Study about the Drought RiskEffect in the Western Region ofBangladesh

Abstract Though drought is a recurrent phenomenon inBangladesh, but very small steps have beentaken to find out the drought risk inscientific way and to mitigate the drought.This study presents a method to find outspatial assessment of drought in Bangladesh.Standard precipitation index (SPI) in GISenvironment is used to develop a map of droughthazards in different time period. Socio-economic and infrastructure indicators are usedto find out the drought vulnerability. Droughtrisk is expressed as the product of droughthazard and drought vulnerability. The resultshows that the northern and northwestern partof Bangladesh is in the highest risk zones.

1. INTRODUCTION

Drought is a prolonged and continuous period ofdry weather along with abnormal insufficientrainfall. It occurs when evaporation andtranspiration exceed the amount of a reasonableperiod. Drought causes the earth to parch and aconsiderable hydrologic or water imbalanceresulting water shortage, well to dry,depletion of groundwater and soil moisture,stream flow reduction, crops to wither leadingto crop failure and scarcity in fodder forlivestock. Drought is a major natural hazardfaced by communities directly dependent onrainfall for drinking water, crop productionand rearing of animals (Islam and Das 2009 ).

Bangladesh is like to be one of the mostvulnerable countries in the world to climatechange. Generally every year, the country isaffected by many kinds of disasters such astropical cyclones, storm surges, coastalerosion, floods, and droughts- causing heavyloss of life and property and jeopardizing thedevelopment activities (Ali 1996). Bangladeshis an over populated country in the world andover 940 people per square km live in thiscountry. Over 40% population of the countrylive under poverty line and the capita income

is only US$ 235. High spatial and temporalclimate variability, extreme weather events,high population density, high incidence ofpoverty and social inequity, poor institutionalcapacity, inadequate financial resources andweak infrastructure have made Bangladesh highlyvulnerable to disaster (Ahmed 2004).

During the last 50 years, Bangladesh sufferedabout 20 drought conditions. Drought is arecurrent phenomenon in some parts of thecountry. Though drought is the recurrence anddevastating nature disaster in Bangladesh, buta very poor scientific attention has been takenthan floods or cyclones (Alexander 1995;Brammer 1987) . However, losses from droughtsin Bangladesh is more noticeable than otherdisasters like floods. An analysis of therelative effects of flood and drought on riceproduction between 1969-1970 and 1983-1984indicates that drought is more devastating thanfloods to aggregate production (World BankBangladesh 1998). 3.5 x 106t rice and wheatproduction was decreased for drought in 1994-1995 (Rahman and Biwas 1995). About 140,000t offood grain was needed to import to remove thiscrisis between July 1994 and March 1995. Anadditional 200,000t of rice was imported to

control the shortage in national stocks andsupply the national demand on an emergency case(Biwas 1995).

In Bangladesh, the major natural hazards arealso in the line with global patterns. Adecrease in precipitation in dry season andincreases in monsoon in South Asia has animpact in global warming (Christensen et al.2007). This causes an adverse combination ofmore extreme floods and droughts in thisregion. Due to the land use changes within thecountry and in neighboring countries Bangladeshhas already shown an increased frequency ofdroughts in recent years (Nation Mitigationcenter 2006). For this reason prediction andimplementing mitigation of drought hazard,drought vulnerability and risk assessment in ascientific way is essential to reduce droughtimpact in Bangladesh.

There are a number of studies have been done onthe impact of droughts on agriculture (Karim etal. 1990; Jabber 1990; Jabber et al. 1982;Saleh et al. 2000; Mazid et al. 2005), foodproduction (Ahmed and Bernrad 1989; Erickson etal. 1993), land degradation (Rasheed 1998;Karim and Iqbal 2001; Government of Bangladesh2005), economy (Erickson et al. 1993; World

Bank Bangladesh 2000) and society (Erickson etal. 1993; Paul 1998) in Bangladesh. The firstagricultural drought risk map in Bangladesh wasprepared by Karim et al. (1990) by consideringthe cumulative effect of dry days, highertemperatures during pre monsoon period and soilmoisture availability. Winter and pre-monsoondrought prone areas maps of Bangladesh wasprepare by WARPO-EGIC (1996) using theagroecological zones database and landresources inventory map at 1: 1,000,000 scale.Karim and Iqbal (2001) reviewed the concept ofWARPO-EGIC (1996) and produced three differentdrought maps for winter, pre-monsoon, andmonsoon seasons. They defined drought riskclasses as slight, moderate, severe and verysevere related to the yield losses of 15-20%,20-35%, 35-45% and 45-70%, respectively, fordifferent crops. In Bangladesh no standarddrought index method is applied for determiningdrought risk. Also no study has been taken toidentify the geographical distribution ofvulnerability to drought. The main objective ofthis study is to discuss about the droughthazard, identify the drought vulnerability anddraw a drought risk zones map of the west partof Bangladesh.

To identify the drought hazard pattern inBangladesh Standard Precipitation Index (SPI)method has been used (Mckee et al. 1993).Various socio-economical andphysical/structural indicators have been usedto calculate the vulnerability of population bydrought. Drought risk is defined as the productof the drought hazard and drought vulnerabilityaccording to Blaikie et al. (1994). Naturalhazards, disasters and risk are essential innature (Cutter 1993; Hewitt 1999). Drought riskanalysis requires assimilation of physical andsocio-economic information from many sites eachwith a unique geographical location. GISmaintains he spatial location of samplingpoints or area and provide tools to relate thesampling data contained through a relationaldatabase (Shahid et al. 2000). Therefore, GIShas been used to levels of drought risk throughthe analysis of spatially distributed hydro-meteorological and socio-economic data.

In the next section of the article, the methodwhich has been used for the analysis of thedrought risk in west Bangladesh will bediscussed. Also the factors that affect thevulnerability of drought in west part ofBangladesh have been identified. This is

followed by the results and discussion section,where spatial distribution of drought hazard,vulnerability and risk in west parts ofBangladesh has been discussed, with thenecessary maps and graphs. Also drought riskzones map is drawn.

2 Hydro-climatic condition ofBangladeshGeographically, Bangladesh extends from 20034/

N to 26038/ N latitude and from 88001/ E to92041/ E longitude. Climatically Bangladesh isin the sub-tropical region where monsoonweather prevails throughout the year. Threedistinct seasons can be characterized in thiscountry depending upon the climate view: (i)the dry winter season from November toFebruary, (ii) the pre-monsoon hot summerseason from March to May and (iii) the rainymonsoon season which lasts from June to Octoberand the average temperature of the countryvaries from 17 to 20.60C during winter and 26.9to31.10C during summer (Rashid 1991).

The gradient of rainfall from west to east isapproximately 9mm/km in the country. Theaverage recorded rainfall varies from 1,329 mmin northwest to 4,338 mm in the northeast partof the country. The average rainfall of thewestern part of Bangladesh is about 2,044 mmwhich is very lower than other part of thecountry. In this low quantity of rainfallalmost 77% of rainfall occurs during monsoonperiod and only 23% of rainfall occurs duringother seasons. In summer the temperature isvery high in this region and sometimes it isnear about 450C or even more. In winter thetemperature even falls at 50C in some places.These type of tropical climate clearly separatethis zone from the other part of the country inclimate study (Banglapedia 2003). The drynessindex in the northwestern part of Bangladesh isclose to that of a dry region (Shahid et al.2005). The average rainfall is very small andalso the total annual evapotranspiration islower than or equal to the annual rainfall insome places and for this groundwater level alsobecome lowering. Therefore, the climate of thisregion of Bangladesh is sometimes is definedvery close to dry. So drought risk assessmentis carried out of the western part of

Bangladesh. The extent of the study area inBangladesh is shown in Fig. 1.

The changes of rivers flow is also a majorcauses for dryness in dry season. For example,it can be told about the Ganges River, which isone of the major rivers of the country. Itchanges its flow for Farakka Barrage which wasmade by India in 1975. Recent data shows thatthe Ganges river flow is 57% lower in Marchthan in the pre-Farakka days (World BankBangladesh 1998). The flow become to decreasein October and reaches its lowest point inFebruary and March, which still remaining untilJune. Low river water flow in dry season has avery negative impact on river morphology,salinity and ecosystem of the western part ofBangladesh. Decreased water flow in regionalrivers also affects existing traditional andlow-lift pump irrigation as well as fisheries.The reduction in the discharge of major rivers,drying of water channels and falling ofgroundwater tables due to over-exploitationexacerbates the crisis of water in the areaduring the dry season are the main causes ofdrought.

Bangladesh is mainly an agricultural countryand about 59% of the cultivated area in

Bangladesh presently under irrigation and thisis expected to increase in future. With theincreasing of population, urbanization andeconomic development the demand for other usesof water will increase. A deficit of rainfallor drought causes severe impact on agricultureand economy of the country.

3 Methodology

3 & 6 months precipitation data

Find out probability

SPI index SPI curve

Define drought category

Prepare drought map

Find out weight andrating

Drought Hazard Index (DHI)

Find out socio-economic indicators

Find out physical/infrastructur

Drought Vulnerability Index (DVI)

Drought Risk Index, DRI=DHI x DVI

Risk is the probability of harmful consequencesor expected losses resulting from interactionbetween hazards and vulnerable conditions. So,the risk assessment study is nothing but acombined study of the hazard and vulnerability.Drought hazard depends upon the combination ofnature of drought and drought vulnerabilitydepends on the degree to which population oractivity is vulnerable to the effect ofdrought. Therefore to study about the droughtrisk, it is necessary to study the frequency,severity and spatial extent of drought withalso study to infrastructure and socioeconomicability of the region against drought. Toidentify the drought risk pattern in westernpart of Bangladesh the following steps areadopted-

1. Identify the drought hazard with regardto its frequency, severity and spatialextends.

2. Identify and characterize droughtvulnerability, e.g; people, economy andstructure exposed to the drought hazard.

3. Compute drought risk pattern fromdrought hazard and vulnerability.

A brief description of the methods and dataused for drought risk assessments of westernpart of Bangladesh are given below.

4 Drought hazard assessmentTo find out the frequency, severity and spatialextends of drought occurrences in the studyarea, Standardized Precipitation Index (SPI)(Mckee et al. 1993) is used. This method is awidely used drought index method. It is basedon the probability of precipitation on multipletime scales. It has been demonstrated by manyresearchers (Mckee et al. 1995; Guttman1998,1999; Hayes et al. 1999) that it is a goodtool in monitoring and detecting the droughtevents. SPI provides a comparison of theprecipitation over a specific period with theprecipitation totals from the same period forall years including the historical record. Inthe present topics, SPI for 3 & 6 months timesteps are computed to study the characteristicsof drought in short and medium range timescales. To describe the dry winter and premonsoon drought 3 months SPI is used, while 6months SPI is used to characterize seasonal

droughts, due rainfall deficit in monsoon andnon- monsoon months.

To calculate the SPI, historic rainfall data ofeach station are fited to a gamma probabilitydistribution function:

g (x)=1/(βαГ(α)) * xα-1e-x/β

where x ˃ 0 it is the amount of precipitation,α ˃ 0 is a shape parameter, β ˃ 0 is a scaleparameter, and Г(x) defines the gamma function.

The maximum likelihood solutions are used tooptimally estimate the gamma distributionparameters, α and β for each station and foreach (3 and 6 months) time steps:

α = 1/4A *{1+ (1+ 4A/3)½}

β =x̅/α

where A= ln(x̅) – Σln(x̅)/n

n, number of precipitation observations.

This allows the rainfall distribution at thestation to be effectively represented by amathematical cumulative probability function asgiven by;

G(x) = ∫0

x

g (x )dx = 1Г(α)βα

∫0

x

xα−1e−x /βdx

Since the gamma function is undefined for x = 0and a precipitation distribution may containzeros, the cumulative probability becomes:

H(x) = q+ (1-q)G(x)

Where, q is the probability of a zero. Thecumulative probability H(x) is then transformedto the standard normal distribution to yieldthe SPI (Mckee et al. 1993).

If the precipitation rate is fitted to gammadistribution function for different time scalesfor each month of the year then the resultingfunction defines the cumulative probability ofa rainfall event for a station for a givenmonth of dataset and a different time scale ofinterest. This permit to establishclassification values for SPI. Mckee et al.(1993) classified drought severity according toSPI values as shown in Table 1. The SPI valuelies between 0 to -.99 means mild droughtoccurs about 34.1% of the time or has a returnperiod of 35 years. A SPI values ranges from -1to -1.49 means moderate drought happens 9.2% ora return period 10 years. If this values are -

1.50 to -1.99 it means severe drought which mayoccur 4.4% of the time or with a return period25% and extreme drought happens if the SPIvalues lies from -2.00 and less with aprobability of occurrence 2.3% or return period50 years. Details of the SPI algorithm can befound in Guttman (1998, 1999), Mekee et al.(1993, 1995) and Hayes et al. (1999).

Based on the percentage of occurrences it isidentified the area vulnerable to drought. Theprobability of occurrence is calculated by theratio of drought occurrences in each time stepto the total drought occurrences in the sametime step (Sonmez et al. 2005). Kriginginterpolation method is used for mapping ofspatial extents of rainfall and drought.Geostatistical analysis tool of ArcMap 9.1(Ennvironmental System Research Institute 2004)is used for this research. Kriging is astochastic interpolation method (Journel andHuijbregts 1981; Isaaks and Srivastava 1989),which is widely recognized as standard approach

for surface interpolation based on scalarmeasurements at different points. By many studyit is said that Kriging show better result thanother method about global prediction (Oliverand Webster 1990; Zimmermap et al. 1999; VanBeers and Kleijnen 2004). To prepare thedrought hazard maps at 3 and 6 months timesteps first prepare moderate, severe andextreme drought maps of 3 and 6 months timesteps and then integrated separately. Tocompute drought severity of the integratedlayer each drought theme is given a particularweight and each feature of the theme is given arating. The weight and rating is used forintegration are given in Table 2. Droughthazard index (DHI) of integrated layer iscalculated as :

DHI = (MDr x MDw) + (SDr x SDw) + (VSDr x VSDw)

Where, MDr, rating assigned to moderatedroughts occurrence classes; MDw, weight givento the theme of moderate drought occurrencestheme; SDr, rating assigned to severe droughtsoccurrence classes; SDw, weight given to thetheme of severe drought occurrence theme; VSDr,rating assigned to very severe droughtsoccurrence classes; VSDw, weight given to thetheme of moderate drought occurrences theme.

Then the final drought hazard maps are overlaidon the district map of western part ofBangladesh to produce district scale hazardmaps. For this purpose Region Wide Overlay or“Cookie Cutter Approach” is used and thisanalysis allows natural features, like asnatural boundaries or soil polygons, to becomethe spatial areas which will be analyzed onanother map (Institute of Water Research 1996).GIS is used to overlay drought hazard datasetonto the district map to calculate the area-weighted average DHI for each individualdistrict.

5 Drought vulnerability assessment

The concepts and definition of vulnerabilityhave been analyzed by many authors (Kates 1985;Blaikie et al. 1994; Downing and Bakker 2000).Vulnerability describes the degree to which asocio-economic system or physical assets areeither susceptible or resilient to the impactof natural hazards (Wilhelmi and Wilhite 2002).To determine the vulnerability index severalfactors including condition of humansettlements, infrastructure, public policy andadministration, organizational abilities,social inequalities, gender relations, economicpattern etc. should study.

Drought vulnerability varies from individualsand nations depending upon the economiccondition, population density, infrastructureetc. It affects the developing countries morethan the developed countries (Downing andBakker 2000). Therefore, selection ofvulnerability indicators is directly relevantto the local study context and the particularhazard (United Nation Development Program2004). After careful consideration ofobtainable socio-economic and physicalindicators, four individual socio-economic andthree physical indicators are identified asimportant to this study and are subsequently

selected to represent the vulnerability ofvarious geographic populations to the impact ofdroughts. The socio-economic indicators arepopulation density, female to male ratio,percentage of people living below poverty line,and percentage of people depending onagricultural. The physical indicators arepercentage of irrigated land, soil moistureholding capacity and food production per unitarea. These are explained below:Socio-economic indicators:

1. Population density: Population density meansnumber of population per km2. Disaster withsimilar severity will affect more in high densepopulated area than lower dense populated area.

2. Female to male ratio: It represents numberof women to number of men in n area. Women andmen are differently affected by disasters.Women are naturally weak about disaster so,they affected much in disaster. Therefore,vulnerable is more where women are more. It hasbeen shown in widely diverse population thatwomen are most at risk when disaster unfolds,whether it is a drought (Vaughan 1987) or acyclone (Ikeda 1995).

3. Poverty level: It represents percentage ofpopulation living under poverty line.Vulnerability is a combination ofcharacteristics of a person or group, whichderives from the socio and economic conditionof the individual, family or communityconcerned (Blaikie et al. 1994). There is adirect relation between vulnerability andpoverty. As a rule poor suffer more than rich(Yodmani 2001). In Bangladesh, the poorcommunity is not only economic vulnerable butalso lack of social, cultural and politicalcapacities to cope with disasters.

4. Agricultural occupation: This represents thepercentage of people depending on theagriculture including farmers and agriculturalworkers. In Bangladesh more than 75% of thepeople depend on agriculture. Than any othersection agricultural section is more affectedby drought.

Physical/infrastructural factors:

5. Irrigated land: It represents percentage ofirrigated area to total land. About 59%cultivated lands are under irrigation inBangladesh. About 75% water comes from groundwater and rest comes from surface water (Bari

and Anwar 2000). So a deficit of rainfalllowers the groundwater table as well as riverwater and this affects the irrigation purpose.

6. Soil water holding capacity: It defines thedifferences in water content between fieldcapacity and permanent wilting point. Thisproperty of soil has a great significance onplants stress and critical to water managementplanning for irrigation (Kern 1995; Klocke andHergert 1990).

7. Food production: It represents the amount offood produced in metric ton per squarekilometer. Drought in higher food productivearea will have a higher negative impact.Multiple cropped lands produced more foodcompared to single-cropped lands.

For each of the above seven indicators fourclasses were selected ranging from the lowestto the highest values. The natural break methodis used for the classes. This method ensuresthat the ranges are well represented by theiraverages, and that data values within eachrange are fairly close together (Smith 1986).GIS software Arc View 9.0 is used to identifythe natural break points in the data.

A vulnerability map is represented byintegrating the district-level thematic maps.Rating values 0 to 1 is used as an indicatorfor each class. Without soil holding capacityall other indicators, classes with highervalues are given higher rating and lower givenlower rating. And soil holding capacity givesvice-versa result and land with low holdingcapacity is more vulnerable than a higher waterholding capacity. The drought vulnerabilityindex (DVI) of the integrated area is computedby using the following formula:

DVI = PDr+FMRr+PLr+AOr+ILr+SWHCr+FPr

Numberofindicators

Where, PDr, rating assigned to populationdensity classes; FMRr, rating assigned tofemale to male ratio; PLr, rating assigned topoverty level classes; AOr, rating assignmentto agricultural occupation classes; ILr, ratingassigned to irrigated land classes; SWHCr,rating assigned to soil water holding capacityclasses; FPr, rating assigned to foodproduction per land unit classes.

6 Drought risk assessment

Risk patterns were mapped using the formula(Blaikie et al. 1994; Downing and Bakker 2000;Wilhite 2000).

DRI = DHI x DVI

Where, DRI is the drought risk index

Due to product relation if there is no chancefor hazard or vulnerability, drought risk forthat location is zero.

7 Data Monthly rainfall data for the period of 1961-1999 from 12 rain-gauge stations of BangladeshMeteorological Department (BMD) in the westernpart of Bangladesh is used for the mapping offrequency, severity and spatial extents ofoccurrence of droughts in the area. Locationsof gauge stations are shown in Fig. 1. The mainproblem occurs during drought hazard study ismissing rainfall data. Percentage of rainfalldata are given in Table 3.

A feed-forward artificial neural network (ANN)is used for the estimation of missing rainfalldata. The topology of ANN used for theestimating of missing data is 6:4:1. Theneutral network training is done by using

supervised back-propagation training algorithm(Haykin 1994).

The performance of ANN is tested by applying itin estimating historical data at differentrain-gauge station located in western part inBangladesh. Monthly mean rainfall data fromJanuary 1991 to December 1999 is used for thispurpose. Root mean square method is used tomeasure the efficiency of the method.

RMSE = √1n∑i=1

n(e−a)2

Where n is the total number of observation, eis the estimated value and a is the actualvalue of the observation.

Approximate 60% of the historical data (January1991- May 1996) are used as train ANN and therest data are used for validation. In next stepthe training data is increased about 70% and80% of the historical data. The iteration limitwas kept to 500. The RMS errors at differentstations are shown in Table 3. In the presentstudy 70% historical data is used for allstations except Khepupara. Due tounavailability of data, 60% historical data isused for estimating of missing data atKhepupara.

In order to study the spatial distribution ofdrought vulnerability, population density,percentage of people depending on agriculture,and female to male ratio maps are prepared fromBangladesh national census data (BangladeshBureau of Statistics 2003). Poverty map isprepared by sub district level jointly byBangladesh Bureau of Statics and United NationsWorld Food Programme (Bangladesh Bureau ofStatics and United Nations World Food Programme2004). Percentage of irrigated land and foodproduction per land maps are prepared fromBangladesh agricultural census data (BangladeshBureau of Statistics 2002). Preparation of soil

moisture holding capacity maps from digitalsoil map at 1:25,000 scale given in Bangladeshcountry Almanac (Bangladesh country Almanac2004).

8 Result and discussionBy study drought hazards maps, vulnerabilitymaps and drought risk maps are produced whichare discussed below.

8.1 Drought hazard maps

Based on the frequency of the event for eachdrought category at 3 and 6 months time steps,drought hazard in the western part ofBangladesh has been investigated. In Figs. 2and 3 SPI values at 3 and 6 months time stepsat different stations are shown respectively.The spatial extent of percentage of droughtoccurrence of moderate, severe and very severecategories for 3 and 6 months time steps aregiven in Figs. 4 and 5 respectively.

The spatial extent of moderate drought (Fig.4a) shows a higher frequency of droughtoccurrence in southeastern part of Bangladesh

at 3 months time step. The north and westernpart of Bangladesh indicates a low frequency ofdrought at the same time steps. For the severaldrought maps (Fig. 4b) shows a different resultfrom the moderate drought map. It shows thatwestern part of Bangladesh is affected muchwith high frequency of drought. Low frequencyof drought affect in southern part ofBangladesh and central part of the country isfound moderate prone. Fig 4c is developed forvery severe drought occurrence. It gives ahighly frequency drought effect in northernpart, moderate frequency in western area andlow frequency in central zone at 3 months timesteps.

With the increase of time steps from 3 to 6months time steps shows that, the highfrequency drought shifted from southeastern tosouthwestern part of the country in moderatedrought (Fig. 5a). Low frequency occurs in the

north part. In severe drought northwestern partcovers the high frequency area at 6 months timesteps (Fig. 5b). Low frequency occurs in thecentre eastern part and moderate prone occursin the centre to southern part. Fig. 5crepresents very severe drought occurrence witha high prone in northern also with northwestpart at 6 months time steps. The central areashows a less prone area.

From the above analysis it is shown that thenorthern and northwestern parts are moreaffected area for severe and very severedrought in both 3 and 6 months time steps.Moderate drought occurs more frequently in thesouthern part of Bangladesh. The central partof the country is moderately prone for both

moderate and severe droughts. For very severedrought the central area is less prone. It canalso be told that there is no relation betweenthe amount of rainfall and the droughtpotential zones because the average rainfall inthe northern part is more than the study areabut the area is highly prone to drought compareto the study area.

Using the Eq. 7 moderate, severe and verysevere drought maps of the each time steps areintegrated and is overlaid the integrated areaon the district map to complete the district

average DHI. Using natural break method thedistricts are classified into four classesaccording to their DHI values which are shownin Fig. 6a and 6b for 3 and 6 months time stepsrespectively.

From the district level drought hazard maps at3 and 6 months time steps the study area aredivided into two broadly zones: (i) high tovery high drought hazard zone which are coverednorth northwest and central western part of thecountry (ii) low to moderate zone whichincludes the south and central eastern part ofBangladesh. A concept is also developed fromthe study that drought frequency is not onlydepended on the low rainfall but also avariability of rainfall in different time inthat region. A data shows that the rainfalldata is about 1,738 mm in 1981 and it was aboutonly 798mm in 1992 in the northwestern part ofthe country, which is also a reason to make thearea highly dangerous in drought (Banglapedia2003).

8.2 Vulnerability maps

District level maps are produced depending uponthe (i) socio-economic indicators viz.

population density, female to male ratio,poverty level and percentage of populationdepending on the agriculture which is shown inFig. 7a-d respectively and (ii) physicalindicators viz. percentage of irrigated land,soil moisture holding capacity and foodproduction per unit area which is shown in Fig.8a-c respectively.

Integrate the vulnerability indicators mapsusing Eq. 8 and is overlaid on the districtmaps. Using nature break method the integratedlayer is classified into four zones accordingto the DVI values shown in Fig. 9. From thecharacteristics of vulnerability to drought inthe western part of Bangladesh, the study areaare separated into three zones: (i) high andvery high vulnerability in the north andnorthwestern part (ii) moderate zone in centralpart and (iii) lower vulnerable prone areaindicates in the southern part of Bangladesh.So the north and northwestern part of thecountry is highly vulnerable zone where the

people live under poverty line compare to theother part of the country and more than 70% ofthe people of that area depended only on theagriculture.

8.3 Drought risk maps

Drought risk maps are then integrated using GISto produced drought risk map and the DRI ofeach districts are calculated using the Eq. 9.Then this is overlaid on the district map andthe integrated area is

classified into four zones according to DRIvalues by using natural break method at 3 and 6months time steps which is shown in Fig.10a,brespectively.

Risk maps of drought at 3 months time period(Fig. 10a) shows that north and northwest partof the country is high risk zones. Central part

is low risk region and southern part ismoderately risk area. 6 months time steps alsogive the same result for high risk zones (Fig.10b) and this is north and northwestern part.Central and southwestern part of country showsa less risk region and southeastern part is inmoderate risk zones.

Percentage of drought area of different droughtrisk categories in western zone of Bangladeshis given in Table 4. The table shows that for 3months time periods 21.9% area is in highlyrisk, 12.7% area high risk, 30.4% is moderatelyrisk, and 35% in low risk condition in westernpart of the country. And for 6 months timesteps study gives that about 19.8% area ishighly risk, 13% area is in high risk, 19.7% isin moderate risk and 48.4% area under low risk.

High poverty rates, dependency on agriculture,annual rainfall variability has made thenorthern and northwestern region more prone todrought.

9 Conclusion and recommendation

By this study the impact of drought in thewestern part of Bangladesh has beencharacterized. The high risk is happened wherethe higher value of drought hazard and droughtvulnerability is coincides. The study showsthat drought risk has a prone condition innorth and northwestern part of the Bangladesh.vulnerability study shows that higher poverty,dependency on agriculture have this region verymuch vulnerable than the other part of thecountry. Thought we have no control of naturaldisaster but we can take some steps to reducethis drought’s bad impact such as: better watersupply management in irrigation purposes,augmentation of water supplies from othersources, proper uses of water, increase publicawareness and education, local planning andwater conservation.

A major outcome of the study is to producedrought risk maps which can be in otherresearch works. As the assessment of risk isone of the main purposes to mitigate droughtand planning, it hopes this maps and study willhelp as a guideline for the authorities toreduce the drought impact in western part ofBangladesh.

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