How human activities have altered hydrological droughts (streamflow deficits) in China during the past five decades (1961-2016) is investigated using the latest version (v2.0) of PCR-GLOBWB model at high spatial resolution (~10 km). Although both human activities and climate variability have significant effects on river flows over China, there are large regional north-south contrasts. Over northern China, human activities generally intensify hydrological droughts. We find that human activities exacerbated drought deficit by about 70-200% from 2004 to 2015. In contrast, droughts over southern China are generally alleviated by human activities. For instance, irrigation and water management (such as reservoir operation and water abstraction) increase drought StDef (standardized drought deficit volume) by about 80% in the Yellow River (north) but reduce it by about 20% in the Yangtze River (south). Human activities slightly reduce drought deficit in the Yangtze River due to the combination of large reservoir storage and low ratio of agriculture consumption to abstracted irrigation water. In contrast, hydrological drought is aggravated in the semiarid Yellow River basin because of high water consumption from agricultural sectors. This study suggests that human activities have contrasting influences on hydrological drought characteristics in the northern (intensification) and southern (mitigation) parts of China. Therefore, it is critical to consider the variable roles of human activities on hydrological drought in China when developing mitigation and adaptation strategies. Plain Language Summary China faces unprecedented challenges for water resources management under a changing climate, which is expected to lead to more frequent and severe droughts in the future. Of particular importance is streamflow drought, which jeopardizes regional water supply and local ecosystem services. On one hand, human activities through reservoir operation can effectively alleviate drought by releasing water during the low flow period. But on the other hand, water abstraction to meet sectoral water demand (such as irrigation) could exacerbate the streamflow deficit. To what extent such human activities differ across regions is not clear. In this study, we use a physically based hydrological and water resources model to investigate how human activities have altered streamflow droughts in China during the past five decades (1961-2016). We find that human activities generally alleviate streamflow droughts in the southern region (e.g., Yangtze River) but intensify them in the northern part of China (e.g., Yellow River). Our research highlights the contrasting geographical differences of human influences on hydrological drought across China, which can be useful for making more effective drought adaptation strategies.

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A multimodel ensemble of general circulation models (GCM) is a popular approach to assess hydrological impacts of climate change at local, regional, and global scales. The traditional multimodel ensemble approach has not considered different uncertainties across GCMs, which can be evaluated from the comparisons of simulations against observations. This study developed a comprehensive index to generate an optimal ensemble for two main climate fields (precipitation and temperature) for the studies of hydrological impacts of climate change over China. The index is established on the skill score of each bias-corrected model and different multimodel combinations using the outputs from phase 5 of the Coupled Model Intercomparison Project (CMIP5). Results show that the optimal ensemble of the nine selected models accurately captures the characteristics of spatial–temporal variabilities of precipitation and temperature over China. We discussed the uncertainty of subset ensembles of ranking models and optimal ensemble based on historical performance. We found that the optimal subset ensemble of nine models has relative smaller uncertainties compared with other subsets. Our proposed framework to postprocess the multimodel ensemble data has a wide range of applications for climate change assessment and impact studies.

The growth front of isotactic polypropylene (iPP) spherulites is studied with series of in-situ microanalyzing techniques: conventional source infrared microspectroscopic (CS-μIR), polarized infrared microspectroscopic imaging (SR-μPIR), and scanning X-ray microdiffraction (SR-μSXRD). By SR-μSXRD, the actual growth front boundary of spherulite was clearly defined, which is the boundary observed with an optical microscope. Measurements of CS-μIR and SR-μPIR on growing spherulites reveal that a growth front layer (GFL) with high content of conformational ordered long helices exists outside the growth front of spheurlite, which has a thickness up to 30 μm above 142 °C. These long helices preferentially orient perpendicular to the radial direction of spherulite, whose growth fashion seems correlating with the growth of spherulite.

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Acidic CO2 reduction (CO2R) holds promise for the synthesis of low‐carbon‐footprint chemicals using renewable electricity. However, the corrosion of catalysts in strong acids causes severe hydrogen evolution and rapid deterioration of CO2R performance. Here, by coating catalysts with an electrically nonconductive nanoporous SiC‐NafionTM layer, a near‐neutral pH was stabilized on catalyst surfaces, thereby protecting the catalysts against corrosion for durable CO2R in strong acids. Electrode microstructures played a critical role in regulating ion diffusion and stabilizing electrohydrodynamic flows near catalyst surfaces. This surface‐coating strategy was applied to three catalysts, SnBi, Ag, and Cu, and they exhibited high activity over extended CO2R operation in strong acids. Using a stratified SiC‐NafionTM/SnBi/polytetrafluoroethylene (PTFE) electrode, constant production of formic acid was achieved with a single‐pass carbon efficiency of >75 % and Faradaic efficiency of >90 % at 100 mA cm−2 over 125 h at pH 1.

Climate change directly impacts the hydrological cycle via increasing temperatures and seasonal precipitation shifts, which are variable at local scales. The water resources of the Upper Yangtze River Basin (UYRB) account for almost 40% and 15% of all water resources used in the Yangtze Basin and China, respectively. Future climate change and the possible responses of surface runoff in this region are urgent issues for China’s water security and sustainable socioeconomic development. This study evaluated the potential impacts of future climate change on the hydrological regimes (high flow (Q5), low flow (Q95), and mean annual runoff (MAR)) of the UYRB using global climate models (GCMs) and a variable infiltration capacity (VIC) model. We used the eight bias-corrected GCM outputs from Phase 5 of the Coupled Model Intercomparison Project (CMIP5) to examine the effects of climate change under two future representative concentration pathways (RCP4.5 and RCP8.5). The direct variance method was adopted to analyze the contributions of precipitation and temperature to future Q5, Q95, and MAR. The results showed that the equidistant cumulative distribution function (EDCDF) can considerably reduce biases in the temperature and precipitation fields of CMIP5 models and that the EDCDF captured the extreme values and spatial pattern of the climate fields. Relative to the baseline period (1961–1990), precipitation is projected to slightly increase in the future, while temperature is projected to considerably increase. Furthermore, Q5, Q95, and MAR are projected to decrease. The projected decreases in the median value of Q95 were 21.08% to 24.88% and 16.05% to 26.70% under RCP4.5 and RCP8.5, respectively; these decreases were larger than those of MAR and Q5. Temperature increases accounted for more than 99% of the projected changes, whereas precipitation had limited projected effects on Q95 and MAR. These results indicate the drought risk over the UYRB will increase considerably in the future.

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