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Process and Mechanism of Controlling Outburst Floods of landslide Dams through Artificial Structures: Physical Experiments

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Journal of Earth Science 2024年

作者： Hechun Ruan Huayong Chen Xiaoqing Chen Wanyu Zhao Xiao Li key laboratory of mountain hazards and surface processes， institute of mountain hazards and environment， Chinese Academy of Sciences University of Chinese Academy of Sciences

The scale of the outburst flood resulting from a landslide dam failure significantly influences the extent of the disaster and losses downstream. This study proposes a method for controlling the discharge of landslide dam failure using the artificial structure (AS). The primary approach involves strategically arranging the designed AS on both sides of the excavated spillway. As the breach is eroded， ASs gradually falls into the breach， serving to control the discharge. Fourteen sets of flume experiments were conducted to investigate the impact of various factors， including AS types， distances from the breach boundary， arrangements， columns， numbers， on the discharge control effectiveness. The mechanism how AS controls outburst discharge was revealed. Results indicate a pronounced control effect of AS on landslide dam-break discharge， with the maximum reducing rate of the peak discharge in the experiment reaching 47.4%. In controlling outburst discharge， four-sided framed structures demonstrate superior performance compared to four-sided solid structures， and serial structures outperform discrete structures. When arranging ASs， it is essential to ensure that the structure initiates its descent into the breach at the onset of the rapid increase in outburst discharge and continues until the peak discharge occurs. Building upon this foundation， augmenting the number of ASs and columns significantly enhances the efficacy of discharge control. The fundamental rationale for this discharge control lies in the AS’s capacity to reduce the headward scarp height， constrain sediment transport， and diminish the erosion capacity of the outburst flood， ultimately lowering the breach erosion rate. Lastly， a calculation method for the size design of the AS is established based on mechanical analysis. The research findings offer a new technological option for the emergency disposal of landslide dams.

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Economic Risk Assessment of Future Debris Flows by Machine Learning Method

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International Journal of Disaster Risk Science 2024年第1期15卷 149-164页

作者： Chenchen Qiu Lijun Su Alessandro Pasuto Giulia Bossi Xueyu Geng School of Engineering University of WarwickCoventry CV47ALUK key laboratory of mountain hazards and Earth surface Process Institute of Mountain Hazards and EnvironmentChinese Academy of SciencesChengdu 610041China Research institute for Geo-Hydrological Protection(IRPI-CNR) National Research Council of ItalyPadova 35127Italy

A reliable economic risk map is critical for effective debris-flow ***,the uncertainties surrounding future scenarios in debris-flow frequency and magnitude restrict its *** estimate the economic risks caused by future debris flows,a machine learning-based method was proposed to generate an economic risk map by multiplying a debris-flow hazard map and an economic vulnerability *** selected the Gyirong Zangbo Basin as the study area because frequent severe debris flows impact the area every *** debris-flow hazard map was developed through the multiplication of the annual probability of spatial impact,temporal probability,and annual *** employed a hybrid machine learning model-certainty factor-genetic algorithm-support vector classification-to calculate ***,a Poisson model was applied for temporal probabilities,while the determination of annual probability of spatial impact relied on statistical ***,four major elements at risk were selected for the generation of an economic loss map:roads,vegetation-covered land,residential buildings,and *** economic loss of elements at risk was calculated based on physical vulnerabilities and their economic ***,we proposed a physical vulnerability matrix for residential buildings,factoring in impact pressure on buildings and their horizontal distance and vertical distance to debrisflow *** this context,an ensemble model(XGBoost) was used to predict debris-flow volumes to calculate impact pressures on *** results show that residential buildings occupy 76.7% of the total economic risk,while roadcovered areas contribute approximately 6.85%.Vegetation-covered land and farmland collectively represent 16.45% of the entire *** findings can provide a scientific support for the effective mitigation of future debris flows.

关键词： Economic risk Future debris fows Gyirong Zangbo Basin Machine learning model Physical vulnerability matrix Southwest Tibet,China

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Quick and automatic detection of co-seismic landslides with multifeature deep learning model

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Science China Earth Sciences 2024年第7期67卷 2311-2325页

作者： Wenchao HUANGFU Haijun QIU Peng CUI Dongdong YANG Ya LIU Bingzhe TANG Zijing LIU Mohib ULLAH College of Urban and environmental Sciences Northwest UniversityXi'an 710127China institute of mountain hazards and environment Chinese Academy of SciencesChengdu 610041China Shaanxi key laboratory of Earth surface System and environmental Carrying Capacity Northwest UniversityXi'an 710127China institute of Earth surface System and hazards Northwest UniversityXi'an 710127China

Co-seismic landslide detection is essential for post-disaster rescue and risk assessment after an earthquake ***,a variety of ground objects,including roads and bare land,have spectral characteristics similar to those of co-seismic landslides,making it difficult to gather information and assess their impact rapidly and ***,an automatic detection method based on a deep learning model,named ENVINet5,with multiple features(ENVINet5_MF)was proposed to solve this problem and improve the detection accuracy of co-seismic *** ENVINet5_MF method is advantageous for co-seismic landslide detection because it features a landslide gain index(LGI)that effectively eliminates the spectral interference of bare land and *** conducted two experiments using multi-temporal PlanetScope images acquired in Hokkaido,Japan,and Mainling,*** accuracy evaluation and rationality analysis show that ENVINet5_MF performed better than comparative methods and that the co-seismic landslide areas detected by ENVINet5_MF were the most consistent with ground reference *** findings of this study suggest that ENVINet5_MF can provide an efficient and accurate method for coseismic landslide detection to ensure a rapid response to co-seismic landslide disasters.

关键词： Co-seismic landslide Automatic detection Deep learning landslide gain index PlanetScope images

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Frequency and size change of ice–snow avalanches in the central Himalaya:A case from the Annapurna Ⅱ glacier

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Advances in Climate Change Research 2024年第3期15卷 464-475页

作者： Yao LI Yi-Fei CUI Jian-Sheng HAO Zheng-Tao ZHANG Hao WANG Jian GUO Shuo-Fan WANG State key laboratory of Hydroscience and Engineering Department of Hydraulic EngineeringTsinghua UniversityBeijing 100084China key laboratory of Hydrosphere Sciences of the Ministry of Water Resources Beijing 100084China key laboratory of land surface Pattern and Simulation Institute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijing 100101China School of National Safety and Emergency Management Beijing Normal UniversityBeijing 100875China key laboratory of mountain hazards and Earth surface Process Institute of Mountain Hazards and EnvironmentChinese Academy of SciencesChengdu 610041China

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 ***,the complex relationship between iceesnow avalanches and factors such as climate and potential triggers are difficult to understand because of the lack of observational ***,we addressed iceesnow avalanches on the Annapurna Ⅱ glacier in Nepal,Central *** 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 ***,we investigated the impact of climate change and earthquakes on the frequency and size of iceesnow *** 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 *** evolutionary characteristic of ice avalanches is linked to the impact of glacier retreat(reduction in ice material supply)and increased activity under climate *** glacier movement velocity controls the size of iceesnow avalanches and can be set as an indicator for iceesnow avalanche *** 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.

关键词： Iceesnow avalanche Glacier instability Climate change Central Himalaya Remote sensing

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Antecedent snowmelt and orographic precipitation contributions to water supply of Pakistan disastrous floods,2022

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Advances in Climate Change Research 2024年第3期15卷 419-430页

作者： Yan WANG Peng CUI Chen-Di ZHANG Guo-Tao ZHANG Jian-Sheng HAO Xu YUAN Yao-Zhi JIANG Lu WANG key laboratory of land surface Pattern and Simulation Institute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijing 100101China key laboratory of mountain hazards and Earth surface Process Institute of Mountain Hazards and EnvironmentChinese Academy of SciencesChengdu 610299China Polar and Marine Research institute College of Harbor and Coastal EngineeringJimei UniversityXiamen 361021China School of Resources and environment University of Electronic Science and Technology of ChinaChengdu 610054China Hebei Province Tangshan Caofeidian Meteorological Bureau Tangshan 063000China

In 2022,the Pakistan witnessed the hottest spring and wettest summer in *** devastating floods inundated a large portion of Pakistan and caused enormous ***,the primary water source and its contributions to these unprecedented floods remain *** on the reservoir inflow measurements,Multi-Source Weighted-Ensemble Precipitation(MSWEP),the fifth generation ECMWF atmospheric reanalysis(ERA5)products,this study quantified the contributions of monsoon precipitation,antecedent snow-melts,and orographic precipitation enhancement to floods in *** found that the Indus experienced at least four inflow up-rushes,which was mainly supplied by precipitation and snowmelt;In upper Indus,abnormally high temperature continued to influence the whole summer and lead to large amounts of snowmelts which not only was a key water supply to the flood but also provided favorable soil moisture conditions for the latter *** July,the snowmelt has higher contributions than the precipitation to the streamflow of Indus River,with contribution value of more than 60%.Moreover,the snowmelt could still supply 20%-40%water to the lower Indus in July and August;The leading driver of 2022 mega-floods over the southern Pakistan in July and August was dominated by the precipitation,where terrain disturbance induced precipitation account to approximately 33%over the southern *** results help to understand the mechanisms of flood formation,and to better predict future flood risks over complex terrain regions.

关键词： Extreme heavy rainfall Snowmelt Orographic precipitation Floods Pakistan

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Climate-Vegetation Coverage Interactions in the Hengduan mountains Area, Southeastern Tibetan Plateau, and Their Downstream Effects

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Advances in Atmospheric Sciences 2024年第4期41卷 701-716页

作者： Congxi FANG Jinlei CHEN Chaojun OUYANG Lu WANG Changfeng SUN Quan ZHANG Jun WEN key laboratory of mountain hazards and Earth surface processes Institute of Mountain Hazards and EnvironmentChinese Academy of SciencesChengdu 610299China State key laboratory of Cryospheric Science Northwest Institute of Eco-Environment and ResourcesChinese Academy of SciencesLanzhou 730000China College of Urban and environmental Sciences Peking UniversityBeijing 100871China institute of Global environmental Change Xi’an Jiaotong UniversityXi’an 710049China The State key laboratory of Loess and Quaternary Geology Institute of Earth EnvironmentChinese Academy of SciencesXi’an 710061China College of Atmospheric Sciences Chengdu University of Information TechnologyChengdu 610225China

Little is known about the mechanism of climate-vegetation coverage coupled changes in the Tibetan Plateau(TP)region,which is the most climatically sensitive and ecologically fragile region with the highest terrain in the *** study,using multisource datasets(including satellite data and meteorological observations and reanalysis data)revealed the mutual feedback mechanisms between changes in climate(temperature and precipitation)and vegetation coverage in recent decades in the Hengduan mountains Area(HMA)of the southeastern TP and their influences on climate in the downstream region,the Sichuan Basin(SCB).There is mutual facilitation between rising air temperature and increasing vegetation coverage in the HMA,which is most significant during winter,and then during spring,but insignificant during summer and *** temperature significantly enhances local vegetation coverage,and vegetation greening in turn heats the atmosphere via enhancing net heat flux from the surface to the *** atmospheric heating anomaly over the HMA thickens the atmospheric column and increases upper air *** high pressure anomaly disperses downstream via the westerly flow,expands across the SCB,and eventually increases the SCB *** effect lasts from winter to the following spring,which may cause the maximum increasing trend of the SCB temperature and vegetation coverage in *** results are helpful for estimating future trends in climate and eco-environmental variations in the HMA and SCB under warming scenarios,as well as seasonal forecasting based on the connection between the HMA eco-environment and SCB climate.

关键词： Hengduan mountains Area normalized difference vegetation index climate change net heat flux downstream effects

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Unsupervised Color Segmentation with Reconstructed Spatial Weighted Gaussian Mixture Model and Random Color Histogram

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Computers, Materials & Continua 2024年第3期78卷 3323-3348页

作者： Umer Sadiq Khan Zhen Liu Fang Xu Muhib Ullah Khan Lerui Chen Touseef Ahmed Khan Muhammad Kashif Khattak Yuquan Zhang School of Computer and Information Science Hubei Engineering UniversityXiaogan432000China institute for AI Industrial Technology Research Hubei Engineering UniversityXiaogan432000China key Lab of mountain hazards and surface processes Institute of Mountain Hazards and EnvironmentChinese Academy of SciencesChengdu610041China University of Chinese Academy of Sciences Beijing100049China College of Aviation Zhongyuan University of TechnologyZhengzhou451191China Research Center of Digital mountain and Remote Sensing Application Institute of Mountain Hazards and EnvironmentChinese Academy of SciencesChengdu610041China School of Computer Science University of PoonchAzad Jammu Kashmir12350Pakistan School of Computer Science and Information Engineering Hubei UniversityWuhan430062China

Image classification and unsupervised image segmentation can be achieved using the Gaussian mixture *** the Gaussian mixture model enhances the flexibility of image segmentation,it does not reflect spatial information and is sensitive to the segmentation *** this study,we first present an efficient algorithm that incorporates spatial information into the Gaussian mixture model(GMM)without parameter *** proposed model highlights the residual region with considerable information and constructs color ***,we incorporate the content-based color saliency as spatial information in the Gaussian mixture *** segmentation is performed by clustering each pixel into an appropriate component according to the expectation maximization and maximum ***,the random color histogram assigns a unique color to each cluster and creates an attractive color by default for segmentation.A random color histogram serves as an effective tool for data visualization and is instrumental in the creation of generative art,facilitating both analytical and aesthetic *** experiments,we have used the Berkeley segmentation dataset BSDS-500 and Microsoft Research in Cambridge *** the study,the proposed model showcases notable advancements in unsupervised image segmentation,with probabilistic rand index(PRI)values reaching 0.80,BDE scores as low as 12.25 and 12.02,compactness variations at 0.59 and 0.7,and variation of information(VI)reduced to 2.0 and 1.49 for the BSDS-500 and MSRC datasets,respectively,outperforming current leading-edge methods and yielding more precise segmentations.

关键词： Unsupervised segmentation color saliency spatial weighted GMM random color histogram

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Seasonal constraint of dynamic water temperature on riverine dissolved inorganic nitrogen transport in land surface modeling

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Atmospheric and Oceanic Science Letters 2024年第4期17卷 35-40页

作者： Shuang Liu Kaiheng Hu Zhenghui Xie Yan Wang State key laboratory of mountain hazards and Engineering Safety Institute of Mountain Hazards and EnvironmentChinese Academy of SciencesChengduChina State key laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics Institute of Atmospheric PhysicsChinese Academy of SciencesBeijingChina The National key laboratory of Water Disaster Prevention Nanjing Hydraulic Research InstituteNanjingChina

水体温度变化对河流可溶性无机氮(DIN)输送有着强烈控制作用.然而,在全球尺度上河流DIN输送量对水温度变化的响应尚不清楚.因此,本文基于陆面过程模式,耦合河流水温估算和DIN传输方案,设定有,无动态水温情景,对比研究陆面模拟中水温变... 详细信息

水体温度变化对河流可溶性无机氮(DIN)输送有着强烈控制作用.然而,在全球尺度上河流DIN输送量对水温度变化的响应尚不清楚.因此,本文基于陆面过程模式,耦合河流水温估算和DIN传输方案,设定有,无动态水温情景,对比研究陆面模拟中水温变化对河流DIN通量变化的影响.结果表明:在考虑水温动态变化后,在30°N和30°S之间, DIN通量年振幅减小5%–25%.在中国东部地区,水温动态变化使河流DIN通量在夏季减少1%–3%,在冬季增加1%–5%,对DIN通量具有明显的季节性约束作用,表明动态水温的表达在河流DIN输送模拟中的重要性.

关键词：陆面模拟河流氮输送水温变化季节变化全球尺度

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Human disturbance exacerbated erosion and deposition in the karst peak-cluster depressions during the Ming and Qing dynasties

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Science China Earth Sciences 2024年第11期67卷 3550-3561页

作者： Shuai YUAN Yuemin YUE Xinbao ZHANG Lu WANG Lu ZHAI Kelin WANG key laboratory for Agro-Ecological processes in Subtropical Region Institute of Subtropical Agriculture Chinese Academy of Sciences Huanjiang Observation and Research Station for Karst Ecosystems Chinese Academy of Sciences University of Chinese Academy of Sciences institute of mountain hazards and environment Ministry of Water Resources Chinese Academy of Sciences State key laboratory of environmental Geochemistry Institute of Geochemistry Chinese Academy of Sciences

Under the background of large-scale ecological restoration, China's southwestern karst region has become a hotspot of global vegetation cover “greening” in the past 20 years. However, because of geological constraints, it is difficult to restore the forest landscapes in some areas. It is urgent to understand the impacts of human disturbances during the historical period on the difficult-to-forestation rocky-desertification areas of the karst region in order to guide future afforestation. In this study, we quantified the changes of specific sediment yield in typical karst depressions over the past 500 years by using137Cs,210Pb, and14C dating methods in karst depressions, and identified the main human disturbances related to historical erosion and sedimentation by combining with historical data. The results showed that the erosion and sedimentation of the three depressions in 1921–1963 were significantly higher than that in 1963–2021, and the sedimentation rate(0.64–1.33 cm a-1) and the specific sediment yield(2.51–13.11 t ha-1a-1) during Ming and Qing dynasties（1504–1812） were higher than the sedimentation rate(0.26–0.95 cm a-1) and specific sediment yield(0.95–6.99 t ha-1a-1) in the recent century（1921–2021）. Reconstruction data and literature from the Ming and Qing dynasties show an empirical link between changes in population, arable land, food, forest area,and deforestation events during the same period. It was found that the population and arable land in Guangxi increased more than three-fold and the forest area decreased significantly in the 17th century after the migration of the Yao ethnic group and the introduction of maize to the region, which may be the main reason for intensifying the erosion of depressions. This study is of great significance to understanding the evolution history of rocky desertification in this region and to answer the potential of afforestation.

关键词： Karst region 14C dating Peak-cluster depressions Ethnic minirity migration Specific sediment yield

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Regulatory potential of soil available carbon,nitrogen,and functional genes on N_(2)O emissions in two upland plantation systems

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Journal of Integrative Agriculture 2024年第8期23卷 2792-2806页

作者： Peng Xu Mengdie Jiang Imran Khan Muhammad Shaaban Hongtao Wu Barthelemy Harerimana Ronggui Hu key laboratory of mountain surface processes and Ecological Regulation Institute of Mountain Hazards and EnvironmentChinese Academy of SciencesChengdu 610041China College of Resources and environment Huazhong Agricultural UniversityWuhan 430070China Hubei Collaborative Innovation Centre for Grain Industry College of AgricultureYangtze UniversityJingzhou 434025China College of Agriculture Henan University of Science and TechnologyLuoyang 471000China College of Urban and environmental Sciences Hubei Normal UniversityHuangshi 435002China University of Chinese Academy of Sciences Beijing 100049China

Dynamic nitrification and denitrification processes are affected by changes in soil redox conditions,and they play a vital role in regulating soil N_(2)O emissions in rice-based *** is imperative to understand the influences of different upland crop planting systems on soil N_(2)O *** this study,we focused on two representative rotation systems in Central China:rapeseed–rice(RR)and wheat–rice(WR).We examined the biotic and abiotic processes underlying the impacts of these upland plantings on soil N_(2)O *** results revealed that during the rapeseed-cultivated seasons in the RR rotation system,the average N_(2)O emissions were 1.24±0.20 and 0.81±0.11 kg N ha^(–1)for the first and second seasons,*** values were comparable to the N_(2)O emissions observed during the first and second wheat-cultivated seasons in the WR rotation system(0.98±0.25 and 0.70±0.04 kg N ha^(–1),respectively).This suggests that upland cultivation has minimal impacts on soil N_(2)O emissions in the two rotation *** positive correlations were found between N_(2)O fluxes and soil ammonium(NH_(4)^(+)),nitrate(NO_(3)^(–)),microbial biomass nitrogen(MBN),and the ratio of soil dissolved organic carbon(DOC)to NO_(3)^(–)in both RR and WR rotation ***,the presence of the AOA-amoA and nirK genes were positively associated with soil N_(2)O fluxes in the RR and WR systems,*** implies that these genes may have different potential roles in facilitating microbial N_(2)O production in various upland plantation *** using a structural equation model,we found that soil moisture,mineral N,MBN,and the AOA-amoA gene accounted for over 50%of the effects on N_(2)O emissions in the RR rotation *** the WR rotation system,soil moisture,mineral N,MBN,and the AOA-amoA and nirK genes had a combined impact of over 70%on N_(2)O *** findings demonstrate the interactive effects of functional genes and soil factors,including

关键词： upland-rice cultivation N_(2)O emission regulatory factors functional genes

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