scholarly journals Prediction of Precipitation in the Western Mountainous Regions of China Using a Statistical Model

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Yijia Hu ◽  
Yuan Sun ◽  
Yao Ha ◽  
Yimin Zhu ◽  
Zhixian Luo
Keyword(s):  
Statistical Model ◽  
Debris Flows ◽  
Summer Precipitation ◽  
Heavy Rain ◽  
Precipitation Anomaly ◽  
Economic Losses ◽  
Sample Return ◽  
Mountainous Regions ◽  
Landslides And Debris Flows ◽  
Cross Test

During the summer in the western mountainous regions of China (WMR), the disasters such as mountain floods, landslides, and debris flows caused by heavy rain occur frequently, which often result in huge economic losses and many casualties. Therefore, it is of great significance to predict the precipitation accurately in these regions. In this paper, a statistical model is established to predict the precipitation in the WMR using the linear regression statistical method, in which the summer area-averaged precipitation anomaly in WMR is taken as the predictand and the prewinter Niño3 SST is taken as the predictor. The results of the return cross test for the historical years from 1979 to 2008 and independent sample return test from 2009 to 2018 show that this statistical model has a good performance in predicting the summer precipitation in the WMR, especially in the flood years. It has better skill in the prediction of WMR precipitation than the dynamical model SINTEX-F.

Settlement Isolation Susceptibility due to Heavy Rain Caused Road Closure

2013 ◽  
Vol 723 ◽  
pp. 656-663
Author(s):  
Shu Rong Yang
Keyword(s):  
River Basin ◽  
Debris Flows ◽  
Heavy Rain ◽  
Transportation Infrastructure ◽  
Public Administrators ◽  
Typhoon Morakot ◽  
Loss Of Life ◽  
Southern Taiwan ◽  
Road Closure ◽  
Landslides And Debris Flows

On August 9, 2009, Typhoon Morakot struck Taiwan, triggering landslides and debris flows and destroying transportation infrastructure in the southern mountains. Many settlements in this area were isolated due to road closure. Residents were trapped in the settlements and unable to evacuate to safe places. Also, emergency goods were unable to be transported to the settlements. In order to minimize the loss of life and property associated with future typhoon, public administrators should evacuate residents before access routes to settlements are affected.In this study, settlements in Lao-Nong River basin of Southern Taiwan were ranked in accordance to isolation susceptibility. Susceptibility was estimated by overlaying maps of landslides, debris flows, temporary roads and primary mountain road layers. Criteria used to evaluate the isolation susceptibility were developed using an expert-based approach. The isolation susceptibilities of settlements were categorized into 3 levels, namely high, moderate and low.

RESEARCH OF LANDSLIDES AND DEBRIS FLOWS IN BAILONG RIVER BASIN:PROGRSS AND PROSPECT

2013 ◽  
Vol 33 (4) ◽  
pp. 1 ◽  
Author(s):  
Xingmin MENG ◽  
Guan CHEN ◽  
Peng GUO ◽  
Muqi XIONG ◽  
Wasowski Janusz
Keyword(s):  
Debris Flows ◽  
Landslides And Debris Flows

scholarly journals Comparison of length and dynamics of wood pieces in streams covered with coniferous and broadleaf forests mapped using orthophotos acquired by an unmanned aerial vehicle

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Haruka Tsunetaka ◽  
Slim Mtibaa ◽  
Shiho Asano ◽  
Takashi Okamoto ◽  
Ushio Kurokawa
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Debris Flows ◽  
Rain Gauge ◽  
Japan Meteorological Agency ◽  
Landslide Occurrence ◽  
Direct Measurements ◽  
Wood Piece ◽  
Aerial Vehicle ◽  
Main Components ◽  
Landslides And Debris Flows

AbstractAs wood pieces supplied by landslides and debris flows are one of the main components of ecological and geomorphic systems, the importance of quantifying the dimensions of the wood pieces is evident. However, the low accessibility of disturbed channels after debris flows generally impedes accurate and quick wood-piece investigations. Thus, remote-sensing measurements for wood pieces are necessitated. Focusing on sub-watersheds in coniferous and broadleaf forests in Japan (the CF and BF sites, respectively), we measured the lengths of wood pieces supplied by landslides (> 0.2 m length and > 0.03 m diameter) from orthophotos acquired using a small unmanned aerial vehicle (UAV). The measurement accuracy was analyzed by comparing the lengths derived from the UAV method with direct measurements. The landslides at the CF and BF sites were triggered by extremely heavy rainfalls in 2017 and 2018, respectively. UAV flights were operated during February and September 2019 at the CF site and during November 2018 and December 2019 at the BF site. Direct measurements of wood pieces were carried out on the date of the respective second flight date in each site. When both ends of a wood piece are satisfactorily extracted from an orthophoto acquired by the UAV, the wood-piece lengths at the CF site can be measured with an accuracy of approximately ±0.5 m. At the BF site, most of the extracted lengths were shorter than the directly measured lengths, probably because the complex structures of the root wad and tree crown reduced the visibility. Most wood pieces were discharged from landslide scars at the BF site, but at the CF site, approximately 750 wood pieces remained in the landslide scars approximately 19 months after the landslide occurrence. The number of wood pieces in the landslide scars of the CF site increased with increasing landslide area, suggesting that some wood pieces can be left even if large landslides occur. The lengths and locations of the entrapped wood pieces at both sites were not significantly changed between the two UAV flight dates. However, during this period, the rainfall intensities around the CF site measured by the closest rain-gauge of the Japan Meteorological Agency reached their second highest values from 1976 to 2019, which exceeded the 30-year return period. This suggests that most of the entrapped wood pieces rarely migrated even under intense rainfall.

scholarly journals Geohazards Susceptibility Assessment along the Upper Indus Basin Using Four Machine Learning and Statistical Models

2021 ◽  
Vol 10 (5) ◽  
pp. 315
Author(s):  
Hilal Ahmad ◽  
Chen Ningsheng ◽  
Mahfuzur Rahman ◽  
Md Monirul Islam ◽  
Hamid Reza Pourghasemi ◽  
...  
Keyword(s):  
Machine Learning ◽  
Land Cover ◽  
Debris Flows ◽  
Regional Scale ◽  
Indus Basin ◽  
Annual Rainfall ◽  
Slope Aspect ◽  
Topographic Wetness Index ◽  
Susceptibility Maps ◽  
Landslides And Debris Flows

The China–Pakistan Economic Corridor (CPEC) project passes through the Karakoram Highway in northern Pakistan, which is one of the most hazardous regions of the world. The most common hazards in this region are landslides and debris flows, which result in loss of life and severe infrastructure damage every year. This study assessed geohazards (landslides and debris flows) and developed susceptibility maps by considering four standalone machine-learning and statistical approaches, namely, Logistic Regression (LR), Shannon Entropy (SE), Weights-of-Evidence (WoE), and Frequency Ratio (FR) models. To this end, geohazard inventories were prepared using remote sensing techniques with field observations and historical hazard datasets. The spatial relationship of thirteen conditioning factors, namely, slope (degree), distance to faults, geology, elevation, distance to rivers, slope aspect, distance to road, annual mean rainfall, normalized difference vegetation index, profile curvature, stream power index, topographic wetness index, and land cover, with hazard distribution was analyzed. The results showed that faults, slope angles, elevation, lithology, land cover, and mean annual rainfall play a key role in controlling the spatial distribution of geohazards in the study area. The final susceptibility maps were validated against ground truth points and by plotting Area Under the Receiver Operating Characteristic (AUROC) curves. According to the AUROC curves, the success rates of the LR, WoE, FR, and SE models were 85.30%, 76.00, 74.60%, and 71.40%, and their prediction rates were 83.10%, 75.00%, 73.50%, and 70.10%, respectively; these values show higher performance of LR over the other three models. Furthermore, 11.19%, 9.24%, 10.18%, 39.14%, and 30.25% of the areas corresponded to classes of very-high, high, moderate, low, and very-low susceptibility, respectively. The developed geohazard susceptibility map can be used by relevant government officials for the smooth implementation of the CPEC project at the regional scale.

scholarly journals On the water hazards in the trans-boundary Kosi River basin

2013 ◽  
Vol 13 (3) ◽  
pp. 795-808 ◽  
Author(s):  
N. Sh. Chen ◽  
G. Sh. Hu ◽  
W. Deng ◽  
N. Khanal ◽  
Y. H. Zhu ◽  
...  
Keyword(s):  
Debris Flows ◽  
Local Population ◽  
Site Investigation ◽  
Population Increase ◽  
Glacial Lake ◽  
Ganges River ◽  
Landslides And Debris Flows ◽  
Water Hazards ◽  
The Ganges ◽  
Basin Area

Abstract. The Kosi River is an important tributary of the Ganges River, which passes through China, Nepal and India. With a basin area of 71 500 km2, the Kosi River has the largest elevation drop in the world (from 8848 m of Mt Everest to 60 m of the Ganges Plain) and covers a broad spectrum of climate, soil, vegetation and socioeconomic zones. The basin suffers from multiple water related hazards including glacial lake outburst, debris flow, landslides, flooding, drought, soil erosion and sedimentation. This paper describes the characteristics of water hazards in the basin, based on the literature review and site investigation covering hydrology, meteorology, geology, geomorphology and socio-economics. Glacial lake outbursts are a huge threat to the local population in the region and they usually further trigger landslides and debris flows. Floods are usually a result of interaction between man-made hydraulic structures and the natural environment. Debris flows are widespread and occur in clusters. Droughts tend to last over long periods and affect vast areas. Rapid population increase, the decline of ecosystems and climate change could further exacerbate various hazards in the region. The paper has proposed a set of mitigating strategies and measures. It is an arduous challenge to implement them in practice. More investigations are needed to fill in the knowledge gaps.

scholarly journals Empirical atmospheric thresholds for debris flows and flash floods in the southern French Alps

2014 ◽  
Vol 14 (6) ◽  
pp. 1517-1530 ◽  
Author(s):  
T. Turkington ◽  
J. Ettema ◽  
C. J. van Westen ◽  
K. Breinl
Keyword(s):  
Debris Flows ◽  
Warning System ◽  
Flash Floods ◽  
Rain Gauge ◽  
Reanalysis Data ◽  
Specific Humidity ◽  
Atmospheric Conditions ◽  
Convective Rainfall ◽  
French Alps ◽  
Mountainous Regions

Abstract. Debris flows and flash floods are often preceded by intense, convective rainfall. The establishment of reliable rainfall thresholds is an important component for quantitative hazard and risk assessment, and for the development of an early warning system. Traditional empirical thresholds based on peak intensity, duration and antecedent rainfall can be difficult to verify due to the localized character of the rainfall and the absence of weather radar or sufficiently dense rain gauge networks in mountainous regions. However, convective rainfall can be strongly linked to regional atmospheric patterns and profiles. There is potential to employ this in empirical threshold analysis. This work develops a methodology to determine robust thresholds for flash floods and debris flows utilizing regional atmospheric conditions derived from ECMWF ERA-Interim reanalysis data, comparing the results with rain-gauge-derived thresholds. The method includes selecting the appropriate atmospheric indicators, categorizing the potential thresholds, determining and testing the thresholds. The method is tested in the Ubaye Valley in the southern French Alps (548 km2), which is known to have localized convection triggered debris flows and flash floods. This paper shows that instability of the atmosphere and specific humidity at 700 hPa are the most important atmospheric indicators for debris flows and flash floods in the study area. Furthermore, this paper demonstrates that atmospheric reanalysis data are an important asset, and could replace rainfall measurements in empirical exceedance thresholds for debris flows and flash floods.

scholarly journals Effects of Air Pollutants on Summer Precipitation in Different Regions of Beijing

Atmosphere ◽  
2022 ◽  
Vol 13 (1) ◽  
pp. 141
Author(s):  
Yan Yang ◽  
Wei Zhou ◽  
Qian Gao ◽  
Delong Zhao ◽  
Xiange Liu ◽  
...  
Keyword(s):  
Air Pollutants ◽  
Summer Precipitation ◽  
Weather Research And Forecasting ◽  
Mountainous Areas ◽  
Cloud Droplets ◽  
Beijing Area ◽  
Pollution Levels ◽  
Mountainous Regions ◽  
Effective Particle ◽  
Air Layers

Many studies have shown that air pollutants have complex impacts on urban precipitation. Meteorological weather station and satellite Aerosol Optical Depth (AOD) product data from the last 20 years, combined with simulation results from the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem), this paper focuses on the effects of air pollutants on summer precipitation in different regions of Beijing. These results showed that air pollution intensity during the summer affected the precipitation contribution rate (PCR) of plains and mountainous regions in the Beijing area, especially in the plains. Over the past 20 years, plains PCR increased by ~10% when the AOD augmented by 0.15, whereas it decreased with lower pollution levels. In contrast, PCR in mountainous areas decreased with higher pollution levels and increased with lower pollution levels. Our analysis from model results indicated that aerosol increases reduce the effective particle size of cloud droplets and raindrops. Smaller cloud raindrops more readily transport to high air layers and participate in the generation of ice-phase substances in the clouds, increasing the total amount of cloud water in the air in a certain time, which ultimately enhanced precipitation intensity on the plains. The removal of pollutants caused by increased precipitation in the plains decreased rainfall levels in mountainous areas.

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