Regional Landslide Hazard Warning and Risk Assessment

EARTH SCIENCE FRONTIERS Volume 14, Issue 6, November 2007 Online English edition of the Chinese language journal Cite this article as: Earth Science Frontiers, 2007, 14(6): 85–97.

RESEARCH PAPER

Regional Landslide Hazard Warning and Risk Assessment YIN Kunlong1,∗, CHEN Lixia1, ZHANG Guirong2 1 Engineering Faculty, China University of Geosciences, Wuhan 430074, China 2 Nanjing Hydraulic Research Institute, Nanjing 210029, China

Abstract: Regional landslide hazard prediction and warning is still a difficult problem and hot topic in the research of landslide hazards. In the past decade, the researches mainly focused on the analysis of the combination of rainfall and geological environment. In this paper, we summarize the current studies of landslide hazard prediction and risk assessment, and propose that the combination of hazard prediction with risk management is not only the need for hazard prediction and prevention, but also the trend in the future. Basic theories are discussed from two aspects: the spatial prediction and time warning. Based on these theories, we set up a landslide hazard information management system and a real-time warning information releasing system, which is developed on MapGIS platform. Taking landslides as examples in Yongjia City, Zhejiang Province, during the period of typhoon Rananim of 2004, we have studied the spatial landslide hazard prediction, life vulnerability assessment and economic risk assessment. Key Words: landslide hazard; WebGIS; prediction and warning; risk assessment

1

Introduction

Regional landslide hazard prediction and warning normally includes spatial prediction and time warning, which is useful for hazard risk assessment and management and also an important research work for hazard control. Due to the economic development levels and hazard control measures, the research is also different in different countries. Some countries, like USA and Japan, have established public-oriented real-time warning system on regional rainfall-induced landslide hazards. The accuracy of warning can reach to 1 hr. Amongst these countries, the warning system by USA is the most representative[1–6]. Meanwhile, all the systems have the similar characters: (1) long time and perfect rainfall data; (2) advanced remote controlling, monitoring and transfer net for rainfall and landslides; (3) detailed landslide investigation data and hazard zonation work. In China, under the national or local government agencies, the similar researches have been finished in some regions or provinces, such as Hong Kong, the Three Gorges Reservoir, Yunnan, Gansu, Sichuan, Zhejiang, China Geological Survey Bureau and China Meteorological Administration[7–20]. The main characteristics of the studies can be summarized as

follows: (1) comprehensive analysis of the geological environments of landslide hazard, which formed the basis of regional landslide hazard zonation by proper mathematical models; (2) short-time dynamic warning models based on triggering factors, such as rainfall-controlled warning models; (3) risk delivering information net to administrative departments or the public by WebGIS. Although great progresses have been reached in the field of landslide hazard prediction and warning, many shortages still exist now, including: (1) lower rainfall forecast accuracy, which dominates regional distribution of landslides. The accuracy of regional landslide hazard prediction and warning influenced by two aspects: the accuracy of weather forecast information and the accuracy of spatial landslide hazard zonation. Dissatisfied information will cause invalid prediction results that is useless for hazard controlling. Therefore, other triggering factors except rainfall should be considered such as earthquake and human activity. (2) hazard prediction does not approach to the sense of risk assessment and management, which inconvenient for the administrative agencies to make decisions for hazard reductions. So, the tendency is to consider together of spatial hazard prediction,

Received date: 2007-09-26; Accepted date: 2007-10-29. ∗ Corresponding author. E-mail: [email protected] Foundation item: Supported by the National Natural Science Foundation of China (No. 40072084). Copyright © 2007, China University of Geosciences (Beijing) and Peking University, Published by Elsevier B.V. All rights reserved.

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time warning, and risk management for regional landslide hazard reduction.

2 Basic principles of regional landslide hazard prediction and warning Regional landslide hazard prediction and warning includes two parts, one is spatial prediction and another is time warning. Spatial prediction is prerequisite for time warning. That is to say, time warning work is effective only when the predictive object is determined. Although such precedence relationship exists, these two parts are independent for the objective hazards reduction. The basic information of spatial landslide hazard prediction can be divided as intrinsic and triggering factors. Intrinsic factors normally include topography, slope, lithology, geological structure and so on. Human activities and rainfall are generally treated as triggering factors. Engineering geological analogism forms the major principle for regional landslide hazard prediction, which can be mathematically modeled for a quantitative analysis in terms of certain useful models, such as statistical model, expert analysis model and information model. Spatial prediction aims to find out the places where the geological environment is prone to slide, which can be expressed as hazard zonation map. Figure 1 presents a nationwide geo-hazard zonation map of China at the scale of 1‫׃‬6,000,000. And a province-wide landslide hazard zonation map is illustrated in Fig. 2[21,22]. Both maps give examples of very large territory landslide hazard prediction that is presented as grades of the slope instabilities. A precondition of regional landslide hazard warning is to find the relationship between landslides and triggering factors. For example, correct relationships between landslide and rainfall can help the determination of critical rainfall or

intensity according to historical frequency analysis or statistical analysis. Based on triggering critical values, regional landslide occurrence time can then be approximately obtained by the real-time monitored dynamic information of the triggering factors.

3 Application of WebGIS to regional landslide hazard prediction and warning WebGIS is the combination product of GIS and internet technology. After the coupling of landslide hazard prediction and warning models with WebGIS technology, users can browse and query landslides basic information, or realize the purpose of hazard prediction and warning by comprehensive analysis of basic geological information, real-timely monitored data of landslide displacement and rainfall. 3.1 Landslide hazard prediction and warning information management system based on WebGIS The purpose of the system is to provide space and attribute information for landslide hazard prediction and warning work. Its main functions include basic data acquisition, processing, query, statistic and management. Because all the data is collected from different departments, data processing is a basic and important step amongst these, which means the same attribute structure, same data type, same map projection, same coordinate system, same units and so on. That is to say, standard data processing is very necessary. The main contents of the system include: (1) basic geography information, including administrative map, land-use map, geographical map, water system map and so on; (2) geo-hazard environment information, including lithology map, geological structure map, rainfall distribution map and so on; (3) special information, including landslide hazard distribution map,

Fig. 1 Geo-hazard zonation map of China[21]

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Fig. 2

Landslide hazard zonation map of Zhejiang Province in China[22]

zonation map and so on. All these maps can be shown by points, lines and partitions in GIS system. For convenient management, all these map units have their own exterior attribute charts, which mainly record some more complex and prefect information about the unit. For example, the information of a landslide may include basic information (the location), background information (slope, lithology, geological structure), triggering factors, (losses, casualties), controlling advices and so on. Exterior attribute charts can be

expressed in the form of tables, which is always saved in the database for information query and statistic. Therefore, the hazards database needs unite standard. Users can query and get statistic information through interactive operation of spatial and special attribute data. Figure 3 shows the detailed information query process. In the database based on WebGIS, the browser proposes the operation to database, and the request can then be transferred to special instructions to database by a certain Web application

YIN Kunlong et al. / Earth Science Frontiers, 2007, 14(6): 85–97

Query range: whole region, defined district, hazards types, magnitude etc.

Hazard distribution map

Specify a hazard to query

Geography and

Map information

Monitoring information

consequence information Basic information

Location Type of hazards Magnitude Occurrence time Property losses Casualties Person for monitoring Tel-number of the person Elements at risk Geological environment Pictures Multimedia data Identification of slope

Basic information

Planar maps

Distributional maps

Profile maps

Curves

Exploring data

…… Fig. 3

Flow chart of hazard information query

in the server, and the results finally return to the browser. Figure 4 shows the process. Such database can be established by different databases, such as Oracal, SQL Server, Access and so on. And the main operation technology to Web database is Web application. Today, different technologies exit to different servers, which include certain advanced and common ones, such as ASP, JSP, ASP.Net and so on. In the completed landslide hazard database, it is possible to combine the maps and attribute data. Users can magnify, reduce, move and couple the maps through the Internet. Amongst the above operations, query is the most frequent one. Because of the same and only identification number of a map unit and its attribute record, they can be queried by each other and the result can be shown for users. 3.2 Information delivering system of rainfall-induced landslide hazard real-time warning based on WebGIS Although landslide occurrence essentially depend on certain factors, such as topography, geological structure, lithology and so on, certain other exterior factors are also very important to slop instability, such as rainfall, earthquake, excavation, loading and water fluctuation. Rainfall, especially rainstorm, is an important and most frequent amongst these factors. Through the regional relationship analysis between landslides and rainfall, effective

Web

database

application server

Browser

result Fig. 4

databasese

server

result

result

Web database service process

rainfall model can be built up, which is proved to be very useful for spatial prediction and time warning. Figure 5[22] shows the model in Zhejiang Province, China. Vertical presents the frequency of landslides, and horizontal presents accumulative effective precipitation from the past 50 years data. From the curves, two critical rainfall values where the gradient is steep are found out which caused obvious increase in landslide increasing: 175 mm and 250 mm. After the receiving of real-time precipitation value or regional precipitation contour from weather forecast department, spatial landslide zonation map can overlap precipitation distribution map to get the warning area in terms of mathematical model analysis. Figure 6 shows the predicted precipitation contour map according to middle-scale forecast model which was based on the radar data (Jun. 23, 2003) from Zhejiang weather observatory of China. The map predicted the precipitation in the next 24 hours in the entire Zhejiang Province.

YIN Kunlong et al. / Earth Science Frontiers, 2007, 14(6): 85–97

applied for real-time landslide warning practice during the period of typhoon Rananim of 2004 in Zhejiang Province, China (Aug. 12, 2004).

4

Fig. 5 Accumulative effective rainfall-landslide relation curve[22]

Research of landslide risk assessment is an international frontier project today, which is very important both in theory and practice[23]. The risk concept (UNDRO United National Disaster Relief Organization, 1982) was transferred to landslide issues by various authors[24]. And the main contents include three parts: landslide probability, element vulnerability and total risk prediction. Because landslide hazards are not only natural phenomena, but also social and economic events, the research of risk involves multiple subjects, including geology, landslides, hazards, social science, economics and so on. From recent research status, the research today has not formed a perfect theory system, and cannot satisfy the need of hazard reduction and prevention in practice. Element vulnerability and total risk research is still a weakness to be overcome. Therefore, a useful regional landslide risk assessment system is in urgent need. 4.1

Fig. 6

Predicted precipitation contour in the next 24 h in

Zhejiang Province, Southeast China on Jun. 23, 2003

The system can deliver real-time warning information through the internet, telecommunication, media and so on. And amongst these technologies, users can select a suitable one depending on the possibility of accessing the technology according to the economic or technical status. But internet technology is becoming a popular and fast method to access new information. WebGIS has not only advantages, such as efficiency, real-time and dynamic, but it can also couple many models and information, such as real-time weather information, hazard database and prediction models. Figure 7 shows the system frame, which has three hierarchies, including GIS database server, WebGIS server and browser. GIS server can store, operate and analyze the hazard data, and can send the prediction results to WebGIS server. After some requests are received from the users, WebGIS server deals with these requests, and quickly creates a series of ASP programs by the GIS Server components. Browsers are different users with different demands. It can visit some ASP pages in WebGIS server and then receive some results or information by HTML. Figure 8 shows the hazard prediction and warning information for users when the system was

Landslide risk assessment

Regional landslide hazard analysis

Regional landslide hazard analysis requires knowing the hazard probability or intensity of occurrence in a research region during a specific period. If landslides occurrence is regarded as a random event, the task of hazard analysis is to estimate the probability or return period of hazard occurrence with various possible intensities. From the aspect of qualitative analysis, higher degree landslide activities are, more hazardous landslides are. But from the aspect of quantitative analysis, hazardous degree should be reflected from detailed indexes. This article discusses semi-quantitative analysis of regional landslide hazards, which has been expatiated in the part of spatial prediction. 4.2

Element vulnerability assessment

The word ‘vulnerability’ comes from the Latin verb ‘vulnerare’, ‘to wound’ or ‘to be susceptible’, and is explained in the dictionary as ‘liability to be damaged or wounded’[25]. The research objects of regional landslides are the elements at risk. The vulnerability assessment of the elements at risk is both a focal point and also a problem in risk assessment, the level of which is still qualitative or semi-quantitative now. According to the type of elements at risk, vulnerability assessment involves two types of element: life and economy. (1) Vulnerability assessment of life. The degree of vulnerability of life depends on multiple factors: (a) the intensity of landslides. Persons have a low vulnerability to the slow-moving landslide but a higher vulnerability to the fast-moving one. (b) Population density. Rural areas with low population density normally have low vulnerability, but cities

YIN Kunlong et al. / Earth Science Frontiers, 2007, 14(6): 85–97

Fig. 7

Frame of hazards real-time prediction and warning information releasing system based on WebGIS

Fig. 8 Information delivering of landslide hazard real-time warning during the period of typhoon Rananim of 2004 in Zhejiang Province, Southeast China on Aug. 12, 2004

or towns at a higher vulnerability, because of higher population density to a landslide under the same magnitude of the disaster. (c) Age structure of population. In contrast to most adults, elders and children might not be able to react adequately to hazards, who have higher vulnerability. (d)

Knowledge or concept of people about hazards or risk. Persons with high hazard prevention recognition have low vulnerability to landslide events, but a higher vulnerability with ignorance to landslides. (e) Recognition degree of governments to landslide hazards. Persons have higher

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hazards prevention concept and low vulnerability if they have good risk management program by the government. (f) Early warning systems affect the vulnerability of persons. If an early warning system is properly established, persons might be able to escape or evacuate to safe places and the vulnerability may be changed. Therefore, the above-mentioned factors should be taken into consideration completely in risk assessment. (2) Vulnerability assessment of economy. In general, economic losses include two parts: direct and indirect economic losses. But because of the difficulties to calculate indirect economic losses, the research is limited to direct losses. And the objects of direct economics losses include damages of buildings, lifeline engineering, economic crop and land resources. Similar to vulnerability of persons, the vulnerability of economic objects also have great relationships with hazards intensity, besides the characteristics of themselves. In quantitative risk assessment, the vulnerability

Fig. 9

analysis of buildings should take some factors into consideration, such as structures, foundations, service life, locations and so on. 4.3

Risk assessment

Landslide risk assessment is based on hazard analysis and vulnerability assessment, which can be expressed by casualties and economic losses in a certain time span, such as year, decade or century consideration. Because landslide economic risk assessment depends on the probability of hazard, vulnerability and values of elements at risk, the risk can be calculated from: n

Rei = Pli × ∑ (Vmi × E mi ) m =1

where Rei is the economic risk assessment value of unit i in a given time; Pli is the hazard probability of unit i in a given

Landslide economic risk assessment in Yongjia County, Zhejiang Province, Southeast China[26]

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time; Vmi is the vulnerability of element m at risk in a given time; Emi is the value of element m in unit i. After the potential losses in a given time in each prediction unit are calculated, a landslide economic risk assessment map can then be obtained. Figure 9 is such a map of the Yongjia county in Zhejiang Province, China[26]. The map is divided into girds of 500 m × 500 m. Each grid has the combinations of factors, economic elements. And it is based on spatial prediction and vulnerability assessment results with WebGIS technology for the future 10 years.

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5

Conclusions

(1) The article summarizes the recent development of landslide hazard prediction and risk assessment. Common characteristics include: (a) it is possible to make spatial landslide hazard prediction based on the analysis of geological environment, historical landslide data and triggering factors; (b) regional landslides warning can be carried out by monitoring regional triggering factors such as rainfall, which is collaborated with weather service agencies; (c) information delivering system through WebGIS technology is a good way for government and public to make risk management before events come. (2) Basic theories are discussed from two aspects of spatial prediction and warning. And just according to these theories, landslide hazard information management system and real-time warning information delivering system are set up, which was developed on MapGIS software platform. (3) Taking landslides during the period of typhoon Rananim of 2004 in Yongjia county of Zhejiang Province as examples, the article well practiced the regional landslide hazard prediction, life vulnerability assessment and economic risk assessment.

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