In this paper,the Taixin Integrated Economic Zone in Shanxi Province is taken as the research object,and the coupling coordination degree model and bivariate spatial autocorrelation model are used to judge the couplin...In this paper,the Taixin Integrated Economic Zone in Shanxi Province is taken as the research object,and the coupling coordination degree model and bivariate spatial autocorrelation model are used to judge the coupling coordination and spatial-temporal correlation between urbanization and ecosystem service,and the hotspot analysis is used to judge the spatial-temporal trend of urbanization and ecosystem service.The results show that:(1)The urbanization level from 2000 to 2020 continued to rise,the areas with relatively high urbanization were concentrated in the central part of the study area,and the relatively high terrain areas on both sides of the study area,the urbanization was relatively slow,and the hotspot areas with highly significant and significant urbanization level from 2000 to 2020 were distributed as bands in the central part of the study area and the area was rising,and there was no Cold spot area distribution;between 2000 and 2020,the ecosystem service value in the study area increased by 2.6800×10^(8) yuan.Over these two decades,it exhibited a development trend that first rose and then declined.The woodland and grassland agglomeration areas were located on the two sides of the study area,forming highly significant and significant hotspots.Conversely,the central and northeastern parts of the study area were characterized by concentrated man-made land surfaces and croplands,resulting in the formation of highly significant and significant cold spots.(2)In the central part of the study area where man-made land surface and cultivated land are concentrated,the coupling coordination between urbanization and ecosystem service is in the intermediate dislocation and mild dislocation interval;the woodland and grassland concentration areas on both sides of the study area are ecologically fragile,and the coupling coordination between the two is in the level of less than intermediate dislocation.(3)From 2000 to 2020,urbanization and the value of ecosystem services were both negatively correlated,although the correlation coefficient was low.In the central and northeastern parts,urbanization and ecosystem service exhibited patterns of high-low,high-high,and low-low clustering.Conversely,on both sides of the study area,most of the clusters showed a low-high pattern.展开更多
Historically,landslides have been the primary type of geological disaster worldwide.Generally,the stability of reservoir banks is primarily affected by rainfall and reservoir water level fluctuations.Moreover,the stab...Historically,landslides have been the primary type of geological disaster worldwide.Generally,the stability of reservoir banks is primarily affected by rainfall and reservoir water level fluctuations.Moreover,the stability of reservoir banks changes with the long-term dynamics of external disastercausing factors.Thus,assessing the time-varying reliability of reservoir landslides remains a challenge.In this paper,a machine learning(ML)based approach is proposed to analyze the long-term reliability of reservoir bank landslides in spatially variable soils through time series prediction.This study systematically investigated the prediction performances of three ML algorithms,i.e.multilayer perceptron(MLP),convolutional neural network(CNN),and long short-term memory(LSTM).Additionally,the effects of the data quantity and data ratio on the predictive power of deep learning models are considered.The results show that all three ML models can accurately depict the changes in the time-varying failure probability of reservoir landslides.The CNN model outperforms both the MLP and LSTM models in predicting the failure probability.Furthermore,selecting the right data ratio can improve the prediction accuracy of the failure probability obtained by ML models.展开更多
The timely and rapid mapping of rapeseed planting areas is desirable for national food security. Most current rapeseed mapping methods depend strongly on images with good observations obtained during the flowering sta...The timely and rapid mapping of rapeseed planting areas is desirable for national food security. Most current rapeseed mapping methods depend strongly on images with good observations obtained during the flowering stages. Although vegetation indices have been proposed to identify the rapeseed flowering stage in some areas, automatically mapping rapeseed planting areas in large regions is still challenging.We developed an automatic phenology-and pixel-based algorithm(APPA) by integrating Landsat 8 and Sentinel-1 satellite data. We found that the Normalized Rapeseed Flowering Index shows unique spectral characteristics during the flowering and post-flowering periods, which distinguish rapeseed parcels from other land-use types(urban, water, forest, grass, maize, wheat, barley, and soybean). To verify the robustness of APPA, we applied APPA to seven areas in five rapeseed-producing countries with flowering images unavailable. The rapeseed maps by APPA showed consistently high accuracies with producer accuracies of 0.87–0.93 and F-scores of 0.92–0.95 based on 4503 verification samples. They showed high spatial consistency at the pixel level with the land cover Scientific Expertise Centres(SEC) map in France,Crop Map of England in United Kingdom, national-scale crop-and land-cover map of Germany, and Annual Crop Inventory in Canada at the pixel level. We propose APPA as a highly promising method for automatically and efficiently mapping rapeseed areas.展开更多
Glaciers have retreated and shrunk in High Mountain Asia since the mid-20th century because of global warming,leading to glacier instability and hazardous iceesnow avalanches.However,the complex relationship between i...Glaciers have retreated and shrunk in High Mountain Asia since the mid-20th century because of global warming,leading to glacier instability and hazardous iceesnow avalanches.However,the complex relationship between iceesnow avalanches and factors such as climate and potential triggers are difficult to understand because of the lack of observational data.Here,we addressed iceesnow avalanches on the Annapurna Ⅱ glacier in Nepal,Central Himalaya.We constructed an iceesnow avalanche history using long-term multi-source remote sensing images(1988-2021)and mapped the velocity fields of glaciers using cross-correlation analysis on SAR and optical images.Then,we investigated the impact of climate change and earthquakes on the frequency and size of iceesnow avalanches.The results demonstrate that the frequency of iceesnow avalanches has increased from 10 in 1988 to 27 in 2020,but the average area of iceesnow avalanche deposits has decreased by approximately 70%,from 3.4×10^(5) m^(2) in 1988 to 1.2×10^(5) m^(2) in 2020.The evolutionary characteristic of ice avalanches is linked to the impact of glacier retreat(reduction in ice material supply)and increased activity under climate change.The glacier movement velocity controls the size of iceesnow avalanches and can be set as an indicator for iceesnow avalanche warnings.On the Annapurna Ⅱ glacier,an iceesnow avalanche occurred when the glacier velocities were greater than 1.5 m d^(-1).These results offer insights into iceesnow avalanche risk assessment and prediction in high-mountain areas,particularly in regions characterised by dense glacier distribution.展开更多
In this study,a multi-source data fusion method was proposed for the development of a Hybrid seismic hazard model(HSHM)in China by using publicly available data of the 5th Seismic Ground Motion Parameter Zoning Map(NS...In this study,a multi-source data fusion method was proposed for the development of a Hybrid seismic hazard model(HSHM)in China by using publicly available data of the 5th Seismic Ground Motion Parameter Zoning Map(NSGM)and historical seismic catalogues and integrating with modern ground motion prediction equations(GMPEs).This model incorporates the characteristics of smoothed seismicity and areal sources for regional seismic hazard assessment.The probabilistic seismic hazard for the North China Plain earthquake belt was investigated through sensitivity analysis related to the seismicity model and GMPEs.The analysis results indicate that the Hybrid model can produce a consistent result with the NSGM model in many cases.However,the NSGM model tends to overestimate hazard values in locations where no major events have occurred and underestimate hazard values in locations where major events have occurred.The Hybrid model can mitigate the degree of such biases.Compared to the modern GMPEs,the GMPE with epicentral distance measures significantly underestimate the seismic hazard under near-field and large-magnitude scenarios.In addition,a comparison of the uniform hazard spectra(UHS)obtained by the models,with China's design spectrum,shows that the current design spectrum is more conservative than the calculated UHS.展开更多
The Taihang Mountains in North China are an important carbon-water ecosystem service supply area.Understanding the coupling effect and influencing mechanisms of mountain carbon sequestration as well as water conservat...The Taihang Mountains in North China are an important carbon-water ecosystem service supply area.Understanding the coupling effect and influencing mechanisms of mountain carbon sequestration as well as water conservation is essential for regional eco-logical restoration and sustainable development.In this study,we utilized models such as the coupled coordination degree model,the random forest and Geodetector to analyze the spa-tio-temporal changes as well as driving factors of carbon sequestration-water conservation coupling coordination in the Taihang Mountains.The results show that:(1)From 1990 to 2020,the carbon sequestration and water conservation capacity of the Taihang Mountains exhibited a spatial pattern with higher values in the southeast and central regions,while lower values in the northwest region.(2)The average coupling coordination degree from 1990 to 2020 was O.23,which was overall low,with a fluctuating decreasing-rising-decreasing trend over time.The coupling coordination degree exhibited a pattern that is high in the middle and low in the periphery,with a fluctuating distribution that initially decreases and then increases with the increasing altitude.The overall trend of coupling coordination is degradation,with concen-trated degradation in the northwest mountainous regions.(3)Precipitation and soil texture were identified as the main driving factors influencing coupling coordination,with the interac-tion between precipitation and soil sand content showing the strongest explanatory power,while that among topography,vegetation and human activities had relatively low explanatory power.Therefore,enhanced protection and the continuous monitoring of vegetation and soil environments in the Taihang Mountains are essential,with particular emphasis on ecological restoration in areas experiencing a persistent degradation of carbon-water coupling.This study can provide assistance in monitoring and managing carbon sink and water resources in the mountains,meanwhile mitigating potential adverse impacts on human well-being.展开更多
Acquiring spatiotemporal patterns of phenological information and its drivers is essential for understanding the response of crops to climate change and implementing adaptation measures.However,current approaches to o...Acquiring spatiotemporal patterns of phenological information and its drivers is essential for understanding the response of crops to climate change and implementing adaptation measures.However,current approaches to obtain phenology and analyse its drivers have deficiencies such as sparse observations,excessive dependence of remote sensing inversion on sensors,and inevitable difficulties in upscaling site-based crop models into larger regions.Based on the Wang-Engel temperature response function,we improved the Crop Estimation through Resource and Environment Synthesis-Wheat(CERES-Wheat)model.First,we calibrated the model at the regional scale and evaluated its performance.Furthermore,the spatiotemporal changes in winter wheat phenology in China from 2000 to 2015 were analysed.The results showed that the improved model significantly enhanced the simulation accuracy of the anthesis and maturity dates by averages of 13%and 12%in most planting areas,especially in the Yunnan-Guizhou Plateau(YG)with improvements of 26%and 28%.The simulated phenology of winter wheat grown in a colder environment(e.g.,the average temperatures during the vegetative growth period range from 0 to 5℃ and from 15 to 20°C,and the reproductive growth period ranges from 10 to 15°C)also notably improved.These results confirmed that the original temperature response function indeed had limitations.Further analyses revealed that the key phenological dates and growth periods over the past 16 years were dominantly advanced and shortened.Specifically,the anthesis date,vegetative growth period(VGP),and reproductive growth period(RGP)indicated obviously spatial characteristics.For example,the anthesis date and VGP in the North China Plain(NCP)and the Middle-Lower Yangtze Plain(YZ)and the RGP in northwestern China(NW)showed opposite trends of delay and prolongation as comparing with the dominant patterns.Sensitivity analysis indicated that the key phenological dates and growth periods were advanced and shortened as the minimum(T_(min))and maximum temperatures(T_(max))rose,while they were postponed and prolonged with the increased precipitation.However,their responses to solar radiation did not show spatial consistency.Additionally,we found that the sensitivity of phenology to climatic factors differed across subregions.In particular,phenology in southwestern China and YG was more sensitive to T_(min),T_(max),and solar radiation than in the NCP and NW.Moreover,the sensitivity to precipitation in NW was higher than that in YZ.Totally,the improved crop model could provide more refined spatial characteristics of phenology at a large scale and benefit to explore its drivers more objectively.Furthermore,our results highlight that different planting areas should adopt suitable adaptation measures to cope with climate change impacts.Ultimately,the improved model is promising to enhance the accuracy of yield prediction and provide powerful tools for assessing regional climate change impact and adaptability.展开更多
In the context of climate change,the impact of extreme precipitation and its chain effects has intensified in the southeastern coastal region of China,posing a serious threat to the socioeconomic development in the re...In the context of climate change,the impact of extreme precipitation and its chain effects has intensified in the southeastern coastal region of China,posing a serious threat to the socioeconomic development in the region.This study took tropical cyclones–extreme precipitation–flash floods as an example to carry out a risk assessment of flash floods under climate change in the Yantanxi River Basin,southeastern China.To obtain the flash flood inundation characteristics through hydrologic–hydrodynamic modeling,the study combined representative concentration pathway(RCP)and shared socioeconomic pathway(SSP)scenarios to examine the change of flash flood risk and used the geographical detector to explore the driving factors behind the change.The results show that flash flood risk in the Yantanxi River Basin will significantly increase,and that socioeconomic factors and precipitation are the main driving forces.Under the RCP4.5-SSP2 and RCP8.5-SSP5 scenarios,the risk of flash floods is expected to increase by 88.79%and 95.57%,respectively.The main drivers in the case study area are GDP density(q=0.85),process rainfall(q=0.74),asset density(q=0.68),and population density(q=0.67).The study highlights the influence of socioeconomic factors on the change of flash flood disaster risk in small river basins.Our findings also provide a reference for regional planning and construction of flood control facilities in flash flood-prone areas,which may help to reduce the risk of flash floods.展开更多
Introduction:The transmissibility of the severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)Omicron variant poses challenges for the existing measures containing the virus in China.In response,this study inves...Introduction:The transmissibility of the severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)Omicron variant poses challenges for the existing measures containing the virus in China.In response,this study investigates the effectiveness of population-level testing(PLT)and contact tracing(CT)to help curb coronavirus disease 2019(COVID-19)resurgences in China.Methods:Two transmission dynamic models(i.e.with and without age structure)were developed to evaluate the effectiveness of PLT and CT.Extensive simulations were conducted to optimize PLT and CT strategies for COVID-19 control and surveillance.Results:Urban Omicron resurgences can be controlled by multiple rounds of PLT,supplemented by CT—as long as testing is frequent.This study also evaluated the time needed to detect COVID-19 cases for surveillance under different routine testing rates.The results show that there is a 90%probability of detecting COVID-19 cases within 3 days through daily testing.Otherwise,it takes around 7 days to detect COVID-19 cases at a 90%probability level if biweekly testing is used.Routine testing applied to the age group 21–60 for COVID-19 surveillance would achieve similar performance to that applied to all populations.Discussion:Our analysis evaluates potential PLT and CT strategies for COVID-19 control and surveillance.展开更多
The variation in near-surface wind speed is a key dynamic parameter in the orographic effect of precipitation over eastern China.In this study,we used the latest high-resolution outputs from six GCMs in CMIP6-HighResM...The variation in near-surface wind speed is a key dynamic parameter in the orographic effect of precipitation over eastern China.In this study,we used the latest high-resolution outputs from six GCMs in CMIP6-HighResMIP to evaluate the performance of high-resolution models in simulating the orographic precipitation characteristics of typical mountainous areas in summer over eastern China.The orographic precipitation under warming scenarios was projected and constrained according to observational data.The results indicated that during the contemporary climate reference period(1979-2009),although the relationship between model-simulated near-surface wind speed and orographic light rain frequency was consistently stable,the sensitivity of the orographic light rain frequency to surface wind variability was generally underestimated,with a deviation approximately 24.1% lower than the observational values.The estimated orographic light rain frequency corrected based on the observed near-surface wind speed under a 1.5℃ warming scenario,was 36.1% lower than that of the contemporary period;this reduction was 8.6 times that without the wind speed constraint(4.2%).The MRI-AGCM3-2-S model,with a longer dataset,demonstrated relatively stable reductions in orographic light rain frequency under different warming scenarios(1.5℃,2℃,3℃,and 4℃)after the application of wind speed constraints.In all cases,the reductions exceeded those for the predictions made without the wind speed constraint.展开更多
This study achieved the construction of earthquake disaster scenarios based on physics-based methods-from fault dynamic rupture to seismic wave propagation-and then population and economic loss estimations.The physics...This study achieved the construction of earthquake disaster scenarios based on physics-based methods-from fault dynamic rupture to seismic wave propagation-and then population and economic loss estimations.The physics-based dynamic rupture and strong ground motion simulations can fully consider the three-dimensional complexity of physical parameters such as fault geometry,stress field,rock properties,and terrain.Quantitative analysis of multiple seismic disaster scenarios along the Qujiang Fault in western Yunnan Province in southwestern China based on different nucleation locations was achieved.The results indicate that the northwestern segment of the Qujiang Fault is expected to experience significantly higher levels of damage compared to the southeastern segment.Additionally,there are significant variations in human losses,even though the economic losses are similar across different scenarios.Dali Bai Autonomous Prefecture,Chuxiong Yi Autonomous Prefecture,Yuxi City,Honghe Hani and Yi Autonomous Prefecture,and Wenshan Zhuang and Miao Autonomous Prefecture were identified as at medium to high seismic risks,with Yuxi and Honghe being particularly vulnerable.Implementing targeted earthquake prevention measures in Yuxi and Honghe will significantly mitigate the potential risks posed by the Qujiang Fault.Notably,although the fault is within Yuxi,Honghe is likely to suffer the most severe damage.These findings emphasize the importance of considering rupture directivity and its influence on ground motion distribution when assessing seismic risk.展开更多
Deep learning models demonstrate impressive performance in rapidly predicting urban floods,but there are still limitations in enhancing physical connectivity and interpretability.This study proposed an innovative mode...Deep learning models demonstrate impressive performance in rapidly predicting urban floods,but there are still limitations in enhancing physical connectivity and interpretability.This study proposed an innovative modeling approach that integrates convolutional neural networks with weighted cellular automaton(CNN-WCA)to achieve the precise and rapid prediction of urban pluvial flooding processes and enhance the physical connectivity and reliability of modeling results.The study began by generating a rainfall-inundation dataset using WCA and LISFLOOD-FP,and the CNN-WCA model was trained using outputs from LISFLOOD-FP and WCA.Subsequently,the pre-trained model was applied to simulate the flood caused by the 20 July 2021 rainstorm in Zhengzhou City.The predicted inundation spatial distribution and depth by CNN-WCA closely aligned with those of LISFLOOD-FP,with the mean absolute error concentrated within 5 mm,and the prediction time of CNN-WCA was only 0.8%that of LISFLOOD-FP.The CNN-WCA model displays a strong capacity for accurately predicting changes in inundation depths within the study area and at susceptible points for urban flooding,with the Nash-Sutcliffe e fficiency values of most flood-prone points exceeding 0.97.Furthermore,the physical connectivity of the inundation distribution predicted by CNN-WCA is better than that of the distribution obtained with a CNN.The CNN-WCA model with additional physical constraints exhibits a reduction of around 34%in instances of physical discontinuity compared to CNN.Our results prove that the CNN model with multiple physical constraints has signifi cant potential to rapidly and accurately simulate urban flooding processes and improve the reliability of prediction.展开更多
The typhoon is one major threat to human societies and natural ecosystems, and its risk perception is crucial for contextualizing and managing disaster risks in different social settings. Social media data are a new d...The typhoon is one major threat to human societies and natural ecosystems, and its risk perception is crucial for contextualizing and managing disaster risks in different social settings. Social media data are a new data source for studying risk perception, because such data are timely, widely distributed, and sensitive to emergencies.However, few studies have focused on crowd sensitivity variation in social media data-based typhoon risk perception. Based on the regional disaster system theory, a framework of analysis for crowd risk perception was established to explore the feasibility of using social media data for typhoon risk perception analysis and crowd sensitivity variation. The goal was to quantitatively analyze the impact of hazard intensity and social and geographical environments on risk perception and its variation among population groups. Taking the Sina Weibo data during Typhoon Lekima of 2019 as an example, we found that:(1)Typhoon Lekima-related Weibo public attention changed in accordance with the evolution of the typhoon track and the number of Weibo posts shows a significantly positive correlation with disaster losses, while socioeconomic factors,including population, gross domestic product, and land area, are not explanatory factors of the spatial distribution of disaster-related Weibo posts;(2) Females, nonlocals with travel plans, and people living in areas with high hazard intensity, low elevation, or near waterbodies affected by Lekima paid more attention to the typhoon disaster;and(3)Descriptions of rainfall intensity by females are closer to the meteorological observation data.展开更多
With the acceleration of urbanization in South China, rainstorms and floods are threatening the safety of people in urban areas. The 11 April 2019(4·11 hereafter)rainstorm in Shenzhen City was a typical pre-rainy...With the acceleration of urbanization in South China, rainstorms and floods are threatening the safety of people in urban areas. The 11 April 2019(4·11 hereafter)rainstorm in Shenzhen City was a typical pre-rainy season rainstorm that caused great damage, yet such pre-rainy season events have not attracted sufficient attention in research.Risk perception of the public may indirectly affect their disaster preparedness, which is important for disaster management. In this study, we conducted a questionnaire survey that considered demographic factors and the level of risk perception, knowledge of risk, impact of the 4·11 rainstorm event on public risk perception, and degree of trust in the government. We used a two-factor model of risk perception to evaluate the factors that influenced public risk perception of the 4·11 rainstorm in Shenzhen. The main conclusions are: The 4·11 rainstorm improved public awareness of both risk and impact through the medium term, but the public’s perceived low probability of disaster occurrence and lack of knowledge of the pre-rainy season rainstorm phenomenon led to serious losses during this event. Although the public has high trust in the Shenzhen government, the management of rainstorm disasters in the pre-rainy season needs to be further improved.展开更多
Playas are common in many arid regions and recognized as a major source of hypersaline particles.A better understanding of wind erosion on crusted playas has significant implications for land management and pollution ...Playas are common in many arid regions and recognized as a major source of hypersaline particles.A better understanding of wind erosion on crusted playas has significant implications for land management and pollution control practices.We hypothesized that wind erosion rates of crusted playas were complicated and controlled by the interactions between playa crust and wind-induced saltation conditions.However,comparisons regarding the effects of different playa crusts on wind erosion under no saltation(NS)and with saltation(WS)conditions were lacking.In this study,laboratory wind tunnel experiments were carried out to simulate both NS and WS conditions,to investigate the erosion rates of different crust types(Salt,Takyr,and Puffic crust)at different wind speeds.Results showed that:1)Salt crust had greater crust strengths than did Takyr crust and Puffic crust;2)wind erosion rates under the WS condition were up to 60 times greater than those under the NS condition,suggesting that sand bombardment was the dominant mechanism responsible for removal of fine material from crusted playa surfaces;3)both sand bombardment rate and wind erosion rate of the playa crusts increased with increasing wind speed under the WS conditions;4)Puffic crust exhibited a greater rate of wind erosion compared to both the Takyr and Salt crusts under the Ns condition,yet tended to have a lower rate of wind erosion compared to both the Takyr and Salt crusts under the WS condition.This difference can be attributed to the fact that soft Puffic crusts are pliable and can dissipate the force of impacting grains under the Ws conditions.Our results indicated that wind erosion processes on crusted playas are complicated and are affected by wind-induced saltation and crust type,specifically crust strength and elasticityofthesurface.展开更多
On 6 February 2023,two 7.8 magnitude earthquakes consecutively hit south-central Türkiye,causing great concern from all governments,the United Nations,academia,and all sectors of society.Analyses indicate that th...On 6 February 2023,two 7.8 magnitude earthquakes consecutively hit south-central Türkiye,causing great concern from all governments,the United Nations,academia,and all sectors of society.Analyses indicate that there is also a high possibility of strong earthquakes with a magnitude of 7.8 or above occurring in the western region of China in the coming years.China is a country that is highly susceptible to catastrophic disasters such as earthquakes,floods,and other natural calamities,which can cause significant damages to both human life and property,as well as widespread impacts on the society.Currently,China's capacity for disaster prevention and control is still limited.In order to effectively reduce the impact of catastrophic disasters,ensure the safety of people's lives and property to the greatest extent possible,maintain social stability in high-risk areas,and ensure high-quality and sustainable regional development,it is urgent to improve the seismic resistance level of houses and critical infrastructure in high earthquake risk zones and increase the earthquake-resistant design level of houses in high-risk fault areas with frequent seismic activities;significantly enhance the ability to defend against extreme weather and ocean disasters in economically developed areas along the southeastern coast,as well as the level of fortification in response to extreme meteorological and hydrological disasters of coastal towns/cities and key infrastructure;vigorously enhance the emergency response capacity and disaster risk prevention level in western and ethnic minority regions;comprehensively improve the defense level of residential areas and major infrastructure in high geological hazard risk zones with flash floods,landslides,and mudslides;systematically promote national disaster prevention and mitigation education;and greatly enhance the societal disaster risk reduction ability,including catastrophic insurance.展开更多
Calcium carbonate(CaCO_(3))is a main component in marine sediment,and sedimentary CaCO_(3) weight percentages(wtCaCO_(3)%)in the global ocean have been extensively measured since the early last century.The tremendous ...Calcium carbonate(CaCO_(3))is a main component in marine sediment,and sedimentary CaCO_(3) weight percentages(wtCaCO_(3)%)in the global ocean have been extensively measured since the early last century.The tremendous database produced has been utilized in oceanographic research to constrain oceanic carbon cycles and to dictate past changes in deep ocean circulation.Inaccurate records in terms of sediment core coordinates,elevation,and wtCaCO_(3)%data have been introduced in the past few decades,especially during compilation practice,rendering them less effective during the reuse of the data.Therefore,we thoroughly scrutinized published wtCaCO_(3)%data and their geographical information and corrected 570 erroneous data points.These corrections help to establish a better basin-wide distribution pattern of sedimentary CaCO_(3) with ocean depth,which would eventually contribute to a more valid estimate of the standing stock of erodible CaCO_(3) in the global ocean.An accurate carbonate dataset could also facilitate applications of wtCaCO_(3)%in paleoceanography and predictions of the buffering capacity of CaCO_(3) to ocean acidification.展开更多
Reliability analysis plays an important role in the risk management of geotechnical engineering.For the random field-based method,it is expected that the uncertainty characterization of geo-material parameters and the...Reliability analysis plays an important role in the risk management of geotechnical engineering.For the random field-based method,it is expected that the uncertainty characterization of geo-material parameters and the realization of random field can be integrated effectively.Moreover,as the increase in measured data size is generally difficult in the field investigation of geotechnical engineering due to limitation of budget and time etc.,the statistical uncertainty resulting from sparse data should be paid great attention.Therefore,taking the determination of hyper-parameters for Bayesian-based conditional random field as the breakthrough,this study proposed a reliability analysis framework to achieve the expectation above.In this proposed reliability analysis framework,the present characterization method of statistical uncertainty is improved by setting the lognormal distribution as the prior distribution of scale of fluctuation(SOF).Subsequently,the performance of statistical uncertainty characterization method is tested by a set of unconfined compressive strength(UCS)database about rocks.Then,a case study about the stability analysis of slope is employed to demonstrate the beneficial effect of the proposed reliability analysis framework.It is found that the uncertainty in both the realization of random field and the reliability analysis results can be significantly mitigated by the proposed reliability analysis framework.展开更多
This study presents a probabilistic seismic risk model for the Beijing-Tianjin-Hebei region in China.The model comprises a township-level residential building exposure model,a vulnerability model derived from the Chin...This study presents a probabilistic seismic risk model for the Beijing-Tianjin-Hebei region in China.The model comprises a township-level residential building exposure model,a vulnerability model derived from the Chinese building taxonomy,and a regional probabilistic seismic hazard model.The three components are integrated by a stochastic event-based method of the OpenQuake engine to assess the regional seismic risk in terms of average annual loss and exceedance probability curve at the city,province,and regional levels.The novelty and uniqueness of this study are that a probabilistic seismic risk model for the Beijing-Tianjin-Hebei region in China is developed by considering the impact of site conditions and epistemic uncertainty from the seismic hazard model.展开更多
Assessing climate change impacts on crop phenology is essential for developing adaptation options.To better understand crop response and adaptation to climate change,there is an urgent need to investigate whether the ...Assessing climate change impacts on crop phenology is essential for developing adaptation options.To better understand crop response and adaptation to climate change,there is an urgent need to investigate whether the impacts weakens and how crops responds to recent climate warming,as well as the roles of different drivers in crop phenology change.Here,we analyzed the spatiotemporal changes in maize phenology and the underlying mechanisms over 1981–2018 using up-to-date 6106 phenological observations at 327 agro-meteorological stations in China.We found that during 1981–2018 maize sowing and maturity dates were generally delayed by 0.6 and 1.2 d per decade,respectively,whereas heading date was advanced by 0.9 d per decade.Maize phenology was most negatively correlated with rising minimum temperature(night-time warming),followed by maximum(daytime)temperature,and least by mean temperature.The trends in maize phenology and the correlation between growth periods and temperature generally declined from 1981 to 1999 to 2000–2018 for both spring and summer maize,although climate warming during growth period did not slow down.The phenological response to temperature weakened mainly owing to agricultural managements,especially cultivar shifts.Climate change shortened growth period by 3.4 and 1.7 d per decade but cultivar shifts prolonged it by 4.5 and 2.1 d per decade for spring and summer maize,respectively.Our study highlights that maize phenology is more sensitive to night-time warming than daytime warming,and cultivar shifts far outweigh climate change.These findings foster the understanding of spatiotemporal dynamics of maize phenology and its drivers,which can benefit to develop effective climate change adaptation options for different regions.展开更多
基金supported by the Natural Science Foundation of Shanxi Province(Grant No.20210302124437)the Graduate Student Research and Innovation Project of Shanxi Province(Grant No.2023KY551).
文摘In this paper,the Taixin Integrated Economic Zone in Shanxi Province is taken as the research object,and the coupling coordination degree model and bivariate spatial autocorrelation model are used to judge the coupling coordination and spatial-temporal correlation between urbanization and ecosystem service,and the hotspot analysis is used to judge the spatial-temporal trend of urbanization and ecosystem service.The results show that:(1)The urbanization level from 2000 to 2020 continued to rise,the areas with relatively high urbanization were concentrated in the central part of the study area,and the relatively high terrain areas on both sides of the study area,the urbanization was relatively slow,and the hotspot areas with highly significant and significant urbanization level from 2000 to 2020 were distributed as bands in the central part of the study area and the area was rising,and there was no Cold spot area distribution;between 2000 and 2020,the ecosystem service value in the study area increased by 2.6800×10^(8) yuan.Over these two decades,it exhibited a development trend that first rose and then declined.The woodland and grassland agglomeration areas were located on the two sides of the study area,forming highly significant and significant hotspots.Conversely,the central and northeastern parts of the study area were characterized by concentrated man-made land surfaces and croplands,resulting in the formation of highly significant and significant cold spots.(2)In the central part of the study area where man-made land surface and cultivated land are concentrated,the coupling coordination between urbanization and ecosystem service is in the intermediate dislocation and mild dislocation interval;the woodland and grassland concentration areas on both sides of the study area are ecologically fragile,and the coupling coordination between the two is in the level of less than intermediate dislocation.(3)From 2000 to 2020,urbanization and the value of ecosystem services were both negatively correlated,although the correlation coefficient was low.In the central and northeastern parts,urbanization and ecosystem service exhibited patterns of high-low,high-high,and low-low clustering.Conversely,on both sides of the study area,most of the clusters showed a low-high pattern.
基金supported by the National Natural Science Foundation of China(Grant No.52308340)the Innovative Projects of Universities in Guangdong(Grant No.2022KTSCX208)Sichuan Transportation Science and Technology Project(Grant No.2018-ZL-01).
文摘Historically,landslides have been the primary type of geological disaster worldwide.Generally,the stability of reservoir banks is primarily affected by rainfall and reservoir water level fluctuations.Moreover,the stability of reservoir banks changes with the long-term dynamics of external disastercausing factors.Thus,assessing the time-varying reliability of reservoir landslides remains a challenge.In this paper,a machine learning(ML)based approach is proposed to analyze the long-term reliability of reservoir bank landslides in spatially variable soils through time series prediction.This study systematically investigated the prediction performances of three ML algorithms,i.e.multilayer perceptron(MLP),convolutional neural network(CNN),and long short-term memory(LSTM).Additionally,the effects of the data quantity and data ratio on the predictive power of deep learning models are considered.The results show that all three ML models can accurately depict the changes in the time-varying failure probability of reservoir landslides.The CNN model outperforms both the MLP and LSTM models in predicting the failure probability.Furthermore,selecting the right data ratio can improve the prediction accuracy of the failure probability obtained by ML models.
基金funded by the National Natural Science Foundation of China (42061144003)。
文摘The timely and rapid mapping of rapeseed planting areas is desirable for national food security. Most current rapeseed mapping methods depend strongly on images with good observations obtained during the flowering stages. Although vegetation indices have been proposed to identify the rapeseed flowering stage in some areas, automatically mapping rapeseed planting areas in large regions is still challenging.We developed an automatic phenology-and pixel-based algorithm(APPA) by integrating Landsat 8 and Sentinel-1 satellite data. We found that the Normalized Rapeseed Flowering Index shows unique spectral characteristics during the flowering and post-flowering periods, which distinguish rapeseed parcels from other land-use types(urban, water, forest, grass, maize, wheat, barley, and soybean). To verify the robustness of APPA, we applied APPA to seven areas in five rapeseed-producing countries with flowering images unavailable. The rapeseed maps by APPA showed consistently high accuracies with producer accuracies of 0.87–0.93 and F-scores of 0.92–0.95 based on 4503 verification samples. They showed high spatial consistency at the pixel level with the land cover Scientific Expertise Centres(SEC) map in France,Crop Map of England in United Kingdom, national-scale crop-and land-cover map of Germany, and Annual Crop Inventory in Canada at the pixel level. We propose APPA as a highly promising method for automatically and efficiently mapping rapeseed areas.
基金the National Natural Science Foundation of China(42301086 and 42120104002)the Second Tibetan Plateau Scientific Expedition and Research Program(STEP)(2019QZKK0906)+2 种基金the China Postdoctoral Science Foundation(2023M731874 and 2022M721771)the Fundamental Research Funds for the Central Universities(2021NTST28)the School of National Safety and Emergency Management of Beijing Normal University Funds,and the Research Fund Program of the State Key Laboratory of Hydroscience and Engineering(2021-KY-04).
文摘Glaciers have retreated and shrunk in High Mountain Asia since the mid-20th century because of global warming,leading to glacier instability and hazardous iceesnow avalanches.However,the complex relationship between iceesnow avalanches and factors such as climate and potential triggers are difficult to understand because of the lack of observational data.Here,we addressed iceesnow avalanches on the Annapurna Ⅱ glacier in Nepal,Central Himalaya.We constructed an iceesnow avalanche history using long-term multi-source remote sensing images(1988-2021)and mapped the velocity fields of glaciers using cross-correlation analysis on SAR and optical images.Then,we investigated the impact of climate change and earthquakes on the frequency and size of iceesnow avalanches.The results demonstrate that the frequency of iceesnow avalanches has increased from 10 in 1988 to 27 in 2020,but the average area of iceesnow avalanche deposits has decreased by approximately 70%,from 3.4×10^(5) m^(2) in 1988 to 1.2×10^(5) m^(2) in 2020.The evolutionary characteristic of ice avalanches is linked to the impact of glacier retreat(reduction in ice material supply)and increased activity under climate change.The glacier movement velocity controls the size of iceesnow avalanches and can be set as an indicator for iceesnow avalanche warnings.On the Annapurna Ⅱ glacier,an iceesnow avalanche occurred when the glacier velocities were greater than 1.5 m d^(-1).These results offer insights into iceesnow avalanche risk assessment and prediction in high-mountain areas,particularly in regions characterised by dense glacier distribution.
基金financial support from the Scientific Research Fund of the Institute of Engineering Mechanics,China Earthquake Administration(Grant No.2023B09)。
文摘In this study,a multi-source data fusion method was proposed for the development of a Hybrid seismic hazard model(HSHM)in China by using publicly available data of the 5th Seismic Ground Motion Parameter Zoning Map(NSGM)and historical seismic catalogues and integrating with modern ground motion prediction equations(GMPEs).This model incorporates the characteristics of smoothed seismicity and areal sources for regional seismic hazard assessment.The probabilistic seismic hazard for the North China Plain earthquake belt was investigated through sensitivity analysis related to the seismicity model and GMPEs.The analysis results indicate that the Hybrid model can produce a consistent result with the NSGM model in many cases.However,the NSGM model tends to overestimate hazard values in locations where no major events have occurred and underestimate hazard values in locations where major events have occurred.The Hybrid model can mitigate the degree of such biases.Compared to the modern GMPEs,the GMPE with epicentral distance measures significantly underestimate the seismic hazard under near-field and large-magnitude scenarios.In addition,a comparison of the uniform hazard spectra(UHS)obtained by the models,with China's design spectrum,shows that the current design spectrum is more conservative than the calculated UHS.
基金Special Program for Survey of National Basic Scientific and Technological Resources,No.2021FY00802。
文摘The Taihang Mountains in North China are an important carbon-water ecosystem service supply area.Understanding the coupling effect and influencing mechanisms of mountain carbon sequestration as well as water conservation is essential for regional eco-logical restoration and sustainable development.In this study,we utilized models such as the coupled coordination degree model,the random forest and Geodetector to analyze the spa-tio-temporal changes as well as driving factors of carbon sequestration-water conservation coupling coordination in the Taihang Mountains.The results show that:(1)From 1990 to 2020,the carbon sequestration and water conservation capacity of the Taihang Mountains exhibited a spatial pattern with higher values in the southeast and central regions,while lower values in the northwest region.(2)The average coupling coordination degree from 1990 to 2020 was O.23,which was overall low,with a fluctuating decreasing-rising-decreasing trend over time.The coupling coordination degree exhibited a pattern that is high in the middle and low in the periphery,with a fluctuating distribution that initially decreases and then increases with the increasing altitude.The overall trend of coupling coordination is degradation,with concen-trated degradation in the northwest mountainous regions.(3)Precipitation and soil texture were identified as the main driving factors influencing coupling coordination,with the interac-tion between precipitation and soil sand content showing the strongest explanatory power,while that among topography,vegetation and human activities had relatively low explanatory power.Therefore,enhanced protection and the continuous monitoring of vegetation and soil environments in the Taihang Mountains are essential,with particular emphasis on ecological restoration in areas experiencing a persistent degradation of carbon-water coupling.This study can provide assistance in monitoring and managing carbon sink and water resources in the mountains,meanwhile mitigating potential adverse impacts on human well-being.
基金This work was supported by the National Natural Science Foundation of China(Grant Nos.41977405,42061144003).
文摘Acquiring spatiotemporal patterns of phenological information and its drivers is essential for understanding the response of crops to climate change and implementing adaptation measures.However,current approaches to obtain phenology and analyse its drivers have deficiencies such as sparse observations,excessive dependence of remote sensing inversion on sensors,and inevitable difficulties in upscaling site-based crop models into larger regions.Based on the Wang-Engel temperature response function,we improved the Crop Estimation through Resource and Environment Synthesis-Wheat(CERES-Wheat)model.First,we calibrated the model at the regional scale and evaluated its performance.Furthermore,the spatiotemporal changes in winter wheat phenology in China from 2000 to 2015 were analysed.The results showed that the improved model significantly enhanced the simulation accuracy of the anthesis and maturity dates by averages of 13%and 12%in most planting areas,especially in the Yunnan-Guizhou Plateau(YG)with improvements of 26%and 28%.The simulated phenology of winter wheat grown in a colder environment(e.g.,the average temperatures during the vegetative growth period range from 0 to 5℃ and from 15 to 20°C,and the reproductive growth period ranges from 10 to 15°C)also notably improved.These results confirmed that the original temperature response function indeed had limitations.Further analyses revealed that the key phenological dates and growth periods over the past 16 years were dominantly advanced and shortened.Specifically,the anthesis date,vegetative growth period(VGP),and reproductive growth period(RGP)indicated obviously spatial characteristics.For example,the anthesis date and VGP in the North China Plain(NCP)and the Middle-Lower Yangtze Plain(YZ)and the RGP in northwestern China(NW)showed opposite trends of delay and prolongation as comparing with the dominant patterns.Sensitivity analysis indicated that the key phenological dates and growth periods were advanced and shortened as the minimum(T_(min))and maximum temperatures(T_(max))rose,while they were postponed and prolonged with the increased precipitation.However,their responses to solar radiation did not show spatial consistency.Additionally,we found that the sensitivity of phenology to climatic factors differed across subregions.In particular,phenology in southwestern China and YG was more sensitive to T_(min),T_(max),and solar radiation than in the NCP and NW.Moreover,the sensitivity to precipitation in NW was higher than that in YZ.Totally,the improved crop model could provide more refined spatial characteristics of phenology at a large scale and benefit to explore its drivers more objectively.Furthermore,our results highlight that different planting areas should adopt suitable adaptation measures to cope with climate change impacts.Ultimately,the improved model is promising to enhance the accuracy of yield prediction and provide powerful tools for assessing regional climate change impact and adaptability.
基金supported by the National Key Research and Development Program(2017YFA0604903,2017YFC1502505)。
文摘In the context of climate change,the impact of extreme precipitation and its chain effects has intensified in the southeastern coastal region of China,posing a serious threat to the socioeconomic development in the region.This study took tropical cyclones–extreme precipitation–flash floods as an example to carry out a risk assessment of flash floods under climate change in the Yantanxi River Basin,southeastern China.To obtain the flash flood inundation characteristics through hydrologic–hydrodynamic modeling,the study combined representative concentration pathway(RCP)and shared socioeconomic pathway(SSP)scenarios to examine the change of flash flood risk and used the geographical detector to explore the driving factors behind the change.The results show that flash flood risk in the Yantanxi River Basin will significantly increase,and that socioeconomic factors and precipitation are the main driving forces.Under the RCP4.5-SSP2 and RCP8.5-SSP5 scenarios,the risk of flash floods is expected to increase by 88.79%and 95.57%,respectively.The main drivers in the case study area are GDP density(q=0.85),process rainfall(q=0.74),asset density(q=0.68),and population density(q=0.67).The study highlights the influence of socioeconomic factors on the change of flash flood disaster risk in small river basins.Our findings also provide a reference for regional planning and construction of flood control facilities in flash flood-prone areas,which may help to reduce the risk of flash floods.
基金Provided by the Beijing Science and Technology Planning Project(Z221100007922019,Z201100005420010)Scientific and Technological Innovation 2030—Major Project of New Generation Artificial Intelligence(2021ZD0111201)+4 种基金National Natural Science Foundation of China(82073616,82204160)National Key Research and Development Program of China(2022YFC2303803,2021YFC 0863400)Beijing Advanced Innovation Program for Land Surface ScienceResearch on Key Technologies of Plague Prevention and Control in Inner Mongolia Autonomous Region(2021ZD0006)Fundamental Research Funds for the Central Universities。
文摘Introduction:The transmissibility of the severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)Omicron variant poses challenges for the existing measures containing the virus in China.In response,this study investigates the effectiveness of population-level testing(PLT)and contact tracing(CT)to help curb coronavirus disease 2019(COVID-19)resurgences in China.Methods:Two transmission dynamic models(i.e.with and without age structure)were developed to evaluate the effectiveness of PLT and CT.Extensive simulations were conducted to optimize PLT and CT strategies for COVID-19 control and surveillance.Results:Urban Omicron resurgences can be controlled by multiple rounds of PLT,supplemented by CT—as long as testing is frequent.This study also evaluated the time needed to detect COVID-19 cases for surveillance under different routine testing rates.The results show that there is a 90%probability of detecting COVID-19 cases within 3 days through daily testing.Otherwise,it takes around 7 days to detect COVID-19 cases at a 90%probability level if biweekly testing is used.Routine testing applied to the age group 21–60 for COVID-19 surveillance would achieve similar performance to that applied to all populations.Discussion:Our analysis evaluates potential PLT and CT strategies for COVID-19 control and surveillance.
基金supported by the National Key Research and Development Program of China(Grant No.2020YFA0608201)the National Natural Science Foundation of China(Grant No.42275180)。
文摘The variation in near-surface wind speed is a key dynamic parameter in the orographic effect of precipitation over eastern China.In this study,we used the latest high-resolution outputs from six GCMs in CMIP6-HighResMIP to evaluate the performance of high-resolution models in simulating the orographic precipitation characteristics of typical mountainous areas in summer over eastern China.The orographic precipitation under warming scenarios was projected and constrained according to observational data.The results indicated that during the contemporary climate reference period(1979-2009),although the relationship between model-simulated near-surface wind speed and orographic light rain frequency was consistently stable,the sensitivity of the orographic light rain frequency to surface wind variability was generally underestimated,with a deviation approximately 24.1% lower than the observational values.The estimated orographic light rain frequency corrected based on the observed near-surface wind speed under a 1.5℃ warming scenario,was 36.1% lower than that of the contemporary period;this reduction was 8.6 times that without the wind speed constraint(4.2%).The MRI-AGCM3-2-S model,with a longer dataset,demonstrated relatively stable reductions in orographic light rain frequency under different warming scenarios(1.5℃,2℃,3℃,and 4℃)after the application of wind speed constraints.In all cases,the reductions exceeded those for the predictions made without the wind speed constraint.
基金supported by the Guangdong Provincial Key Laboratory of Geophysical High-Resolution Imaging Technology (2022B1212010002)Key Special Project for Introduced Talents Team of the Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou) (GML2019ZD0203)the Shenzhen Science and Technology Program (KQTD20170810111725321)
文摘This study achieved the construction of earthquake disaster scenarios based on physics-based methods-from fault dynamic rupture to seismic wave propagation-and then population and economic loss estimations.The physics-based dynamic rupture and strong ground motion simulations can fully consider the three-dimensional complexity of physical parameters such as fault geometry,stress field,rock properties,and terrain.Quantitative analysis of multiple seismic disaster scenarios along the Qujiang Fault in western Yunnan Province in southwestern China based on different nucleation locations was achieved.The results indicate that the northwestern segment of the Qujiang Fault is expected to experience significantly higher levels of damage compared to the southeastern segment.Additionally,there are significant variations in human losses,even though the economic losses are similar across different scenarios.Dali Bai Autonomous Prefecture,Chuxiong Yi Autonomous Prefecture,Yuxi City,Honghe Hani and Yi Autonomous Prefecture,and Wenshan Zhuang and Miao Autonomous Prefecture were identified as at medium to high seismic risks,with Yuxi and Honghe being particularly vulnerable.Implementing targeted earthquake prevention measures in Yuxi and Honghe will significantly mitigate the potential risks posed by the Qujiang Fault.Notably,although the fault is within Yuxi,Honghe is likely to suffer the most severe damage.These findings emphasize the importance of considering rupture directivity and its influence on ground motion distribution when assessing seismic risk.
基金supported by the General Program of National Natural Science Foundation of China(Grant No.42377467)。
文摘Deep learning models demonstrate impressive performance in rapidly predicting urban floods,but there are still limitations in enhancing physical connectivity and interpretability.This study proposed an innovative modeling approach that integrates convolutional neural networks with weighted cellular automaton(CNN-WCA)to achieve the precise and rapid prediction of urban pluvial flooding processes and enhance the physical connectivity and reliability of modeling results.The study began by generating a rainfall-inundation dataset using WCA and LISFLOOD-FP,and the CNN-WCA model was trained using outputs from LISFLOOD-FP and WCA.Subsequently,the pre-trained model was applied to simulate the flood caused by the 20 July 2021 rainstorm in Zhengzhou City.The predicted inundation spatial distribution and depth by CNN-WCA closely aligned with those of LISFLOOD-FP,with the mean absolute error concentrated within 5 mm,and the prediction time of CNN-WCA was only 0.8%that of LISFLOOD-FP.The CNN-WCA model displays a strong capacity for accurately predicting changes in inundation depths within the study area and at susceptible points for urban flooding,with the Nash-Sutcliffe e fficiency values of most flood-prone points exceeding 0.97.Furthermore,the physical connectivity of the inundation distribution predicted by CNN-WCA is better than that of the distribution obtained with a CNN.The CNN-WCA model with additional physical constraints exhibits a reduction of around 34%in instances of physical discontinuity compared to CNN.Our results prove that the CNN model with multiple physical constraints has signifi cant potential to rapidly and accurately simulate urban flooding processes and improve the reliability of prediction.
基金supported by the National Key Research and Development Program of China(No.2018YFC1508903)the Science Technology Department of Zhejiang Province(No.2022C03107)the International Center for Collaborative Research on Disaster Risk Reduction。
文摘The typhoon is one major threat to human societies and natural ecosystems, and its risk perception is crucial for contextualizing and managing disaster risks in different social settings. Social media data are a new data source for studying risk perception, because such data are timely, widely distributed, and sensitive to emergencies.However, few studies have focused on crowd sensitivity variation in social media data-based typhoon risk perception. Based on the regional disaster system theory, a framework of analysis for crowd risk perception was established to explore the feasibility of using social media data for typhoon risk perception analysis and crowd sensitivity variation. The goal was to quantitatively analyze the impact of hazard intensity and social and geographical environments on risk perception and its variation among population groups. Taking the Sina Weibo data during Typhoon Lekima of 2019 as an example, we found that:(1)Typhoon Lekima-related Weibo public attention changed in accordance with the evolution of the typhoon track and the number of Weibo posts shows a significantly positive correlation with disaster losses, while socioeconomic factors,including population, gross domestic product, and land area, are not explanatory factors of the spatial distribution of disaster-related Weibo posts;(2) Females, nonlocals with travel plans, and people living in areas with high hazard intensity, low elevation, or near waterbodies affected by Lekima paid more attention to the typhoon disaster;and(3)Descriptions of rainfall intensity by females are closer to the meteorological observation data.
基金The study was supported by the National Key Research and Development Project(Grant No.2017YFC1503000).The authors would like to thank the reviewers for their valuable comments and the editors’help with this article.
文摘With the acceleration of urbanization in South China, rainstorms and floods are threatening the safety of people in urban areas. The 11 April 2019(4·11 hereafter)rainstorm in Shenzhen City was a typical pre-rainy season rainstorm that caused great damage, yet such pre-rainy season events have not attracted sufficient attention in research.Risk perception of the public may indirectly affect their disaster preparedness, which is important for disaster management. In this study, we conducted a questionnaire survey that considered demographic factors and the level of risk perception, knowledge of risk, impact of the 4·11 rainstorm event on public risk perception, and degree of trust in the government. We used a two-factor model of risk perception to evaluate the factors that influenced public risk perception of the 4·11 rainstorm in Shenzhen. The main conclusions are: The 4·11 rainstorm improved public awareness of both risk and impact through the medium term, but the public’s perceived low probability of disaster occurrence and lack of knowledge of the pre-rainy season rainstorm phenomenon led to serious losses during this event. Although the public has high trust in the Shenzhen government, the management of rainstorm disasters in the pre-rainy season needs to be further improved.
基金supported by the National Natural Science Foundation of China(Grant Nos.41971120,41730639,42107353)。
文摘Playas are common in many arid regions and recognized as a major source of hypersaline particles.A better understanding of wind erosion on crusted playas has significant implications for land management and pollution control practices.We hypothesized that wind erosion rates of crusted playas were complicated and controlled by the interactions between playa crust and wind-induced saltation conditions.However,comparisons regarding the effects of different playa crusts on wind erosion under no saltation(NS)and with saltation(WS)conditions were lacking.In this study,laboratory wind tunnel experiments were carried out to simulate both NS and WS conditions,to investigate the erosion rates of different crust types(Salt,Takyr,and Puffic crust)at different wind speeds.Results showed that:1)Salt crust had greater crust strengths than did Takyr crust and Puffic crust;2)wind erosion rates under the WS condition were up to 60 times greater than those under the NS condition,suggesting that sand bombardment was the dominant mechanism responsible for removal of fine material from crusted playa surfaces;3)both sand bombardment rate and wind erosion rate of the playa crusts increased with increasing wind speed under the WS conditions;4)Puffic crust exhibited a greater rate of wind erosion compared to both the Takyr and Salt crusts under the Ns condition,yet tended to have a lower rate of wind erosion compared to both the Takyr and Salt crusts under the WS condition.This difference can be attributed to the fact that soft Puffic crusts are pliable and can dissipate the force of impacting grains under the Ws conditions.Our results indicated that wind erosion processes on crusted playas are complicated and are affected by wind-induced saltation and crust type,specifically crust strength and elasticityofthesurface.
基金founded by the Sixth Task of the Second Tibetan Plateau Scientific Expedition and Research Program(STEP),“Integrated Disaster Risk Prevention”(Grant No.2019QZKK0906)。
文摘On 6 February 2023,two 7.8 magnitude earthquakes consecutively hit south-central Türkiye,causing great concern from all governments,the United Nations,academia,and all sectors of society.Analyses indicate that there is also a high possibility of strong earthquakes with a magnitude of 7.8 or above occurring in the western region of China in the coming years.China is a country that is highly susceptible to catastrophic disasters such as earthquakes,floods,and other natural calamities,which can cause significant damages to both human life and property,as well as widespread impacts on the society.Currently,China's capacity for disaster prevention and control is still limited.In order to effectively reduce the impact of catastrophic disasters,ensure the safety of people's lives and property to the greatest extent possible,maintain social stability in high-risk areas,and ensure high-quality and sustainable regional development,it is urgent to improve the seismic resistance level of houses and critical infrastructure in high earthquake risk zones and increase the earthquake-resistant design level of houses in high-risk fault areas with frequent seismic activities;significantly enhance the ability to defend against extreme weather and ocean disasters in economically developed areas along the southeastern coast,as well as the level of fortification in response to extreme meteorological and hydrological disasters of coastal towns/cities and key infrastructure;vigorously enhance the emergency response capacity and disaster risk prevention level in western and ethnic minority regions;comprehensively improve the defense level of residential areas and major infrastructure in high geological hazard risk zones with flash floods,landslides,and mudslides;systematically promote national disaster prevention and mitigation education;and greatly enhance the societal disaster risk reduction ability,including catastrophic insurance.
基金supported by the Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai)(no.SML2021SP306)the National Natural Science Foundation of China(grant nos.41976031 and 41976192)+6 种基金the National Key Research and Development Program of China(2019YFE0114800)the Innovation Group Project of Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai)(no.311020005)support from the Guangdong Basic and Applied Basic Research Foundation(2021A1515011395)the Key Laboratory of Global Change and Marine-Atmospheric Chemistry,MNR China(GCMAC1904).Y.L.acknowledges support from the State Key Laboratory of Marine Geology,Tongji University(no.MG201908)a grant from the Open Foundation of Key Laboratory of Submarine Geosciences,MNR(KLSG1904)the Key Laboratory of Global Change and Marine-Atmospheric Chemistry,MNR(GCMAC1803).
文摘Calcium carbonate(CaCO_(3))is a main component in marine sediment,and sedimentary CaCO_(3) weight percentages(wtCaCO_(3)%)in the global ocean have been extensively measured since the early last century.The tremendous database produced has been utilized in oceanographic research to constrain oceanic carbon cycles and to dictate past changes in deep ocean circulation.Inaccurate records in terms of sediment core coordinates,elevation,and wtCaCO_(3)%data have been introduced in the past few decades,especially during compilation practice,rendering them less effective during the reuse of the data.Therefore,we thoroughly scrutinized published wtCaCO_(3)%data and their geographical information and corrected 570 erroneous data points.These corrections help to establish a better basin-wide distribution pattern of sedimentary CaCO_(3) with ocean depth,which would eventually contribute to a more valid estimate of the standing stock of erodible CaCO_(3) in the global ocean.An accurate carbonate dataset could also facilitate applications of wtCaCO_(3)%in paleoceanography and predictions of the buffering capacity of CaCO_(3) to ocean acidification.
基金supported by National Natural Science Foundation of China(No.52078086)Natural Science Foundation,Chongqing(No.CSTB2022NSCQ-LZX0001)+2 种基金NationalEngineering Research Center of Gas Hydrate Exploration and Development(No.NERCY[202406])Guangdong Basic and Applied Basic Research Foundation(No.2023A1515011375)Innovative Projects of Universities in Guangdong(No.2022KTSCX208).
文摘Reliability analysis plays an important role in the risk management of geotechnical engineering.For the random field-based method,it is expected that the uncertainty characterization of geo-material parameters and the realization of random field can be integrated effectively.Moreover,as the increase in measured data size is generally difficult in the field investigation of geotechnical engineering due to limitation of budget and time etc.,the statistical uncertainty resulting from sparse data should be paid great attention.Therefore,taking the determination of hyper-parameters for Bayesian-based conditional random field as the breakthrough,this study proposed a reliability analysis framework to achieve the expectation above.In this proposed reliability analysis framework,the present characterization method of statistical uncertainty is improved by setting the lognormal distribution as the prior distribution of scale of fluctuation(SOF).Subsequently,the performance of statistical uncertainty characterization method is tested by a set of unconfined compressive strength(UCS)database about rocks.Then,a case study about the stability analysis of slope is employed to demonstrate the beneficial effect of the proposed reliability analysis framework.It is found that the uncertainty in both the realization of random field and the reliability analysis results can be significantly mitigated by the proposed reliability analysis framework.
基金The financial support received from the Scientific Research Fund of Institute of Engineering Mechanics,China Earthquake Administration(Grant No.2023B09)National Key R&D Program of China(2022YFC3004404)Shenzhen Science and Technology Program(ZDSYS20210929115800001)are gratefully acknowledged。
文摘This study presents a probabilistic seismic risk model for the Beijing-Tianjin-Hebei region in China.The model comprises a township-level residential building exposure model,a vulnerability model derived from the Chinese building taxonomy,and a regional probabilistic seismic hazard model.The three components are integrated by a stochastic event-based method of the OpenQuake engine to assess the regional seismic risk in terms of average annual loss and exceedance probability curve at the city,province,and regional levels.The novelty and uniqueness of this study are that a probabilistic seismic risk model for the Beijing-Tianjin-Hebei region in China is developed by considering the impact of site conditions and epistemic uncertainty from the seismic hazard model.
基金supported by the National Natural Science Foundation of China(42061144003,41977405).
文摘Assessing climate change impacts on crop phenology is essential for developing adaptation options.To better understand crop response and adaptation to climate change,there is an urgent need to investigate whether the impacts weakens and how crops responds to recent climate warming,as well as the roles of different drivers in crop phenology change.Here,we analyzed the spatiotemporal changes in maize phenology and the underlying mechanisms over 1981–2018 using up-to-date 6106 phenological observations at 327 agro-meteorological stations in China.We found that during 1981–2018 maize sowing and maturity dates were generally delayed by 0.6 and 1.2 d per decade,respectively,whereas heading date was advanced by 0.9 d per decade.Maize phenology was most negatively correlated with rising minimum temperature(night-time warming),followed by maximum(daytime)temperature,and least by mean temperature.The trends in maize phenology and the correlation between growth periods and temperature generally declined from 1981 to 1999 to 2000–2018 for both spring and summer maize,although climate warming during growth period did not slow down.The phenological response to temperature weakened mainly owing to agricultural managements,especially cultivar shifts.Climate change shortened growth period by 3.4 and 1.7 d per decade but cultivar shifts prolonged it by 4.5 and 2.1 d per decade for spring and summer maize,respectively.Our study highlights that maize phenology is more sensitive to night-time warming than daytime warming,and cultivar shifts far outweigh climate change.These findings foster the understanding of spatiotemporal dynamics of maize phenology and its drivers,which can benefit to develop effective climate change adaptation options for different regions.
