Natural Hazards In China Research Articles

Measuring social vulnerability to natural hazards in China: a modified index approach

Measuring social vulnerability to natural hazards in China: a modified index approach

Spatial and temporal changes of social vulnerability of cities to natural hazards in Zhejiang province, China

Understanding how social dynamics interact with natural hazards is one of the main challenges at global and local scales in the world for studying social vulnerability to natural hazards. In this study, we explore the spatial and temporal changes of social vulnerability of cities in Zhejiang province to natural hazards in China for the last decade. Based on the Zhejiang province's census data and the demographics and socioeconomic data during the period from 2009 to 2018, we have characterized social vulnerability through the Social Vulnerability Index (SoVI) for 11 cities throughout the province during 2009–2018 and examined spatial changes in social vulnerability using equal interval method. The results indicated that although the comprehensive vulnerability of Zhejiang province shows a declining trend at a county level, the social vulnerability of different city at the provincial level has obvious differences.

Influencing Mechanism of Tidal Disasters on Locust Breeding Area Evolution in the Eastern Coastal Area of China during the Ming and Qing Dynasties

Locust plagues and tidal disasters are primary natural hazards in China’s eastern coastal regions, yet their interrelationship remains unclear. This study, drawing on historical documents from the Ming and Qing dynasties (1368–1911 AD), focuses on Zhejiang Province and its Hangzhou Bay coastline, areas typically affected by tidal disasters. Employing advanced quantitative analysis and spatiotemporal models, the research aims to reveal the mechanisms behind tidal disasters and their impact on locust population dynamics. The findings indicate a limited spatiotemporal correlation between locust plagues and tidal or drought disasters but a significant association with flooding. The relationship between locust infestations and floods is notably strong in the unique geographical context of Hangzhou Bay’s northern shore. The ‘hydromarginal’ nature of the north coast creates an ideal habitat for locusts. This study pioneers in identifying flooding as a crucial mediator between tidal disasters and locust plagues, shedding light on the ‘typhoon-tidal-flood-locust’ disaster sequence and offering new insights into understanding and mitigating natural disasters in the region. In this study, we primarily employ a quantitative methodology, utilizing advanced data analysis and sophisticated spatiotemporal modeling to investigate the interplay between locust plagues and tidal disasters. Although some progress has been made in the study of historical natural disasters, systematic studies of the relationship between tidal floods and locust breeding sites along the east coast of China during the Ming and Qing dynasties are still scarce. This study fills this gap by employing advanced GIS and time series analysis techniques, combining traditional historical documentary studies with modern scientific methods and providing a new methodological approach to the analysis of historical disaster patterns.

Parameterized Tropical Cyclone Precipitation Model for Catastrophe Risk Assessment in China

Abstract Inland flooding and mudslides from tropical cyclone (TC) rainstorms are among the most destructive natural hazards in China, resulting in considerable direct economic losses and large numbers of fatalities. In this paper, a TC precipitation model (TCPM) is improved by incorporating the effects of complex terrain through a set of new parameters (e.g., slope, roughness, and attenuation distance) for a more accurate assessment of TC rainfall hazards in China. Moreover, by introducing parameterized spiral rainbands, the model could more accurately capture the intensity of extreme precipitation. The model comprehensively considers dynamic and thermodynamic precipitation factors and is adept at capturing the climate characteristics of TC precipitation and the probability distribution of extreme TC precipitation in China. The model is verified by providing two comparisons. One is analysis including detailed results of three typical TC cases, and the other uses empirical cumulative distribution functions for extreme observations and simulations of historical landfalling TCs in China during the period 1960–2018. The comparisons reveal that the TCPM shows impressive performance for strong TCs with heavy precipitation within 200–300 km of the TC center. Moreover, both the modeled extreme hourly and total TC precipitation probability distributions are consistent with the observations. However, the model needs to be further improved for TCs with dispersive or long-distance precipitation. Significance Statement In this paper, an optimized and physics-based model for the simulation of tropical cyclone precipitation is described and used to estimate the risk of TC rainfall hazards in China. The work is innovative in that it considers the effect of complex terrain from three perspectives, including slope, roughness, and attenuation distance. The simulations demonstrated that the model is adept at capturing the main climate characteristics of TC precipitation and the probability distribution of extreme TC precipitation in China, which is simple to run several hundred thousand times, with bright application prospects in catastrophe risk assessment.

Advances in flash flood research based on dendrogeomorpholog

Flash flood is one of the major natural hazards in China. It seriously threatens the lives of people and property in mountainous areas. Various methods have been developed for flash flood study, but most of them focused on the past few decades. As one of the effective methods of historical flash flood events reconstruction, dendrogeomorphology has been used worldwide. It can provide hazard information with long temporal scale and high temporal resolution, sometimes at the seasonal level. By comparing tree ring width and other growth characteristics between disturbed and undisturbed trees, growth disturbance signals can be found in the disturbed trees. Using the growth disturbance in tree rings, flash flood events can be dated, and then the frequency, size, and spatial distribution characteristics of flash floods that have no or little documentary records can be reconstructed. The discharge of flash flood can be reconstructed quantitatively according to the height of scars or by using hydraulic models. With the development of dendrogeomorphology, research tends to probe into the meteorological driving mechanism of flash floods and the pattern of flash floods on a larger spatial scale. In the practical application of dendrogeomorphology, more instrumental data and historical records are applied in the studies. This makes the method increasingly more widely used around the world. But work based on dendrogeomorphology has not been reported in China. In this article, we reviewed the development of the study on flash floods based on tree ring, briefly summarized the research progress, and discussed the advantages, limitations, and potential of this approach, so as to provide some reference information for relevant work in China.

An NGO disaster relief network for small and medium-scale natural hazards in China.

As China is one of the world’s most vulnerable countries to small and medium-scale natural hazards (SMNHs), its NGOs have had a great deal of experience in dealing with disaster relief, especially since the 2008 Wenchuan Earthquake; however, there have been few studies that have comprehensively examined China’s NGO disaster relief networks (NDRNs). One Foundation (OF), which is one of the most active public-fund raising foundations in China, has been engaged in developing a nationwide NDRN made up of 20 independently operating provincial networks that are focused on SMNHs. This paper explored the structures, operations and challenges in the representative North-Sichuan network, from which the following key factors for sustainable NDRNs were identified: (1) a combined hierarchal and networked organizational structure; and (2) a coordinated external and internal network operations mechanism that has a specific entry threshold to ensure healthy network expansion, periodic member NGO training to enhance network capacity, and reciprocal and cooperative government-NGO relationships. These findings provide a useful reference for the establishment and development of NDRNs in other countries.

Changes of Population, Built-up Land, and Cropland Exposure to Natural Hazards in China from 1995 to 2015

By using the latest China population grid and land-use data, we assess the changing exposure of China’s population and land uses to the hazards of storm surges, droughts, earthquakes, floods, and landslides from 1995 to 2015. We found that the single-hazard areas and the multi-hazard areas covered 43% and 26% of China’s territory, respectively. Population grew faster in the hazard-prone areas than in the non-hazard areas. Built-up area expanded more rapidly in the areas prone to earthquakes and landslides. Cropland changed rapidly in many hazard-prone areas. The hazard-prone areas affected by floods featured the highest cropland loss rates, while the areas prone to earthquakes and landslides featured the highest cropland growth rates. We detected areas with significant exposure changes by using hot spot analysis. It was found that population and built-up land in the Pearl River Basin were increasingly exposed to storm surges, floods, and landslides. The Haihe River Basin and Huaihe River Basin also showed a consistent increase of population and built-up land exposure to droughts and earthquakes. These findings can provide a foundation for the design and implementation of protection and adaptation strategies to improve the resilience of Chinese society to natural hazards.

Innovative trend analysis of main agriculture natural hazards in China during 1989–2014

China is a country where the agricultural areas are frequently affected by natural hazards, and comprehending the change trends of natural hazards is of great significance to sustainable development in agriculture. Innovative trend analysis (ITA) is a new and important trend detection method. In this study, the ITA method was used to analyze five kinds of natural hazards in agricultural areas of China during 1989–2014: wind and hail, forest fire, drought, flood, and freezing hazard. The ITA method was compared with two traditional trend analysis methods, i.e., the Mann–Kendall (M–K) test and linear regression analysis (LRA). The results showed that the areas affected by wind and hail, forest fire, drought, and flood in China are showing significant decreasing trends (p < 0.01 or p < 0.05), whereas the areas affected by freezing hazard are showing significant increasing trends. Using the LRA and M–K test methods, 40 and 51 time series with significant trends (p < 0.01 or p < 0.05) were detected, respectively, while ITA was able to successfully detect 138 significant trends (p < 0.01 or p < 0.05), including 89 time series that did not show significant trends when using the LRA or M–K tests. The time series surveyed indicated that the ITA method is superior to the two traditional analysis methods, and it is able to detect the hidden trends in time series. In addition, based on the analysis of the spatial distribution of the ITA data, the areas affected by wind and hail, forest fire, drought, and flood are showing significant decreasing trends in Southwest and East China (p < 0.01 or p < 0.05), whereas in the North China and part of Central China, there are significant increasing trends for these four natural hazards (p < 0.01 or p < 0.05). In most part of North, Central (p < 0.01 or p < 0.05), Northwest (p < 0.01 or p < 0.05), and South (p < 0.01) China, freezing hazard is increasing significantly, and it is showing a significant decreasing trend only in East and Northeast China (p < 0.01).

Analyzing Spatial-Temporal Distribution of Natural Hazards in China by Mining News Sources

AbstractNatural hazards cause severe consequences to society, the economy, and the environment. However, it is difficult to analyze natural hazards occurrences in China because there is no complete...

Modeling flash floods in ungauged mountain catchments of China: A decision tree learning approach for parameter regionalization

Flash floods in small mountain catchments are one of the most frequent causes of loss of life and property from natural hazards in China. Hydrological models can be a useful tool for the anticipation of these events and the issuing of timely warnings. One of the main challenges of setting up such a system is finding appropriate model parameter values for ungauged catchments. Previous studies have shown that the transfer of parameter sets from hydrologically similar gauged catchments is one of the best performing regionalization methods. However, a remaining key issue is the identification of suitable descriptors of similarity. In this study, we use decision tree learning to explore parameter set transferability in the full space of catchment descriptors. For this purpose, a semi-distributed rainfall-runoff model is set up for 35 catchments in ten Chinese provinces. Hourly runoff data from in total 858 storm events are used to calibrate the model and to evaluate the performance of parameter set transfers between catchments. We then present a novel technique that uses the splitting rules of classification and regression trees (CART) for finding suitable donor catchments for ungauged target catchments. The ability of the model to detect flood events in assumed ungauged catchments is evaluated in series of leave-one-out tests. We show that CART analysis increases the probability of detection of 10-year flood events in comparison to a conventional measure of physiographic-climatic similarity by up to 20%. Decision tree learning can outperform other regionalization approaches because it generates rules that optimally consider spatial proximity and physical similarity. Spatial proximity can be used as a selection criteria but is skipped in the case where no similar gauged catchments are in the vicinity. We conclude that the CART regionalization concept is particularly suitable for implementation in sparsely gauged and topographically complex environments where a proximity-based regionalization concept is not applicable.

Forecasting and Providing Warnings of Flash Floods for Ungauged Mountainous Areas Based on a Distributed Hydrological Model

Flash floods occur in mountainous catchments with short response times, which are among the most devastating natural hazards in China. This paper intends to forecast and provide warnings of flash floods timely and precisely using the flash flood warning system, which is established by a new distributed hydrological model (the China flash flood hydrological model, CNFF-HM). Two ungauged mountainous regions, Shunchang and Zherong, are chosen as the study areas. The CNFF-HM is calibrated in five well-monitored catchments. The parameters for the ungauged regions are estimated by regionalization. River water stage data and reservoir water stage data from Shunchang, and reservoir water stage data from Zherong are used to validate the model. The model performs well and the average Nash–Sutcliffe efficiency (NSE) is above 0.8 for the five catchments. The validation shows the difference in the timing of flood peaks using the two types of water stage data is less than 1 h. The rising and declining trends of the floods correspond to the observed trends over the entire validation process. Furthermore, the flash flood warning system was effectively applied in flash flood event on 28 September 2016 in Zherong. Thus, the CNFF-HM with regionalization is effective in forecasting flash floods for ungauged mountainous regions.

Establishing a rainfall threshold for flash flood warnings in China’s mountainous areas based on a distributed hydrological model

Summary Flash flooding is one of the most common natural hazards in China, particularly in mountainous areas, and usually causes heavy damage and casualties. However, the forecasting of flash flooding in mountainous regions remains challenging because of the short response time and limited monitoring capacity. This paper aims to establish a strategy for flash flood warnings in mountainous ungauged catchments across humid, semi-humid and semi-arid regions of China. First, we implement a geomorphology-based hydrological model (GBHM) in four mountainous catchments with drainage areas that ranges from 493 to 1601 km2. The results show that the GBHM can simulate flash floods appropriately in these four study catchments. We propose a method to determine the rainfall threshold for flood warning by using frequency analysis and binary classification based on long-term GBHM simulations that are forced by historical rainfall data to create a practically easy and straightforward approach for flash flood forecasting in ungauged mountainous catchments with drainage areas from tens to hundreds of square kilometers. The results show that the rainfall threshold value decreases significantly with increasing antecedent soil moisture in humid regions, while this value decreases slightly with increasing soil moisture in semi-humid and semi-arid regions. We also find that accumulative rainfall over a certain time span (or rainfall over a long time span) is an appropriate threshold for flash flood warnings in humid regions because the runoff is dominated by excess saturation. However, the rainfall intensity (or rainfall over a short time span) is more suitable in semi-humid and semi-arid regions because excess infiltration dominates the runoff in these regions. We conduct a comprehensive evaluation of the rainfall threshold and find that the proposed method produces reasonably accurate flash flood warnings in the study catchments. An evaluation of the performance at uncalibrated interior points in the four gauged catchments provides results that are indicative of the expected performance at ungauged locations. We also find that insufficient historical data lengths (13 years with a 5-year flood return period in this study) may introduce uncertainty in the estimation of the flood/rainfall threshold because of the small number of flood events that are used in binary classification. A data sample that contains enough flood events (10 events suggested in the present study) that exceed the threshold value is necessary to obtain acceptable results from binary classification.

Screening of social vulnerability to natural hazards in China

In recent decades, losses resulted from natural disasters have dramatically increased and combined with a significant rise in the intensity and frequency of natural hazards, and in exposure. China is prone to multiple hazards and has experienced huge changes in its social fabric during the past two decades, especially in its population density, development patterns, and other social characteristics. These changes may have exposed the population and society to higher risks than ever before. It is, therefore, important to identify and assess regional social vulnerability to natural hazards to strengthen decision making in disaster risk reduction planning and risk governance. To quantify regional social vulnerability to natural hazards and map its temporal–spatial distribution in China, we carefully selected variables from an extensive compilation of provincial socioeconomic and demographic data. Because of the data issue of high dimension and low sample size, we used a two-level approach to calculate social vulnerability index scores. Dynamic geographic patterns of social vulnerability were captured, and spatial autocorrelations were then calculated. The results indicated a quasi-dualistic structure of social vulnerability in China, with a higher distribution in eastern China compared with that in western China, and a declining trend in spatial clustering in recent years.

Hazard Assessment of Debris Flow Based on the TFSE: A Case along Jinsha River close to the Jinsha Dam Site in China

Debris flows are common natural hazards in China. The outbreak of debris flows in reservoir region not only affects the stability of the hydropower stations dam, but also threatens the safety of human life and their property. Therefore, hazard assessment and protection of debris flows close to the dam are necessary and important. In this paper, SPOT5 remote sensing images and DEM model and scene investigation are introduced to acquire the characteristics of debris flow gullies. Ten debris flow occurrence related factors were selected. Then, on the basic of analyzing the relationship of the major factors and fuzzification of debris flow hazard degree, the model of two-stage fuzzy synthetic evaluation (TFSE) was established for hazard assessment. The debris flow risk under different designed rainstorm frequency was calculated. By the evaluation results, we can know that with the design storm intensity increases, the risk of debris flow increases, which is consistent with the actual situation.

Composite risk assessment of typhoon-induced disaster for China’s coastal area

Typhoons, as one of the most devastating natural hazards in China’s coastal area, have caused considerable personal injury and property damage throughout history. An indicator system which included two aspects of hazard and vulnerability with 14 indicators was built up for composite risk assessment of typhoon-induced disaster. The analytic hierarchy process was used to calculate the weight of each indicator, and the composite risk assessment model was then built up. The results indicated that there were no very high- or very low-risk areas in China’s coastal area. Out of the 18,000-km-long China land coastline, 30.99 % was at low risk, mostly along the coastal hill–mountain zone, Hainan and Guangxi coast; the major part (62.71 %) of the coastal area was classified as at moderate risk. Although only 6.30 % of the total was at high risk, the affected area was mainly distributed in Tianjin, Shanghai, and Guangzhou, the three main deltas with low topography, a highly developed economy, and a very dense population.

Methodology for the assessment and classification of regional vulnerability to natural hazards in China: the application of a DEA model

This paper presents a new method for quantifying vulnerability to natural hazards in China. As an important area of vulnerability research, quantitative assessment of vulnerability has raised much focus in academia. Presently, scholars have proposed a variety of methods for quantitative assessment, which usually create an index of overall vulnerability from a suite of indicators, based on the understanding of the cause or mechanism of vulnerability. However, due to the complex nature of vulnerability, this approach caused some arguments on the indicator selection and the weight set for subindices. A data envelopment analysis–based model for the assessment of the regional vulnerability to natural disasters is presented here to improve upon the traditional methods, and a new approach for the classification of vulnerability is proposed. The vulnerability to natural hazards in China’s mainland is illustrated as a case study. The result shows that the overall level of vulnerability to natural hazards in mainland China is high. The geographic pattern shows that vulnerability is highest in western China, followed by diminishing vulnerability in central China, and lowest vulnerability levels in eastern China. There is a negative correlation between the level of vulnerability and the level of regional economic development.

The impacting factors of vulnerability to natural hazards in China: an analysis based on structural equation model

The vulnerability to natural hazard is one of the inner characteristics of social economic system, which is determined and impacted by various factors from almost all the aspects of the system. Although it is widely agreed that the economic development, the migration, and the equity of resource allocation are among the most important impacting factors in forming and developing of the vulnerability, their interrelationship is still unclear enough. The study in this paper employs the method of structural equation model to discover the interrelationship between different latent impacting factors, as well as their contributions to the vulnerability of the system to natural hazards. It is found that, among the factors relating social and economic development, the equity of income allocation is a key point. Also the impacts from industrialization are different for different development levels. The conclusions are expected to be helpful references for the decision consideration of the local development strategies.

Assessment of regional vulnerability to natural hazards in China using a DEA model

This paper presents a new method for quantifying regional vulnerability to natural hazards in China. In recent decades, the study of vulnerability has gained a position of centrality in natural hazards research. How to quantitatively assess vulnerability has raised much interest in academia. Researchers have proposed a variety of methods for quantitative assessment. But these methods are very sensitive to weights set for subindices. As a result, analytic results are often less convincing. A model based on data envelopment analysis (DEA) is used for the assessment of regional vulnerability to natural hazards in an attempt to improve existing analytical methods. Using a regional natural disaster system framework, this article constructs an input-output DEA model for the assessment of regional vulnerability, and takes China’s mainland as a case study area. The result shows that the overall level of vulnerability to natural hazards in mainland China is high. The geographical pattern is that vulnerability is highest in western China, followed by diminishing vulnerability in central China, and lowest vulnerability levels in eastern China. There is a negative correlation between the level of regional vulnerability and level of regional economic development. Generally speaking, the more economically developed a region, the lower its regional vulnerability.

Food self-sufficiency and natural hazards in China

China’s role in the global grain market is expected to expand with increasing demand for food and feed, both within and outside the country. Unforeseen crop failures caused by natural hazards might also be instrumental. This paper uses agricultural production (rice, wheat, maize, tubers, soybeans, and other grains) and natural disaster data (floods and droughts) for 31 provinces in China for the period 1995–2008 to examine the self-sufficiency of China’s domestic harvests. It aims to answer three questions: (1) Is the size of China’s current grain stock adequate as a buffer against seasonal crop failures of the same magnitude as in the past? (2) On a single province basis, does a diversity of grain crops reduce the risk of production shocks due to natural hazards? (3) Which regions are less likely to be affected by natural hazards and should therefore be set aside as agricultural land in order to meet future food self-sufficiency targets? The results show that if the worst crop failures of all provinces between 1995 and 2008 were to happen in the same year, a “theoretical worst-case scenario”, China’s cereal harvest might drop by 140 million tonnes. Therefore, their current grain stock of 120–200 million tonnes is sufficient to buffer China’s cereal supplies against 1 year of production problems. Provinces with a high degree of grain crop diversity over the 13-year period were less affected by floods and more affected by droughts. Food self-sufficiency was the highest in moderately diverse provinces. Key agricultural regions relatively less affected by natural hazards included parts of the North China Plain. In addition, China began to increasingly depend on three provinces in the drought-prone north-east region for attaining grain self-sufficiency. Policies need to enable farms of all sizes to adapt to change and to contribute to food self-sufficiency.

AN EMERGING CIVIL SOCIETY: THE IMPACT OF THE 2008 SICHUAN EARTHQUAKE ON GRASS-ROOTS ASSOCIATIONS IN CHINA

The western China, especially near the Wenchuan region witnessed a terrible earthquake in the year 2008, which led to some severe damage in the country. Several interviews and studies are conducted to explain the impact of this Sichuan earthquake on the development of the various grass-root associations present in the country.