saarc journal jun 2010

Journal of South Asian Disaster Studies

Journal of the SAARC Disaster Management Centre

Volume 3 l Number 1 l June 2010

ii u Journal of South Asia Disaster Studies

SAARC Disaster Management Centre, New Delhi.

All rights reserved. No part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording or by any information stor-age and retrieval system without permission from SAARC Disaster Management Centre, New Delhi.

ISSN: 0974 6463

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Editor: O.P. Mishra and Mriganka Ghatak

Vol 3 No 1 June 2010 u iii

Editors Note vNotes on Contributors vii

1. GIS-based Assessment Of Coastal Vulnerability to Severe Cyclones 1 Along Andhra Pradesh Coast, India B.S. Prakasa Rao, N. Bhaskar Rao, N. Srinivas, G. Srinivas, K. Mrutyunjaya Reddy and M. Satyakumar

2. Glacier Lake Outburst Flood (GLOF) and its Estimation at 21 Nepals Higher Himalaya Binod Shakya

3. Usefulness of some Disaster Anticipatory Measures of Indian Railways 31 in Disaster Management Plan of Mega cities of India with Special Reference to Ahmedabad city. J.G. Macwan

4. Algorithm for Information Retrieval of Earthquake Occurrence from 47 Foreshock Analysis using Random Forest implementation in Earthquake Database Creation and Analysis: A Machine Learning Approach Pushan Kumar Dutta, Mrinal Kanti Naskar, Om Prakash Mishra, Kajal Mukherjee

5. A Concept of a Low-cost Construction Method for Deep Underground Dams 59 Yoshito Kobayashi and Vijay Kumar Jatiya

6. Assessment of Drought Vulnerability in North Western 81 Region of Bangladesh Shams Al-Amin, Umme Salma Rima and Md. Monsurul Huda

Contents

BINOD SHAKYA

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7. Quantifying Disaster Risk and Vulnerability at State 91 Level: A Case of Gujarat, India Shital Hardik Shukla

Vol 3 No 1 June 2010 u v

Editors Note

This issue of the Journal of South Asia Disaster Studies is a reflection of the wide spectrum of disaster

management research and practices going on in the South Asian region. The contributors of the research

documents belong to various levels of disaster management initiatives and national organisations, re-

search and academic institutions and research students in the field of disaster management from and

outside SAARC member states.

In the past decades, Geographical Information System (GIS) has emerged as a vital tool for collecting,

integrating, and finally assessing the datasets related to disasters. The first paper of this volume by Rao

et al. is based on application of GIS for impact assessment of Severe Cyclonic Storms (SCS) on the coastal

regions of the southern state of Andhra Pradesh in India. It uses various parameters like population,

resources, distance from the coast, landfall location of cyclones, cyclone track, slope of the ground and

storm surges and the study analysed 100 years data from Andhra Pradesh.

The glacial lakes nestled in the snow clad Himalayas are growing in size due to melting of glaciers as

a direct consequence of global warming. The communities residing near these lakes are exposed to severe

danger due to silent specter of Glacial Lake Outburst Floods (GLOF). The paper of Shakya proposes a sta-

tistical model based on lake parameters taking Lower Barun, Imja, Thulagi, and Tsho Rolpa glacial lakes

for which, estimates of GLOF risk in the downstream parts are made by the author.

The Indian Railways has one of the biggest global railway networks, and in spite of having a compre-

hensive disaster anticipatory mechanism, faces major accidents. Macwans paper addresses this vital issue,

and provides an overview of the strength and shortcomings of Indian Railways in handling disasters,

preparedness at managerial level, and Standard Operating Procedure (SOP) with reference to Ahmedabad

city in Gujarat. It also discusses the measures undertaken by the Ahmedabad Municipal Corporation in

addressing disaster related issues, constraints, etc. In his paper, the author advocates the need of includ-

ing the related points of Disaster Management Act 2005 of India in the Disaster Management Plan of

Ahmedabad city for effective disaster mitigation practices.

Large number of foreshocks prior to the main shock of an earthquake makes the analysis of earth-

quake catalogues a difficult task. Dutta et al. attempt a machine learning approach to extract attribute

value pairs from the earthquake catalogue, which enables study of earthquake occurrences on proper

compilation of earthquake data before and after the mainstream earthquake. The results outlined in the

research paper has estimated accuracy of the refined catalogue of 98. 81 per cent for correctly classified

foreshocks.

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There has been high degree of interest in construction of underground dams for sustainable surface

water management as these have certain advantages over the surface dams. However, there have been

some concerns regarding requirements of high-end technologies, involvement of heavy machinery and

steep construction costs in their construction. The paper of Kobayashi and Jatiya proposes an answer to

these concerns through Transverse Excavating and Infilling Method (TEIM) as a low cost and widely ap-

plicable construction method that can be applied for constructing deep underground dams.

In many parts of South Asia, the increasing atmospheric dryness conditions are verging on a state

of irreversible condition leading to potential desertification and degradation of already strained land re-

sources. Al-Amin et al. in their paper have proposed a GIS based dryness index map for the northwestern

part of Bangladesh, commonly known as the Barind tract. The paper uses Aridity Index (AI) as a numerical

indicator for dryness, and the maps are very useful for analyzing the trend of precipitation in the selected

study area.

One of the emerging prerequisites for mainstreaming Disaster Risk Reduction (DRR) into develop-

ment process is quantification of vulnerabilities of a region to natural disasters. The paper of this issue by

Shukla attempts to quantify vulnerability indicators up to district level for the western state of Gujarat. It

also discusses a regional model for assessing the pattern of vulnerability within the state, and identifying

the drivers of vulnerability in the state for effective identification of the vulnerable district and prioritisa-

tion of interventions in planning process.

This issue of the Journal of South Asia Disaster Studies exemplifies the emerging trend of highly in-

formative research, and policy analysis practices that is a reflection of the involvement of policy planners,

academicians, researchers, scientists of the region in the larger interest of making the South Asian region

disaster resilient, and shaping up a region with high degree of DRR standards. The volume is placed before

the disaster management stakeholders at various levels in the region for inviting critical appraisal of the

articles featured herein, which will undoubtedly contribute to the improvement of the journal.

O.P.Mishra

Mriganka Ghatak

Vol 3 No 1 June 2010 u vii

l Binod Shakya, Central Department of Hydrology and Meteorology, Tribhuvan University, Email: [email protected]

l B.S. Prakasa Rao, Department of Geo-Engineering, College of Engineering, Andhra University, Vi-sakhapatnam-530003. Email: [email protected]

l G. Srinivas, National Remote Sensing Center, Balanagar, Hyderabad-500625. Email: [email protected]

l J.G. Macwan, Doctoral student (Disaster Management), Singhania University, Rajasthan, India. Email: [email protected]

l Kajal Mukherjee, Geophysicist,Geological Survey of India, Kolkata, India.

l K. Mrutyunjaya Reddy, Andhra Pradesh State Remote Sensing Applications Centre, Hyderabad-500038.Email: [email protected]

l Mrinal Kanti Naskar, Electronics and Communication Dept., Jadavpur University, Kolkata,India.

l Md. Monsurul Huda, Junior Engineer, Institute of Water Modeling, Dhaka, Bangladesh. Email: [email protected]

l M. Satyakumar, Indian Meteorological Department, Hyderabad - 500016. Email: [email protected]

l N. Bhaskar Rao, Department of Geo-Engineering, College of Engineering, Andhra University, Vi-sakhapatnam-530003. Email: [email protected]

l N. Srinivas, Department of Geo-Engineering, College of Engineering, Andhra University, Visakhapa-tnam-530003. Email: [email protected]

l Om Prakash Mishra, Geological Disaster Division, SAARC Disaster Management Centre (SDMC), New Delhi, India

Notes on Contributors

l Pushan Kumar Dutta, Advanced Digital Embedded System Lab, Jadavpur University, Kolkata, India

l Shital Hardik Shukla, Assistant Professor, Sardar Patel Institute of Economic and Social Research, Opp. Udagam School, Drive In Road, ThaltejTekra, Ahmedabad-380054, Gujarat, India.

l Shams Al-Amin, Lecturer, Department of Civil Engineering, Ahsanullah University of Science and Technology, Dhaka, Bangladesh. Email: [email protected]

l Umme Salma Rima, Junior Engineer, Institute of Water Modeling, Dhaka, Bangladesh. Email: ri-mace045_03@yahoo. com

l Yoshito Kobayashi, Searcher, Motive Machinery Group, Center of Search Affairs,Industrial Property Cooperation Center Fukagawa-gatheria-west 3, Kiba 1-2-15, Koto-ku, Tokyo 135-0042, Japan. Email:

[email protected]

viii u Journal of South Asia Disaster Studies

AbstractAssessment and mitigation of flood hazard is an important component of sustainable development in coastal areas which are rich in various resources. About 25 per cent of Indias population lives within 50 km of the coastline. The east coast of India is more prone to cyclones arising in Bay of Bengal as about 80 per cent of total cyclones, generated in the east coast of India, strike here. Being one of the coastal states, Andhra Pradesh (AP) has a long coastline stretching about 1,030km out of 7,500 km of total coastline of India. The severe cyclonic storms during 1831-1970, 20 of them were landfall on the AP coast and accounted for 12,000 deaths. The damages and economic losses due to cyclones and floods are relatively higher in AP, which was estimated at Rs.18,469 core in various spheres. Despite the frequent occurrence of these cyclones, adequate measures to be taken to mitigate their impact need adequate study. Remote Sensing (RS) technology has proved its capability in providing vital information in a disaster situation; it could be used in disaster analysis, hazard zonation, and prior risk assessment. The study adopts RS andGIS (Geographic Information System) to assess the impact of severe cyclonic storms that landfall on the coastal regions of AP. Hence, an attempt is made to study each taluk along the coast and100 km inland (86 taluks) for assessment of vulnerability keeping in view the population, resources, distance from the coast, location of land falling of cyclone and its track, ground slope, and storm surge. The landfall of severe cyclones over 100 years of data is considered in the study. Vulnerability of the coastal taluks is arrived by assigning weight factors to each taluk based on various thematic informations depending upon their capability in the mitigation of storm and economic value. 44 per cent of the study area is categorised as high and very high level of vulnerability, and this area

Vol 3 No 1 June 2010 u 1

GIS-Based Assessment of Coastal Vulnerability to Severe Cyclones

along Andhra Pradesh Coast, India

B.S. Prakasa Rao, N. Bhaskar Rao, N. Srinivas, G. Srinivas, K. Mrutyunjaya Reddy, and M. Satyakumar

B.S. PRAKASA RAO , N. BHASKAR RAO , N. SRINIVAS , G. SRINIVAS, K. MRUTYUNJAYA REDDY AND M. SATYAKUMAR

needs special attention during cyclone period to mitigate the human and related loss.

Key words: Coastal Vulnerability, Severe Cyclone, Estuarine region, Landuse/Landcover, Weight factor.

IntroductionTropical cyclones are very destructive natural hazards with an average wind velocity of 17 m/s. The east coast of India is more prone to cyclones arising in Bay of Bengal as about 80 per cent of cyclones generated in the sea could landfall on the east coast. Vulnerability to disaster can be defined as a gap in community coping capacity, or inherent protection, against the disaster characteristics. Study of historical data on floods and cyclones and its integration in GIS will throw light on the vulnerability of coastal area. The number of peer-reviewed papers in the field of science, impacts and vulnerability along the Indian coasts has been low. Considering the magnitude of these problems and also the long-term interests, research on impacts and vulnerability to the coasts and the necessary adaptation measures is needed (Unnikrishnan 2011:1273). There are numerous reasons why we must live and work in regions subject to cyclones. Hence, proper measures should be adopted to reduce the impact of cyclones. Vulnerability assessment is essentially a systematic integration of factorstopography, slope, morphological features, engineering characteristics of structures, and socioeconomic aspects and infrastructure facilities. Universities need to take up local issues on impacts and adaptation. GIS is capable of assembling, storing, manipulating, and displaying geographically referenced information (Burrough 1986).

Coastal vulnerability is studied by Jayanti (1998:115) as a function of cyclone frequency, coastal topography, bathometry, and population density.Vulnerability was measured and a disaster risk index for the Indian coast was derived at. The Multi Purpose Cyclone Shelter Project (MCSP) in Bangladesh (MCSP 1992) has delineated risk zones by modeling the storm surge with GIS. Damen and Van Western (2003) have studied vulnerability and risk analysis for Bangladesh using population density and storm height. Prakasa Rao (2005: 3611)developed a methodology for the estimation of cyclone-induced flood through remote sensing and GIS for two delta regions in AP.The capability of applying GIS in various aspects of risk assessment has been demonstrated by many researchers. Specifically, Miller and Onwuteaka (1999: 460) evaluated the vulnerability of the landscape to oil spills in the East. Granger et al. ( 1999) equally utilised GIS to synthesise and model the spatial relationship between vulnerability and hazard in

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order to study the risk faced by Cairns in Australia to multi-hazard phenomenon. Thumerer et al. (2000: 265) developed a GIS-based risk assessment model by combining oceanographic and climatic data with data on sea defenses, elevation values and patterns of land use to assess the implication of sea level rise along the English east coast using the Arc-Info GIS package. These include (Jorinet al. 2001: 153) for land suitability assessment, and (Pramojanee et al. 1997: 17) for flood vulnerability mapping. Krishna (2005:1339) discussed science for coastal hazard preparedness to tsunamis, seismicity, storm surges and coastal pollution.Van Westen (2008) used simple data sets from Colombia (South America) to demonstrate on a national scale the meaning of hazard, vulnerability and risk. Similar procedures were used by Damen and Van Westen(2008b) to model cyclone hazard zonation in the South of Chittagong, Bangladesh;Van Westen and Tertien (2008) to demonstrate the potentials of GIS in hazard zonation of landslides triggered by earthquakes in Manizales, Colombia, and Van Westen (2008) to demonstrate the use of quantitatively defined weight values in the making of hazard maps. The overall aim of Udoh and Ekanem (2011: 205) was to examine the ways GIS can be used to effectively appraise the degree of threat posed by oil spill Coastal areas of AkwaIbom State (1989), Nigeria.The present paper describes in detail the methodology for developing vulnerability degreeby making use of GIS to map, analyse, assess, and present these indices in the form of national vulnerability profiles taking taluk as a spatial unit of analysis.

An important component of the coastal population is the seafaring community, of which fishermen form a sizable part although cyclonic damages are severe in the delta regions of the Rivers, Vamsadara, Godavari and Krishna, mitigation measures against floods are said to be meager. Hence, an attempt is made to assess the vulnerability of the coastal area of AP.The total number of villages perched along the coastline is 2,482500 are within 5 km swathe extending inside from the coast, 601 are within 5-10 km and 1,381 villages are between 10-20 km. Coastal AP covers an area of 98,926 sqkm with a total population of 3,15,70,722 as per 2001census. The coastal area of the state, with a significant component of its economy, is related to the sea in some way. This includes fishing, shipping, ports and harbours, and tourism and allied industries in the coastal region. The last few years have also seen new investment being made in the Indian coastal waters (on the continental shelf and slope) for oil and gas exploration. These could eventually become a critical component of the economy. With these new developments also come new threats, while these offshore structures are vulnerable to severe cyclones, storm surges, and tsunamis.


GIS-BASED ASSESSMENT OF COASTAL VULNERABILITY TO SEVERE CYCLONES ALONG ANDHRA PRADESH COAST, INDIA



Historic background of cyclonic eruptions in the state From 1977-2008, there were 29 severe cyclones landfall on AP coast. Table 1 represents a brief history of severe cyclones that have occurred from 1977 to 2008 and the losses occurred in various spheres (damage statistics before 1977 are not available):

Factors that have combined to compound natural disaster vulnerability along the AP coast are: Over50percentofcyclonesintheregionturnintoseverestorms,whichareoften

accompanied by storm surges The low-lying lands that prevail along Godavari, Krishna, and Pennar deltas and

Pulicat lake are subject to widespread flooding and deep inland sea water incursion that even a few metres high storm surge can create

High concentration of population, infrastructure, and harbour-related economicactivities along the shore line

Experiences with the cyclones in AP stressed the need for modernisation and strengthening of existing infrastructure. Therefore, it is proposed to construct new cyclone shelters as well as missing road links/bridges under Component B of the National Cyclone Risk Mitigation project (NCRMP, 2009: 4).

The following severe cyclonic storms that landfalls AP coast are considered for the study (Table 2). These tracks are digitized and created shape files and these are overlaid on the study area having taluk boundaries to identify the vulnerability of each taluk with reference to the track.

Table 1: Brief History of Severe Cyclones 1977 to 2008

No of severe cyclones/Cyclonic storms 18

Population Affected (in Lakh) 218.30

Human Loss 12,000

Livestock loss (in lakh) 6.63

Houses damaged (in lakh) 35.71

Damaged Cropped area (in lakh hectare) 59.65

Estimated loss (in Crore) 18,468.57



Table2: Severe Cyclonic Storms 1906 to 2003 during May, October and November

S.No Year Month Period Nearest location of landfall

1 1906 October 7th to 9th Bheemunipatnam

2 1907 October 1st to 2nd Chillakur

3 1914 May 13th to 16th Ichchapuram

4 1925 May 13th to 16th Koduru

5 1932 November 22nd to 27th Sullurpeta

6 1933 November 14th to 18th Kothapatnam

7 1938 November 21st to 28th Nagayalanka

8 1940 May 17th to 8th Indukurpet

9 1966 November 18th to 22nd Santhabommali

10 1966 November 1st to 8th Vakada

11 1968 November 2nd to 5th Chillakur

12 1969 November 6th to 8th Allavaram

13 1972 November 22nd to 23rd Sullurpeta

14 1976 November 4th to 5th Machilipatnam

15 1976 November 16th to 17th Kavali

16 1977 November 15th to 20th Chirala

17 1977 October 29th to 31st Kavali

18 1979 May 8th to 13th Vidavalur

19 1979 November 21st to 25th Tada

20 1979 November 23rd to 29th Nizampatnam

21 1982 October 17th to 21st Tada

22 1982 October 15th to 16th Katrenikonda

23 1983 October 2nd to 6th Bheeminipatnam

24 1984 November 12th to 13th Vakadu

25 1985 October 10th to 11th Rambilli

26 1989 November 6th to 8th Kavali

27 1990 May 6th to 11th Nizampatnam

28 1998 November 14th to 16th Visakhapatnam

29 2003 December 14th to 16th Kruthivennu



Study areaThe study area covers 86 taluks of AP spread along the coast and about 100-140 km in-land.Geographically, it is located between 780 46 to 840 45 East longitude and 130 01 to 190 16 North latitude (Figure 1).The study area is extracted from the digital database oftaluk map of India.

The coastal districts are primarily agricultural-based. Guntur, Krishna, East Godavari, West Godavari, and Nellore have highly productive network of irrigation canals of the Krishna and Godavari rivers. These four districts, along with Srikakulam, also face the brunt of floods during the monsoons now and then. The coastline ranging from Srikakulam in the north and Nellore in the south is affected by at least one severe/very severe cyclone almost every year.

Data and MethodologyThe cyclonic tracks of 1906-2003, the huge occurrences in the recent years, were selected for the study during the months of May, October and November. About 100 years of se-vere cyclonic storms are considered in the present study. The satellite data is:

Resourcesat-AWiFS sensor data are used to prepare the mosaic of the study area after geo-rectifying the data. This data is selected to show the present status of land use and land cover and other geomorphologic features, which are important for vulnerability assessment.

In order to create the vulnerability map, attribute tables are created for the following input mapssevere cyclonic tracks, population data of all the taluks and creation of density map, various taluks and their distance from the coast by creating buffer zones, location of taluks with respective to cyclone tracks,extraction of coast from image data preparation of slope map from ASTER DEM, and preparation of land use land cover from AWiFS data. Weight factors are assigned to each taluk and their location with respective to various above factors. A vulnerability map is prepared by integrated weight factors of the above themes.

Satellite Path Row Date of pass

Resoucesat-(AWiFS) 105 056 January 24, 2009

099 060 March 07, 2009



Figure 1: Location of the study area



Direction of the cyclone trackThe areas in the direction of cyclone track/nearby will have maximum effect due to flood inundation and strong winds. Hence, this parameter is important in the determination of vulnerability risk. Considering the direction of the movement of the cyclonic storm, buffers have been created on taluk map up to a distance of 40 km on the both sides of the main track, assuming the approximate area of maximum influence of the cyclone would be up to 40 kmrange on both sides of the track, while the risk would be less with increase in distance from the track. While assigning the weight factors, 10 is assigned to taluks in the direction of the track and up to 20 km on either side. Factor 5 is assigned to 20-40 km distance from the track. The remaining taluks are assigned with factor 1. The landfall of cyclones is shown over the study area as shown in Figure 2.

Land use/Land coverIn order to study the land use and land cover, the Resourcesat data is taken to build classi-fication map of the study area.The area is covered in two scenes of AWiFS sensor data and the scene informationis given in the above table. It is 10-bit data with spatial resolution of 55 m. The scenesare geo-referencedusing reference maps of 1:250,000 toposheetsin ERDAS software. These scenes are used to prepare mosaic and the study area polygon is taken to extract the image by preparation of subset (Figure 3). The study area is demar-cated with a boundary line in white colour from the total state image of the state.

Land use land cover, one of the important inputs for vulnerability map that has to be given priority during cyclones, as it reflects the economy of the region. The image is classified into 7, land use land cover classes using Maximum Likelihood Algorithm in ERDAS software. The land use classes are agriculture land, fallow land, semi-ever green forest, deciduous forest, evergreen forest, water bodies, and others. Others class include settlements, road network, etc.

Classification result shows that about 80 per cent of the study area is occupied with agricultural land,which is mostly spread along the coast and confined in river deltas and flood plains. Accordingly, maximum weight is assigned to this class and the other classes are given low priority. Various land use classes and their areal extent are given in the Table3.



Agriculture land and Wetlands (lakes, etc.) are shown in yellow and blue respectively. The former is an important component of ecosystem and the latter form the economy of the region. Generally the coastal areas are highly prone to flood/inundation during sever cyclones due to heavy rain and storm surge aroused from strong winds. The areas, with

Figure 2: Landfall of sever cyclonic storms over the study area

Table 3: Land use classes and their areal extent in the study area.

S.No. Classification Area occupied in sqkm % of Total area

1 Agricultural Land 81,014.00 81.89

2 Fallow Land 4,371.62 4.42

3 Semi Green Forest 817.57 0.82

4 Deciduous Forest 5,546.12 5.60

5 Ever Green Forest 390.20 0.40

6 Water Bodies 4,747.49 4.80

7 Others 2,040.00 2.07



intensive agriculture, nearer to the coast and adjacent to the delta have been assigned weight factor 10 indicating high priority zone where as the areas of barren land, away from the coast are assigned weight factor 1. Weights are tabulated to all the taluks for the land use/land cover classes. The satellite image and corresponding classification maps are shown Figure 3.

Ground slopeDEM of land surface provides significant information for many research activities and important data as the input of image processing and image analysis, such as image cor-rection due to height of land surface (Ortho rectification), contour mapping, 3D images generation, disaster management (determination of vulnerable area due to landslide, flood and tsunami disaster), monitoring land subsidence phenomenon and many oth-ers. ASTER (Advance Space borne Thermal Emission and Reflection Radiometer) DEM is downloaded from the web site. ASTER on board of Terra spacecraft is multi-spectral opti-cal sensor that is launched on December 1999. ASTER sensor has 14 spectral bands that range from visible to thermal infrared band. There is also stereo coverage in band from 3n (nadir looking) 3b (backward looking). Therefore, the capabilities of ASTER stereo image that provides DEM with high spatial resolution (30 m) is very important for remote sens-ing and GIS (Geographic Information System) users to enhance the accuracy of desired height information.

(a) AWiFS image of AP state (b) Land use/land cover

Figure 3



A ground slope map is prepared using the DEM data in Arc GIS. Slope is derived in degrees and is broadly divided into 4 categories, which ranges from 0 to 5, 5 to 10, 10 to 20, and > 20 for the study area. The range 0 to 5 is considered as plain area, 5 to 10 as moderate slope, 10 to 20 moderately steep, and > 20 is taken as steep slope. The areas near the coastal plain come under 0 to 5 are given high weight value whereas lower values are assigned for other categories of slope. The weight factor 10 is assigned to slope 0 to 5 range, factor 5 to moderate slope and 1to moderately steep and steep slopes. The slope map is shown in (Figure 4a).

Population Density The population density is high along the coast due to agricultural resources industrial establishments, which generally depend on water resources of the area. Hence, major-ity of cities are located along the coast with dense population, ports, and shipyards. The population density is very important parameter in vulnerability mapping of any area. Demographic details are obtained from the Department of Statics and Population Stud-ies, Government of India censes 2001. Population density map is prepared taking taluk as a unit. Collected population data is divided with the area of the taluk and tabulated as density per square kilometer and spatial distribution of density map is prepared. Popu-lation density is shown in 4 classes; namely very high, high, medium and low. Different colours are assigned to each density class as shown in Figure 4b.Thus, any single taluk with population in a definite range has single colour. Also more than one taluk may have a single colour as they may have population with the same range.

In the present analysis, the taluks with more population are located nearer to the coast or cyclone path have been given higher weights, as there would be heavy human loss if a cyclone landfall on these areas.The areas with low population density and away from the track or coastline are given lower weights. All the four categories are assigned by the factors 2, 6, 8 and 10 according to density ranges in increasing order. Visakhapatnam and Vijayawada taluks showed high density, and Vizianagaram and Sulurpet showed the medium level of density followed by remaining taluks.

Distance from the coastThe coastal area and the delta region commonly are very fertile with adequate water re-sources, and hence are the centers of immense human activity. Therefore, the assessment of their location with respective to the coast is essential in deriving the vulnerability of an area for flood hazard.



Buffer zones have been created for every 20km distance from the coast. Likewise, 4 buffers have been created in Arc GIS and weights are assigned to each taluk. Considering the distance of the taluk from the coast and main river course, weight factors have been assigned. The weight factor 10 is assigned to first 20 km and 5 assigned to 20-40km distance and 1 is assigned to 40-60 and beyond. The nearest/along the coastline, the value of weight is maximum while the factor decreases with increasing distance from the coast. There are 31 taluks in the first buffer zone and 20 in the second level of intensity of the study area (Figure 4c), which shows that 51 taluks are under flood threat.

Storm surgeThe storm surge is the sudden rise of seawater due to tropical cyclone and is greatly ampli-fied when the coastal water is shallow, in the estuarine region and the shape of the coast is like a tunnel. Because of the dense populations along the coast, storm surge associated the cyclones is the greatest potential threat to life and property. It is, sometimes a large dense of water from 80 to 150 km wide that sweeps across the coast line where the cy-clone makes its landfall caused by the high winds pushing the ocean surface ahead of the storm. (Krishna Rao, and Ramana Murty, 2003: 2). The level of the surge in a particular area is determined by the intensity of the storm and the slope of the continental shelf. A shallow slope off the coast will allow a greater surge to inundate coastal communities.

The phenomenon is so sudden that there is hardly any time for the victim to react and unless and until prior evacuation is carried out, the loss of life in the effected region will be nearly complete. The storm surge map of the AP coast is taken from the APCHMP report and scanned. The scanned map is geo-referenced and digitised the boundary of the storm surge and overlay on the taluk boundary map. The weight factor 10 is assigned to taluks covered by the storm surge boundary and 5 is to half or partly covered taluks and 1 to the uncovered. The taluks existing along the coast from Nellore to Kakinada have shown the effect of storm surge. However, its affect is more in the case of Machilipatnam and Avanigedda taluks(Figure 4d).



(a) (b)

(c) (d)Figure 4.a. Ground slopeb. Population densityc. Buffer zones from the coast,

d. Storm surge



Table 3: Weight factors based on location and theme.

DISTRICT TALUK Weight factors

Direction of the track

Land Use/Land Cover

Slope Population density

Distance From the coast

Storm surge

Result

Srikakulam Sompeta 5 1 10 6 10 1 High

Pathapatnam 10 1 1 2 5 1 Medium

Tekkali 10 10 10 6 10 1 V. High

Palakonda 1 1 1 2 5 1 Medium

Srikakulam 10 10 10 10 10 1 V. High

Narsannapeta 5 10 10 8 10 1 High

Ichchapuram 10 1 5 10 10 1 High

Chipurupalle 10 10 10 2 10 1 High

Vizianagaram Parvathipuram 1 1 1 2 1 1 Low

Salur 1 1 1 6 1 1 Low

Bobbili 1 1 1 8 1 1 Medium

Gajapatinaga-

ram

1 1 1 6 1 1 Medium

Vizianagaram 5 1 5 10 5 1 High

Srungavarapu-

kota

1 1 1 2 5 1 Medium

Puspatirega 10 10 10 6 10 1 V. High

Visakhapat-

nam

Paderu 5 1 1 2 1 1 Low

Anantagiri 1 1 1 2 1 1 Low

Chodavaram 5 1 1 2 5 1 Medium

Chintapalle 1 1 1 2 1 1 Low

Bhimunipat-

nam

10 10 10 8 10 1 V. High

Vishakhapat-

nam

10 10 5 10 10 1 V. High

Anakapalli 10 1 5 6 10 1 High

Narsipatnam 5 10 10 2 5 1 High

Yellamanchili 10 10 5 2 10 5 V. High



East Godavari Ellavaram 5 1 1 2 1 1 Low

RampaChoda-

varam

1 1 5 2 1 1 Low

Tuni 10 10 10 8 10 10 V. High

Prathipadu 5 10 5 6 5 5 High

Rajahmundry 5 1 10 10 1 1 Medium

Peddapuram 5 10 10 8 5 5 High

Pithapuram 10 10 10 10 10 10 V. High

Kakinada 10 10 10 10 10 10 V. High

Kottapeta 10 1 10 8 5 5 High

Ramachan-drapuram

10 10 10 8 5 5 High

Mummidivaram 10 10 10 6 10 10 V. High

Amalapuram 10 10 10 10 10 10 V. High

Razole 10 10 10 8 10 10 V. High

Yanam Yanam 10 10 10 4 10 10 V. High

West Godavari Polavaram 5 1 1 2 1 1 Low

Chintalapudi 1 1 1 2 1 1 Low

Kovvur 5 1 5 6 1 1 Medium

Eluru 5 1 5 8 1 1 Medium

Tadepallegu-

dem

5 10 5 8 1 1 High

Tanuku 5 10 10 8 5 5 High

Bhimavaram 10 10 10 8 5 10 V. High

Narsapur 10 10 10 8 10 10 V. High

Krishna Vijayawada 5 10 5 10 1 1 High

Nuzvid 1 1 1 6 1 1 Low

Kaikalur 10 1 10 6 5 10 High

Gannavaram 5 10 5 6 1 1 High

Gudivada 10 10 10 8 5 5 V. High

Machilipat-

nam

10 10 10 8 10 10 V. High

Avanigadda 10 10 10 2 10 10 V. High



Guntur Sattenapalle 5 10 1 2 1 1 Medium

Guntur 10 10 5 10 1 1 High

Tenali 10 10 10 8 5 5 V. High

Narasaraopet 5 1 5 8 1 1 Medium

Vinukonda 5 1 1 2 1 1 Medium

Repalle 10 10 10 6 10 10 V. High

Bapatla 10 10 10 8 10 10 V. High

Prakasam Markapur 1 1 1 2 1 1 Low

Addanki 5 1 5 2 5 5 Medium

Chirala 10 10 10 8 10 10 V. High

Darsi 1 1 5 2 1 1 Medium

Giddalur 1 1 1 2 1 1 Low

Podili 5 1 5 2 1 1 Low

Ongole 10 10 10 8 10 10 V. High

Kanigiri 1 1 5 2 1 1 Low

Kandukur 10 10 10 2 10 10 V. High

Nellore Udayagiri 5 10 1 2 1 1 Medium

Kavali 10 10 10 2 10 10 V. High

Atmakur 5 10 5 2 5 1 High

Kovvur 10 10 10 2 10 10 V. High

Nellore 10 10 10 10 10 10 V. High

Rapur 5 10 5 2 5 1 High

Gudur 10 10 10 6 10 10 V. High

Venkatagiri 5 10 5 2 5 1 High

Sulurpet 10 10 10 10 10 10 V. High

Cuddapah Badvel 1 10 1 2 1 1 Medium

Sidhout 1 1 1 2 1 1 Low

Rajampet 1 1 1 6 1 1 Medium

Chittoor Sri Kalahasti 1 10 1 2 5 1 High

Chandragiri 1 1 1 2 1 1 Low

Satyavedu 5 10 5 2 5 5 Medium

Puttur 1 1 1 2 1 1 Low

Chittoor 1 1 1 2 1 1 Low

Vulnerability mapAs discussed above, the weights are tabulated to all the taluks for all vulnerability param-eters as shown in Table 3. To all classes in the above maps, different weight values are assigned in their attribute table. Finally, all factor maps are analysed in Arc GIS software to obtain a hazard map which is then classified into four classes: low, moderate, high, and very high vulnerability hazard. The vulnerability map is shown in Figure 5.

There are 20 taluks, which spread along the coast come under very high category of vulnerability to cyclone-induced floods. Under high vulnerability category, 9 taluks are along the coast and 9 taluks are 20 km away from the coast which are spread in Guntur, Krishna, East Godavari and Northern districts. 44 per cent of the taluks are categorised as very high and high and the remaining come under medium and low category of vulnerability. On the levels of extent of damage arrived at form ground truth, for the



Figure5: Vulnerable intensity of the study area


study area. This ground data are comparable with the levels of vulnerability arrived from this integrated study. The remaining taluks of the study area come under medium and low vulnerability. Special attention be given to these taluks in providing better infrastructure, shelter belts along the coast, cyclone shelters, better drainage facility to mitigate the losses due to floods. The hazard storm surge could be controlled by mangrove afforestation and shelterbelts in the case of taluks right on the coast with plains.

ConclusionThe study of the coastal AP for flood vulnerability has high importance to manage the flood disaster in the state. An ideal flood disaster management system need to support the activities related to preparedness, damage assessment and rehabilitation based on the vulnerability map. The space inputs could be used in taking preventive measure through vulnerability analysis, hazard zonation, and prior risk assessment at regional and local levels. Hence, an attempt is made to study the coast vulnerability of AP using spatial out puts and the secondary data.

The area immediately close to the coast is relatively less populated, less accessible due to poor communication. The people living in the belt of 20 km from the coast generally comprise fisher folk and weaker sections and majority of them live in thatched houses, which are vulnerable to the wind pressures of cyclonic gale, which exceed 100 km per hour. Out of 86 taluks of the study area 38 are under threat to cyclone-induced floods. The risk index estimated by Jaiyanti (1998: 115) has indicated C (11- 15 of 1 to 25 scale) category to the above coastal area. However, it is to be rated as B due to its economic importance and population density in the present context.

The major cities Srikakulam, Visakhapatnam, Machilipatnam, Kakinadaand Nellore are densely populated with major industries which are within the above zone besides major deltas of Krishna, Godavari and Pennar rivers. Hence, the study results are to be adopted to improve flood management strategies, necessary precautions to reduce the population losses, crop damages, housing problems and infrastructure facilities in the coastal areas, based on their vulnerability.

Acknowledgement The first author acknowledges DST for awarding 3D flood simulation project. He also extends his thanks to AICTE for awarding Emeritus Fellowship.


ReferencesAkwaIbom State, AkwaIbom State- Physical Background, Soils andLand use and Ecological

Problems, Technical Report of the Task Force on Soils and Land use Inventory, AkwaIbom State, 1989.

Burrough P.A., Principles of Geographic Information Systems for Land resources Assessment,(Oxford,

the UK: Clarendom Press, 1986).

Damen M.C.J. and Van Westen C.J., Modelling Cyclone Hazard in Bangladesh. ILWISApplications

03, 2008b.ITC, http://www.itc.nl/ilwis/applications /application03.asp.

Damen M.C.J. and Van Westen C.J., Modeling Cyclone Flood Hazards and Population at Risk in

Bangladesh. Application guide chapter-3, 2003.Goswami P., and Ramesh K.V., Extreme Rainfall Events: Vulnerability Analysis for Disaster Management and Observation System Design. Current science, vol. 94, no. 8, April 25, 2008, pp. 1037-1044.Granger K., Jones T., Leibaand M., Scott G., Community Risk in Cairns: A Multi-Hazard Risk

Assessment. Australian Geological Survey Organization, Commonwealth Australia, 1999.

Jayanti N., Cyclone hazard, Coastal Vulnerability and Disaster Risk Assessment along the Indian

Coasts,Vayumandal, vol.28, no.3-4, July-December1998, pp. 115-119.

Jorin F., Theriaultand F.M., Musy A., Using GIS and Outranking Multicriteria Analysis for Land-

use Suitability Assessment, 2001, Int. J. Geogr. Info. Sys, 15(2):153 - 174.

Krishna K.S., Science Plan for Coastal Hazard Preparedness,Current science, vol. 89, no. 8, October

25, 2005, pp. 1339-1347.

Krishna Rao A.V. and RamanaMurty P.V.,Andhra Pradesh Cyclone Hazard Mitigation Project

Integrated Coastal Zone Management in Andhra Pradesh, Storm Surge Preparedness Plan, July

2003.

Miller J.B., and Onwuuteaka J., Oil Spill Emergency Response GIS: Using GIS to Model Environmental

Vulnerability in Coastal Oil Fields, 1999, East Central Nigeria, in Proceedings of ESRI Users

Conference ,http:gis.esri.com/library/userconf/proc99/proceed/papers/pap460/p460.htm.

Multipurpose Cyclone Shelter Programme (MCSP) - Draft final report, vol. IV, Planning and

development issues, UNDP/World Bank/GOB project BGD/91/025,1992.

Prakasa Rao B.S., Ammineduand E., Murty K.S.R., Estimation of Flood Vulnerability Index for

Delta Areas through RS&GIS. International Conference on Geosciences and Remote Sensing,

Coexseoul, Korea, IEEE proceedings vol. 5, July 2005, pp. 3611-3614.

Thumerer A., Jones P. and Brown D., A GIS based Coastal Management Style for Climate Chang

Associated Risk on the East Coast of England, 2000, Geogr. Info. Sci., 14(3): 265-281.

Triskti Bambang and Carolita Ita, Comparison Result of DEM Generated from ASTER Stereo Data

and SRTM. Research officer of the Indonesian National Institute of Aeronautics and Space

(LAPAN), GIS development.net




Udoh J.C. and Ekanem E.M., GIS-based Risk Assessment of Oil Spill in the Coastal Areas of

AkwaIbom State, Nigeria, 2011.

Unnikrishnan A.S., Assessment of impacts and vulnerability to Indias coastline due to climate

change,Current science, vol.100, no.9, May 10, 2011, p.1273.

Van Westen C.J. and Terlien M.T.J.,Seismic Landslide Hazard Zonation, 2008,ILWIS Applications

07, ITC, http://www.itc.nl/ilwis/applications /application07.asp.

Van Westen C.J., Hazard, Vulnerability and Risk Analysis, 2008, ILWIS Applications 1, ITC,

http://www.itc.nl/ilwis/applications /application1.asp.



AbstractChanging climate and global warming are the key issues today due to which the world com-munity isfacing several risks. According to D. Douglos, the magnitude of warming was rapid in the 19thcentury than in the 17th and 18th century in Nepal. In addition, the research shows that annual warming at Himalayan region of Nepal, between 1977 and 1994, was found to be 0.060C/year. These changes could have large effects on Himalayan glaciers by shrinkage of glaci-ated areas. Also, there will be substantial increase in the aerial extent of Glacier Lake which may cause catastrophic Glacial Lake Outburst Floods (GLOF). During GLOF, the rocks and debris are also released into the valleys downstream with such intensity that the valley floor is badly eroded, and becomes extremely unstable. The extent of GLOF damage depends on the speed of the release of the impounded glacier waters. The method presented in paper will enable researchers and plan-ners to estimate GLOF at downstream of lake.

Key words: GLOF, IPCC,Zangzhangbo

BackgroundIntergovernmental Pannel for Climate Change (IPCC 2001 b) indicates that warming in the Asian Region is projected to be 30C by 2050. According to Douglos (1995), the mag-nitude of warming was more rapid in the 19thCentury than in the 17th and 18th century at higher elevation in Nepal. In addition, the annual warming of the Himalayan Region of Nepal between 1977 and 1994 was found to be 0.060C/year (Shrestha et al 1999). These

Glacier Lake Outburst Flood (GLOF) and its Estimation at Nepals

Higher Himalaya

Binod Shakya

BINOD SHAKYA


changes could have large effects on Himalayan Glaciers by shrinking of glaciated areas. Also, there will be substantial increases in the aerial extent of glacier lakes, which may cause catastrophic Glacier Lake Outburst Floods (GLOFs). Rapid melting of snow enlarge the existing Glacier Lake or create a new Glacier Lake and a small disturbance can break the Glacier Lake dam resulting in release of huge amount of water and generates a devas-tating flood (J.E. Costa, 1988).

In Nepal, Climate change and GLOF studies have been carried out by different insti-tutions including government organisations, international non governmental organisa-tions, academic institutes and the privet sector. CDHM 1999 report showed the growth of glacier lakes and the formation of new glacier lake in the Nepals Eastern Himalayas with liable threats of GLOF. Between 1960 and 2000, moraine dammed lakes increased from 33 to 89 in numbers in Khumbhu Region only. Further, it was reported that total moraine dammed lakes reached 7.254 km2 from 2.291 km2 (Bajracharya et al 2007). In 2001, B. Shakya identified the most potentially dangerous glacier lakes using criteria based on, size of a lake and topographic features around the lakeLower Barun glacier Lake, Imja glacier lake, Thulagi glacier lake, and TshoRolpa glacier lake. Dig Tsho Glacier Lake was considered a potentially dangerous glacier lake and it burst in August 1985. ImjaGlacierLake is a similar type of potentially dangerous lake with rapidly expanding and larger lake. The estimated volume of water stored in the lake was around 28 million m3 in 1992 and 35.8 million m3 in 2002 (Bajracharya et al 2007). The study carried out by B. Shakya 2001 over 9 EasternNepal Himalayan Basin shows active formation of lakes over six basins out of nine.

From various researches, it was noted that Eastern Nepal and the adjoining Tibet Re-gion (China) have most active glaciers and there are numerous occurrences of glacier lakes over there. The detailed studies of GLOF of the Himalayan region were not done properly. But, after GLOF of Zhangzamgbo1981 and Dig Tsho 1985, the scientific atten-tion of the phenomena was realized (WECS Report, 1988). The records show that most of the cases GLOF have occurred on all major tributaries of the Saptakoshi catchment.

WWF Nepal and Tribhuvan University, Department of Hydrology and Meteorology have jointly carried out vulnerability assessment from climate change to GLOF in Khum-bu Region (sub basin of Saptakoshi catchment) in 2007. Though the environment looks calmduring assessment, a high threat of GLOF to new settlements, hotels and lodges in the future was anticipated especially from LakeImja. Some settlements were highly exposed to GLOF, but such settlements are still growing despite the threat of GLOF (B. Shakya and K.B. Thapa, 2007).



GLACIER LAKE OUTBURST FLOOD (GLOF) AND ITS ESTIMATION AT NEPALS HIGHER HIMALAYA

During GLOF, the rocks and debris are also released into the valleys downstream with such intensity that the valley floor is badly eroded, and becomes extremely unstable. The extent of GLOF damage depends on the speed of the release of the impounded gla-cier waters. If it is gradual, the effect may not be as devastating. The GLOF impact is generally devastating at nearby settlements and infrastructures of downstream of lake that are situated near or across the river. In addition to this GLOF occur randomly and give insufficient warning, they may cause much damage to human settlements of upper mountain areas. Dig Cho GLOF of August 1985 destroyed nearly completed Namche small hydroelectric project. Even small GLOF of Chuffing on July 12, 1991 destroyed six houses and riverbanks. The GLOF of Zhagzanbo at Poque on 1981 July (Bhote - Sunkoshi) destroyed the diversion wire at the Sunkoshi hydroelectric project in Nepal. Two bridges were also swept away. Therefore,to reduce the vulnerability from GLOF in Nepal, manage-ment of settlement, proper designing of major infrastructures such as bridge, dam, roads, etc. are necessary. To approximately design Lake burst flood and anticipated Lake burst flood level for settlement, it is first necessary to estimate the volume of flow at outlet of lake and at the downstream of the lake. This paper aims to present some formulae to estimate GLOF at outlet of lake and at the downstream of lake. The research is based on Scientific Research of Central Asian Hydrometeorological Institute (SANIGMI) conducted between1998 and 2001. The developed formulas are based on lake volume and statistical modeling of past GLOFs data from Nepal and other lake burst data. The paper also aims to present implementation of method on Imja Lake study by WWF project.

GLOF in NepalThe detail studies of GLOF of the Himalayan region were carried out properly before 1980s, nevertheless, after GLOF of 1981 (Zhangzamgbo) and 1985 (Dig Tsho) the scien-tific attention of the phenomena was realized (WECS Report, 1988). Most of the GLOF cases were identified at the all major tributaries of the Saptakoshi catchment. Some of the recorded events are:

GLOFonBhotekoshifromDigTsho(August04,1985) TinkoGLOFof1982inYairuzangboRiverofPoiquecatchment(inTibet,Chinaand

Arun catchment in Nepal) GLOFonBhote-SunkoshiinNepalfromZhanzangbolake1964,1981 GLOFfromPhuchanglacierlakesontheTamurriverin1980andNareglacierlakes

(South slopes of Mt. Ama Dablam in Nepal) in 1977

BINOD SHAKYA


GLOFofAyacoatNorthernslopeWestofMt.EverestinPumpquecatchment(Tibet,China) 1968, 1969 and 1970

GLOFofChubungJuly12,1991Rolwalingvalley GLOFofZhagzanbolakeatPoquinJuly1981(Bhote-Sunkoshi)

The location of glacier lakes bursts are presented in Figure 1.1.

Figure 1.1: GLOF in Nepal

Dam Break ModelsThe GLOF modelling is in the initial stage in Nepal. S. Bajracharya et al 2007 attempted to predict GLOF attenuation from Imja Lake using Hydrodynamic model. Nevertheless, many types of Dam Break Flood models have been developed worldwideranging from simple computation based on historical dam failure data to complicated hydrodynamic models. It is very complicated and complex to collect detail field survey of Himalayan



Glacier Lake and river cross-sections. In such case, the reliable estimation of the peak flow and flow attenuation at downstream from a dam is statistical modeling from historical dam failure data. Kirkpatrick in 1977 shows relation between flow volume and height of dam considering 21 dam failure data and statistical modeling. Similar type of equation was developed by U.S Soil Conservation Service in 1981 produce relations using 31 dam fail cases. Hagen in 1982 and Syldler 1984 developed equation between Flood at outlet and lake volume. Similar method was adopted by Clague and Mathews (1973) glacier lake outburst (cited J.J. Clague and S.G. Evans, 1994).

MethodFor statistical model the basic data needed are historical flood data at lake outlet, flood attenuation data downstream of lake and other data such as lave volume or dam height before it burst. Only few data on flood downstream attenuation, flood at outlet of lake and lake volume prior to burst is available in Nepal. However, some data on surface area of lake corresponding to lake volume is available for regression analysis. Therefore, three regression equations are combined to develop GLOF statistical model as:

VL=f(SA)Qo=f(VL)QD/Qo=f(D)

where, VL is lake volume, SA is lake surface area, Qo is GLOF at outlet of lake and QD is GLOF at any downstream distance D.

In other to develop GLOF attenuation formulae, various GLOF data, lake volume and surface area of lake, and downstream distances are collected from different literatures. Beside these, primary data from field survey of Phuchan and Dudh Koshi GLOF were also collected.

Key research findingsBased on Lower Barun, Imja, Thulagi and TshoRolpa glacier lakes, and some lakes from Arun and Kumbhu basins, the best-fit regression equation for glacier lake surface area and vol-ume relation developed is:

VL = 0.0408 x SA1.429 (1)

where, SA is surface area in km2 and VL is total volume of glacier lake in km

3. The square of correlation coefficient is 0.88. The developed regression equation is presented

BINOD SHAKYA


in Figure 1.2. Similarly based on TshoRolpa and Dig Tshobursts in Nepal and 10 more GLOF data outside Nepal, regression equation is developed between lake volume and GLOF at outlet. The developed equation is:

Q0 = 95. 97VL0.5981 (2)

Where, VL is total volume of lake in 106 m3 and Qo is GLOF at outlet of lake in cumecs. The square of correlation coefficient for the relationships equals to 0.90. The developed regression equation is presented in figure 1.3. The historical GLOFs with volume of lake is presented in Table 1.1.

Figure 1.2. Relation between volume and surface area of glacier lakes

Figure 1.3. Relation between total volume and discharge at outlet of the lake

Table 1.1: GLOF with lake volume

Name of lake Burst year VL , 106 m3 Qo, m

3/s

DudhKoshi, Nepal 1977 8.80 1,100

Demmevatn, Norway 1937 11.6 1,000

GraenalonIceland 1939 1500 5,000

GjanupsvatnIceland 1951 20.0 370

George, Alaska 1951 1730 10,100

Tulsequah, British Colombia 1958 229 1,556

Summit lake, British Colombia 1967 251 3,260

Ekalugad valley, Baffin island 1967 4.80 200

Hazard lake, Canada 1978 19.6 640

Gruben, Switzerland 1970 0.17 15

Gorner, Switzerland 1944 6.00 200

Dig Tsho, Nepal 1985 25.0 1,600

Source: Clague, J.J and Evans, S.G. (1994)



The records on downstream attenuation of GLOF are rarely available. The GLOF at-tenuationstrengthforZangzhangboGLOFwaspresentedbyYamada,1998.Thebest-fitregression equation (figure 1.4) of GLOF attenuation is constructed with data of Zhang-zangbo GLOF and with primary data from field visit at Phuchen burst site (B. Shakya, 2001) and two historical floods from dam failure in the US (Table 1.2). The developed equation is:

(3)

where, Q0 and QDare GLOF at outlet of lake and at distance D (km) downstream re-spectively.

Figure 3.1: Downstream attenuation from lake burst

Estimation of Imja GLOF:This lake is located at 2705917 North latitude and 8605531 East longitude over eastern Nepal. The total volume at present is about 35.8 million m3 in 2002 (Bajracharya et al 2007). The WWF project on Khumbu climate change (2007) adopted the above equations and estimated flood assuming incase of GLOF in 2008. The result is shown in Table 1.4.

Table 1.2: Flood attenuation, %

Lake name Distance, km

Flood attenuation, %

L.D. creek (US) 0.0 100.0

17.0 82.0

22.0 37.0

80.0 11.0

124 6.3

Teton (US) 0.0 100.0

16.0 46.0

138 3.9

178 2.9

D. Tsho (Nepal) 0.0 100.0

5.4 60.2

12.0 26.9

15.8 15.3

Phuchen (Nepal) 0.0 100.0

7.6 67.0

10.5 40.0

Source: cited Shakya B 2001

BINOD SHAKYA


ConclusionA detailed research on all glacier lake is a tough task due to the harsh topography, poor economy and lack of scientific research. The possible GLOF mark at downstream lake and other management from GLOF threat is still not started. However, Nepal Govern-ment lowered a TshoRolpa Lake level using siphons and set up GLOF early stations at and downstream of Lake. To reduce GLOF vulnerability, estimation of downstream flood from burst is key data to mark the dangerous level at downstream and to design any infrastruc-ture near or across river. In this connection the only easily achievable data is surface area of the lake e.g. via Satellite Images. The area also can be extracted from different litera-tures and reports. Therefore, equations 1,2, and 3 presented above can be used to estimate GLOF at downstream of lake.

ReferencesCDHM T.U., Glacier Lake Assessment of Nepal Himalayas Uning NASDA satellite Image. Research

Report, Tribhuvan University., 1999.

Chinese Academy of Sciences, WECS, NEA: Report On First Expedition To Glacier And Glacier Lakes

In The Pumqu (Arun) And Poiqu (Bote-Sunkoshi ) River Catchments Xizang (Tibet), China, 1988.

Clague J.J. and Evans S.G., Formation and failure of natural dams in the Canadian Cordillera.

Geological Society, Canada, Bull. 464, 1994.

ClarkeG.K.C.,Glacieroutburstfloods fromHazardLake,YukonTerritory,and theproblemof

flood magnitude prediction. Journal of Glaciology, 1982, vol. 28, pp. 3- 21.

Costa J.E. and Schuster R.L., The formation and failure of natural dams.Geological Society of America

Bulletin, vol.100, pp. 1054- 1068, 1988.

Douglos D., Climate Change in Nepal Himalaya, Research Paper, Arizona State University,

Publication, ASU, 1995.

IPCC (2001b) and Climate Change (2001):Impacts, Adaptation and Vulnerability, Contribution of

working group II to the Third Assessment Report of the Intergovernmental Panel on Climate

Change, (Cambridge: Cambridge University Press).

Ives J.D., Glacier Lake Outburst Floods and Risk Engineering in the Himalaya. ICIMOD, occasional

paper no.5, 1986).

Table: 1.4: GLOF at outlet and downstream of Imja incase of burst

Distance, km 0 5 10 20 30 40 50

GLOF, m3/s 4,757 2,900 2,344 1,678 1,249 949 735



Shakya B. and Thapa K.B., Integrated Study in Hydrology and Meteorology of Khumbu Region with

Climate Change Perspectives, Research Report, WWF publ., 2007.

Shakya B., Estimation of Main Hydrological Characteristics for Mountain Rivers of Nepal.Research

Paper, publ. Central Asian Research Hydrometeorological Institute, publno. 556.535.3, 2001.

Shrestha A.B., Wake C.P., Mayewski P.A. and Dibb J.E., Maximum Temperature Trends in the

Himalaya and its Vicinity: An Analysis based on Temperature Records from Nepal for the period

1971-1994. In Journal of Climate, publ. no 12: 2775-2767, 1999.

YamadaT.,GlacierlakeanditsoutburstfloodintheNepalHimalayas.Monographno1,Japanese

Society of Snow and Ice, 1998.


AbstractThis paper focuses on the present disaster anticipatory systems of the Indian railways and useful-ness of some measures in the disaster management plan of mega cities of India. Indian Railways is the biggest network of Asia, and possesses efficient Disaster Management (DM) system. Hence, some disaster anticipatory measures become very useful and effective in DM plan of a Mega civic body in India. In this paper, these important useful points of DM plan of Indian Railways are shown in reference to Ahmedabad city DM plan.

key words: Disaster, anticipatory measures Preventive actions, DM plan, Efficient city DM plan

IntroductionThe Indian subcontinent can be primarily divided into three geophysical regions. The topographic and climatic characteristics of each region make them susceptible to differ-ent type of disasters54 per cent of land is vulnerable to Earthquakes, 40 million hec-tares of land is vulnerable to floods; hilly areas are at risk from landslides and avalanches. Moreover, vulnerability to disasters/emergencies of terrorist attack, Chemical, Biological, Radiological and Nuclear (CBRN) origin also exists.

The Indian Railways came into existence with the running of the first train from Kurla to Thane in 1853. Ever since then, handling train accidents has been a priority area for the railways. Thus, in the Indian Railways, disasters may be in the form of natural calami-

Usefulness of some Disaster Anticipatory Measures of the Indian Railways in Disaster

Management Plan of Mega cities of India with Special Reference to Ahmedabad city

J.G. Macwan

J.G. MACWAN


ties like cyclones, heavy rains, earthquake, landslides, or manmade calamities accidents like fire, collision or derailment. The Indian Railways has its own DM system and plan.

Ahmedabad is a mega city, commercial capital of Gujarat, the former capital of Gu-jarat, a major centre for industries as well as trade and commerce, was founded in 1411 AD as a walled city on the eastern bank of River Sabarmati. In the past, due to its textile industries, Ahmedabad was famous as the Manchester of India. Presently, Ahmedabad is the 7th largest city of Gujarat and also its commercial capital. Ahmedabad is vulnerable to multiple natural hazards like earthquake, flood, cyclone, heavy rain due to its geo-graphical position. Moreover, the city is vulnerable to manmade technical and biological hazards like terrorist attacks, communal riots/civil disorders, fire, Air/rail, road/industrial accidents and epidemic disasters. In the past, Ahmedabad has faced destruction in 2001 and 2002 due to earthquake and communal riots. To handle disasters, Ahmedabad Mu-nicipal Corporation has prepared DM plan. Some important points of DM plans of the Indian Railways became useful in city DM plan.

Indian Railways:Railways were first introduced to India in 1853. By 1947, the year of Indias independ-ence, there were forty-two rail systems. In 1951, the systems were nationalised as one unit, becoming one of the largest networks in the world. Indian Railways operate both long distance and suburban rail systems on a multi-gauge network of broad, meter, and narrow gauges. It also owns locomotive and coach production facilities.

1.1. OrganisationThe Indian Railways is Asias largest and the worlds 2nd largest Railway system, next to Russia. The Indian Railways is the nations largest undertakings employing more than 16 lakh people. The Indian Railways is owned and managed by the Central Government be-ing the principal mode of inland transport.

The responsibility for the administration and management of the Railways vests with the Railway Board under the overall supervision of the Minister for Railways. The Board is empowered to function as the Ministry of the Government of India, and exercise all powers related to the operation of the Railway organisation. The Railway Board con-sists of six members and chairman who has special position as principal secretary to the Government of India. The Indian Railways is divided into zones, which are further sub-divided into divisions. The number of zones in the Indian Railways increased from six to eight in 1951, nine in 1952, and finally 16 in 2003. Each zonal railway is made up of a



USEFULNESS OF SOME DISASTER ANTICIPATORY MEASURES OF INDIAN RAILWAYS IN DISASTER MANAGEMENT PLAN OF MEGA CITIES OF INDIA -WITH SPECIAL REFERENCE TO AHMEDABAD CITY

certain number of divisions, each having a divisional headquarter. At present, there are sixty-seven divisions.

Each of the sixteen zones, as well as the Kolkata Metro, is headed by a General Man-ager (GM) who reports directly to the Railway Board. The zones are further divided into divisions under the control of Divisional Railway Managers (DRMs). The divisional of-ficers of engineering, mechanical, electrical, signal and telecommunication, accounts, personnel, operating, commercial and safety branches report to the respective Divisional Manager, and are in charge of operation and maintenance of assets. Further down the hierarchy tree are the Station Masters who control individual stations and the train move-ment through the track territory under their stations administration.

1.2 Technical and operating systemThe total length of track used by the Indian Railways was about 1,11,600 km while the total route length of the network was 64,061 km on March 31, 2010. About 31 per cent of the route-kilometer and 46 per cent of the total track kilometer was electrified on March 31, 2010.

The Indian Railways operates about 9,000 passenger trains and transports 20 million passengers daily across 28 states and 2 union territories. Sikkim and Meghalaya are the only states not yet connected by rail.

1.3 Types of DisastersDisaster in the railway context was traditionally a serious train accident, caused by hu-man/equipment failure, which may affect normal movement of train services with loss of human life, or property, or both. This is now extended to include natural and other manmade disasters.

Different types of disasters along with a few examples are:(i) Natural DisasterEarthquakes, floods, cyclones, landslides, tsunami, etc.(ii) Train Accident related DisasterCollisions (with a huge number of casualties), train marooned (flash floods), derailments at a bridge over a river, and coaches falling down; train washed away in cyclone, derail-ment of a train carrying explosives or highly inflammable material, tunnel collapse on a train, fire or explosion in trains, and other miscellaneous cases, etc.(iii) Manmade DisastersActs of Terrorism and Sabotage, that is, causing deliberate loss of life and/or damage to

J.G. MACWAN


property. It includes setting fire to a train, railway installations, etc., bomb blast at railway station/inside train, chemical (terrorism) disaster, biological and nuclear disaster.

1.4 Nodal department for Policy Formulation on DM in the Indian RailwaysThere are control offices in the Railway headquarter and the divisional offices which monitor and control train movements round the clock.

The preparation of the DM plans of the Indian Railways and on the Zonal Railways in co-ordination with the different departments of the railways, other Central/State Govt. agencies, NGOs, Private agencies, etc. has to be done by the Safety department in the Railway Board, on the Zonal Railways and Divisions. Safety Director in the Railway Min-istry, Chief Safety Officer in each zonal headquarter, and Sr. Divisional Safety Officer in the Divisional headquarters are full-time emergency officers.

Besides the above, organisation which functions under the control of Ministry of Railways, there exists a Commission of Railway Safety headed by Chief Commis-sioner of Railway Safety with Commissioners of Railway Safety reporting to him. To maintain independence, the safety Commissioner functions under the control of Ministry of Civil Aviation and enquires into cases of all serious accidents. Its permis-sion is also needed for opening of new lines, introduction of new rolling stock, etc. The Commissioner has quasi-judicial powers, and the work is manned by officers from the Indian Railways.

The Hospital DM plans and the Security arrangements (drills, etc.) are prepared and coordinated by the Medical and the Security department respectively. The management of floods, cyclones, earthquakes, landslides, etc., and the preventive actions required for mitigation are coordinated by the the Civil Engineering Department. The Rescue and Restoration of DM Plans including preparing plans and procurement of specialised equip-ment and rescue-centric training of personnel has to be coordinated by the Mechanical Department

1.5 Disaster Anticipatory Measures of Indian RailwaysThe Indian Railways have an elabourate scheme for collecting information and pre-warn-ing of the staff located in areas likely to be affected, for taking precautionary arrange-ments to prevent any mishap to moving trains or passengers by giving relief to passengers and staff and restoration of communication expeditiously if any stretch of line is affected. These form part of mandatory instructions to the staff on action to be taken during train accidents; they also form part of General and subsidiary rule of working of Railways.



1.6 Strengths of the Indian Railways to handle a DisasterIn handling disasters, the Indian Railways is in a unique position as it has a number of strengths not available with many other government departments. These include: Own communication and control networkwith each Station,Division, and Zonal

headquarter OwnforceofRPF/RPSF,firebrigade,territorialarmyunitsandcivildefense Railwaysownmedicalinfrastructure Fulltimesafetyofficerandsafetydepartmentavailableatdivisionlevel,Zonallevel

and Ministry level to see DM. Railwayorganisationisdistributedinsectionsofeach8kmareaandsectionin-charge,

essential staffs with army of gangmen are bound to stay in railway quarters available in each section 24 hours

Allarea/divisionalofficersareboundtostayinrailwaybungalowsprovidedineachcon-cerned area/division so that they can reach at the time and place of disaster immediately.

Medicalandrescuetrainwithessentialmaterialsisalwaysreadyineachdivisionorearmarked area to reach assistance and handle disaster.

EssentialstaffsofeachdepartmentofRailwaysareinstructedtokeepthemready24hours so that at the time of occurrence of disaster and when warning siren starts, they can reach he relief and rescue train placed in the yard with in 30 to 60 minutes depends on disasterserious disaster-30 minutes, Average disaster-60 minutes. (In-termittent voice of siren means serious disaster and continuous voice of siren means average disaster.)

InspectionscheduleofRailwayinfrastructureisverypowerfulasapreventiveaction.From the section in- charge to General Manger, all are bound to complete their inspec-tion schedule in fix time frame

1.7 Railways shortcomings to handle DisasterThere are, however, a few inadequacies in the Railways own resources, which are very essential for handling a specific type of disaster: Absenceoftunnelrescueequipment Non-availabilityoftraineddivers/swimmersforextricationofpassengersand/orcasu-

alties (dead bodies and drowning/drowned passengers) from rolling stock falling down in sea/river/lake, etc.

Non-availabilityofcranesoperatedfromaship/bargeforliftingofthecoaches/bogiesfrom a water body

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Limitedresourcestohandleaterroristattackonatrainand/orastation,otherrailwaypremises, etc.

1.8 Managerial PreparednessAn emergency organisation is formed to suit each situation. When a disaster causes dam-ages resulting in interruption to traffic, managers and staff are drawn from among the regular serving personnel, and emergency organisation is formed for supervision till nor-mal situation restores. For attending this activities, suitably equipped relief trains, medical vans and emergency building /track materials including emergency bridge components are kept in readiness all the time. Railways carries out potential training programmes just like periodical training, refresher training, promotional course etc., for staff in executive and supervisory levels and from field staff on DM aspects, either as part of their regular training programmes or through special course.

Moreover, in order to expedite work, some unorthodox management methods are adopted; for example, fixing agencies to carry out work, purchase of urgently required materials, engaging of labour, revising priority for movement of trains working across ones jurisdiction in respect of territorial as well as sectional boundaries. Any senior rail-way officer who happens to travel in a train, which meets with a disaster or faces disaster, is expected to inform all concerned on the nature of the trouble and take charge of the situation till the officer in charge of the area arrives at site.

1.9 Action during Disasters(i) Action on Division/Zones on Orange/Red Alert On the issue of an Orange Alert (or of a higher level), the Responders have to be activated as required for relief, etc.: Mobilisationofgangmen Hospitalstomobilisedoctorsandpara-medicalstaff deploymentofrailwayprotectionforce,staterailwaypoliceandactivatecivildefense,

territorial army units, and scouts and guides OperationandmanningofthedisastercontrolroomandCoordinationamongstvari-

ous stake holders through advance warnings

(ii) Monitoring/Reporting of Effects of DisasterThe Safety Department. in the Board would be given information regarding Orange/Red Alerts. On the declaration of an incident as a Disaster by a State Government or District



Administrator or even by the GM/AGM of the Zonal Railway, the CSO would give time-to-time updates to the Safety Control in Railway Board of the situation. Assistance of other departments would be made available by the GM to the Safety Department of the Zonal Railways.

1.10 Standard Operating Procedure (SOP) on Railways(i) National DisastersThe Civil Engineering Department at the field level and on the divisions gets informa-tion through advance warning sent by the respective government departments on the possibility of floods, cyclones, earthquakes, landslides, etc. Depending on the gravity of the disaster/crises/calamity expected, the information would be passed on to the Divi-sional officers through the Emergency Control, which will act as the ICS. Where train operations have to be suspended or regulated, the operating departments would be suit-ably advised. After making the train regulation plan, the divisional control would advise the commercial and security departments for management of the welfare of passengers. Alerts to the passengers would be issued through the PR Department of the Railways in the print and electronic media.

The Divisional Railway Managers of the divisions shall ensure coordination among the departments for ensuring running of train services (including relief special trains) as also relief arrangements for the passengers and for the Welfare of Railways own staff. Assistance of other divisions and from the Zonal Railways would be taken through the Headquarter of the Zonal Railways (i.e. by involving the General Manager). Coordination with the IOC of Ministry of Home affairs and National DM authority/NDRF would be through the Emergency Control of each zonal headquarter.

Priority in the rail operating will be shifted towards first giving relief to standard pas-sengers, and then, to the restoration of line to the minimum extent required to enable trains to pass at slow speed. A foot-by-foot survey is done over the entire length affected by the disaster at the earliest possible time to assess the extent of damages and estimate requirement of men and materials communication. Depending on the seriousness of damages and likely duration of carrying out temporary repairs, a senior Executive from the Railway headquarter would be sent to the site to take charge of the work. All officials of different disciplines would be answerable to this executive and progress of work is monitored at divisional, zonal, and Central (Railway Ministry) level on day-to-day basis. In some cases, it is done on twice a day basis.

As a large number of men would be working at different locations on a continuous

J.G. MACWAN


basis, arrangements are made for supply of free cooked food to them in proper time, and temporary staying arrangements closer to the site are provided. A proper medical and health team would be posted to look after the hygiene at site and render medical treat-ment to staff at site itself including inoculation against cholera and typhoid. Engaging a lot of labour for short duration directly by the Railways paying them and discharge them on completion of work is not practicable by following laid down procedure of Railways; same applies to procurement of some construction materials. These are, therefore, done by engaging contractors. Time being precious, the executive in charge is given freedom to fix agencies on the site by directly negotiation with experienced contractors who are available close by and who have the necessary resources readily available with them. The negotiation are carried out at site itself by committee comprising of engineer concerned, the finance and accounts officer for the section and another officer. There have been oc-casions during such emergencies when contractors have been fixed on 24 hour basis for assessment of damages.

The labour of the track work, bridgework, signal, and telecom and electrical traction works call for special skill. Hence, such staff is collected from other different sections or divisions or by diversion from construction work to the said site of work temporarily. Railways normally hold emergency stock of stones and temporary bridge materials in different areas.

(ii)Manmade Disasters Different forms of terrorism fall under the ambit of manmade disasters. A major role has to be played by the Security Department of the Railways who will coordinate with the State Governments, and when required, coordinate with the para-military and other forces. The Security Control of the division will act as the ICS. The headquarter of Security Control will coordinate with the IOC of MHA.

1.11 Initiative actions after DM plan 2005 of Government of India Preparation of DM Plans on Zonal Railways with periodical review Safety Department: Nodal Department for compilation/updating of DM Plans ISO certification of DM plans Creation of national disaster response and mitigation funds Modernisation of relief/rescue during disasters Crowd control and management of rush at railway stations during festivals Action plan to handle terrorist attacks on a freight train carrying inflammables



Strengthening works of Railway infrastructure to reduce destruction due to earth-quakes, floods, etc.

Creation of network of mobile medical infrastructure to handle disaster on Railways Preparation of hospital DM Plan to handle disaster on Railways Constitution of specialised trained team of Railway Police force in each divisional

headquarter in crowd control and functional support in case of disasters An integrated security scheme has been sanctioned for installation at 195 stations

of the Indian Railways to prevent explosion in trains and railway premises; the sys-tem envisages multi-layered surveillance of vehicles, luggage and passengers in station premises

Crisis management plans are prepared to handle terrorist acts and hijacking of trains Modernisation of communication on the Railways through Satellite The Railways have their own ICS as they have to deal with crises like situations and

mini-disasters in the day-to-day operational working, and especially, with handling of train accidents. With the setting up of the Rescue Centric Training Institute at Ben-galuru, the ICS structure will get streamlined

Coordinating Integrated Command System of Railways with Integrated Operations Centre of Ministry of Home affairs

Preparation of different DM plans for various disasters like earthquakes, floods, cy-clones, landslides and avalanches, biological disasters, chemical Disasters, chemical (terrorism) disasters, nuclear and radiological emergency

Formation of detailed training programmes for senior officers and subordinate staffs regarding DM

AhmedabadAhmedabad, the former capital of Gujarat and a major centre for industries as well as trade and commerce, was famous as the Manchester of India. Presently, it is the 7th larg-est city of Gujarat, and also its commercial capital.

2.1 Demographic CharacteristicAdministrative Body-Municipal Corporation Area:458.14sqkm NoofWards:57 Polulation:66,00,000(asper2001censusandwithnewcitylimit) NoofHouseholds:10,55,851

J.G. MACWAN


2.2 Organisation setupAdministration of Ahmedabad Municipal Corporation is being done by two wings(1) Elected wing, and (2) Executive wing. The head of the elected wing is called Mayor who is a first citizen of Ahmedabad. There are so many other committees like standing com-mittee,transportcommittee,Legalcommittee,etc.,whichareheadedbytheconcernedchairmen. The Mayor, and all committees are policy makers, While Commissioner, a Secretary rank IAS officer is Administrative head and appointed by state Government, is assisted by other Dy. and Assistant Commissioners. Presently, Ahmedabad Municipal Corporations staff strength is 35,000. For administrative conveniences, municipal area is divided in 5 zones and 57 wards, which are headed by Dy. Municipal Commissioner and Ward Officer respectively.

2.3 Potential Hazard Possibility In AhmedabadAhmedabad is vulnerable to multiple natural, manmade, technical, and biological haz-ards:

Table 1 Possibility and intensity of Disasters in Ahmedabad

Type of disasters Possibility

Earthquake Medium

Flood Medium

Heat wave High

Cold wave Medium

Cyclone Medium

Terrorist Attack High

Civil Disorder High

Mutinity of state police force Less

Road Accident Medium

Railway Accident Less

Air Accident Medium

Fire High

Wall/Building Collapse High

Industrial Accident Medium

Epidemic Disease High

Animal Disease Very less

2.4 Strengths of Ahmedabad Municipal Corporation to handle a Disaster OwnFirebrigadestaffswhoaretrainedpersonnel,tohandlereliefrescueworkofdis-

aster like flood, earthquake, cyclone, etc. Ownmedicalinfrastructurewith5bighospitalsand79smallhospitals/urbanhealth

centre. ( Civil hospital, the biggest hospital of Asia is in Ahmedabad also) Emergencymedicalassistanceservice(1-0-8)establishedbytheGovernmentofGuja-

rat in public-private partnership basis is available Owncitytransportservicewithabout1,000busesandothervehicles Wellestablishedwardandzonalofficeswithabout35,000staff Efficientpublic information system through cablenetwork,mobile vans,Doordar-

shan, Radio/Akashvani Bigpoliceforceisavailableincity,whichisusefulatthetimeofdisaster Assistanceofvariousgovernmentofficessituatedinthecityareaareavailableatthe

time of disaster, that is, Collectors office, PWD, Meteorological department, Electric-ity Company/Gujarat Electricity Board, Railway, State transport, Water supply Board, BSNL,etc.

ServicesofvariousNGOslikeCivilDefense,ScoutsandGuides,NCC,Redcross,In-dianMedicalAssociation,Rotaryclub,Lionsclub,etc.areavailable

2.5 Shortcomings of Ahmedabad Municipal Corporation to handle DisasterPolice force and communication systems are major requirements for DM but these two are not under the control of the Ahmedabad Municipal Corporation; only assistanceship is available.

2.6 Disaster Anticipatory Measures of Ahmedabad Municipal Corporation(i) System to handle Natural disasterThe Ahmedabad Municipal Corporation receives the forecast and warning messages from the meteorological department regularly for natural disasters like cyclones, and heavy rain, while it receives warning/forecast from the State Irrigation Department. Whenever an emergency is feared, the action plan is initiated. To handle the situation, Zonal Dy. Municipal Commissioner starts work with the concerned ward officer, fire brigade and other staff under the guidance/instruction of the Municipal Commissioner. In the case of floods/heavy rain, earthquakes, cyclones,

saarc journal jun 2010

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