REMOTE SENSING AND GIS BASED CRITICAL … The present study ... Management Pan 2002-2012). ... would be to replicate the project we are doing in larger scale in future. Following are

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International Journal of Mechanical Engineering and Technology (IJMET) Volume 8, Issue 10, October 2017, pp. 434–447, Article ID: IJMET_08_10_048 Available online at http://www.iaeme.com/IJMET/issues.asp?JType=IJMET&VType=8&IType=10 ISSN Print: 0976-6340 and ISSN Online: 0976-6359 © IAEME Publication Scopus Indexed

REMOTE SENSING AND GIS BASED CRITICAL

EVALUTION OF WATER BALANCE STUDY

FROM WOOCHU WATERSHED, BHUTAN

SS. Asadi

Associate Dean Academics & Professor, Department of Civil Engineering, K L University, Vaddeswaram, Guntur(D.t), A.P, India

Abel Dungana, Paras Mani Ghalley

B.Tech Students, Department of Civil Engineering, K L University, Guntur, A.P, India

ABSTRACT

The present study deals with the water balance study in Woochu, Paro District,

Bhutan .The Studies Involves identifying the current drainage pattern and changes

occurred over a period due to the natural disasters and man-made activities by

adopting Remote Sensing Technologies and GIS tools The study area is Woochu, Paro

District, Bhutan laying between Longitude: 89º20’ to 89º26’E Latitude: 27º21’30” to

27º24’30” N covering the Survey of Bhutan Toposheet no 78E/7 with scale 1:50000

and Multi-Spectral imageries from Land sat 7 (TM), RADAR (SRTM) data and IRS-

1D, LISS-III geocoded Satellite data are acquired as primary and secondary data for

analysis. Interpretation techniques are used to identify the drainage and soil

information by applying both pre- interpretation, ground truth and post visual

interpretation of the satellite image layers are prepared .The interpreted maps

Topology is created by linking the spatial data file and attribute data file and using

SCS-CN Method Analysis of water balance study has been carried for meet the

feature.

Keywords: Remote sensing, Geographical Information System (GIS), SCS-CN Method Analysis, water balance study.

Cite this Article: SS. Asadi, Abel Dungana and Paras Mani Ghalley, Remote Sensing and Gis Based Critical Evalution of Water Balance Study from Woochu Watershed, Bhutan, International Journal of Mechanical Engineering and Technology 8(10), 2017, pp. 434–447. http://www.iaeme.com/IJMET/issues.asp?JType=IJMET&VType=8&IType=10

1. INTRODUCTION

In the past hundred years, the global population has tripled while demand for water has increased seven-fold. The world’s population is growing by about 80 million people a year, implying increased freash water demand of about 64 billion cubmeter a year(WWAP 2011)Optimum and efficient of scarce fresh water resources is becoming a prime concern

SS. Asadi, Abel Dungana and Paras Mani Ghalley


these days as the disperity between the demands by ever increasing population to these precious resources is widening at a alarming rate. In and around semi-araid areas recurrent drought and water shortag are common phenomenon. In recent years the advancement in satellite and computer technology along with different models and basis. Some of the parameters are we can abstract the attributed datas for the required applications with the help of RS and GIS softwares that will immensely benefit for proper determination of of it leads to a proper quantification of the catchment water balanc components and thereby proper assement of the hydrologic behaviors of the catchment.

In this study, study of run off from sub watershed catchment of Woo-chu area located in Paro Distrct, Bhutan has been assessed using catchment water balance method. This component of water balance were derived using ground based data collected from concerned offices. While the sattelite images were used for derivation of various components for preparation of base map, interipatation and analysis.Woochu water shed area is located at the slope ranging from gentle slope to very steep slope where there is no potential of exploring ground water. Due to the mountainous and steep terrain of the country, most of the rainfall immediately flows as surface runoff despite the significant vegetation cover and adequate annul rain fall. While water resources are seemingly abundant with the stream flowing through the middle of the catchment area, there have come signs of water scarcity as more people put increasing pressure on the scarce and erratic waters for irrigation and drinking purposes. A significant portion of the agricultural lands depend on the seasonal rainfall due to there is no proper conservation of runoff (excess water) during seasonal and more over this area being located in the hills, the stream flowing in deep gorges joining with main river ‘PA CHHU’ is out of reach and the lack of flat terrain also limits the utilization of water for irrigation

1.1 Description of Study Area

1.1.1. Location and Extent

Woochu watershed is located in Luni Geog under Paro Dzongkhag (refer Figure 1). The watershed extends from Pa Chhu in the east to Chelela in the west and the Paro–Haa highway passes through the watershed. The watershed is located between 27º 22’6’’ and 27º 24’1.3’’ N and between 91º 20’ 40.1” and 91º 25’ 51.1” E. The survey area covers about 2810ha (about 6940.61 acres).[1]

Figure 1 Location map of Study Area

Remote Sensing and Gis Based Critical Evalution of Water Balance Study from Woochu Watershed, Bhutan


The study area stretches from an altitude of about 2240m asl (above sea level) near the Pa Chhu to about 3910m asl, which is about 2.0km NW upslope along the ridge of Chelela Pass. It falls within a wide range of climatic zones, stretching from warm temperate to sub-alpine. The survey area has approximately equal cover of cool and cold temperate zones, with broadleaf forest as the dominant natural vegetation along the later stages of Jew Rongchhu and coniferous forest on the surrounding hill slopes. The survey area has predominantly southerly and northerly aspect.

1.1.2. Demography

The average population growth of Bhutan is currently estimated at approximately 3%. Luni geog has a total of 267 households with a population of 1735 (Paro-Zonglela Forest Management Pan 2002-2012). A total of 50 households in 2 villages Woochu and Jewphu under Luni geog from the catchment area. Jewphu had a total household of 21 and a population of 202 according to 2007 census. Woochu had a total of 48 households and a population of 297 (2007 census). The average family member in Jewphu is 9 and in Woochu is 6.

The population structure of Jewphu and Woochu were studied for the year 2009. It was seen that the age distribution is regular. The population increased from 0-4-age class to 15-19-age class and then it showed a declining trend. The more number of people in 15-19 age group indicates that there are potential producers rather than consumers in both the villages. The population of Woochu and Jewphu over the last 10 years (2000-2009) was studied and it was seen that the population was increasing over the past years with 3% growth rate. Population structure in Woochu: distribution of the population according to age class. Source: National Statistical Bureau, 2009, Bhutan.

Figure 2 Sex Ratio

Figure 3 Literacy Rate



The ratio of male to female showed that male dominates over female (Figure 1.2) with a sex ratio between male to female 51:49. The literacy rate is 43.5% including primary, lower, secondary, higher form of education (Figure 1.3). It is seen that the literacy rate is lower as compared to the national literacy rate of about 65%. 56.5% of interviewed people were farmers.

1.1.3. Source of Income

A major portion of the income of the farmers of both villages was from apple orchards. The farmers sell their apples to the nearest market and also to international markets. From the survey it was recorded that a farmer earns about Nu.2, 30,000 (approximately 4,953 US $) in a year from apple business. The profitability of the apple business clearly indicates the larger extent of ownership of kamzhings (dry lands) within which they have their apple orchards. It was followed by agricultural income mainly from paddy cultivation. Then it was followed by the sale of vegetables; asparagus, potato and chilies were their main vegetables that fetched good price in the domestic market. The other activities such as hiring of vehicles, contract business and others were small contributors to their source of income.

Figure 4 Sources of income of farmers of Woochu and Jewphu villages

1.1.4. Climate

Both the temperature and the rainfall data are an averaged subtotal for 10 years (Metrology Department). The mean minimum temperature drops to about -3.47º C in January, and rises to about 14.34º C in July. The mean maximum temperature rises from about 18.11º C in January to 28.84º C during August.

Figure 5 Mean, Maximum & Minimum Temperature(°C) for Ten Years

Source of income

8%7%

2%

19%

45%

4%

3%

2%

3%

7%Hiring Vechicle

Contract

Others

Agriculture

Apple

Daily Wages

Diary Products

Salary

Rent

Straw Mushroom



The mean annual rainfall at Woochu watershed is about 662.13mm. The maximum rainfall occurs during the month of July (175.38mm) and the minimum rainfall occurs during the month of November (1.87mm). The rainfall data suggest about 72% of the total annual rainfall occurs during the months of June to September. [2]

Figure 6 Temporal Variation of Average Rainfall over the Study Area

1.2. Objective of the Study

Basically the main objective of the study is to do water balance study of a particular catchment. We will calculate all water resource available using water balancing equation, and then come out with plan and strategy to make the maximum possible use of that water resources available for this particular catchment area. And later this idea and long term plan would be to replicate the project we are doing in larger scale in future. Following are the objective of our research:-

1. To extract and understand the topographical characteristics of the study area for effective management and future development (Preparation of thematic maps using RS and GIS).

2. To do water balance for the study area using SCS-CN Method Analysis.

3. To implement the action plan for sustainable management of water resource in order to enhance socio-economy, food security and to reduce the poverty.

3. METHODOLOGY

The two types of data products are spatial data and non-spatial/attribute data. The spatial data comprised of drainage, base details, slope maps. The non-spatial or attribute data is composed of rainfall, geology, topography, climate, soil data and cropping pattern and crop water requirement in Bhutan, all those had been collected from the various departments.In this study the steps involved in deriving all these data products, the sources of the data acquisition and the ways transforming these data products which are suitable to GIS software are discussed.

3.1. Data Collection

The GIS data used in this study are classified as

• Topographical data

• Thematic data

• Field data

• Collateral data



The topographical and thematic data are classified as spatial data and the field data and collateral data as attribute data. The details of these types of data products are discussed below.

Spatial data

The spatial is derived from satellite sensing system and survey of Bhutan topo-sheets. Survey of Bhutan topo-sheets are 78E/7 on 1:50,000 scale.

Figure 7 Survey of Bhutan Toposheet no 78E/7, 1: 50000, 1998

Figure 8 LAND SAT 7 data (Path 138, Row 049)

3.2. Collateral Data

The collateral data is acquired from various offices of the Government Organizations in Bhutan like Department of Agriculture, Meteorology Department, Survey of Bhutan and National Soil Service Center, MoAF, Bhutan. In the present study four different sources are used to collect the required data. The four sources are remote sensing satellite systems, survey of Bhutan topo-sheets, related Government and private agencies for existing data products and field surveys for collection of primary data products. In transforming this raw data to data compatible to GIS, care is taken for appropriate level of data precision and accuracy.



3.2.1. Building Digital Database

The database development consumes substantial resources particularly, in the initial stages of system development. The geographic information databases are developed from multiple sources and by a variety of methods, namely, digitization, scanning and automated digitization, coordinate geometry (COGO), remote sensing, SOB topo maps and other sources.

Data Creation

In GIS, topology is the term used to describe the geometric characteristic of objects, which do not change under transformations and are independent of any coordinate system. The topological characteristics of an object are also independent of scale of measurement. Topology as it relates to spatial data and non-spatial data consists of three elements, namely adjacency, containment and connectivity. Broadly, topology can be explained in two ways. Topology consists of metric aspects of spatial relations, such as size, shape, distance and direction. Many spatial relations between objects are topological in nature, including adjacency, containment and overlap. The geometric relationship between spatial entities and corresponding attributes are very crucial for spatial analysis and integration in GIS. In topology creation both the spatial and attribute data are linked from which different parameter maps are generated. These maps depict the special distribution of non-spatial information on spatial locations.

Digital Thematic Mapping

Using the image interpretation key, preliminary interpretation of satellite imagery is carried by transferring the features from base map on to the transparency. This transparency with base line data feature is then overlaid on the satellite imagery. Then the features of soil map are extracted and transferred from the satellite pictorial data.[3]

Data Integration

The work schedule gives the following principle steps involved.

1) Collection of toposheet from survey of Bhutan(1:50,000 scale)

2) Data from satellite imagery(LAND SAT 7 from) obtained from NRSA.

3) Delineation of the study area and conversion of raster data into vector data.

4) Preparation of thematic maps with the help of secondary data and primary data.

5) The above data is then exported to ARC GIS /INFO and further processed in ArcView GIS software to create digital database for subsequent data analysis.

6) Study of the land use and soil features and their application in obtaining CN values for generation of runoff in this study area.





4. RESULT AND DISCUSSION

4.1. WATER BALANCE STUDIES

4.1.1. Analysis of SCS-CN Method

SCS-CN method, developed by Soil Conservation Services (SCS) of USA in 1969, is a simple, predictable, and stable conceptual method for estimation of direct runoff depth based on storm rainfall depth. It relies on only one parameter, CN. Currently, it is a well-established method, having been widely accepted for use in USA and many other countries. The details of the method are described in this section.[5]

Basic Theory: The SCS-CN method is based on the water balance equation of the rainfall in a known interval of time ∆t, which can be expressed as

P = Ia + F + Q (4.1)

Where, P = Total precipitation,

Ia = Initial abstraction,

F = Cumulative infiltration excluding Ia and

Q = Direct surface runoff (all in units of volume occurring in time ∆t)

Two other concepts as below are also used with eq. (4.1)

1) The first concept is that the ratio of actual amount of direct runoff (Q) to maximum potential runoff (=P-Ia) is equal to the ratio of actual infiltration (F) to the potential maximum retention ( or infiltration), S. This proportionality concept can be schematically

This S

F

IP

Q

a

=−

(4.2)

Q F

(P-Ia)

Proportionality Concept

2) This second concept is that the amount of initial abstraction (Ia) is some fraction of the potential maximum retention (S)

Thus Ia = λS (4.3) Combining Eqn. (3.2) and (3.3), and using (3.1)

Q = ( ) ( )

( )SP

SP

SIP

IP

a

A

λ

λ

−+

−=

+−

−

1

22

for P>λS (4.4)

The relation between Ia and S was developed by analyzing the rainfall and runoff data from experimental small watersheds and is expressed as Ia = 0.2S. Combining the water balance equation and proportional equality hypothesis, the SCS-CN method is represented as

( )( )SP

SPQ

8.0

2.02

+

−=

(4.5)

Further Q = 0 for P ≤ λS (4.6)

For operation purposes a time interval ∆t = 1 day is adopted.



Thus

P = Daily rainfall and

Q = Daily runoff from the catchment.

1. Curve Number (CN).

The parameter S representing the potential maximum retention depends upon the soil-vegetation-land use complex of the catchment and also upon the antecedent soil moisture condition in the catchment just prior to the commencement of the rainfall event. For convenience in practical application the Soil Conservation Service (SCS) of USA has expressed S (in mm) in terms of a dimensionless parameter CN (the Curve Number) as

S =

−=− 1

100254254

25400

CNCN (4.7)

The constant 254 is used to express S in mm

The curve number CN is now related to S as

CN = 254

25400

+I (4.8)

and has a range of 100 ≥ CN ≥ 0. A CN value of 100 represents a condition of zero potential retention (i.e. impervious catchment) and CN = 0 represents an infinitely abstracting catchment with S = ∞. This curve number CN depends upon

• Soil type

• Antecedent moisture condition

2. Soil Classification

In the determination of CN, the hydrological soil classification is adopted. Here, soils are classified into four classes A, B, C and D based upon the infiltration and other characteristics. The important soil characteristics that influence hydrological classification of soils are effective depth of soil, average clay content, infiltration characteristics and permeability. Following is a brief description of four hydrologic soil groups:

• Group – A: (Low Runoff Potential): Soils having high infiltration rates even when thoroughly wetted and consisting chiefly of deep, well to excessively drained sands or gravels. These soils have high rate of water transmission. [Example: Deep sand, Deep loss and Aggregated silt]

• Group – B: (Moderately Low runoff Potential): Soils having moderate infiltration rates when thoroughly wetted and consisting chiefly of moderately deep to deep, moderately well to well-drained soils with moderately fine to moderately coarse textures. These soils have moderate rate of water transmission. [Example: Shallow loess, Sandy loam, Red loamy soil, Red sandy loam and Red sandy soil].

• Group – C: (Moderately High Runoff Potential): Soil having low infiltration rates when thoroughly wetted and consisting chiefly of moderately deep to deep, moderately well to well-drained soils with moderately fine to moderately coarse textures. These soils have moderate rate of water transmission. [Example: Clayey loam, Shallow sandy loam, Soils usually high in clay, Mixed red and black soils]

• Group – D: (High Runoff Potential): Soils having very low infiltration rates when thoroughly wetted and consisting chiefly of clay soils with a high swelling potential, soils with a permanent high-water table, soils with a clay pan, or clay layer at or near



the surface, and shallow soils over nearly impervious material. [Example: Heavy plastic clays, certain saline soils and deep black soils].

• Antecedent Moisture Condition (AMC)

Antecedent Moisture Condition (AMC) refers to the moisture content present in the soil at the beginning of the rainfall-runoff event under consideration. It is well known that initial abstraction and infiltration are governed by AMC. For purposes of practical application three levels of AMC are recognized by SCS as follows:

AMC – I: Soils are dry but not to wilting point. Satisfactory cultivation has taken place.

AMC – II: Average conditions.

AMC – III: Sufficient rainfall has occurred within the immediate past 5 days. Saturated soil Conditions prevail.

The limits of these three AMC classes, based on total rainfall magnitude in the previous 5 days, are given in Table 4.1. It is to be noted that the limits also depend upon the seasons: two seasons, viz. growing season and dormant season are considered.

Table 1 AMC for Determining the Value of CN as per the SCS of USA.

AMC Type Total Rain in Previous 5 days

Dormant Season Growing Season

I Less than 13 mm Less than 36 mm

II 13 to 28 mm 36 to 53 mm

III More than 28 mm More than 53 mm

The variation of CN under AMC-II, called CNII, for various land use conditions commonly found in practice are shown in Table 4.2

Table 2 Runoff [CNII] for Hydrological Soil Cover Complexes [Under AMC-II Conditions]

Land use

Cover Hydrologic soil group

Treatment or

practice

Hydrologic

condition A B C D

Cultivated ContouredTerraced Poor 66 74 80 82

Good 62 71 77 81

Cultivated Bunded Poor 67 75 81 83

Good 59 69 76 79

Forest

Dense 26 40 58 61

Open 28 44 60 64

Scrub 33 47 64 67

For AMC – I: CNI = II

II

CN

CN

1281.0281.2 − (4.9)

For AMC – III: CNII= II

II

CN

CN

00573.0427.0 + (4.10)

The equation (4.9) and (4.10) are applicable for finding out CNI and CNII under the condition AMC-I and AMC-III. In this case studies, the CN values were determined based on the Table 4.2 and hydrological soil group. To create and detect the curve number values for each classified area; the hydrological soil group, the land use and land cover results were used. By applying expression in ArcGIS.9 and evaluating this expression, the curve number



can be determined. The details of CN value which is worked out against the land use and soil group were illustrated in the table 4.3.

According to National Soil Service Centre of Bhutan, the soils characteristics of Woochu watershed can be classified into several categories based on colour, grain size particles, drainage condition etc. Sand, loamy, or Sandy Loam, Silt loam or loam, Sandy clay Loam and Clay loam, silt clay loam, sandy clay, silt clay or clay with its areas coverage as distributed at the watershed as shown in Table 3.

Table 3 Classification of Soil in the Study Area

Sl. No. Soil Texture Area covered Unit Percent(%)

1 Sand, Loamy sand or Sandy Loam (Poorly

graded or Well graded) 2.6569 Km2 9.72%

2 Silt Loam or Loam 20.7528 Km2 75.94%

3 Sandy Clay Loam 1.7384 Km2 6.36%

4 Clay Loam, Silt Clay Loam, Sandy Clay or

Clay 2.1800 Km2 7.98%

TOTAL 27.3282 Km2 100%

By using the datas of soil classification, Woochu watershed was further grouped into four hydrological soil groups: Group A, Group B, Group C and Group D based on grade condition and classification texture of the soil (poorly or well graded). This logical condition is applied in ArcGIS.9.1, and the hydrological soil group classification as given in Table 4.4. and displayed in Fig. No.2

Table 4 Classification of Hydrological Soil Group

Hydrological Soil Group Area Km² Percentage of Area%

A 2.659 9.72

B 20.7528 75.94

C 3.18 7.98

D 0.7384 6.36

Actually the equation (4.7) and (4.8) are applicable for finding out CNI and CNII under the condition AMC-I and AMC-III. In this case studies, the CN values were determined based on the Table 5 and hydrological soil group. To create and detect the curve number values for each classified area; the hydrological soil group, the land use and land cover results were used. By applying expression in ArcGIS.9 and evaluating this expression, the curve number can be determined. The values of curve number for each area are briefly presented in Table 4.4. The details of CN value which is worked out against the land use and soil group were illustrated in (Figure 10 & 11)

Figure 10 Hydrological Soil Group



Figure 11 Soil Group Map

5. RUNOFF

The final result in this project studies determine the water balance parameters of Woochu Watershed in Paro area whereas the precipitation (662.50 mm/year) is the main input parameter in the water balance. The water from the runoff is the quantity of water considered to be available that can be collected for use .After the runoff amount is known to the fact, the dam or reservoir for storage of runoff can be provided. The remaining quantities are losses due to infiltration and evaporation as shown in the pie chart.

Table 5.Annual Rainfall and Runoff

Month Rain fall(m3) Run off(m3)

January 81896.56 0.00 February 177818.22 0.00

March 256458.96 0.00 April 388069.49 123.16 May 706013.48 14760.22 June 1101471.18 73669.17 July 2196180.27 513817.57

August 1495551.43 187299.47 September 1136659.16 81686.44

October 688106.43 13210.09 November 23416.91 0.00 December 39946.49 603.12

Figure 12 Annual Yield Showing Runoff



REFERENCES:

[1] A. sadoddin, V. Sheikh, R. Mostafazadeh, M. Gh. Hslili, Analysis of vegetation-based management scenarios in Raman watershed, Golestan, Watershed Management, Gorgan University of Agriculture Science and Natural Resources, Iran, 2010: 1735-8043

[2] Tshering, K. Water Harvesting Policies and Institutions in Bhutan. In Waters of Life Perspectives of Water Harvesting in the HKH. Eds. 2000

[3] SS. Asadi, Padmaja Vuppala, K. Santosh Kumar and M. Anji Reddy Evaluation and Mapping of Groundwater Prospects Zone Usingremote Sensing and Geographical Information System Jour. of Geophysics January-April-July & October 2009,Vol. XXX No.1- 4, pp 63 to 7,

[4] SS. Asadi , A. K. Vuppaladadiyam, M. V. Raju, T. Lakshmi Prasad Assessment Of Hydrogeological Characteristics Using Remote Sensing & GIS: A Model Study From Guntur (Dt. ), A. P, International Journal of Applied Environmental Sciences ISSN 0973-6077 Volume 10, Number 2 (2015), pp. 785-798

[5] SS.Asadi, Rakesh Kumar Yadav, Yettapu Sai Sruthi, Sanjay Yadav, Gauri Shankar Sah Land Sliding Zones Identification Using Remote Sensing And Gis: A Model Study From Pokhara To Kurintar, Prithvi Highway, Nepal International Journal of Applied Engineering Research ISSN 0973-4562 Volume 10, Number 8 (2015) pp. 19585-19599.

[6] SS. Asadi, B. Harish kumar, M. Sumanth, P. Sarath Chandra, T. Eswar Rao Evaluation of soil quality using Geospatial technology International Journal of Applied Chemistry. ISSN 0973-1792 Volume 12, Number 1 (2016) pp. 37-49SS.Asadi , P. Neela Rani ,B.V.T.Vasantha Rao and M.V.Raju Estimation of Ground Water Potantial Zones Using Remote Sensing And Gis: A Model Study International Journal of Advanced Scientific Research and Technology Issue 2, Volume 2 (APRIL 2012) ISSN: 2249-9954

[8] Integrated Mission for Sustainable Development (IMSD)Technical guidelines (1995) Andhra Pradesh State Remote Sensing Application Centre (APSRAC), Government of Andhra Pradesh.

[9] National Watershed Atlas of India (1990) Prepared by All India Soil and Land use Survey, Department of Agriculture and Co-operation, Government of India.

[10] RiverBasin Atlas of India, Prepared by Central board for the prevention and control of water pollution, India, 1985.D Dadoria, H L Tiwari and R K Jaiswal, Assessment of Reservoir Sedimentation In Chhattisgarh State Using Remote Sensing and GIS. International Journal of Civil Engineering and Technology, 8(4), 2017, pp. 526–534.M. Satish Kumar ,SS. Asadi, S.S. Vutukuru, Assessment of Heavy Metal Concentration in Ground Water by Using Remote Sensing and GIS, International Journal of Civil Engineering and Technology, 8(4), 2017, pp.1562-1573B. Ramyaa Sree and SS. Asadi A Remote Sensing and GIS Based Critical Evaluation of Change Detection Study in Thimmaipally Watershed for Land Resources Management, International Journal of Civil Engineering and Technology, 8(4), 2017, pp. 2110-2124.

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REMOTE SENSING AND GIS BASED CRITICAL … The present study ... Management Pan 2002-2012). ... would be to replicate the project we are doing in larger scale in future. Following are