Red-bed mudstone, prevalent in southwest China, poses a formidable challenge due to its hydrophilic clay minerals, resulting in expansion, deformation, and cracking upon exposure to moisture. This study addresses upli...Red-bed mudstone, prevalent in southwest China, poses a formidable challenge due to its hydrophilic clay minerals, resulting in expansion, deformation, and cracking upon exposure to moisture. This study addresses uplift deformation disasters in high-speed railways by employing a moisture diffusion-deformation-fracture coupling model based on the finite-discrete element method(FDEM). The model integrates the influence of cracks on moisture diffusion. The investigation into various excavation depths reveals a direct correlation between depth and the formation of tensile cracks at the bottom of the railway cutting. These cracks expedite moisture migration, significantly impacting the temporal and spatial evolution of the moisture field. Additionally, crack expansion dominates hygroscopic deformation, with the lateral coordinate of the crack zone determining peak vertical displacement. Furthermore, key factors influencing deformation in railway cuttings, including the swelling factor and initial moisture content at the bottom of the cutting, are explored. The number of tensile and shear cracks increases with greater excavation depth, particularly concerning shear cracks. Higher swelling factors and initial moisture contents result in an increased total number of cracks, predominantly shear cracks. Numerical calculations provide valuable insights, offering a scientific foundation and directional guidance for the precise prevention, control, prediction, and comprehensive treatment of mudstone-related issues in high-speed railways.展开更多
Stable water isotopes are natural tracers quantifying the contribution of moisture recycling to local precipitation,i.e.,the moisture recycling ratio,but various isotope-based models usually lead to different results,...Stable water isotopes are natural tracers quantifying the contribution of moisture recycling to local precipitation,i.e.,the moisture recycling ratio,but various isotope-based models usually lead to different results,which affects the accuracy of local moisture recycling.In this study,a total of 18 stations from four typical areas in China were selected to compare the performance of isotope-based linear and Bayesian mixing models and to determine local moisture recycling ratio.Among the three vapor sources including advection,transpiration,and surface evaporation,the advection vapor usually played a dominant role,and the contribution of surface evaporation was less than that of transpiration.When the abnormal values were ignored,the arithmetic averages of differences between isotope-based linear and the Bayesian mixing models were 0.9%for transpiration,0.2%for surface evaporation,and–1.1%for advection,respectively,and the medians were 0.5%,0.2%,and–0.8%,respectively.The importance of transpiration was slightly less for most cases when the Bayesian mixing model was applied,and the contribution of advection was relatively larger.The Bayesian mixing model was found to perform better in determining an efficient solution since linear model sometimes resulted in negative contribution ratios.Sensitivity test with two isotope scenarios indicated that the Bayesian model had a relatively low sensitivity to the changes in isotope input,and it was important to accurately estimate the isotopes in precipitation vapor.Generally,the Bayesian mixing model should be recommended instead of a linear model.The findings are useful for understanding the performance of isotope-based linear and Bayesian mixing models under various climate backgrounds.展开更多
Landslides are highly dangerous phenomena that occur in different parts of the world and pose significant threats to human populations. Intense rainfall events are the main triggering process for landslides in urbaniz...Landslides are highly dangerous phenomena that occur in different parts of the world and pose significant threats to human populations. Intense rainfall events are the main triggering process for landslides in urbanized slope regions, especially those considered high-risk areas. Various other factors contribute to the process;thus, it is essential to analyze the causes of such incidents in all possible ways. Soil moisture plays a critical role in the Earth’s surface-atmosphere interaction systems;hence, measurements and their estimations are crucial for understanding all processes involved in the water balance, especially those related to landslides. Soil moisture can be estimated from in-situ measurements using different sensors and techniques, satellite remote sensing, hydrological modeling, and indicators to index moisture conditions. Antecedent soil moisture can significantly impact runoff for the same rainfall event in a watershed. The Antecedent Precipitation Index (API) or “retained rainfall,” along with the antecedent moisture condition from the Natural Resources Conservation Service, is generally applied to estimate runoff in watersheds where data is limited or unavailable. This work aims to explore API in estimating soil moisture and establish thresholds based on landslide occurrences. The estimated soil moisture will be compared and calibrated using measurements obtained through multisensor capacitance probes installed in a high-risk area located in the mountainous region of Campos do Jordão municipality, São Paulo, Brazil. The API used in the calculation has been modified, where the recession coefficient depends on air temperature variability as well as the climatological mean temperature, which can be considered as losses in the water balance due to evapotranspiration. Once the API is calibrated, it will be used to extrapolate to the entire watershed and consequently estimate soil moisture. By utilizing recorded mass movements and comparing them with API and soil moisture, it will be possible to determine thresholds, thus enabling anticipation of landslide occurrences.展开更多
Climate change is one of the major global challenges and it can have a significant influence on the behaviour and resilience of geotechnical structures.The changes in moisture content in soil lead to effective stress ...Climate change is one of the major global challenges and it can have a significant influence on the behaviour and resilience of geotechnical structures.The changes in moisture content in soil lead to effective stress changes and can be accompanied by significant volume changes in reactive/expansive soils.The volume change leads to ground movement and can exert additional stresses on structures founded on or within a shallow depth of such soils.Climate change is likely to amplify the ground movement potential and the associated problems are likely to worsen.The effect of atmospheric boundary interaction on soil behaviour has often been correlated to Thornthwaite moisture index(TMI).In this study,the long-term weather data and anticipated future projections for various emission scenarios were used to generate a series of TMI maps for Australia.The changes in TMI were then correlated to the depth of suction change(H s),an important input in ground movement calculation.Under all climate scenarios considered,reductions in TMI and increases in H s values were observed.A hypothetical design scenario of a footing on expansive soil under current and future climate is discussed.It is observed that a design that might be considered adequate under the current climate scenario,may fail under future scenarios and accommodations should be made in the design for such events.展开更多
Monitoring agricultural drought using remote sensing data is crucial for precision irrigation in modern agriculture.Utilizing unmanned aerial vehicle(UAV)remote sensing,we explored the applicability of an empirical cr...Monitoring agricultural drought using remote sensing data is crucial for precision irrigation in modern agriculture.Utilizing unmanned aerial vehicle(UAV)remote sensing,we explored the applicability of an empirical crop water stress index(CWSI)based on canopy temperature and three-dimensional drought indices(TDDI)constructed from surface temperature(T_(s)),air temperature(T_(a))and five vegetation indices(VIs)for monitoring the moisture status of dryland crops.Three machine learning algorithms(random forest regression(RFR),support vector regression,and partial least squares regression)were used to compare the performance of the drought indices for vegetation moisture content(VMC)estimation in sorghum and maize.The main results of the study were as follows:(1)Comparative analysis of the drought indices revealed that T_(s)-T_(a)-normalized difference vegetation index(TDDIn)and T_(s)-T_(a)-enhanced vegetation index(TDDIe)were more strongly correlated with VMC compared with the other indices.The indices exhibited varying sensitivities to VMC under different irrigation regimes;the strongest correlation observed was for the TDDIe index with maize under the fully irrigated treatment(r=-0.93).(2)Regarding spatial and temporal characteristics,the TDDIn,TDDIe and CWSI indices showed minimal differences Over the experimental period,with coefficients of variation were 0.25,0.18 and 0.24,respectively.All three indices were capable of effectively characterizing the moisture distribution in dryland maize and sorghum crops,but the TDDI indices more accurately monitored the spatial distribution of crop moisture after a rainfall or irrigation event.(3)For prediction of the moisture content of single crops,RFR models based on TDDIn and TDDIe estimated VMC most accurately(R^(2)>0.7),and the TDDIn-based model predicted VMC with the highest accuracy when considering multiple-crop samples,with R^(2)and RMSE of 0.62 and 14.26%,respectively.Thus,TDDI proved more effective than the CWSI in estimating crop water content.展开更多
Recycled moisture is an important indicator of the renewal capacity of regional water resources.Due to the existence of Yulong Snow Mountain,Lijiang in Yunnan Province,southeast of the Qinghai-Tibet Plateau,China,is t...Recycled moisture is an important indicator of the renewal capacity of regional water resources.Due to the existence of Yulong Snow Mountain,Lijiang in Yunnan Province,southeast of the Qinghai-Tibet Plateau,China,is the closest ocean glacier area to the equator in Eurasia.Daily precipitation samples were collected from 2017 to 2018 in Lijiang to quantify the effect of sub-cloud evaporation and recycled moisture on precipitation combined with the d-excess model during monsoon and non-monsoon periods.The results indicated that the d-excess values of precipitation fluctuated between–35.6‰and 16.0‰,with an arithmetic mean of 3.5‰.The local meteoric water line(LMWL)wasδD=7.91δ^(18)O+2.50,with a slope slightly lower than the global meteoric water line(GMWL).Subcloud evaporation was higher during the non-monsoon season than during the monsoon season.It tended to peak in March and was primarily influenced by the relative humidity.The source of the water vapour affected the proportion of recycled moisture.According to the results of the Hybrid Single-Particle Lagrangian Integrated Trajectory(HYSPLIT)model,the main sources of water vapour in Lijiang area during the monsoon period were the southwest and southeast monsoons.During the non-monsoon period,water vapour was transported by a southwesterly flow.The recycled moisture in Lijiang area between March and October 2017 was 10.62%.Large variations were observed between the monsoon and non-monsoon seasons,with values of 5.48%and 25.65%,respectively.These differences were primarily attributed to variations in the advection of water vapour.The recycled moisture has played a supplementary role in the precipitation of Lijiang area.展开更多
The yield of winter wheat is hindered by drought and low temperature in the Loess Plateau of China.Two common mulching methods to conserve soil moisture,ridge furrows with plastic film mulching (RP) and flat soil surf...The yield of winter wheat is hindered by drought and low temperature in the Loess Plateau of China.Two common mulching methods to conserve soil moisture,ridge furrows with plastic film mulching (RP) and flat soil surfaces with plastic film mulching (FP) are helpful for wheat production.Our previous study indicated that FP could improve wheat yield more effectively than RP,but the reason remains unclear.The effect of mulching method on functional bacteria also needs to be further studied.In this study,winter wheat was employed to evaluate the impacts of mulching method on soil temperature,moisture content,microorganisms and grain yield.The results showed that FP had a warming effect when the soil temperature was low and a cooling effect when the temperature was too high.However,the ability to regulate soil temperature in the RP method was unstable and varied with year.The lowest negative accumulated soil temperature was found in the FP treatment,which was 20–89 and 43–99%lower than that of the RP and flat sowing with non-film mulching control (NP) treatments,respectively.Deep soil moisture was better transferred to topsoil for wheat growth in the FP and RP treatments than the NP treatment,which made the topsoil moisture in the two treatments (especially FP) more sufficient than that in the NP treatment during the early growing stage of wheat.However,due to the limited water resources in the study area,there was almost no difference between treatments in topsoil water storage during the later stage.The wheat yield in the FP treatment was significantly higher,by 12–16and 23–56%,respectively,than in the RP and NP treatments.Significant positive correlations were observed among the negative accumulated soil temperature,spike number and wheat yield.The Chao1 and Shannon indices in the RP treatment were 17 and 3.9%higher than those in the NP treatment,respectively.However,according to network relationship analysis,the interspecific relationships of bacteria were weakened in the RP treatment.Phosphorus solubilizing,ammonification and nitrification bacteria were more active in the RP than in the FP treatment,and microbes with nitrate reduction ability and plant pathogens were inhibited in the RP treatment,which improved nutrient availability and habitat for wheat.展开更多
Maize kernel moisture content(KMC)at harvest greatly affects mechanical harvesting,transport and storage.KMC is correlated with kernel dehydration rate(KDR)before and after physiological maturity.KMC and KDR are compl...Maize kernel moisture content(KMC)at harvest greatly affects mechanical harvesting,transport and storage.KMC is correlated with kernel dehydration rate(KDR)before and after physiological maturity.KMC and KDR are complex traits governed by multiple quantitative trait loci(QTL).Their genetic architecture is incompletely understood.We used a multiomics integration approach with an association panel to identify genes influencing KMC and KDR.A genome-wide association study using time-series KMC data from 7 to 70 days after pollination and their transformed KDR data revealed respectively 98and 279 loci significantly associated with KMC and KDR.Time-series transcriptome and proteome datasets were generated to construct KMC correlation networks,from which respectively 3111 and 759 module genes and proteins were identified as highly associated with KMC.Integrating multiomics analysis,several promising candidate genes for KMC and KDR,including Zm00001d047799 and Zm00001d035920,were identified.Further mutant experiments showed that Zm00001d047799,a gene encoding heat shock 70 kDa protein 5,reduced KMC in the late stage of kernel development.Our study provides resources for the identification of candidate genes influencing maize KMC and KDR,shedding light on the genetic architecture of dynamic changes in maize KMC.展开更多
Electronic skins can monitor minute physiological signal variations in the human skins and represent the body’s state,showing an emerging trend for alternative medical diagnostics and human-machine interfaces.In this...Electronic skins can monitor minute physiological signal variations in the human skins and represent the body’s state,showing an emerging trend for alternative medical diagnostics and human-machine interfaces.In this study,we designed a bioinspired directional moisture-wicking electronic skin(DMWES)based on the construction of heterogeneous fibrous membranes and the conductive MXene/CNTs electrospraying layer.Unidirectional moisture transfer was successfully realized by surface energy gradient and push-pull effect via the design of distinct hydrophobic-hydrophilic difference,which can spontaneously absorb sweat from the skin.The DMWES membrane showed excellent comprehensive pressure sensing performance,high sensitivity(maximum sensitivity of 548.09 kPa^(−1)),wide linear range,rapid response and recovery time.In addition,the single-electrode triboelectric nanogenerator based on the DMWES can deliver a high areal power density of 21.6μW m^(−2) and good cycling stability in high pressure energy harvesting.Moreover,the superior pressure sensing and triboelectric performance enabled the DMWES for all-range healthcare sensing,including accurate pulse monitoring,voice recognition,and gait recognition.This work will help to boost the development of the next-generation breathable electronic skins in the applications of AI,human-machine interaction,and soft robots.展开更多
Green sand is a mixture of silica sand,bentonite,water and coal powder,and other additives.Moisture content is an important index to characterize the properties of green sand.Based on the dielectric characteristics of...Green sand is a mixture of silica sand,bentonite,water and coal powder,and other additives.Moisture content is an important index to characterize the properties of green sand.Based on the dielectric characteristics of green sand and transmission line theory,a method for rapidly measuring the moisture content of green sand by means of a low frequency multiprobe detector was proposed.A system was constructed,where six detectors with different arrangements and probes were designed.The experimental results showed that the voltage difference of transmission line increases with the increasing frequency before 29 MHz while decreases after 35 MHz.A voltage difference platform occurs in the range of 29-35 MHz,which is suitable for measuring the moisture content due to its insensitivity to frequency.The electric field intensity gradually decreases with the increase of the probe depth,and the intensity of central probe is always greater than that of the edge probe.When the distance of the probe away from the sand sample surface is 80 mm,the electric field intensity of the edge probe is found to be very weak.The optimal excitation frequency for measuring the moisture content of green sand is 29-33 MHz.The optimal detector is the one with one center probe and three edge probes,and their lengths are 80 mm and 60 mm,respectively.The distance between the center and edge probes is 25 mm,and the diameter of probes is 5 mm.Taking the voltage difference of transmission line,bentonite content,coal powder content and compactability as parameters of the input layer,and the moisture content as a parameter of the output layer,a three-layer BP artificial neural network model for predicting the moisture content of green sand was constructed according to the experimental results at 33 MHz.The prediction error of the model is not higher than 3.3% when the moisture content of green sand is within the range of 3wt.%-7wt.%.展开更多
To better understand the mass transfer process of moisture in the soy protein isolate-corn starch(SPI-CS)films during preparation and storage process,the drying kinetics model of SPI-CS films with different formation ...To better understand the mass transfer process of moisture in the soy protein isolate-corn starch(SPI-CS)films during preparation and storage process,the drying kinetics model of SPI-CS films with different formation conditions during the drying process and the moisture adsorption characteristics of the SPI-CS films under different humidity conditions were investigated.Within the range of experimental conditions,the moisture migration rule in the SPI-CS films during the drying preparation was combined with the Page model which was expressed as MR=exp(-kt^(n)).It was found that the adsorption equilibrium needed shorter time(about 3 h)when the SPI-CS films existed in the environment with lower humidity(RH<54%).Additionally,the secondorder adsorption kinetic equation was successful to describe the moisture adsorption characteristic of the SPICS films during storage under different humidity conditions.展开更多
Seasonal prediction of summer precipitation over eastern China is closely linked to the East Asian monsoon circulation,which is largely affected by the El Niño-Southern Oscillation(ENSO).In this study,results sho...Seasonal prediction of summer precipitation over eastern China is closely linked to the East Asian monsoon circulation,which is largely affected by the El Niño-Southern Oscillation(ENSO).In this study,results show that spring soil moisture(SM)over the Indo-China peninsula(ICP)could be a reliable seasonal predictor for eastern China summer precipitation under non-ENSO conditions.When springtime SM anomalies are present over the ICP,they trigger a structured response in summertime precipitation over most of eastern China.The resultant south-to-north,tri-polar configuration of precipitation anomalies has a tendency to yield increased(decreased)precipitation in the Yangtze River basin and decreased(increased)in South and North China with a drier(wetter)spring soil condition in the ICP.The analyses show that ENSO exerts a powerful control on the East Asian circulation system in the ENSO-decaying summer.In the case of ENSO forcing,the seasonal predictability of the ICP spring SM for eastern China summer precipitation is suppressed.However,in the absence of the influence of ENSO sea surface temperature anomalies from the preceding winter,the SM anomalies over the ICP induce abnormal local heating and a consequent geopotential height response owing to its sustained control on local temperature,which could,in turn,lead to abnormal eastern China summer precipitation by affecting the East Asian summer monsoon circulation.The present findings provide a better understanding of the complexity of summer climate predictability over eastern China,which is of potential significance for improving the livelihood of the people.展开更多
With the extreme drought(flood)event in southern China from July to August in 2022(1999)as the research object,based on the comprehensive diagnosis and composite analysis on the anomalous drought and flood years from ...With the extreme drought(flood)event in southern China from July to August in 2022(1999)as the research object,based on the comprehensive diagnosis and composite analysis on the anomalous drought and flood years from July to August in 1961-2022,it is found that there are significant differences in the characteristics of the vertically integrated moisture flux(VIMF)anomaly circulation pattern and the VIMF convergence(VIMFC)anomaly in southern China in drought and flood years,and the VIMFC,a physical quantity,can be regarded as an indicative physical factor for the"strong signal"of drought and flood in southern China.Specifically,in drought years,the VIMF anomaly in southern China is an anticyclonic circulation pattern and the divergence characteristics of the VIMFC are prominent,while those are opposite in flood years.Based on the SST anomaly in the typical draught year of 2022 in southern China and the SST deviation distribution characteristics of abnormal draught and flood years from 1961 to 2022,five SST high impact areas(i.e.,the North Pacific Ocean,Northwest Pacific Ocean,Southwest Pacific Ocean,Indian Ocean,and East Pacific Ocean)are selected via the correlation analysis of VIMFC and the global SST in the preceding months(May and June)and in the study period(July and August)in 1961-2022,and their contributions to drought and flood in southern China are quantified.Our study reveals not only the persistent anomalous variation of SST in the Pacific and the Indian Ocean but also its impact on the pattern of moisture transport.Furthermore,it can be discovered from the positive and negative phase fitting of SST that the SST composite flow field in high impact areas can exhibit two types of anomalous moisture transport structures that are opposite to each other,namely an anticyclonic(cyclonic)circulation pattern anomaly in southern China and the coastal areas of east China.These two types of opposite anomalous moisture transport structures can not only drive the formation of drought(flood)in southern China but also exert its influence on the persistent development of the extreme weather.展开更多
Complex topography,special geographical location and sea-land-air interactions lead to high interannual variability of summer precipitation in the east of Southwest China(ESWC).However,the contributions,influencing fa...Complex topography,special geographical location and sea-land-air interactions lead to high interannual variability of summer precipitation in the east of Southwest China(ESWC).However,the contributions,influencing factors and mechanisms of remote and local evaporation remain to be further investigated.Using clustering analysis and Hybrid Single-Particle Lagrangian Integrated Trajectory version 5 model,we analyze the contributions of remote moisture transport and local evaporation to summer precipitation in the ESWC and their causes.There are mainly five remote moisture channels in the ESWC,namely the Arabian Sea channel,Bay of Bengal channel,western Pacific channel,Northwest channel 1 and Northwest channel 2.Among the five channels,the western Pacific channel has the largest number of trajectories,while the Bay of Bengal channel has the largest contribution rate of specific humidity(33.33%)and moisture flux(33.14%).The amount of regional average precipitation is close to that of the precipitation caused by remote moisture transport,and both are considerably greater than the rainfall amount caused by local evaporation.However,on interannual time scales,precipitation recirculation rates are negatively correlated to regional average precipitation and precipitation caused by remote moisture transport but are consistent with that caused by local evaporation.An apparent"+-+"wave train can be found on the height anomaly field in East Asia,and the sea surface temperature anomalies are positive in the equatorial Middle-East Pacific,the South China Sea,the Bay of Bengal and the Arabian Sea.These phenomena cause southwest-northeast moisture transport with strong updrafts,thereby resulting in more precipitation in the ESWC.展开更多
Soil moisture plays an important role in crop yield estimation,irrigation management,etc.Remote sensing technology has potential for large-scale and high spatial soil moisture mapping.However,offline remote sensing da...Soil moisture plays an important role in crop yield estimation,irrigation management,etc.Remote sensing technology has potential for large-scale and high spatial soil moisture mapping.However,offline remote sensing data processing is time-consuming and resource-intensive,and significantly hampers the efficiency and timeliness of soil moisture mapping.Due to the high-speed computing capabilities of remote sensing cloud platforms,a High Spatial Resolution Soil Moisture Estimation Framework(HSRSMEF)based on the Google Earth Engine(GEE)platform was developed in this study.The functions of the HSRSMEF include research area and input datasets customization,radar speckle noise filtering,optical-radar image spatio-temporal matching,soil moisture retrieving,soil moisture visualization and exporting.This paper tested the performance of HSRSMEF by combining Sentinel-1,Sentinel-2 images and insitu soil moisture data in the central farmland area of Jilin Province,China.Reconstructed Normalized Difference Vegetation Index(NDVI)based on the Savitzky-Golay algorithm conforms to the crop growth cycle,and its correlation with the original NDVI is about 0.99(P<0.001).The soil moisture accuracy of the random forest model(R 2=0.942,RMSE=0.013 m3/m3)is better than that of the water cloud model(R 2=0.334,RMSE=0.091 m3/m3).HSRSMEF transfers time-consuming offline operations to cloud computing platforms,achieving rapid and simplified high spatial resolution soil moisture mapping.展开更多
Climate change impacts on grasslands that cover a quarter of the global land area, have become unprecedented during the 21~(st) century. One of the important ecological realms, arid grasslands of northern China, which...Climate change impacts on grasslands that cover a quarter of the global land area, have become unprecedented during the 21~(st) century. One of the important ecological realms, arid grasslands of northern China, which occupy more than 70% of the region's land area. However, the impact of climate change on vegetation growth in these arid grasslands is not consistent and lacks corresponding quantitative research. In this study, NDVI(normalized difference vegetation index) and climate factors including temperature, precipitation, solar radiation, soil moisture, and meteorological drought were analyzed to explore the determinants of changes in grassland greenness in Inner Mongolia Autonomous Region(northern China) during 1982–2016. The results showed that grasslands in Inner Mongolia witnessed an obvious trend of seasonal greening during the study period. Two prominent climatic factors,precipitation and soil moisture accounted for approximately 33% and 27% of grassland NDVI trends in the region based on multiple linear regression and boosted regression tree methods. This finding highlights the impact of water constraints to vegetation growth in Inner Mongolia's grasslands. The dominant role of precipitation in regulating grassland NDVI trends in Inner Mongolia significantly weakened from 1982 to 1996, and the role of soil moisture strengthened after 1996. Our findings emphasize the enhanced importance of soil moisture in driving vegetation growth in arid grasslands of Inner Mongolia, which should be thoroughly investigated in the future.展开更多
When expansive soils in the original location are artificially transferred to landfill in different seasons,and subject to engineering activities afterwards,the corresponding deformation and stability of retaining str...When expansive soils in the original location are artificially transferred to landfill in different seasons,and subject to engineering activities afterwards,the corresponding deformation and stability of retaining structures become unpredictable.This necessitates the determination of lateral pressure coefficient at rest(k_(0) value)for expansive soils in landfill.Considering compaction,excavation of expansive soils,as well as construction of landfill in different seasons,series of stepwise loading and unloading consolidation tests at various moisture contents were carried out in this work to explore the evolution characteristics of k_(0) value and assess the dependence of k_(0) value on vertical stress and moisture content.Besides,scanning electron microscope(SEM)was used to track the change in microstructural features with vertical stresses.The results indicated that the k_(0) value of expansive soil shows a pronounced nonlinearity and is inextricably linked with vertical stress and moisture content,based on which a prediction formula to estimate the variation in k_(0) value with vertical stress during loading stage was proposed;there is a significant exponential increase in k_(0) value with overconsolidation ratio(OCR)during unloading stage,and OCR dominates the release of horizontal stress of expansive soil;SEM results revealed that with an increase in vertical stress,the anisotropy of expansive soil microstructure increases dramatically,causing a significant directional readjustment,which is macroscopically manifested as an initially rapid increase in k_(0) value;but when vertical stress increases to a critical value,the anisotropy of microstructure increases marginally,indicating a stable orientation occurring in the soil microstructure,which causes the k_(0) value to maintain a relatively stable value.展开更多
Environmental stability is a major bottleneck of perovskite solar cells.Only a handful of studies are investigating the effect of moisture on the structural degradation of the absorber.They mostly rely on ex situ expe...Environmental stability is a major bottleneck of perovskite solar cells.Only a handful of studies are investigating the effect of moisture on the structural degradation of the absorber.They mostly rely on ex situ experiments and on completely degraded samples,which restrict the assessment on initial and final stage.By combining in situ X-ray diffraction under controlled 85%relative humidity,and live observations of the water-induced degradation using liquid-cell transmission electron microscopy,we reveal two competitive degradation paths leading on one hand to the decomposition of state-of-theart mixed cation/anion(Cs_(0.05)(MA_(0.17)FA_(0.83))_(0.95)Pb(Br_(0.17)I_(0.83))_(3)(CsMAFA)into PbI_(2) through a dissolution/recrystallization mechanism and,on the other hand,to a non-equilibrium phase segregation leading to CsPb_(2)Br_(5) and a Cesium-poor/iodide-rich Cs_(0.05)-x(MA_(0.17)FA_(0.83))_(0.95)Pb(Br_(0.17-2y)I_(0.83)+2y)_(3) perovskite.This degradation mechanism is corroborated at atomic-scale resolution through solid-state ^(1)H and ^(133)Cs NMR analysis.Exposure to moisture leads to a film containing important heterogeneities in terms of morphology,photoluminescence intensities,and lifetimes.Our results provide new insights and consensus that complex perovskite compositions,though very performant as champion devices,are comparatively metastable,a trait that limits the chances to achieve long-term stability.展开更多
For many environmental and agricultural applications, an accurate estimation of surface soil moisture is essential. This study sought to determine whether combining Sentinel-1A, Sentinel-2A, and meteorological data wi...For many environmental and agricultural applications, an accurate estimation of surface soil moisture is essential. This study sought to determine whether combining Sentinel-1A, Sentinel-2A, and meteorological data with artificial neural networks (ANN) could improve soil moisture estimation in various land cover types. To train and evaluate the model’s performance, we used field data (provided by La Tuscia University) on the study area collected during time periods between October 2022, and December 2022. Surface soil moisture was measured at 29 locations. The performance of the model was trained, validated, and tested using input features in a 60:10:30 ratio, using the feed-forward ANN model. It was found that the ANN model exhibited high precision in predicting soil moisture. The model achieved a coefficient of determination (R<sup>2</sup>) of 0.71 and correlation coefficient (R) of 0.84. Furthermore, the incorporation of Random Forest (RF) algorithms for soil moisture prediction resulted in an improved R<sup>2</sup> of 0.89. The unique combination of active microwave, meteorological data and multispectral data provides an opportunity to exploit the complementary nature of the datasets. Through preprocessing, fusion, and ANN modeling, this research contributes to advancing soil moisture estimation techniques and providing valuable insights for water resource management and agricultural planning in the study area.展开更多
The objective of this study was to evaluate and recommend an asphalt mixture design with emerging additive technologies that would provide superior performance against asphalt concrete(AC)stripping and cracking.To ach...The objective of this study was to evaluate and recommend an asphalt mixture design with emerging additive technologies that would provide superior performance against asphalt concrete(AC)stripping and cracking.To achieve this objective,a laboratory test program was developed to evaluate the use of nanomaterials(nanoclay and graphene nanoplatelet),an emerging anti-stripping agent(adhere),and warm-mix asphalt technologies(ZycoTherm,Sasobit,and EvoTherm).Two mix types were evaluated,which were a stone-matrix asphalt(SMA)and a dense-graded binder mix.In addition,the modified Lottman test(AASHTO T 283)and the indirect tensile asphalt cracking test(IDEAL-CT)test were used as performance indicators of moisture damage resistance and cracking susceptibility.Results were analyzed statistically to identify and quantify the effects of the design variables and selected additives on the performance,moisture damage resistance,and durability of asphalt mixes.Based on the cracking test results,a superior cracking resistance performance was observed with ZycoTherm,irrespective of the mix type.Adhere had the lowest average cracking indices for both mix types,which suggest that it would not perform as well as the other additives in terms of cracking resistance.Overall,SMA mixes displayed greater cracking resistance than the dense-graded mixtures,which may have been the result of the reclaimed asphalt pavement(RAP)material used in the dense-graded mix and its lower asphalt binder content.In terms of moisture resistance,both nanomaterials(graphene nanoplatelet and nanoclay)did not perform well as they did not meet the minimum required tensile strength ratio(TSR)criterion(>0.80).In addition,nanomaterials showed the lowest TSR values in both mix types suggesting that their effectiveness against moisture-induced damage may not be as good as warm-mix additives.On the other hand,warm-mix additives were expected to show enhanced performance in terms of moisture resistance as compared to the other additives evaluated in this study.展开更多
基金funded by the National Natural Science Foundation of China (No. 42172308, No.51779018)the Youth Innovation Promotion Association CAS (No. 2022331)the Science and Technology Research and Development Program of China State Railway Group Co., Ltd. (No. J2022G002)。
文摘Red-bed mudstone, prevalent in southwest China, poses a formidable challenge due to its hydrophilic clay minerals, resulting in expansion, deformation, and cracking upon exposure to moisture. This study addresses uplift deformation disasters in high-speed railways by employing a moisture diffusion-deformation-fracture coupling model based on the finite-discrete element method(FDEM). The model integrates the influence of cracks on moisture diffusion. The investigation into various excavation depths reveals a direct correlation between depth and the formation of tensile cracks at the bottom of the railway cutting. These cracks expedite moisture migration, significantly impacting the temporal and spatial evolution of the moisture field. Additionally, crack expansion dominates hygroscopic deformation, with the lateral coordinate of the crack zone determining peak vertical displacement. Furthermore, key factors influencing deformation in railway cuttings, including the swelling factor and initial moisture content at the bottom of the cutting, are explored. The number of tensile and shear cracks increases with greater excavation depth, particularly concerning shear cracks. Higher swelling factors and initial moisture contents result in an increased total number of cracks, predominantly shear cracks. Numerical calculations provide valuable insights, offering a scientific foundation and directional guidance for the precise prevention, control, prediction, and comprehensive treatment of mudstone-related issues in high-speed railways.
基金This study was supported by the National Natural Science Foundation of China(42261008,41971034)the Natural Science Foundation of Gansu Province,China(22JR5RA074).
文摘Stable water isotopes are natural tracers quantifying the contribution of moisture recycling to local precipitation,i.e.,the moisture recycling ratio,but various isotope-based models usually lead to different results,which affects the accuracy of local moisture recycling.In this study,a total of 18 stations from four typical areas in China were selected to compare the performance of isotope-based linear and Bayesian mixing models and to determine local moisture recycling ratio.Among the three vapor sources including advection,transpiration,and surface evaporation,the advection vapor usually played a dominant role,and the contribution of surface evaporation was less than that of transpiration.When the abnormal values were ignored,the arithmetic averages of differences between isotope-based linear and the Bayesian mixing models were 0.9%for transpiration,0.2%for surface evaporation,and–1.1%for advection,respectively,and the medians were 0.5%,0.2%,and–0.8%,respectively.The importance of transpiration was slightly less for most cases when the Bayesian mixing model was applied,and the contribution of advection was relatively larger.The Bayesian mixing model was found to perform better in determining an efficient solution since linear model sometimes resulted in negative contribution ratios.Sensitivity test with two isotope scenarios indicated that the Bayesian model had a relatively low sensitivity to the changes in isotope input,and it was important to accurately estimate the isotopes in precipitation vapor.Generally,the Bayesian mixing model should be recommended instead of a linear model.The findings are useful for understanding the performance of isotope-based linear and Bayesian mixing models under various climate backgrounds.
文摘Landslides are highly dangerous phenomena that occur in different parts of the world and pose significant threats to human populations. Intense rainfall events are the main triggering process for landslides in urbanized slope regions, especially those considered high-risk areas. Various other factors contribute to the process;thus, it is essential to analyze the causes of such incidents in all possible ways. Soil moisture plays a critical role in the Earth’s surface-atmosphere interaction systems;hence, measurements and their estimations are crucial for understanding all processes involved in the water balance, especially those related to landslides. Soil moisture can be estimated from in-situ measurements using different sensors and techniques, satellite remote sensing, hydrological modeling, and indicators to index moisture conditions. Antecedent soil moisture can significantly impact runoff for the same rainfall event in a watershed. The Antecedent Precipitation Index (API) or “retained rainfall,” along with the antecedent moisture condition from the Natural Resources Conservation Service, is generally applied to estimate runoff in watersheds where data is limited or unavailable. This work aims to explore API in estimating soil moisture and establish thresholds based on landslide occurrences. The estimated soil moisture will be compared and calibrated using measurements obtained through multisensor capacitance probes installed in a high-risk area located in the mountainous region of Campos do Jordão municipality, São Paulo, Brazil. The API used in the calculation has been modified, where the recession coefficient depends on air temperature variability as well as the climatological mean temperature, which can be considered as losses in the water balance due to evapotranspiration. Once the API is calibrated, it will be used to extrapolate to the entire watershed and consequently estimate soil moisture. By utilizing recorded mass movements and comparing them with API and soil moisture, it will be possible to determine thresholds, thus enabling anticipation of landslide occurrences.
基金supported by President’s Scholarships from the University of South Australia towards his PhD study。
文摘Climate change is one of the major global challenges and it can have a significant influence on the behaviour and resilience of geotechnical structures.The changes in moisture content in soil lead to effective stress changes and can be accompanied by significant volume changes in reactive/expansive soils.The volume change leads to ground movement and can exert additional stresses on structures founded on or within a shallow depth of such soils.Climate change is likely to amplify the ground movement potential and the associated problems are likely to worsen.The effect of atmospheric boundary interaction on soil behaviour has often been correlated to Thornthwaite moisture index(TMI).In this study,the long-term weather data and anticipated future projections for various emission scenarios were used to generate a series of TMI maps for Australia.The changes in TMI were then correlated to the depth of suction change(H s),an important input in ground movement calculation.Under all climate scenarios considered,reductions in TMI and increases in H s values were observed.A hypothetical design scenario of a footing on expansive soil under current and future climate is discussed.It is observed that a design that might be considered adequate under the current climate scenario,may fail under future scenarios and accommodations should be made in the design for such events.
基金supported by the National Key Research and Development Program of China(2022YFD1901500/2022YFD1901505)the Key Laboratory of Molecular Breeding for Grain and Oil Crops in Guizhou Province,China(Qiankehezhongyindi(2023)008)the Key Laboratory of Functional Agriculture of Guizhou Provincial Higher Education Institutions,China(Qianjiaoji(2023)007)。
文摘Monitoring agricultural drought using remote sensing data is crucial for precision irrigation in modern agriculture.Utilizing unmanned aerial vehicle(UAV)remote sensing,we explored the applicability of an empirical crop water stress index(CWSI)based on canopy temperature and three-dimensional drought indices(TDDI)constructed from surface temperature(T_(s)),air temperature(T_(a))and five vegetation indices(VIs)for monitoring the moisture status of dryland crops.Three machine learning algorithms(random forest regression(RFR),support vector regression,and partial least squares regression)were used to compare the performance of the drought indices for vegetation moisture content(VMC)estimation in sorghum and maize.The main results of the study were as follows:(1)Comparative analysis of the drought indices revealed that T_(s)-T_(a)-normalized difference vegetation index(TDDIn)and T_(s)-T_(a)-enhanced vegetation index(TDDIe)were more strongly correlated with VMC compared with the other indices.The indices exhibited varying sensitivities to VMC under different irrigation regimes;the strongest correlation observed was for the TDDIe index with maize under the fully irrigated treatment(r=-0.93).(2)Regarding spatial and temporal characteristics,the TDDIn,TDDIe and CWSI indices showed minimal differences Over the experimental period,with coefficients of variation were 0.25,0.18 and 0.24,respectively.All three indices were capable of effectively characterizing the moisture distribution in dryland maize and sorghum crops,but the TDDI indices more accurately monitored the spatial distribution of crop moisture after a rainfall or irrigation event.(3)For prediction of the moisture content of single crops,RFR models based on TDDIn and TDDIe estimated VMC most accurately(R^(2)>0.7),and the TDDIn-based model predicted VMC with the highest accuracy when considering multiple-crop samples,with R^(2)and RMSE of 0.62 and 14.26%,respectively.Thus,TDDI proved more effective than the CWSI in estimating crop water content.
基金Under the auspices of National Natural Science Foundation of China (No.42101044,42077188,52109007)。
文摘Recycled moisture is an important indicator of the renewal capacity of regional water resources.Due to the existence of Yulong Snow Mountain,Lijiang in Yunnan Province,southeast of the Qinghai-Tibet Plateau,China,is the closest ocean glacier area to the equator in Eurasia.Daily precipitation samples were collected from 2017 to 2018 in Lijiang to quantify the effect of sub-cloud evaporation and recycled moisture on precipitation combined with the d-excess model during monsoon and non-monsoon periods.The results indicated that the d-excess values of precipitation fluctuated between–35.6‰and 16.0‰,with an arithmetic mean of 3.5‰.The local meteoric water line(LMWL)wasδD=7.91δ^(18)O+2.50,with a slope slightly lower than the global meteoric water line(GMWL).Subcloud evaporation was higher during the non-monsoon season than during the monsoon season.It tended to peak in March and was primarily influenced by the relative humidity.The source of the water vapour affected the proportion of recycled moisture.According to the results of the Hybrid Single-Particle Lagrangian Integrated Trajectory(HYSPLIT)model,the main sources of water vapour in Lijiang area during the monsoon period were the southwest and southeast monsoons.During the non-monsoon period,water vapour was transported by a southwesterly flow.The recycled moisture in Lijiang area between March and October 2017 was 10.62%.Large variations were observed between the monsoon and non-monsoon seasons,with values of 5.48%and 25.65%,respectively.These differences were primarily attributed to variations in the advection of water vapour.The recycled moisture has played a supplementary role in the precipitation of Lijiang area.
基金supported by the State Key Laboratory of Integrative Sustainable Dryland Agriculture (in preparation)Shanxi Agricultural University, China (202105D121008)+1 种基金the National Natural Science Foundation of China (42007121)the National Key R&D Program of China (2021YFD1900700)。
文摘The yield of winter wheat is hindered by drought and low temperature in the Loess Plateau of China.Two common mulching methods to conserve soil moisture,ridge furrows with plastic film mulching (RP) and flat soil surfaces with plastic film mulching (FP) are helpful for wheat production.Our previous study indicated that FP could improve wheat yield more effectively than RP,but the reason remains unclear.The effect of mulching method on functional bacteria also needs to be further studied.In this study,winter wheat was employed to evaluate the impacts of mulching method on soil temperature,moisture content,microorganisms and grain yield.The results showed that FP had a warming effect when the soil temperature was low and a cooling effect when the temperature was too high.However,the ability to regulate soil temperature in the RP method was unstable and varied with year.The lowest negative accumulated soil temperature was found in the FP treatment,which was 20–89 and 43–99%lower than that of the RP and flat sowing with non-film mulching control (NP) treatments,respectively.Deep soil moisture was better transferred to topsoil for wheat growth in the FP and RP treatments than the NP treatment,which made the topsoil moisture in the two treatments (especially FP) more sufficient than that in the NP treatment during the early growing stage of wheat.However,due to the limited water resources in the study area,there was almost no difference between treatments in topsoil water storage during the later stage.The wheat yield in the FP treatment was significantly higher,by 12–16and 23–56%,respectively,than in the RP and NP treatments.Significant positive correlations were observed among the negative accumulated soil temperature,spike number and wheat yield.The Chao1 and Shannon indices in the RP treatment were 17 and 3.9%higher than those in the NP treatment,respectively.However,according to network relationship analysis,the interspecific relationships of bacteria were weakened in the RP treatment.Phosphorus solubilizing,ammonification and nitrification bacteria were more active in the RP than in the FP treatment,and microbes with nitrate reduction ability and plant pathogens were inhibited in the RP treatment,which improved nutrient availability and habitat for wheat.
基金supported by Natural Science Foundation of Shaanxi Province(S2021-JC-WT-006)the National Key Research and Development Program of China(2018YFD0100200)+1 种基金the China Postdoctoral Science Foundation(2018M633588)the China Agriculture Research System(CARS-02-77)。
文摘Maize kernel moisture content(KMC)at harvest greatly affects mechanical harvesting,transport and storage.KMC is correlated with kernel dehydration rate(KDR)before and after physiological maturity.KMC and KDR are complex traits governed by multiple quantitative trait loci(QTL).Their genetic architecture is incompletely understood.We used a multiomics integration approach with an association panel to identify genes influencing KMC and KDR.A genome-wide association study using time-series KMC data from 7 to 70 days after pollination and their transformed KDR data revealed respectively 98and 279 loci significantly associated with KMC and KDR.Time-series transcriptome and proteome datasets were generated to construct KMC correlation networks,from which respectively 3111 and 759 module genes and proteins were identified as highly associated with KMC.Integrating multiomics analysis,several promising candidate genes for KMC and KDR,including Zm00001d047799 and Zm00001d035920,were identified.Further mutant experiments showed that Zm00001d047799,a gene encoding heat shock 70 kDa protein 5,reduced KMC in the late stage of kernel development.Our study provides resources for the identification of candidate genes influencing maize KMC and KDR,shedding light on the genetic architecture of dynamic changes in maize KMC.
基金support from the Contract Research(“Development of Breathable Fabrics with Nano-Electrospun Membrane,”CityU ref.:9231419)the National Natural Science Foundation of China(“Study of Multi-Responsive Shape Memory Polyurethane Nanocomposites Inspired by Natural Fibers,”Grant No.51673162)+1 种基金Startup Grant of CityU(“Laboratory of Wearable Materials for Healthcare,”Grant No.9380116)National Natural Science Foundation of China,Grant No.52073241.
文摘Electronic skins can monitor minute physiological signal variations in the human skins and represent the body’s state,showing an emerging trend for alternative medical diagnostics and human-machine interfaces.In this study,we designed a bioinspired directional moisture-wicking electronic skin(DMWES)based on the construction of heterogeneous fibrous membranes and the conductive MXene/CNTs electrospraying layer.Unidirectional moisture transfer was successfully realized by surface energy gradient and push-pull effect via the design of distinct hydrophobic-hydrophilic difference,which can spontaneously absorb sweat from the skin.The DMWES membrane showed excellent comprehensive pressure sensing performance,high sensitivity(maximum sensitivity of 548.09 kPa^(−1)),wide linear range,rapid response and recovery time.In addition,the single-electrode triboelectric nanogenerator based on the DMWES can deliver a high areal power density of 21.6μW m^(−2) and good cycling stability in high pressure energy harvesting.Moreover,the superior pressure sensing and triboelectric performance enabled the DMWES for all-range healthcare sensing,including accurate pulse monitoring,voice recognition,and gait recognition.This work will help to boost the development of the next-generation breathable electronic skins in the applications of AI,human-machine interaction,and soft robots.
基金financially supported by the National Natural Science Foundation of China (Grant No.51975165)。
文摘Green sand is a mixture of silica sand,bentonite,water and coal powder,and other additives.Moisture content is an important index to characterize the properties of green sand.Based on the dielectric characteristics of green sand and transmission line theory,a method for rapidly measuring the moisture content of green sand by means of a low frequency multiprobe detector was proposed.A system was constructed,where six detectors with different arrangements and probes were designed.The experimental results showed that the voltage difference of transmission line increases with the increasing frequency before 29 MHz while decreases after 35 MHz.A voltage difference platform occurs in the range of 29-35 MHz,which is suitable for measuring the moisture content due to its insensitivity to frequency.The electric field intensity gradually decreases with the increase of the probe depth,and the intensity of central probe is always greater than that of the edge probe.When the distance of the probe away from the sand sample surface is 80 mm,the electric field intensity of the edge probe is found to be very weak.The optimal excitation frequency for measuring the moisture content of green sand is 29-33 MHz.The optimal detector is the one with one center probe and three edge probes,and their lengths are 80 mm and 60 mm,respectively.The distance between the center and edge probes is 25 mm,and the diameter of probes is 5 mm.Taking the voltage difference of transmission line,bentonite content,coal powder content and compactability as parameters of the input layer,and the moisture content as a parameter of the output layer,a three-layer BP artificial neural network model for predicting the moisture content of green sand was constructed according to the experimental results at 33 MHz.The prediction error of the model is not higher than 3.3% when the moisture content of green sand is within the range of 3wt.%-7wt.%.
基金the Grain,Oil and Food Engineering Technology Research Center of the State Grain and Reserves Administration/Key Laboratory of Henan Province,Henan University of Technology(G0202205)the Key Scientific Research Projects of Colleges and Universities of Henan(23A550012)the Science Foundation of Henan University of Technology(2020BS013)。
文摘To better understand the mass transfer process of moisture in the soy protein isolate-corn starch(SPI-CS)films during preparation and storage process,the drying kinetics model of SPI-CS films with different formation conditions during the drying process and the moisture adsorption characteristics of the SPI-CS films under different humidity conditions were investigated.Within the range of experimental conditions,the moisture migration rule in the SPI-CS films during the drying preparation was combined with the Page model which was expressed as MR=exp(-kt^(n)).It was found that the adsorption equilibrium needed shorter time(about 3 h)when the SPI-CS films existed in the environment with lower humidity(RH<54%).Additionally,the secondorder adsorption kinetic equation was successful to describe the moisture adsorption characteristic of the SPICS films during storage under different humidity conditions.
基金supported by the National Natural Science Foundation of China (Grant No. 41831175)the Fundamental Research Funds for the Central Universities (Grant No. B210201029)+2 种基金the Key Scientific and Technological Project of the Ministry of Water Resources, P. R. China (SKS2022001)the Joint Open Project of the KLME and CIC-FEMD (Grant No. KLME202202)the Open Research Fund of the State Key Laboratory of Tropical Oceanography (South China Sea Institute of Oceanology, Chinese Academy of Sciences) (Grant No. LTO2110)
文摘Seasonal prediction of summer precipitation over eastern China is closely linked to the East Asian monsoon circulation,which is largely affected by the El Niño-Southern Oscillation(ENSO).In this study,results show that spring soil moisture(SM)over the Indo-China peninsula(ICP)could be a reliable seasonal predictor for eastern China summer precipitation under non-ENSO conditions.When springtime SM anomalies are present over the ICP,they trigger a structured response in summertime precipitation over most of eastern China.The resultant south-to-north,tri-polar configuration of precipitation anomalies has a tendency to yield increased(decreased)precipitation in the Yangtze River basin and decreased(increased)in South and North China with a drier(wetter)spring soil condition in the ICP.The analyses show that ENSO exerts a powerful control on the East Asian circulation system in the ENSO-decaying summer.In the case of ENSO forcing,the seasonal predictability of the ICP spring SM for eastern China summer precipitation is suppressed.However,in the absence of the influence of ENSO sea surface temperature anomalies from the preceding winter,the SM anomalies over the ICP induce abnormal local heating and a consequent geopotential height response owing to its sustained control on local temperature,which could,in turn,lead to abnormal eastern China summer precipitation by affecting the East Asian summer monsoon circulation.The present findings provide a better understanding of the complexity of summer climate predictability over eastern China,which is of potential significance for improving the livelihood of the people.
基金The Second Tibetan Plateau Scientific Expedition and Research(STEP)Program(2019QZKK0105)the Science and Technology Development Fund of the Chinese Academy of Meteorological Sciences(2022KJ022)+2 种基金Special Fund for the Basic Scientific Research Expenses of the Chinese Academy of Meteorological Sciences(2021Z013)the Science and Technology Development Fund of the Chinese Academy of Meteorological Sciences(2022KJ021)Major Projects of the Natural Science Foundation of China(91337000)。
文摘With the extreme drought(flood)event in southern China from July to August in 2022(1999)as the research object,based on the comprehensive diagnosis and composite analysis on the anomalous drought and flood years from July to August in 1961-2022,it is found that there are significant differences in the characteristics of the vertically integrated moisture flux(VIMF)anomaly circulation pattern and the VIMF convergence(VIMFC)anomaly in southern China in drought and flood years,and the VIMFC,a physical quantity,can be regarded as an indicative physical factor for the"strong signal"of drought and flood in southern China.Specifically,in drought years,the VIMF anomaly in southern China is an anticyclonic circulation pattern and the divergence characteristics of the VIMFC are prominent,while those are opposite in flood years.Based on the SST anomaly in the typical draught year of 2022 in southern China and the SST deviation distribution characteristics of abnormal draught and flood years from 1961 to 2022,five SST high impact areas(i.e.,the North Pacific Ocean,Northwest Pacific Ocean,Southwest Pacific Ocean,Indian Ocean,and East Pacific Ocean)are selected via the correlation analysis of VIMFC and the global SST in the preceding months(May and June)and in the study period(July and August)in 1961-2022,and their contributions to drought and flood in southern China are quantified.Our study reveals not only the persistent anomalous variation of SST in the Pacific and the Indian Ocean but also its impact on the pattern of moisture transport.Furthermore,it can be discovered from the positive and negative phase fitting of SST that the SST composite flow field in high impact areas can exhibit two types of anomalous moisture transport structures that are opposite to each other,namely an anticyclonic(cyclonic)circulation pattern anomaly in southern China and the coastal areas of east China.These two types of opposite anomalous moisture transport structures can not only drive the formation of drought(flood)in southern China but also exert its influence on the persistent development of the extreme weather.
基金National Natural Science Foundation of China(41875111)Special program for innovation and development of China Meteorological Administration(CXFZ2022J031,CXFZ2021J018)National Natural Science Foundation of China(40975058)。
文摘Complex topography,special geographical location and sea-land-air interactions lead to high interannual variability of summer precipitation in the east of Southwest China(ESWC).However,the contributions,influencing factors and mechanisms of remote and local evaporation remain to be further investigated.Using clustering analysis and Hybrid Single-Particle Lagrangian Integrated Trajectory version 5 model,we analyze the contributions of remote moisture transport and local evaporation to summer precipitation in the ESWC and their causes.There are mainly five remote moisture channels in the ESWC,namely the Arabian Sea channel,Bay of Bengal channel,western Pacific channel,Northwest channel 1 and Northwest channel 2.Among the five channels,the western Pacific channel has the largest number of trajectories,while the Bay of Bengal channel has the largest contribution rate of specific humidity(33.33%)and moisture flux(33.14%).The amount of regional average precipitation is close to that of the precipitation caused by remote moisture transport,and both are considerably greater than the rainfall amount caused by local evaporation.However,on interannual time scales,precipitation recirculation rates are negatively correlated to regional average precipitation and precipitation caused by remote moisture transport but are consistent with that caused by local evaporation.An apparent"+-+"wave train can be found on the height anomaly field in East Asia,and the sea surface temperature anomalies are positive in the equatorial Middle-East Pacific,the South China Sea,the Bay of Bengal and the Arabian Sea.These phenomena cause southwest-northeast moisture transport with strong updrafts,thereby resulting in more precipitation in the ESWC.
基金Under the auspices of National Key Research and Development Project of China(No.2021YFD1500103)Strategic Priority Research Program of the Chinese Academy of Sciences(No.XDA28100500)+2 种基金National Natural Science Foundation of China(No.4197132)Science and Technology Development Plan Project of Jilin Province(No.20210201044GX)Land Observation Satellite Supporting Platform of National Civil Space Infrastructure Project(No.CASPLOS-CCSI)。
文摘Soil moisture plays an important role in crop yield estimation,irrigation management,etc.Remote sensing technology has potential for large-scale and high spatial soil moisture mapping.However,offline remote sensing data processing is time-consuming and resource-intensive,and significantly hampers the efficiency and timeliness of soil moisture mapping.Due to the high-speed computing capabilities of remote sensing cloud platforms,a High Spatial Resolution Soil Moisture Estimation Framework(HSRSMEF)based on the Google Earth Engine(GEE)platform was developed in this study.The functions of the HSRSMEF include research area and input datasets customization,radar speckle noise filtering,optical-radar image spatio-temporal matching,soil moisture retrieving,soil moisture visualization and exporting.This paper tested the performance of HSRSMEF by combining Sentinel-1,Sentinel-2 images and insitu soil moisture data in the central farmland area of Jilin Province,China.Reconstructed Normalized Difference Vegetation Index(NDVI)based on the Savitzky-Golay algorithm conforms to the crop growth cycle,and its correlation with the original NDVI is about 0.99(P<0.001).The soil moisture accuracy of the random forest model(R 2=0.942,RMSE=0.013 m3/m3)is better than that of the water cloud model(R 2=0.334,RMSE=0.091 m3/m3).HSRSMEF transfers time-consuming offline operations to cloud computing platforms,achieving rapid and simplified high spatial resolution soil moisture mapping.
基金funded by the National Natural Science Foundation of China (42101295)the Science and Technology Department of Jiangsu (BK20210657)the Natural Science Foundation of Jiangsu Higher Education Institutions of China (21KJB170003)。
文摘Climate change impacts on grasslands that cover a quarter of the global land area, have become unprecedented during the 21~(st) century. One of the important ecological realms, arid grasslands of northern China, which occupy more than 70% of the region's land area. However, the impact of climate change on vegetation growth in these arid grasslands is not consistent and lacks corresponding quantitative research. In this study, NDVI(normalized difference vegetation index) and climate factors including temperature, precipitation, solar radiation, soil moisture, and meteorological drought were analyzed to explore the determinants of changes in grassland greenness in Inner Mongolia Autonomous Region(northern China) during 1982–2016. The results showed that grasslands in Inner Mongolia witnessed an obvious trend of seasonal greening during the study period. Two prominent climatic factors,precipitation and soil moisture accounted for approximately 33% and 27% of grassland NDVI trends in the region based on multiple linear regression and boosted regression tree methods. This finding highlights the impact of water constraints to vegetation growth in Inner Mongolia's grasslands. The dominant role of precipitation in regulating grassland NDVI trends in Inner Mongolia significantly weakened from 1982 to 1996, and the role of soil moisture strengthened after 1996. Our findings emphasize the enhanced importance of soil moisture in driving vegetation growth in arid grasslands of Inner Mongolia, which should be thoroughly investigated in the future.
基金supported by the National Key Research and Development Program of China(Grant No.2019YFC1509901)。
文摘When expansive soils in the original location are artificially transferred to landfill in different seasons,and subject to engineering activities afterwards,the corresponding deformation and stability of retaining structures become unpredictable.This necessitates the determination of lateral pressure coefficient at rest(k_(0) value)for expansive soils in landfill.Considering compaction,excavation of expansive soils,as well as construction of landfill in different seasons,series of stepwise loading and unloading consolidation tests at various moisture contents were carried out in this work to explore the evolution characteristics of k_(0) value and assess the dependence of k_(0) value on vertical stress and moisture content.Besides,scanning electron microscope(SEM)was used to track the change in microstructural features with vertical stresses.The results indicated that the k_(0) value of expansive soil shows a pronounced nonlinearity and is inextricably linked with vertical stress and moisture content,based on which a prediction formula to estimate the variation in k_(0) value with vertical stress during loading stage was proposed;there is a significant exponential increase in k_(0) value with overconsolidation ratio(OCR)during unloading stage,and OCR dominates the release of horizontal stress of expansive soil;SEM results revealed that with an increase in vertical stress,the anisotropy of expansive soil microstructure increases dramatically,causing a significant directional readjustment,which is macroscopically manifested as an initially rapid increase in k_(0) value;but when vertical stress increases to a critical value,the anisotropy of microstructure increases marginally,indicating a stable orientation occurring in the soil microstructure,which causes the k_(0) value to maintain a relatively stable value.
基金financial support from Region Hauts-de-France,FEDER,and Electricité de France(EDF)through PEROVSTAB programfinancial support from the IR-RMN-THC FR-3050 CNRS France for conducting solid-state NMR measurements.P.R.and G.N.M.R+1 种基金financial support from University of Lille and région Hauts-de-France.F.S“IMPRESSIVE”project which received funding from the European Union’s Horizon 2020 Research and Innovation Program under grant agreement number 826013.
文摘Environmental stability is a major bottleneck of perovskite solar cells.Only a handful of studies are investigating the effect of moisture on the structural degradation of the absorber.They mostly rely on ex situ experiments and on completely degraded samples,which restrict the assessment on initial and final stage.By combining in situ X-ray diffraction under controlled 85%relative humidity,and live observations of the water-induced degradation using liquid-cell transmission electron microscopy,we reveal two competitive degradation paths leading on one hand to the decomposition of state-of-theart mixed cation/anion(Cs_(0.05)(MA_(0.17)FA_(0.83))_(0.95)Pb(Br_(0.17)I_(0.83))_(3)(CsMAFA)into PbI_(2) through a dissolution/recrystallization mechanism and,on the other hand,to a non-equilibrium phase segregation leading to CsPb_(2)Br_(5) and a Cesium-poor/iodide-rich Cs_(0.05)-x(MA_(0.17)FA_(0.83))_(0.95)Pb(Br_(0.17-2y)I_(0.83)+2y)_(3) perovskite.This degradation mechanism is corroborated at atomic-scale resolution through solid-state ^(1)H and ^(133)Cs NMR analysis.Exposure to moisture leads to a film containing important heterogeneities in terms of morphology,photoluminescence intensities,and lifetimes.Our results provide new insights and consensus that complex perovskite compositions,though very performant as champion devices,are comparatively metastable,a trait that limits the chances to achieve long-term stability.
文摘For many environmental and agricultural applications, an accurate estimation of surface soil moisture is essential. This study sought to determine whether combining Sentinel-1A, Sentinel-2A, and meteorological data with artificial neural networks (ANN) could improve soil moisture estimation in various land cover types. To train and evaluate the model’s performance, we used field data (provided by La Tuscia University) on the study area collected during time periods between October 2022, and December 2022. Surface soil moisture was measured at 29 locations. The performance of the model was trained, validated, and tested using input features in a 60:10:30 ratio, using the feed-forward ANN model. It was found that the ANN model exhibited high precision in predicting soil moisture. The model achieved a coefficient of determination (R<sup>2</sup>) of 0.71 and correlation coefficient (R) of 0.84. Furthermore, the incorporation of Random Forest (RF) algorithms for soil moisture prediction resulted in an improved R<sup>2</sup> of 0.89. The unique combination of active microwave, meteorological data and multispectral data provides an opportunity to exploit the complementary nature of the datasets. Through preprocessing, fusion, and ANN modeling, this research contributes to advancing soil moisture estimation techniques and providing valuable insights for water resource management and agricultural planning in the study area.
基金support of the Transportation Consortium of SouthCentral States(Tran-SET)is greatly appreciated(Tran-SET project 21BLSU03).
文摘The objective of this study was to evaluate and recommend an asphalt mixture design with emerging additive technologies that would provide superior performance against asphalt concrete(AC)stripping and cracking.To achieve this objective,a laboratory test program was developed to evaluate the use of nanomaterials(nanoclay and graphene nanoplatelet),an emerging anti-stripping agent(adhere),and warm-mix asphalt technologies(ZycoTherm,Sasobit,and EvoTherm).Two mix types were evaluated,which were a stone-matrix asphalt(SMA)and a dense-graded binder mix.In addition,the modified Lottman test(AASHTO T 283)and the indirect tensile asphalt cracking test(IDEAL-CT)test were used as performance indicators of moisture damage resistance and cracking susceptibility.Results were analyzed statistically to identify and quantify the effects of the design variables and selected additives on the performance,moisture damage resistance,and durability of asphalt mixes.Based on the cracking test results,a superior cracking resistance performance was observed with ZycoTherm,irrespective of the mix type.Adhere had the lowest average cracking indices for both mix types,which suggest that it would not perform as well as the other additives in terms of cracking resistance.Overall,SMA mixes displayed greater cracking resistance than the dense-graded mixtures,which may have been the result of the reclaimed asphalt pavement(RAP)material used in the dense-graded mix and its lower asphalt binder content.In terms of moisture resistance,both nanomaterials(graphene nanoplatelet and nanoclay)did not perform well as they did not meet the minimum required tensile strength ratio(TSR)criterion(>0.80).In addition,nanomaterials showed the lowest TSR values in both mix types suggesting that their effectiveness against moisture-induced damage may not be as good as warm-mix additives.On the other hand,warm-mix additives were expected to show enhanced performance in terms of moisture resistance as compared to the other additives evaluated in this study.