Environ Monit Assess (2007) 127:419–428

DOI 10.1007/s10661-006-9291-9

O R I G I N A L A R T I C L E

A web-based decision support system for slopelandhazard warningYu Fan-Chieh · Chen Chien-Yuan ·Lin Sheng-Chi · Lin Yu-Ching · Wu Shang-Yu ·Cheung Kei-Wai

Received: 25 October 2005 / Accepted: 8 May 2006 / Published online: 14 December 2006C© Springer Science + Business Media B.V. 2006

Abstract A WebGIS decision support system for

slopeland hazard warning based on real-time monitored

rainfall is introduced herein. This paper presents its

framework, database, processes of setting up the thresh-

old line for debris flow triggering and the calculation

algorithm implemented in the system. The web-based

GIS via the Microsoft Internet Explorer is designed for

analysis of areas prone to debris flows outburst and

landslides during torrential rain. Its function is to pro-

vide suggestions to commander for immediate response

to the possibility of slopeland hazards, and determine if

pre-evacuation is necessary. The defining characteris-

tics of the internet-based decision support system is not

to automatically show the dangerous areas but acts as

part of the decision process via information collection

to help experts judge the prone debris flow creeks and

the tendency of landslides initiation. The combination

with real-time rainfall estimation by the QPESUMS

radar system is suggested for further enhancement.

Y. Fan-ChiehNational Chung Hsing Universitye-mail: fcyu@dragon.nchu.edu.tw

C. Chien-Yuan (�)National Chiayi University Addr: No. 300 Syuefu Rd.Chiayi City 60004, Taiwane-mail: chienyuc@mail.ncyu.edu.tw

L. Sheng-Chi · L. Yu-Ching · W. Shang-Yu · C. Kei-WaiNational Science and Technology Center for DisasterReduction (NCDR). Addr.: 9F., No. 200, Sec. 3, HoPing E.Beisin Rd., Sindian City, Taipei County 23143, Taiwan

Keywords Landslide . Debris flow . Decision support

system . Real-time monitoring . WebGIS

1. Introduction

The current trend for the development of decision sup-

port systems (DSS) is to use powerful tools in com-

puter graphics, artificial intelligence and visual inter-

active modeling (Eom et al., 1998). In recent years,

combining with the population of Geographic Infor-

mation System (GIS) has become a basis of DSS be-

cause GIS has the advantage to explore and analyze

spatial database efficiently. For example, Lazzari et al.(1999) constructed a landslide hazard monitoring sys-

tem with GIS, and Junkhiaw et al. (2004) developed a

DSS for flood warning with GIS techniques. The con-

cept of DSS for spatial analysis has also been termed a

spatial decision support system (SDSS) (Densham and

Goodchild, 1989; Crossland et al., 1995). The combi-

nation of GIS and the internet is also a widespread trend

of DSS. One example of the application of DSS via the

internet for flood risk assessment was presented in the

project of ANFAS (http://ups.savba.sk/ parcom/anfas/,

Prastacos, 2002).

There is a population of 23 million people in

an area of about 36,000 km2 of the main island

of Taiwan. This level of population density makes

Taiwan one of the most crowded areas in the world.

The losses of lives and damages to facilities by nat-

ural hazards have been increasing with the mounting

Springer

420 Environ Monit Assess (2007) 127:419–428

population. According to the Central Weather Bureau

(http://www.cwb.gov.tw/V4e/, CWB) there was a total

loss of 174 billion Taiwan dollars per year from 1980

to 1998 that could be attributed to typhoon induced

hazards. The National Fire Agency, Taipei city govern-

ment, National Center for Research on Earthquake En-

gineering, CWB, Soil and Water Conservation Bureau

(SWCB), Water Resources Agency, and Central Geo-

logical Survey have developed various disaster man-

agement information systems for mitigation of natural

hazards (Lin and Hsu, 2005) because the government

is the main domain for DSS application (Eom et al.,1998).

Debris flow is one of the most serious natural hazards

in terms of its potential hazard to lives and damages to

facilities. This is especially the case with the increasing

urban development in the limited space of Taiwan. The

requirement of a DSS for slopeland hazard pre-warning

for areas with recurring natural hazards is urgent espe-

cially in the aftermath of the M7.6 Chi-Chi earthquake

that occurred in Taiwan in 1999. This article introduces

the current development of a DSS for slopeland hazards

in the National Science & Technology Center for Disas-

ter Reduction (http://www.ncdr.nat.gov.tw/ncdr eng/,

NCDR) and suggestions for its improvement. We em-

phasize the necessary background and theory to set up a

slopeland threshold line, the architecture of web-based

SDSS, and the process of decision support/ making for

slopeland hazard precaution.

2. Slopeland hazards in Taiwan

According to the CWB, approximately 3.5 typhoons

on average hit Taiwan every year. Figure 1 presents the

tracks of typhoons that affected Taiwan in recent years

and caused catastrophic slopeland hazards. In the single

year of 2001, Taiwan was affected by eight typhoons, of

which two were of typhoon intensity: Toraji and Nari.

Fig. 1 Track of typhoons that affected Taiwan in recent years

These two typhoons caused the most serious damages

in slopeland hazard in the aftermath of the M7.6 Chi-

Chi earthquake. For example, Typhoon Nari hit western

Taiwan directly and caused great amount of damages

in areas of high population density.

The total number of slopeland hazards, includ-

ing landslides, debris flows, rockfalls and road-related

landslides that were triggered in recent years are shown

in Table 1. The statistics of slopeland hazards were ob-

tained from SWCB, Directorate General of Highway

(DGH), National Fire Agency, newspapers and wire-

less news. In 1990 Typhoon Ofile destroyed 32 build-

ings and buried 36 residents under masses of debris in

eastern Taiwan (Chen et al. 1999). This major catas-

trophic debris flow highlighted the necessity of debris

flow prevention work in Taiwan. The M7.6 Chi-Chi

earthquake in 1999 triggered 21,970 landslide spots

over 113 km2 (source: SWCB, 2000). One of the most

Table 1 Total number of recent years’ typhoon-related slopeland hazards in Taiwan

Typhoon Max. intensity Accumulative No. of ∗ No. of No. of died/

event (mm/hr) rainfall (mm) slopeland hazards evacuated disappeared

Toraji 2001/07/28 147 757 673 – 214

Nari 2001/09/17 142 1,462 475 24,000 104

Mindulle 2004/06/30 167 2,005 1,023 9,500 41

∗ Source from SWCB, DGH, National Fire Agency, newspapers and wireless news

Springer

Environ Monit Assess (2007) 127:419–428 421

Fig. 2 Huge landslide at Chiufenerhshan township, NantouCounty, triggered by the M7.6 Chi-Chi earthquake in 1999

damaging landslides was located in Tsaoling township

in Yulin County. The landslide had an area of up to

4 km2 and a landslide dam formed, in which there were

29 victims (Chigira et al., 2003, Chen et al., 2004b).

The other landslide case was triggered at the epicen-

ter of the Chi-Chi earthquake with a landslide area of

2 km2 and a dammed lake formed in the Chiufen-

erhshan township in Nantou County. There were 19

houses and 41 residents trapped inside the sliding mass

(Fig. 2) (Shou and Wang, 2003, Wu et al., 2005).

Typhoon Xangsane in 2000 induced debris flows

at the Dacukeng stream of Taipei County in northern

Taiwan. More than 20 houses were affected and there

were eight victims attributed to a landslide dam breach-

ing that induced debris flow (Chen et al., 2004a). After

the Chi-Chi earthquake and the additional impact of

Typhoon Xangsane, the number of streams with po-

tential for debris flow in Taiwan increased from 485

to 722 according to field investigations by SWCB.

Typhoon Toraji gave outburst to the most serious debris

flow hazards in history for the 673 spots of slopeland

hazards and debris flows initiated in all 14 counties

of Taiwan. This disaster caused by Toraji had 103 vic-

tims, 111 missing people and 189 injuries. Two months

later, another Typhoon Nari hit northern Taiwan, caus-

ing 475 slopeland hazards and 104 deaths. The typhoon

induced flood hazards that paralyzed the transportation

system of Taipei city. In June 2004, Typhoon Mindulle

struck Taiwan. This typhoon caused 1,023 slopeland-

related hazards from more than 2,000 mm of rain with

the highest intensity of 167 mm/hr. There were 41 vic-

tims during the impact of Typhoon Mindulle. One of

Fig. 3 Debris flow hazard after Typhoon Mindulle at SongheTribute, Taichung County (photo by SWCB)

the most damaging debris flows in Songhe Tribute of

Taichung County is shown in Fig. 3.

3. Landslide and debris flow threshold setting

Chen et al. (2005) collected 61 historical debris flow

cases and their triggering time in Taiwan for the pur-

pose of performing linear regression analysis of a debris

flow threshold line. The triggering equation for critical

averaged rainfall intensity (Ic) versus rainfall duration

(D) can be expressed as:

Ic = 115.47D−0.80 (1)

This equation was verified when Typhoon Mindulle

hit Taiwan and the threshold equation for triggering the

29 debris flows in 2004 is represented as:

Ic = 101.81D−0.69 (2)

As shown in Fig. 4, equation (2) was found to have

higher values than equation (1) and therefore equation

(1) can be employed as a threshold line for debris flow

monitoring in Taiwan, especially in the northern and

middle parts of the island.

For the purpose of landslide threshold monitoring,

3,629 cases of rainfall induced landslide were collected

from 1971 to 2004 for mapping critical isohyet to trig-

ger landslides by rainfall intensity (Fig. 5) and by daily

accumulated rainfall (Fig. 6) using spatial interpolation

of rain gauge data that employs the Kriging method.

Springer

422 Environ Monit Assess (2007) 127:419–428

1 10 100 1000Duration (hr)

0.1

1

10

100

1000

Mea

n R

ain

fall

In

ten

sity

(m

m/h

r)

Mindulle event nothing with the 921 EQ

Mindulle event affected by the 921 EQ

Historical events affected by the 921 EQ

Historical events nothing with the 921 EQ

I=115.47D-0.80

I=101.81D-0.69

(Mindulle)

Fig. 4 Debris flow threshold line implemented in the WebGISsystem

Fig. 5 Critical rainfall intensity triggering landslides in Taiwan

Fig. 6 Critical daily accumulated rainfall triggering landslidesin Taiwan

4. Architecture of the web-based decisionsupport system

The internet-based DSS is based on the AutoDesk’s

MapGuide and the operational environment is a com-

ponent of Microsoft Windows 2000 server, while Au-

todesk MapGuide Server 5.0 and Microsoft SQL Server

2000 are used for data inquiry. The user interface is

structured in Microsoft Internet Explorer 5.0 or above,

and Autodesk MapGuide Viewer R6 is optimized for

screen resolution 1024×768. It is available from the

web site http://map2.ncdr.nat.gov.tw/ for authorized

users. The architecture of the system is presented in

Fig. 7 and Fig. 8 illustrates some components of the

platform for slopeland hazard warning.

As shown in Fig. 7 and Fig. 8, there are four dynamic

databases and three major modules in the WebGIS

platform. The spatial rainfall distribution from rain

gauge stations and the radar data display system

QPESUMS (Quantitative Precipitation Estimation and

Segregation Using Multiple Sensors) are connected in

Springer

Environ Monit Assess (2007) 127:419–428 423

Fig. 7 Architecture of the web-based GIS decision support system for slopeland hazard warning

Fig. 8 Components of WebGIS platform for slopeland hazard warning

Springer

424 Environ Monit Assess (2007) 127:419–428

real-time to the CWB in Taiwan. Data received from the

CWB is interpolated in GIS and automatically updated

every ten minutes. A preliminary application of QPE-

SUMS for monitoring rainfall for debris flow warn-

ing was introduced by Chen et al. (2006). Options

of rainfall information display in the web system in-

clude monitored ground-based rainfall spatial distribu-

tion with one-, three-, six-, twelve- and 24-hour accu-

mulated values. These rainfall data can also be ranked

and sorted from the highest to the lowest value in the

past hour (up to previous six hours) based on monitored

rain gauge stations. Another important function of the

rainfall module is to display rainfall estimates from the

climatology and persistence model that is built upon

a database of 66 typhoons that affected Taiwan from

1989 to 2002. The model estimates, displays, sorts and

performs inquires for 1-, 3-, 6-, and 24-hour rainfall dis-

tribution based on the forecast track of typhoons from

the CWB and with consideration the topographical lift-

ing effect (Lee et al., 2006).

The spatial distribution of rainfall is an important

factor in the overlap analysis for identifying zones

of rainfall concentration and judging the possibility

of hazards. The monitored river water level in the

WEbGIS system is connected to the Water Resource

Agency (http://eng.wra.gov.tw/) and displays the dis-

charge information of the specified rivers. The hazard

occurrence information in the WebGIS is manually up-

dated with hazard information from newspapers and

wireless news as they are collected continuously. The

location of hazards displayed in the system let the com-

mander know in which manner the hazards occur. The

basic GIS map layers in the system include locations

of the 365 rain gauge stations, national highways, lo-

cal ways, division of counties, townships, villages, and

watersheds. These features are then overlayed on topo-

graphic maps in scales of 1:50,000 and 1:25,000 and

aerial photos of 1:5,000 scale.

5. Implementation of debris flow triggeringmechanism

The representative rainfall of a landslide or a debris

flow creek is identified from its five nearby rain gauge

stations and is interpolated to the landslide spot or

overflow point of the creek using the IDW method in

ArcGIS (Yu et al., 2006a). A rain event begins (at time

t1) when the rainfall intensity is over 0.4 mm/hr and

Current time (t2)

(unit: hr)

Rainfall duration D = t2-t1

(unit: hr)

Debris flow threshold line

Ic = 115.47D-0.8

(unit: mm/hr)

Accumulative rainfall R

(unit: mm)

Averaged rainfall intensity

Iavg = R/D (unit: mm/hr)

Start of a rainfall event (t1)

(unit: hr)

Iavg > Ic

No

Display streams and regions over threshold in WebGIS

Judgments of regions prone to debris flow

Warning of debris flow prone areas

Ye s

Fig. 9 Implementation of debris flow threshold line for real-timerainfall monitoring in WebGIS

the duration (D) is defined as the time passed of current

time (t2) from t1. The averaged rainfall intensity (Iavg)

is the mean value of accumulated rainfall (R) per hour

(R/D). The algorithm of comparing rainfall intensity

and the threshold line is implemented in the WebGIS

system and updated every 10 minutes with the real-time

monitored raingauge stations (Fig. 9). Figure 10 shows

the marked townships with their averaged rainfall, Iavg,

over the threshold value in equation (1) in the WebGIS.

The decision support for areas prone to landslide is im-

plemented using the same algorithm by monitoring the

rainfall intensity and daily rainfall according to the crit-

ical isohyet of rainfall intensity and accumulated rain

amount.

6. Databases in the WebGIS for hazardanalysis

Map layers in the WebGIS for aiding judgment of po-

tential slopeland hazards during heavy rain events in-

clude the locations of 1,420 creeks prone to debris flow

(Fig. 11) and their corresponding potentially endan-

gered downstream areas. The creeks prone to debris

flow are classified into three grades as low, medium

Springer

Environ Monit Assess (2007) 127:419–428 425

Fig. 10 Display of townships over critical threshold rainfall level

and high potential according to their mitigated engi-

neering facilities, geological, topographic, hydraulic

characteristics and field investigations by SWCB. The

debris flow potentially endangered downstream areas

were delineated according to the historical hazard ar-

eas, numerical modeling and field investigations. Chen

et al. (2004a) and Yu et al. (2006b) also defined the

endangered downstream areas from debris flow us-

ing GIS. One delineated example in Songher Tribute,

Taichung County is shown in Fig. 12. The routes for re-

current rockfall are presented in Fig. 13 and those with

agricultural areas are prepared for emergency rescue

or evacuation in the 455 potentially isolated mountain-

ous villages during heavy rains. The historical rain and

seismic induced landslides and also their correspond-

ing geologic conditions are presented in Fig. 14.

7. Operational process during typhoonhit Taiwan

The Central Emergency Operation Center (CEOC)

is activated when a typhoon is about to hit Taiwan.

The function of the Assessment Group in CEOC

is assembling and coordinating the Central Weather

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debris flow potentialhigh potentialmedium potentiallow potential

locations of 455 mountainous villages#S secure buildings over 15%U secure buildings over 5~15

0 50 100 Kilometers

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Fig. 11 Locations of 1,420 debris flow prone streams and 455potentially isolated mountainous villages

Bureau, SWCB, National Fire Agency, Water Re-

sources Agency, NCDR and advisory specialists for

judgment of potential hazards, declaration and provide

suggestions for the CEOC commander. The NCDR

provides risk vulnerability assessments of flood and

slopeland hazards based on the WebGIS decision sup-

port system.

The determinanting factors and information for is-

suing slopeland hazard warnings include rainfall in-

tensity, duration, accumulated rainfall, time to peak

rainfall, potential risk of stream to debris flow, site

conditions, and the initiation histories. The spatial rain-

fall distribution is an important information to identify

areas with concentrated rainfall and those with high po-

tential to initiate slopeland-related hazards. Figure 15

shows the decision process of slopeland hazards us-

ing the system. The areas prone to initiated debris flow

can be listed for the purpose of inquiring and editing.

For example, areas that are not going to initiate de-

bris flow based on judgment from specialists can be

deleted from the list. In addition, the temporal rainfall

history of nearby rain gauge stations for debris flow

prone area can be listed and their intensity can be dis-

played on the desktop for determining whether its type

and intensity is correlated to the initiation time of de-

bris flow (Chen et al., 2005). Figure 16 shows the areas

with concentrated rains and the rainfall intensity at rain

Springer

426 Environ Monit Assess (2007) 127:419–428

Fig. 12 Delineated debris flow downstream endangered areas at Songher Tribute, Taichung County

gauge stations during the impact of Typhoon Mindulle

that brought torrential rains in 2004.

The Web-based decision support system started to

operate and provided decision support from 2001 when

0 50 100 Kilometers

routes potential to rockfall and landslide

agricultural roads

N

EW

S

Fig. 13 Routes for recurrent rockfall areas and for agriculturein mountainous areas

Typhoon Nari hit Taiwan. The number of fatalities was

considerably less in the aftermath of Typhoon Nari

and Mindulle compared to the number of victims dur-

ing Typhoon Toraji (Table 1). The creeks prone to

outburst debris flow for judgment from the available

Fig. 14 Historical rains and seismic induced landslides and theircorresponding geologic conditions

Springer

Environ Monit Assess (2007) 127:419–428 427

Historical landslide events Historical debris flow events

Critical isohyet for landslides Debris flow threshold line

Basic GIS layers :

• Locations of 1,420 debris

flow prone areas and

debris overflow points

• Delineated debris flow

endangered areas

• Secure objects

• 455 mountainous villages

• Routes for agriculture

• Historical landslides and

debris flows

• Geologic map

Analysis of slopeland hazards:

debris flow potential

rainfall time history

topography

geology

engineering facilities

areas of rains concentrated

rainfall intensity

accumulative rainfall

rainfall duration

Ground based

rainfall monitoring

QPESUMS

Rainfall events to hazard

Rainfall over

threshold line

Slopeland hazards warning

Fig. 15 Decision support process for slopeland hazard warning

information are displayed in the screen on the user’s

desktop (Fig. 17), and the locations of initiated haz-

ards were uploaded to the system to provide real-time

information for the user (Fig. 18).

8. Conclusion

A web-based slopeland hazard decision support system

(DSS) based on real-time monitored rainfall is devel-

oped in NCDR. The spatial DSS for slopeland hazard

Fig. 16 Real-time display of rainfall intensity when TyphoonMindulle hit Taiwan

warning was particularly developed in the aftermath

of the M7.6 Chi-Chi earthquake that induced loose soil

mantle. The essence of the internet-based decision sup-

port system is not to automatically show the potentially

dangerous area, but rather utilize a judgment process by

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Fig. 17 Display of streams prone to outburst debris flow whenTyphoon Mindulle brought heavy rainfall to Taiwan in 2004

Springer

428 Environ Monit Assess (2007) 127:419–428

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19?12?????????????????40???__???????

19?12?????????71?89?????20???__???????

19?12??????????????20???__???????

??????????????500????30???__???????

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????????__????tvbs??

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19?12?????????????40-80???__?????????

???????????????15-20???__???????

?????????TaipeiCity

????????????

KeelungCity

????????????

TaoyuanCounty

???????????? YilanCounty

????????????

HsinchuCounty

????????????

????????????

MiaoliCounty

????????????

TaichungCounty

????????????

TaitungCounty

????????????NantouCounty

?????????

ChanghuaCounty

????????????YunlinCounty

????????????ChiayiCounty

????????????

KaoshiungCounty

????????????

HualienCounty

????????????TainanCounty

????????????TainanCity

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PingtungCounty

????????????Kaoshiung

City

TaipeiCounty

Damage

Flood disaster

Debris flow disaster

Landslide disaster

Roads cut-off

Destroyed bridges

Destroyed Infrastructure corridors

others

Fig. 18 Hazard locations when Typhoon Mindulle broughtheavy rainfall to Taiwan in 2004

which information is collected to help experts judging

the location of the potential slopeland hazards. Victims

of slopeland hazards have been decreasing since the

implementation of the response mechanism by the As-

sessment Group in Taiwan’s Central Emergency Op-

eration Center for declaration and pre-evacuation in

potentially endangered areas during heavy rains. Nev-

ertheless, the system is limited by the available num-

ber of rain gauge stations and other environmental in-

formation especially in the mountainous areas. This

warning system can be further enhanced with the in-

corporation of GIS for the monitoring of spatial dis-

tribution of rainfall, and identifying the areas prone to

triggering slopeland hazards in zones that experience

torrential rainfall, and in combination with the QPE-

SUMS radar system for short-range rainfall distribution

estimation.

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