Land Use:
Land use pattern of this area of the sub basin has been classified into six categories - such as agricultural land, forest land, grass land, built up area (village etc.), tea gardens and water bodies. Agricultural and forest land occupy most of the areas in the sub basin.
Objectives
The main objective is to use GIS as tools for assessment of flood risk zones in the study area at different flood levels calculated by frequency analysis methods.
The specific objectives area as below :
- To create a digital elevation model (DEM) of the study area.
- To find out flood levels (Gauge) for different return periods by frequency analysis of available gauge data.
- To create area inundation map of the study area with levels computed from frequency analysis and using the DEM, in case of embankment failure.
- To calculate the area that will be flooded by a particular return period flood.
- To assess flood damage.
Materials and Software Used
Data Used :
- Survey of India toposheet on 1:50,000 scale 83 E/16, 83 F/13, 83 I/4 & 83 J/I.
- IRS 1B data (LISS II) of 14 Feb. 1995.
- Landuse map of Lakhimpur district, Assam prepared by Assam Remote Sensing Application Centre.
- Hydrologic data from Brahmaputra Board, Ministry of Water Resources, Govt. of India.
- Literature and Maps on various themes of the area from Brahmaputra Board.
Software Used :
- ILWIS (Integrated Land and Water Information System) for digitization, calculation and all analysis with spatial and attribute data.
- MS Excel for flood frequency analysis.
Methodology
Frequency Analysis :
The flood frequency analysis is one of the important studies of river hydrology. It is essential to interpret the past record of flood events in order to evaluate future possibilities of such occurrences. The estimation of the frequencies of flood is essential for the quantitative assessment of the flood problem. The knowledge of magnitude and probable frequency of such recurrence is also required for proper design and location of hydraulic structures and for other allied studies. The gauge data which are random variable, follow the law of statistical distribution. After a detailed study of the distribution of the random variables and its parameters such as standard deviation, skewness etc. and applying probability theory, one can reasonably predict the probability of occurrence of any major flood events in terms of discharge or water level for a specified return period.
Flood frequency analysis are done in our study by selecting annual maximum gauge levels at Sisapathar gauge site located in the study area. Two methods of statistical distribution i.e. Gumbel’s extreme value distribution and Log Pearson type III distribution are attempted by selecting peak gauge level data for 21 years (1974-1994) at Sisapathar.
This extreme value distribution was introduced by Gumbel (1941) and is commonly known as Gumbel’s distribution. It is one of the most widely used probability analysis for extreme values in hydrologic and meteorological studies for prediction of flood, rainfall etc.
Gumbel defined a flood as the largest of the 365 daily flows and the annul series of flood flows constitute a series of largest values of flows. In our attempt to find out water levels at different return period, we have used the Gumbel’s equation
xT = x + k * SDV
where,
x
T = Value of variate with a return period ‘T’
x = Mean of the variate
SDV = Standard deviation of the sample
k = Frequency factor expressed as
k = ( yT - yn ) / Sn
y
T=Reduced variate expressed by
( yT ) / ( T - 1 ) = -( LN * LN )
T =Return period
Yn =Reduced mean from table
Sn =Reduced standard deviation from table.