadal Oscillation (AMO), while summer CDD is mainly controlled by PDO phases. We also calculated seasonal CDD anomalies during selected climatic phases to further evaluate the impacts of large-scale oceanic oscillation on the spatial pattern of droughts. We found that AMO+/PDO− will contribute to a consistent drought condition during the winter in the western United States. El Niño will bring a dry winter to the northern part of western United States while La Niña will bring a dry winter to the southern part. During El Niño years, the drought center changes with the type of El Niño events. Considering the future states of the examined ocean oscillations, we suggest possible drier than normal conditions in the western United States for upcoming decades, and moreover, an intensified drought for the coast areas of the north Pacific region and upper Mississippi River Basin. [ABSTRACT FROM AUTHOR]

Grylloprimevala jilina is a true cave insect living in the dark areas of caves. It has the characteristics of sparse skin pigmentation, degeneration of the compound eyes and monocular eyes, and obvious preference for high‐humidity and low‐temperature environments. Given the highly specialized, rare, and limited distribution, G. jilina is considered an endangered species and also a first‐level national protected insect in China. Cave creatures often undergo dramatic morphological changes in their sensory systems to adapt to the cave environment. Most previous studies mainly focused on morphological adaptive changes in cave insects, and only a few studied the changes at the gene level. In this study, we performed transcriptome analysis of G. jilina and constructed phylogenetic trees of genes that are related to environmental adaptation, including chemosensory, visual‐related, reproduction‐related, temperature adaptation‐related, and winged morph differentiation‐related genes. Besides, the expression levels of environmental adaption‐related genes in different tissues, including antennae, heads, thoraxes, abdomens, legs, and tails, were analyzed. The results showed the loss of chemosensory genes and vision‐related genes, the conservation of reproduction‐related genes and temperature adaptation‐related genes, and the conservation of wing‐related genes despite the loss of wings, and the results were consistent with other cave insects. The identification and expression study of genes possibly related to the environmental adaptability in G. jilina provided basic data for the protection of this endangered species and increased knowledge about insect evolution in general. [ABSTRACT FROM AUTHOR]