International Journal of Scientific & Engineering Research Volume 4, Issue 2, February-2013 1

ISSN 2229-5518

Mapping of Fishes of Brahmaputra River Using

GIS Technology:

A New Introduction to Fishery Business

1Chandasudha Goswami, 2Amol Nale

Abstract— GIS helps to answer questions and solve problems by looking at data in a way that is quickly understood and easily shared. GIS benefits organizations of all sizes and in almost every industry. The benefits of GIS are generally: Increased Efficiency, Better Decision Making, Improved Com- munication, and Better Recordkeeping & Managing Geographically. We have taken our study area as Brahmaputra River: the largest river of Assam to make some GIS analysis. It includes mapping of collected data (Primary & Secondary) about fish seed production and fish generation, various compara- tive analysis etc. This basin covers the areas of Tibet, China, India and Bangladesh. The Ganges River originates in China, and along its 2,500 km long

course, the river flows through northern India and passes through the state of West Bengal in India and then enters Bangladesh (A. Bhaduri and E. Barb- ier). Normalized Differential Vegetative Index (NDVI) is sensitive to the presence of green vegetation and has been successfully used in numerous re- gional and global applications for studying the state of vegetation (Seller P J, 1985).

Index Terms— GIS, Mapping, NDVI, Vegetation.

INTRODUCTION

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HIS is an era of globalization. Now every task is possible at low rate as well as consuming less energy. It makes our life so easy that from bill payment to analysis of a world-
wide project or its decision making we can do sitting in one place by a single click.
One of the most prominent businesses existing in India is Fish farming & export. In addition to transportation what makes this business possible; another modern analyzing tool in this respect is GIS and RS. GIS describes any information system that integrates stores, edits, analyzes, shares, and dis- plays geographic information for proper decision making. GIS applications are tools that allow users to create interactive queries (user-created searches), analyze spatial information, edit data in maps, and present the results of all these opera- tions.
We have taken our study area as Brahmaputra River of As- sam to make some of the GIS analysis. This basin covers the areas of Tibet, China, India and Bangladesh. The Brahmaputra changes its course and pattern along with its current flow very frequently especially in its upper stretches and this has a strong bearing on its hydrobiology. There are about 217 fish species have been recorded from the upper Brahmaputra of which about 150 may be considered as ornamental varieties (Web 1)

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1. JRF, Dept. of Biodiversity, Abasaheb Garware College, Pune, India; Email: goswami.chandasudha@gmail.com

2. Research Scholar, Dept. of Business Administration, Nagpur Univer- sity, Nagpur, India.

OBJECTIVES/AIM OF THE STUDY:

 The main aim of this study is to know how GIS helps us in decision making. In this study the district wise fish count along the Brahmaputra River is analysed using GIS and RS.

 To analyse the fishery attribute of the river using GIS Technology.

 To know about the PFZ (Potential Fishing Zone): A

new concept.

LITERATURE REVIEW:

Fisheries management and planning has many spatial components (e.g. movements and migrations of resources, definition of fishing grounds, transportation networks, mar- kets), and many serious issues like habitat loss and environ- mental degradation have spatial dimensions.In this regard, GIS is a technology that can help to clarify the issues and lead to solutions by treating many spatial components simultane- ously. However, many people are still unaware or afraid of the technology and its potential for fisheries management. (Web 2)
Flood impact on fishery (Fig 1, 2)
The before and after Brahmaputra River flooding satellite
image pair. Their image shows the river as a blue color instead
of the actual brown, sediment-laden color. Recent satellite
surveys indicate that the Brahmaputra basin, as a whole, has a
forest cover of about 14.5%, grasslands occupy about 44%,
agricultural lands about 14%, cropland/natural vegetation

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mosaic 12.8%, barren/sparsely vegetated land 2.5%, water bodies 1.8%, snow and ice 11%, urban land 0.02% and perma- nent wetlands 0.05%. The total forest cover of the Brahmapu- tra basin in India is 1, 14,894 sq. km. i.e. 54% of the total area. The distribution of forest covers in Assam (20.6 %). Recent satellite surveys indicate a considerable decline in forest cover due to deforestation, land-use conversion and land degrada- tion. Shifting (jhum) cultivation, which is widely practiced in the northeastern region and is a major cause of deforestation and has a disastrous impact on the region’s ecology through soil erosion, loss of soil fertility, falling crop yields, lowering of groundwater recharge, increase in surface run-off, sinking of the groundwater table and acceleration in the rates of sedi- mentation in rivers and reservoirs downstream ultimately leading to a significant rise in riverbed levels and intensifica- tion of flood hazards.
Fig 1. Satellite view of flooding around Brahmaputra River captured on September 25, 2012 by MODIS/Aqua satellite (Web 3)
Fig 2. Map of flood water over the affected Assam:Aqua im- agery 2-5th august, 2007 (Web 4)
Potential Fishing Zone: (Fig 3)
In recent years, study of ocean from satellite in terms of
temperature, sea level and ocean colour has given an insight
into the changing climate of the world. Phytoplankton pig-
ment which is present in all living plant and which is respon-
sible for photosynthesis is chlorophyll.
NDVI gives positive values to the vegetation based on the
spectral characteristic of chlorophyll present in them. NDVI is
commonly used for land applications, but in the present study
it has been used for water bodies as the NDVI is negative to
water surfaces (Prangsma G J, Roozekrans J N, 1989). Presence
of chlorophyll gives positive value for NDVI, which indicates
the presence of phytoplankton, which intern indicates the presence of zooplankton and fish. This becomes an indicator to identify potential fishing zones.
Fig 3. Image showing PFZ zones of India: (Web 5) PFZ Forecast Date: 04-DEC-2009
Valid up to: 06-DEC-2012
Remote sensing data is used extensively for large area vege- tation monitoring. Various mathematical combinations of these bands have been used for the computation of NDVI,

IJSER © 2 http://www.ij

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which is an indicator of the presence and condition of green vegetation.
NDVI = NIR – RED / NIR + RED

METHODOLOGY:

Methodology is the body part of any study. Different methods are implemented as a set of well defined steps or phases which aids with a clear measurable set of existing enti- ties. The methodology adopted in this study incorporates GIS analysis. It is a schematic presentation of procedures and rules used by the analyst who working in a discipline or engaged in an enquiry.
Data is the soul of any information system. The effi-
ciency and performance of any information system highly de-
pends on nature, quality and availability of data. For GIS
analysis we need two types of data at the same time viz. spa-
tial & non-spatial. These data may of primary data type or
secondary data type. (Table 1, 2)

FINDING AND DISCUSSION:

N.E. Region of India in particular has rich fish re- source. Several migratory fishes have also been listed. All the fish species of Assam are more or less inhabitant of the river Brahmaputra or its tributaries i.e. fish attributes of Assam are directly or indirectly related with the Brahmaputra river envi- ronment. We can analyze district wise fish production by tak- ing in account the fishes of the river Brahmaputra and its trib- utaries.

Fig 4 shows that Production of fish (in tone) increases remarkably in Dhubri district in the year 06-07. Karimganj and Jorhat also show increasing fish production trend. But the re-
maining most of the districts has decreasing trend and few has almost same rate. Overall performance of the state in fish pro- duction comes drastically downward due to low district wise fish production.

Fig 5 depicts Fish seed (in million) production is very poor throughout the state. But among all the districts Nagaon, Barpeta, Karimganj and Nalbari bears some value accordingly. All remaining has negligible value. In the session 2005-06 the above districts show some good result. But in the next session the seed production number decreases. This in turn leads to less number of fish productions in 2006-07. The decreasing trend of fish seed and fish production is due to increasing pol- lution rate and unstable climatic condition. So for the preser- vation of these natural recourses scientific way of culture must be taken in Assam as production rate is low here and as graph is also in decreasing trend.

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Fig 6 (Thematic map of Fish seed & fish production in
2005-06) shows Fish seed production is highest in Nagaon and
Barpeta in 2005-06, and in the same year fish production is
highest in Nagaon, Barpeta and also in Cachar and Lakhimpur
within a range of 11776 tonne to 18335 tonne.second position
in fish seed production are Karimganj and Nalbari, again in
fish production second position is occupied by several states
viz. Karimganj, Nalbari, Dhuburi, Kamrup, Darrang, Sonitpur,
Jorhat, Sibsagar and Dibrugarh. From this it is clear that

though seed production is very very low in the districts like
Dhuburi, Kamrup, Darrang, Sonitpur, Jorhat, Sibsagar, Dibru- garh etc but fish production is not bad, i.e. less number of eggs is spoiled. The remaining districts have low seed as well as fish production.
Again, in Fig 7 (Thematic map of Fish seed & fish production in 2006-07) the legend itself clarifies the decreasing trend of seed and fish number. In 2006-07 seed production is highest again in Nagaon, Barpeta and in Karimganj. Then comes the position of Sonitpur, Cachar and Lakhimpur. In the same session fish production is comparatively highest in many of the districts like Dhuburi, Kamrup etc along with Nagaon, Barpeta and Karimganj. But the highest range of fish seed production decreases from 509-1207 million to 46-748 million. Again in the same way fish production also decreases from
11776 -18335 tones to 9359-17939 tone. Such lowering of popu- lation size and genetic resource indicates threat to the time to come.

Tables and Figures

Table 1 Type of Data

Table2: District-wise production of fish seed and fish in Assam
In large low-gradient rivers, benthic fish may actually be more likely to survive floods due to a higher tolerance for suspended sediment (Whitfield and Paterson, 1995). In all sys- tems, direct impacts on fish are inseparable from habitat changes and fluctuations in other parts of the food chain. In high-gradient systems, recovery periods and long-term effects of flooding on fish populations are closely tied to geomorphic changes in aquatic habitat. In cases where key habitat is lost and must be repaired by future geomorphic Processes, popu- lation levels may be depressed for decades.

CONCLUSION:

Brahmaputra being an international river of immense size, huge resource base and high hazard potential, only effec- tive cooperation and coordination among the basin countries,

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together with persistent efforts at the national and regional levels using higher technologies like GIS and RS can create an effective response mechanism to the problem like floods and also help in decision making purpose for the progress and prosperity for the region. Thus we can use such tools any- where to analyze the situations from another corner using var- ious databases like satellite imagery at low investment and within effective time period.

REFERENCES:

[1] Bhaduri, E. Barbier (2012), Linking Rivers in the Ganges- Brahmaputra River Basin: Exploring the Transboundary Effects.

[2] Sellers, P. J. (1985) 'Canopy reflectance, photosynthesis, and transpi- ration', International Journal of Remote Sensing, 6, 1335-1372.

[3] Prangsma. G. J., and Roozekrans. J. N., Using NOAA AVHRR image- ry in assesing water quality parameters., Int. J. RS., 1989, vol 10, Nos

4 and 5, 811-818.

[4] Whitfield, A.K. and Paterson. Q.W. (1995). “Flood-associated mass mortalities of fishes in the Sundays Estuary”, Water SA, 21(4), 385-

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[4] Web-4:http://www.unitar.org/unosat/node/44/956, accessed on

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