Climatic Features Related to Eastern China Summer Rainfalls in the NCAR CCM3

The climatic features associated with the eastern China summer rainfalls (ECSR) are examined in the National Center for Atmospheric Research (NCAR) Community Climate Model Version 3 (CCM3) of the United States of America, and run with time-evolving sea surface temperature (SST) from September 1978 to August 1993. The CCM3 is shown to capture the salient seasonal features of ECSR. As many other climate models, however, there are some unrealistic projections of ECSR in the CCM3. The most unacceptable one is the erroneously intensified precipitation center on the east periphery of the Tibetan Plateau and its northeastward extension. The artificial strong rainfall center is fairly assessed by comparing with the products of the station rainfall data, Xie and Arkin (1996) rainfall data and the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis (Gibson et al., 1997). The physical processes involved in the formation of the rainfall center are discussed. The preliminary conclusion reveals that it is the overestimated sensible heating over and around the Tibetan Plateau in the CCM3 that causes the heavy rainfall. The unreal strong surface sensible heating over the southeast and northeast of Tibetan Plateau favors the forming of a powerful subtropical anticyclone over the eastern China. The fake enclosed subtropical anticyclone center makes the moist southwest wind fasten on the east periphery of the Tibetan Plateau and extend to its northeast. In the southeast coast of China, locating on the southeast side of the subtropical anticyclone, the southwest monsoon is decreased and even replaced by northeast wind in some cases. In the CCM3, therefore, the precipitation is exaggerated on the east periphery of the Tibetan Plateau and its northeast extension and is underestimated in the southeast coast of China. Key words Eastern China summer rainfall - Model validation - Subtropical anticyclone - Diabatic heating This study was sponsored by Chinese Academy of Sciences under grant “ Hundred Talents” for “ Validation of Coupled Climate models” and the National Natural Science Foundation of China (Grant No.49823002), and IAP innovation fund (No. 8-1204).

Variation Diagnosis and Regional Comparison of Different Intensity of Rainfalls and Their Contribution to Total Rainfall in China in the Context of Global Warming

Using the data of 545 meteorological stations in 1961-2015,according to the rainfall intensity classification standard issued by the China Meteorological Administration,the rainfall events were divided into six intensities: light rain,moderate rain,heavy rain,torrential rain,downpour and heavy downpour. The latter three were recorded as total torrential rain,and all the six were recorded as the total rainfall. In terms of the interannual rainfall and rainy days,the whole China was regarded as an object. Firstly,the annual rainfall and rainy day of different intensity of rainfalls of 545 stations in 1961-2015 were calculated. Then,the variation trend of rainfall and rainy days was calculated. Finally,the variation trend of contribution of different intensity of rainfalls and rainy days to total rainfall and rainy days were diagnosed. It obtained the following results.( i) The light rain in China was declining from 1961 to 2015,and the trend values of light rain and rainy days were-411. 44 mm/yr and-136. 99 d/yr,respectively. Heavy rain and total heavy rainfall showed an increasing trend,with rainfall and rainy day trends of 127. 02 and 463. 94 mm/yr and 7. 93 and 4. 24 d/yr,respectively. The total rainfall showed a ' hockey' phenomenon of ' first rise,then decline',and the trend values of rainfall and rainy days were 204. 29 mm/yr and-95. 81 d/yr,respectively. Except the northern region,the rainfall in most parts of China was dominated by increasing trends and was moving towards extremes.( ii) In terms of rainfall contribution rate,the contribution of light rain to total rainfall showed a declining trend,and the trend values of rainfall and rainy day contribution were both-0. 11%/yr. The contribution of other intensity rainfalls to total rainfall showed an increasing trend. The contribution of torrential rain to the total torrential rain showed a declining trend. The contribution trends of rainfall and rainy days were-0. 06% and-0. 03%/yr,respectively. The contribution of downpour and heavy downpour to total torrential rain showed an increasing trend,indicating the intensity of torrential rain in China is increasing. Although the contribution rate of different intensity of rainfalls to total rainfall was different in different areas of China,the contribution rate of heavy rainfall to total rainfall in most areas showed an increasing trend.( iii) Through comparing the rainfall and rainy days of six different intensity of rainfalls,it can be found that China’s heavy rainfall events are increasing and the rainfall intensity is developing towards extremes.

Natural hazards in Romania induced by heavy rainfalls in 1996-1997

Romania is one of the European countries most frequently affected by natural hazards due to its position within the alpine orogenic system and against the main atmospheric pressure centres.Hence the impact of exogenous factors that trigger strong earthquakes with several epicentres, and of exogenous or climate-driven factors with extreme climatic phenomena causing frequent floods, mass movements, soil erosion, droughts, hailstorms and strong winds. This paper deals mainly with natural disasters cased by the variability of climatic conditions (mostly by precipitations) in the years 1996 and 1997, their temporal and spatial distributions and the way they affected human life. In point of rainfall distribution and the ensuing natural hazards, the mentioned period shows two distinct intervals: December, 1996-March 1997 (mass movements) and June-August, 1997 (floods, hailstorm,Strong wind,landslides, soil erosion).

The statistical prediction of East African rainfalls using quasi-biennial oscillation phases information

A simple correlation method and a quasi-biennial oscillation (QBO)/rainfall composite analysis were used to examine the teleconnections be-tween the seasonal rainfall anomalies of March through May (long-rains) over East Africa and the different QBO phases in the stratospheric zonal winds, and also explore the predictive potential of the long rainy season using infor-mation about the phases of the QBO for the pe-riod 1979-2003. We study the spatial correlation patterns statistically to understand the climatic associations between the equatorial strato-spheric zonal wind and regional rainfall at the interannual time scale. The aim of this analysis is to establish whether this global signal can be employed as predictor variable in the long-range forecasts. Principal component analysis (PCA) is employed in the first instance to reduce the large dimensionality of the predictant (monthly rainfall data), to retain the time series of the principal components (PCs) and to delineate the rain gauge network of East Africa into homo-geneous zones. Spatial patterns of the factor loading were used to delineate East Africa into 11 homogeneous zones.

Comparative Analysis on Physical Quantity Diagnosis and Wind Profile Radar Data of Two Heavy Rainfalls

[ Objective] The research aimed to contrast physical quantity diagnosis and wind profile radar data of two heavy rainfalls. [ Method ] From circulation background, physical quantity field and wind profile radar data, we analyzed two big rainstorm weather processes （8 -9 July and August 10） in Lianyungang City in 2012. [ Result] Rainstorm generation was related to favorable large-scale circulation situation. The first-stage precipitation during 8 -9 July was warm-zone precipitation, and the precipitation at the second stage was triggered by shear line. Precipitation on August 10 was generated by typhoon low-pressure inverted trough and cold air. Sufficient water vapor content and strong water vapor transportation were favorable for generation of the heavy precipitation. Suction effect by divergence at high layer and convergence at middle and low layers was favorable for maintenance of the strong ascending motion. Occurrence of the heavy precipitation must have ascending motion condition. But it was not that the stronger the ascending motion, the stronger the rainfall intensity. Kindex and θse500 -θse 850 were closely related to rainstorm occurrence. Horizontal wind data of the wind profile radar provided fine structure of the atmospheric horizontal motion at vertical direction, could clearly display vertical structure of the wind field in rainstorm process, and directly reflected change characteristics of the wind field in precipitation process. [ Conclusion] The research could provide reference for future forecast work.

Trend and Return Level Analysis of Extreme Rainfalls in Senegal

In recent years, Senegal has been confronted with increasingly frequent and damaging extreme events. In the context of climate change, we conducted this study to characterize the trends of rainfall extremes in Senegal. In this work, we used daily rainfall data from 27 stations in Senegal from the period 1951 to 2005 (55 years). To study their linear trends, non-stationary extreme value models with time as a covariate are fitted to evaluate them. Our results indicate a decreasing trend of extreme rainfalls at most of the stations except for 5 stations. However, the decreasing trends are only significant for two stations (Thiès and Kidira), however, this can only be taken as information that climate change may have already impacted extreme rainfalls. For the 20-year and 30-year return periods, the results show that they have undergone changes, in fact for almost all stations, the trends in return periods are decreasing.

Genetic Mechanism of Water-Rich Landslide Considering Antecedent Rainfalls:A Case Study of Pingyikou Landslide in Three Gorges Reservoir Area

Water-rich slope,which could easily fail after prolonged or heavy rain,is very sensitive to rainfall.Pingyikou Landslide is a typical water-rich slope located in the Three Gorges Reservoir area of China.It was unstable because of the continuous rainfall that occurred from September to October 2017.To understand the deformation process and genetic mechanism of the landslide,the geomorphological features,geological characteristics,hydrological conditions,and rainfall characteristics were systematically studied by a detailed field investigation of the slope and monitoring of rainfall,water level,and displacement.In addition,the influence of different initial conditions on the stability of the slope was also studied through numerical simulation using measured rainfall data on the basis of which,the effect of antecedent rainfall on slope stability was studied by unsaturated seepage analysis method.The results show that the deformation of slope is strongly correlated with the rainfall and groundwater level,and this landslide is a typical rainfall-induced landslide.In the analysis of genetic mechanism of the same type of landslide,a maximum initial pore water pressure of -25 kPa as the initial condition is reasonable.And the antecedent rainfall has a greater effect on the stability of the slope,more than 10 days of antecedent rainfall should be considered when designing and controling the slope.

Evaluation of rainfall threshold models for debris flow initiation in the Jiangjia Gully,Yunnan Province,China

Systematically determining the discriminatory power of various rainfall properties and their combinations in identifying debris flow occurrence is crucial for early warning systems.In this study,we evaluated the discriminatory power of different univariate and multivariate rainfall threshold models in identifying triggering conditions of debris flow in the Jiangjia Gully,Yunnan Province,China.The univariate models used single rainfall properties as indicators,including total rainfall(R_(tot)),rainfall duration(D),mean intensity(I_(mean)),absolute energy(Eabs),storm kinetic energy(E_(s)),antecedent rainfall(R_(a)),and maximum rainfall intensity over various durations(I_(max_dur)).The evaluation reveals that the I_(max_dur)and Eabs models have the best performance,followed by the E_(s),R_(tot),and I_(mean)models,while the D and R_(a)models have poor performances.Specifically,the I_(max_dur)model has the highest performance metrics at a 40-min duration.We used logistic regression to combine at least two rainfall properties to establish multivariate threshold models.The results show that adding D or R_(a)to the models dominated by Eabs,E_(s),R_(tot),or I_(mean)generally improve their performances,specifically when D is combined with I_(mean)or when R_(a)is combined with Eabs or E_(s).Including R_(a)in the I_(max_dur)model,it performs better than the univariate I_(max_dur)model.A power-law relationship between I_(max_dur)and R_(a)or between Eabs and R_(a)has better performance than the traditional I_(mean)–D model,while the performance of the E_(s)–R_(a)model is moderate.Our evaluation reemphasizes the important role of the maximum intensity over short durations in debris flow occurrence.It also highlights the importance of systematically investigating the role of R_(a)in establishing rainfall thresholds for triggering debris flow.Given the regional variations in rainfall patterns worldwide,it is necessary to evaluate the findings of this study across diverse watersheds.

Analysis of the effect of the 2021 Semeru eruption on water vapor content and atmospheric particles using GNSS and remote sensing

Mount Semeru,an active volcano in East Java,Indonesia,erupted on December 4,2021,following extreme rainfall that caused an avalanche of hot pyroclastic flows and lava.The tropospheric conditions and dominant particle components in the atmosphere can be monitored using Global Navigation Satellite System(GNSS)technology and remote sensing satellites.GNSS signal propagation delay in Precise Point Positioning(PPP)processing can be used to determine Zenith Tropospheric Delay(ZTD)and Precipitable Water Vapor(PWV)variables so that atmospheric conditions can be generated.In addition,by using remote sensing satellite data,it is possible to obtain rainfall data with high temporal resolution as well as the dominant particle and gas content values during eruptions.During the eruption period,the high value of PWV was dominated by the high intensity of precipitation during the rainy season.High rainfall before the eruption caused activity inside the mountain to increase,which occurred in avalanche type eruption.Apart from that,the atmosphere around Semeru was also dominated by SO_(2)content,which spreaded for tens of kilometers.SO_(2)content began to be detected significantly by remote sensing sensors on December 7,2021.In this study,deformation and atmospheric monitoring were also carried out using low-cost GNSS at the Semeru Monitoring Station on September 9-15,2022.The results of the ZTD and ZWD values show the dominance of the wet component,which is directly proportional to rainfall activity in this period.

Spatiotemporal Characteristics of Rainfall over Different Terrain Features in the Middle Reaches of the Yangtze River Basin during the Warm Seasons of 2016–20

Based on hourly rain gauge data during May–September of 2016–20,we analyze the spatiotemporal distributions of total rainfall(TR)and short-duration heavy rainfall(SDHR;hourly rainfall≥20 mm)and their diurnal variations over the middle reaches of the Yangtze River basin.For all three types of terrain(i.e.,mountain,foothill,and plain),the amount of TR and SDHR both maximize in June/July,and the contribution of SDHR to TR(CST)peaks in August(amount:23%;frequency:1.74%).Foothill rainfall is characterized by a high TR amount and a high CST(in amount);mountain rainfall is characterized by a high TR frequency but a small CST(in amount);and plain rainfall shows a low TR amount and frequency,but a high CST(in amount).Overall,stations with high TR(amount and frequency)are mainly located over the mountains and in the foothills,while those with high SDHR(amount and frequency)are mainly concentrated in the foothills and plains close to mountainous areas.For all three types of terrain,the diurnal variations of both TR and SDHR exhibit a double peak(weak early morning and strong late afternoon)and a phase shift from the early-morning peak to the late-afternoon peak from May to August.Around the late-afternoon peak,the amount of TR and SDHR in the foothills is larger than over the mountains and plains.The TR intensity in the foothills increases significantly from midnight to afternoon,suggesting that thermal instability may play an important role in this process.

Local Torrential Rainfall Event within a Mei-Yu Season Mesoscale Convective System:Importance of Back-Building Processes

An extreme rainfall event occurred over Hangzhou,China,during the afternoon hours on 24 June 2013.This event occurred under suitable synoptic conditions and the maximum 4-h cumulative rainfall amount was over 150 mm.This rainfall event had two major rainbands.One was caused by a quasi-stationary convective line,and the other by a backbuilding convective line related to the interaction of the outflow boundary from the first rainband and an existing low-level mesoscale convergence line associated with a mei-yu frontal system.The rainfall event lasted 4 h,while the back-building process occurred in 2 h when the extreme rainfall center formed.So far,few studies have examined the back-building processes in the mei-yu season that are caused by the interaction of a mesoscale convergence line and a convective cold pool.The two rainbands are successfully reproduced by the Weather Research and Forecasting(WRF)model with fourlevel,two-way interactive nesting.In the model,new cells repeatedly occur at the west side of older cells,and the backbuilding process occurs in an environment with large CAPE,a low LFC,and plenty of water vapor.Outflows from older cells enhance the low-level convergence that forces new cells.High precipitation efficiency of the back-building training cells leads to accumulated precipitation of over 150 mm.Sensitivity experiments without evaporation of rainwater show that the convective cold pool plays an important role in the organization of the back-building process in the current extreme precipitation case.

黄河流域生态保护迈向高质量发展的特征——植被绿度、生产力和降水利用效率的差异性变化

Globally,vegetation has been changing dramatically.The vegetation-water dynamic is key to understanding ecosystem structure and functioning in water-limited ecosystems.Continual satellite monitoring has detected global vegetation greening.However,a vegetation greenness increase does not mean that ecosystem functions increase.The intricate interplays resulting from the relationships between vegetation and precipitation must be more adequately comprehended.In this study,satellite data,for example,leaf area index(LAI),net primary production(NPP),and rainfall use efficiency(RUE),were used to quantify vegetation dynamics and their relationship with rainfall in different reaches of the Yellow River Basin(YRB).A sequential regression method was used to detect trends of NPP sensitivity to rainfall.The results showed that 34.53%of the YRB exhibited a significant greening trend since 2000.Among them,20.54%,53.37%,and 16.73%of upper,middle,and lower reach areas showed a significant positive trend,respectively.NPP showed a similar trend to LAI in the YRB upper,middle,and lower reaches.A notable difference was noted in the distributions and trends of RUE across the upper,middle,and lower reaches.Moreover,there were significant trends in vegetation-rainfall sensitivity in 16.86%of the YRB’s middle reaches—14.08%showed negative trends and 2.78%positive trends.A total of 8.41%of the YRB exhibited a marked increase in LAI,NPP,and RUE.Subsequently,strategic locations reliant on the correlation between vegetation and rainfall were identified and designated for restoration planning purposes to propose future ecological restoration efforts.Our analysis indicates that the middle reach of the YRB exhibited the most significant variation in vegetation greenness and productivity.The present study underscores the significance of examining the correlation between vegetation and rainfall within the context of the high-quality development strategy of the YRB.The outcomes of our analysis and the proposed ecological restoration framework can provide decision-makers with valuable insights for executing rational basin pattern optimization and sustainable management.

Spatial distribution of shallow landslides caused by Typhoon Lekima in 2019 in Zhejiang Province, China

In recent years, the coastal region of Southeast China has witnessed a significant increase in the frequency and intensity of extreme rainfall events associated with landfalling typhoons. The hilly and mountainous terrain of this area, combined with rapid rainfall accumulation, has led to a surge in flash floods and severe geological hazards. On August 10, 2019, Typhoon Lekima made landfall in Zhejiang Province, China, and its torrential rainfall triggered extensive landslides, resulting in substantial damage and economic losses. Utilizing high-resolution satellite images, we compiled a landslide inventory of the affected area, which comprises a total of 2,774 rainfallinduced landslides over an area of 2965 km2. The majority of these landslides were small to mediumsized and exhibited elongated, clustered patterns. Some landslides displayed characteristics of high-level initiation, obstructing or partially blocking rivers, leading to the formation of debris dams. We used the inventory to analyze the distribution pattern of the landslides and their relationship with topographical, geological, and hydrological factors. The results showed that landslide abundance was closely related to elevation, slope angle, faults, and road density. The landslides were predominantly located in hilly and low mountainous areas, with elevations ranging from 150 to 300 m, slopes of 20 to 30 degrees, and a NE-SE aspect. Notably, we observed the highest Landslide Number Density(LND) and Landslide Area Percentage(LAP) in the rhyolite region. Landslides were concentrated within approximately 4 km on either side of fault zones, with their size and frequency negatively correlated with distances to faults, roads, and river systems. Furthermore, under the influence of typhoons, regions with denser vegetation cover exhibited higher landslide density, reaching maximum values in shrubland areas. In areas experiencing significantly increased concentrated rainfall, landslide density also showed a corresponding rise. In terms of spatial distribution, the rainfall-triggered landslides primarily occurred in the northeastern part of the study area, particularly in regions characterized by complex topography such as Shanzao Village in Yantan Town, Xixia Township, and Shangzhang Township. The research findings offer crucial data on the rainfallinduced landslides triggered by Typhoon Lekima, shedding light on their spatial distribution patterns. These findings provide valuable references for mitigating risks and planning reconstruction in typhoon-affected area.

Performance evaluation of laterite soil embankment stabilized with bottom ash,coir fiber,and lime

In tropical regions,heavy rainfall induces erosion and shallow landslides on road embankments.Cement-based stabilization methods,common in these regions,contribute to climate change due to their high carbon footprint.This study explored the potential application of coir fiber-reinforced laterite soil-bottom ash mixtures as embankment materials in the tropics.The objective is to enhance engineered embankment slopes'erosion resistance and stability while offering reuse options for industrial byproducts.This study examined various mix designs for unconfined compressive strength(UCS)and permeability,utilizing 30%bottom ash(BA)and 1%coir fiber(CF)with varying sizes ranging from 10 to 40 mm,6%lime,and laterite soil(LS),followed by microstructural analyses.The results demonstrate that the compressive strength increases as the CF length increases to 25 mm.In contrast,permeability increases continuously with increasing CF length.Lime-treated mixtures exhibit superior short-and long-term strength and reduce permeability owing to the formation of cementitious materials,as confirmed by microstructural analyses.A lab-scale slope box was constructed to evaluate the surface erosion of the stabilized laterite soil embankment.Based on the rainfall simulation results,the LS-BA-CF mixtures show better resistance to erosion and deformation compared to untreated LS,especially when lime is added to the top layer.This study provides insights into a sustainable and cost-effective approach for slope stabilization using BA and CF,offering a promising solution for tropical regions susceptible to surface erosion and landslides.

Determination of the critical rainfall of runoff-initiated debris flows by the perspective of physical mechanics and Shields stress

The critical rainfall of runoff-initiated debris flows is utmost importance for local early hazard forecasting.This paper presents research on the critical rainfall of runoff-initiated debris flows through comparisons between slope gradients and three key factors,including topographic contributing area,dimensionless discharge,and Shields stress.The rainfall amount was estimated by utilizing in-situ rainfall records and a slope-dependent Shields stress model was created.The created model can predict critical Shields stress more accurately than the other two models.Furthermore,a new dimensionless discharge equation was proposed based on the corresponding discharge-gradient datasets.The new equation,along with factors such as contributing area above bed failure sites,channel width,and mean diameter of debris flow deposits,predicts a smaller rainfall amount than the in-situ measured records.Although the slope-dependent Shields stress model performs well and the estimated rainfall amount is lower than the in-situ records,the sediment initiation in the experiments falls within sheet flow regime due to a large Shields stress.Therefore,further sediment initiation experiments at a steeper slope range are expected in the future to ensure that the sediment transport belongs to mass failure regime characterized by a low level of Shields stress.Finally,a more accurate hazard forecast on the runoff-initiated debris flow holds promise when the corresponding critical slope-dependent dimensionless discharge of no motion,fluvial sediment transport,mass flow regime,and sheet flow regime are considered.

Identification and distribution of 13003 landslides in the northwest margin of Qinghai-Tibet Plateau based on human-computer interaction remote sensing interpretation

The periphery of the Qinghai-Tibet Plateau is renowned for its susceptibility to landslides.However,the northwestern margin of this region,characterised by limited human activities and challenging transportation,remains insufficiently explored concerning landslide occurrence and dispersion.With the planning and construction of the Xinjiang-Tibet Railway,a comprehensive investigation into disastrous landslides in this area is essential for effective disaster preparedness and mitigation strategies.By using the human-computer interaction interpretation approach,the authors established a landslide database encompassing 13003 landslides,collectively spanning an area of 3351.24 km^(2)(36°N-40°N,73°E-78°E).The database incorporates diverse topographical and environmental parameters,including regional elevation,slope angle,slope aspect,distance to faults,distance to roads,distance to rivers,annual precipitation,and stratum.The statistical characteristics of number and area of landslides,landslide number density(LND),and landslide area percentage(LAP)are analyzed.The authors found that a predominant concentration of landslide origins within high slope angle regions,with the highest incidence observed in intervals characterised by average slopes of 20°to 30°,maximum slope angle above 80°,along with orientations towards the north(N),northeast(NE),and southwest(SW).Additionally,elevations above 4.5 km,distance to rivers below 1 km,rainfall between 20-30 mm and 30-40 mm emerge as particularly susceptible to landslide development.The study area’s geological composition primarily comprises Mesozoic and Upper Paleozoic outcrops.Both fault and human engineering activities have different degrees of influence on landslide development.Furthermore,the significance of the landslide database,the relationship between landslide distribution and environmental factors,and the geometric and morphological characteristics of landslides are discussed.The landslide H/L ratios in the study area are mainly concentrated between 0.4 and 0.64.It means the landslides mobility in the region is relatively low,and the authors speculate that landslides in this region more possibly triggered by earthquakes or located in meizoseismal area.

Stability analysis of loose accumulation slopes under rainfall:case study of a high‑speed railway in Southwest China

The high and steep slopes along a high-speed railway in the mountainous area of Southwest China are mostly composed of loose accumulations of debris with large internal pores and poor stability,which can easily induce adverse geological disasters under rainfall conditions.To ensure the smooth construction of the high-speed railway and the subsequent safe operation,it is necessary to master the stability evolution process of the loose accumulation slope under rainfall.This article simulates rainfall using the finite element analysis software’s hydromechanical coupling module.The slope stability under various rainfall situations is calculated and analysed based on the strength reduction method.To validate the simulation results,a field monitoring system is established to study the deformation characteristics of the slope under rainfall.The results show that rainfall duration is the key factor affecting slope stability.Given a constant amount of rainfall,the stability of the slope decreases with increasing duration of rainfall.Moreover,when the amount and duration of rainfall are constant,continuous rainfall has a greater impact on slope stability than intermittent rainfall.The setting of the field retaining structures has a significant role in improving slope stability.The field monitoring data show that the slope is in the initial deformation stage and has good stability,which verifies the rationality of the numerical simulation method.The research results can provide some references for understanding the influence of rainfall on the stability of loose accumulation slopes along high-speed railways and establishing a monitoring system.

Automated machine learning for rainfall-induced landslide hazard mapping in Luhe County of Guangdong Province,China

Landslide hazard mapping is essential for regional landslide hazard management.The main objective of this study is to construct a rainfall-induced landslide hazard map of Luhe County,China based on an automated machine learning framework(AutoGluon).A total of 2241 landslides were identified from satellite images before and after the rainfall event,and 10 impact factors including elevation,slope,aspect,normalized difference vegetation index(NDVI),topographic wetness index(TWI),lithology,land cover,distance to roads,distance to rivers,and rainfall were selected as indicators.The WeightedEnsemble model,which is an ensemble of 13 basic machine learning models weighted together,was used to output the landslide hazard assessment results.The results indicate that landslides mainly occurred in the central part of the study area,especially in Hetian and Shanghu.Totally 102.44 s were spent to train all the models,and the ensemble model WeightedEnsemble has an Area Under the Curve(AUC)value of92.36%in the test set.In addition,14.95%of the study area was determined to be at very high hazard,with a landslide density of 12.02 per square kilometer.This study serves as a significant reference for the prevention and mitigation of geological hazards and land use planning in Luhe County.

Unstable evolution of railway slope under the rainfall-vibration joint action

Understanding the unstable evolution of railway slopes is the premise for preventing slope failure and ensuring the safe operation of trains.However,as two major factors affecting the stability of railway slopes,few scholars have explored the unstable evolution of railway slopes under the joint action of rainfall-vibration.Based on the model test of sandy soil slope,the unstable evolution process of slope under locomotive vibration,rainfall,and rainfall-vibration joint action conditions was simulated in this paper.By comparing and analyzing the variation trends of soil pressure and water content of slope under these conditions,the change laws of pore pressure under the influence of vibration and rainfall were explored.The main control factors affecting the stability of slope structure under the joint action conditions were further defined.Combined with the slope failure phenomena under these three conditions,the causes of slope instability resulting from each leading factor were clarified.Finally,according to the above conclusions,the unstable evolution of the slope under the rainfall-vibration joint action was determined.The test results show that the unstable evolution process of sandy soil slope,under the rainfall-vibration joint action,can be divided into:rainfall erosion cracking,vibration promotion penetrating,and slope instability sliding three stages.In the process of slope unstable evolution,rainfall and vibration play the roles of inducing and promoting slide respectively.In addition,the deep cracks,which are the premise for the formation of the sliding surface,and the violent irregular fluctuation of soil pressure,which reflects the near penetration of the sliding surface,constitute the instability characteristics of the railway slope together.This paper reveals the unstable evolution of sandy soil slopes under the joint action of rainfall-vibration,hoping to provide the theoretical basis for the early warning and prevention technology of railway slopes.

Extensive identification of landslide boundaries using remote sensing images and deep learning method

The frequent occurrence of extreme weather events has rendered numerous landslides to a global natural disaster issue.It is crucial to rapidly and accurately determine the boundaries of landslides for geohazards evaluation and emergency response.Therefore,the Skip Connection DeepLab neural network(SCDnn),a deep learning model based on 770 optical remote sensing images of landslide,is proposed to improve the accuracy of landslide boundary detection.The SCDnn model is optimized for the over-segmentation issue which occurs in conventional deep learning models when there is a significant degree of similarity between topographical geomorphic features.SCDnn exhibits notable improvements in landslide feature extraction and semantic segmentation by combining an enhanced Atrous Spatial Pyramid Convolutional Block(ASPC)with a coding structure that reduces model complexity.The experimental results demonstrate that SCDnn can identify landslide boundaries in 119 images with MIoU values between 0.8and 0.9;while 52 images with MIoU values exceeding 0.9,which exceeds the identification accuracy of existing techniques.This work can offer a novel technique for the automatic extensive identification of landslide boundaries in remote sensing images in addition to establishing the groundwork for future inve stigations and applications in related domains.