INTERNATIONAL JOURNAL OF GEOMATICS AND GEOSCIENCES Volume 7, No 3, 2017

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1 INTERNATIONAL JOURNAL OF GEOMATICS AND GEOSCIENCES Volume 7, No 3, 2017 Copyright by the authors - Licensee IPA- Under Creative Commons license 3.0 Research article ISSN Rainfall frequency analysis to predict flood in West Tripura District, Tripura, North-East India Moujuri Bhowmik 1, Nibedita Das (Pan) 2, Istak Ahmed 1, Jatan Debnath 1 1-Research Scholar, Department of Geography and Disaster Management, Tripura University, Suryamaninagar , Tripura, India 2- Associate Professor and Head, Department of Geography and Disaster Management, Tripura University, Suryamaninagar , Tripura, India moujurigeo14@gmail.com ABSTRACT Flood is a common problem in West Tripura District where two rivers namely the Haora River and the Sonai Gang are flood affected. About 60% area and 55% people are affected by flood in the whole district. Monsoon rainfall, mainly intensity and duration of rainfall, is the main causative factor of flood. Therefore, this present study has been carried out to predict the flood hazard in West Tripura District for 50 and 100 years return period on the basis of the rainfall frequency curve analysis. For this frequency analysis Weibul s method has been applied. The annual rainfall data from the year of the West Tripura District have been provided by the Department of Agriculture, Govt. of Tripura and Indian Council for Agricultural Research (ICAR), Lembucherra. Rainfall frequency curve shows that rainfall will be 390 mm and 410 mm or more on 50 and 100 years return period respectively which will increase the discharge of these two rivers and ultimately will cause devastating flood in this district. Therefore, proper flood hazard management is necessary through proper land use planning of the flood plains of these two rivers and through changing the cropping pattern. Keywords: Flood, West Tripura district, Intensity and duration of rainfall, Rainfall frequency analysis. 1. Introduction Flood simply means inundation of extensive land area with water for several days in continuation. Generally after a spell of heavy rain (due to depression) which may lasts for a period of several hours to several days, that large volume of runoff is generated in the upper catchment and river experiences floods (Kale, 2003). Flood hazard is the probability of occurrence of a potentially damaging flood event of a certain magnitude within a given time period and area (Brooks, 2003). In West Tripura District two rivers, namely, the Haora River and the Lohar Nala experience flood and these basins also experience flash flood. Flash floods caused by relatively small cells of convectional activity, have received much attention and are deemed characteristic of small to medium basins. Flow increases from zero to peak discharge in a few minutes or a few hours and they often have a steep bore front (Leopold and Miller, 1956; Renard and Keppel, 1966; Sharon, 1972; Schick, 1988; Hassan, 1990; Abrahams et al., 1995; Reid and Frostick, 1997). About 40% mouzas and 41% people of West Tripura District are severely affected by flood. Piedmont plain (areas of flash flood) and the alluvial plains cover about 70% of the District out of which 60% experiences flood hazard and 55% population are affected. The most common cause of flooding in this district is prolonged and heavy rains. Submitted on November 2016 published on February

2 The present study carried out the analysis of rainfall frequency to predict the flood hazard in West Tripura District for 50 and 100 years return period. 2. Study area West Tripura District extends from 'N to 'N latitude and 'E to 'E longitude (Figure 1). Geologically, the study area falls under Dupitilla series and Tipam group of rocks which is characterized by sand rocks. Surma group and alluvium deposition are also found in this district. Tropical monsoon type of climate prevails here. The area is characterized by (i) hill range, (ii) piedmont slopes and uplands, (iii) terraces and tillas and (iv) flood plains. In this district (i) reddish yellow brown sandy soil, (ii) red loam and sandy loam soils, (iii) younger and older alluvial soils and (iv) lateritic soils are found. Figure 1: Location map of the study area 3. Methodology 3.1 Materials In order to carry out this study Geomatica V 10.1, MS Excel, Adobe Photoshop, GPS tool, SOI topographical maps (Ref. No. 79M/1, 2, 5, 6, 9, 10, 78 P/8 and 12), Land sat Imagery (ETM PAN and MSS) have been used. 3.2 Method For Rainfall frequency analysis Weibul s Method has been followed. The annual rainfall data from the year of West Tripura District have been provided by the Department of Agriculture, Govt. of Tripura and Indian Council for Agricultural Research (ICAR), Lembuchhera. On that basis, return period and percent probability of rainfall have been calculated. Then, rainfall data were plotted against return periods and the trend line was 311

3 drawn, extrapolated and expected rainfall for 50 and 100 years return period has been identified. 4. Results and discussion The rainfall frequency is usually defined by reference to the annual maximum series, which consists of the largest values observed in each year (Borga et al., 2005). Intense rainfall may generate overland flows and pooling in urban areas, causing damage to buildings, infrastructure and inconvenience to people. This process is commonly known as pluvial flooding (Spekkers, et al., 2012). Flood occurs repeatedly in this district. The mouzas located in the lower reach of the Haora River from Purba Noagaon up to Bangladesh border, including Khayerpur, Mekhlipara, Bridhyanagar, Uttar Champamura, Jogendranagar, Pratapgarh etc. and the mouzas located in the lower reach of the Lohar Nala namely Bamutia, Fatikchhara, Kalkalia, Tulabagan suffer from flood inundation. Flash floods usually occur within the piedmont plain from Champanagar up to Purba Noagaon in case of the Haora River and at Wakkinagar and Uttar Debendra Chandra Nagar in case of the Lohar Nala, as a result of high intensity rainfall with less duration. Monsoon Rainfall is the most important factor for flood in this district. More than 70% rainfall takes place in the monsoon months in this district (Figure 2). Monsoon generally arrives during 1 st week of June in the study area. The two key elements cause flooding are rainfall intensity and duration. Intensity is the rate of rainfall and duration is how long the rain continued. Figure 2: Amount of monsoon rainfall to total rainfall in three stations of the West Tripura District. 312

4 Source: Calculated and prepared by the researcher based on rainfall data provided by the Dept. of Agriculture, Govt. of Tripura and ICAR, Tripura Centre, Lembucherra. 4.1 Intensity and duration of rainfall It has been suggested that rainfall intensities are of prime importance for flood generation in all catchment sizes (Costa, 1987; Schick, 1988; Pitlick, 1994) and it has been appreciated that high discharges are produced by an optimal combination of basin morphometry and storm intensity (Costa, 1987; Yair and Raz-Yassif, 2004). The flood of the Haora River due to intense rainfall of July 19, 2015 explains the impact of high intensity rainfall as a potent causative factor of it. Rainfall was nearly mm within a day period (July 18-19). Figure 3 shows that there was a high discharge (152 cumec) on 19 th July 2015, which created flood at Pratapgarh, Bridhyanagar, Jogendranagar, Khayerpur and Uttar Champamura (Plate 1). Plate 1: High intensity rainfall of 24 hours (July 18-19, 2015) caused flood at Pratapgarh, located in the lower reach of the Haora River. The Lohar Nala also experienced high intensity rainfall of 102 mm on 19 th July, 2015 within a day period (July 18-19). This rainfall created cumec discharge which also caused flood at Bamutia, Kalkalia, Tulabagan and Fatikchhara (Figure 4). It is due to the fact that due to heavy shower of less duration, all storage capacities became satisfied as a result of which excessive amount of water spread over the surrounding areas and inundated parts of the lower catchment of the river basins. The flooding from the 24 hours duration rainfall is very common in these two river basins (Table 1). Table 1: Rainfall of 24 hours duration in different years Date Rainfall (mm) during 24 hours Haora River Lohar Nala 24 th June, th July, th July, 2009 Nil th May, Nil 15 th August rd September

5 Source: Department of Agriculture, Govt. of Tripura and Indian Council for Agricultural Research (ICAR), Lembucherra. Duration of rainfall also plays an important role for flooding. Sometimes, short duration intense rainstorms can produce rapid overland flow and show steep rising limb of the hydrograph. In July, 2015 the Haora and Lohar experienced havoc flood due to continuous rainfall of 19 days (623 mm) and 22 days (607.8 mm) respectively. That means, due to heavy shower of small duration, all storage capacities became satisfied, as a result of which excessive amount of water spread over the surrounding areas and inundated lower catchments of the river basins. Figure 3: Rainfall - discharge graph of the Haora River in July, Source: Prepared by the researcher on the basis of data provided by the CWC, Meghna Division, Shillong (Restricted Data). Figure 4: Rainfall - discharge graph of the Lohar Nala in July, Source: Prepared by the researcher using Khosla s method on the basis of rainfall and temperature data provided by ICAR, Tripura Centre, Lembucherra. Figure 5 indicates two distinct phases in rainfall variation. Prior to 1990, higher rainfall variation ( mm to mm) is observed and 1990 onwards this variation becomes lesser ( mm to mm). 314

6 Thus, from the above discussion it is evident that though the fluctuation of rainfall during last 24 years has been decreased but the vagaries of monsoon rainfall have been experienced by different areas of lower elevation along either side of the rivers. Figure 5: Variation in rainfall ( ) at Agartala station in accordance with mean rainfall. Source: Prepared by the researcher on the basis of rainfall data provided by the Dept. of Agriculture, Govt. of Tripura. 4.2 Coefficient of variation Rainfall variability assessment is a frequent practice in hydrology. An important application is the estimation of total rainfall over an area, e.g., a catchment as an input for hydrological models. Precipitation is in many cases the most important input factor in hydrological modelling (Beven, 2001). Though rainfall is decreasing still risk is increasing due to rapid increase in population. Variability of annual rainfall has been computed with the help of the following formula: Coefficient of Variation (CV) = Standard Deviation X 100 Mean 315

7 The coefficient of variation indicates the amount of fluctuation recorded by rainfall over 11 years ( ) from the mean values of three stations namely Sadar, Jirania and Mohanpur of West Tripura District. It generally ranges between 41 to 49% for the district as a whole. The variability is highest where the amount of rainfall is the lowest. In other words, the rainfall variability is inversely related to the total amount of rainfall and reliability of rainfall is inversely proportional to the coefficient of variability. That means the areas of high variability are the areas of low rainfall. The coefficient of variation is highest in Jirania (49.05%), moderate in Mohanpur (47%) and lowest in Sadar (41.74%) (Figure 6). Thus, Jirania is the area with higher variability which experiences lower rainfall in comparison to the other two areas. On the other hand, Sadar is the area of low variability which experiences highest rainfall of the district. Mohanpur experiences moderate rainfall which indicates moderate variability. 4.3 Rainfall frequency analysis The rainfall frequency analysis is one of the important aspects of river flood. It is essential to interpret the past record of flood events in order to evaluate future possibilities of such occurrences. The return period or recurrence interval (Tr), which is the time scale used for rainfall frequency curve and plotted along the abscissa, is the average interval of time within which rainfall of a given magnitude will be equalled or exceeded at least once. Here the return period has been calculated using Weibul s formula: Tr = (n + 1) / m Where, n = number of events i.e., years of record m = order or rank of the event (rainfall item) T= recurrence interval For the present study rainfall data of 45 years have been considered for calculating the return period and percent probability (Table 2). These rainfall values have been arranged in descending order of magnitude and ranks have been assigned as 1 to the highest value, 2 to the next highest value and so on. Rainfall data of this district show that the highest rainfall recorded in the year 1987, was 463 mm which has very low (2.17%) probability of occurrence in next 29 years. On contrary, the lowest rainfall recorded in the year 1994, was 61.4 mm which has very high (98.04%) probability of occurrence in every year. Annual rainfall corresponding to the exceedence probabilities of 100%, 50%, 25%, 15% and 10% are read as 70, 135, 185, 225 and 260 mm respectively (Figure 7). Though the rainfall is less in recent years as a consequence of global warming, but due to increase of population the flood risk is also increasing. To identify the rainfall for the 50 and 100 years return period, Rainfall Frequency Curve of the West Tripura District has been prepared, where rainfall recurrence and associated rainfall have been plotted on log-log graph along the abscissa and ordinate respectively. Then, the frequency curve has been extrapolated graphically along the upper trend, so as to include 50 and 100 years rainfall event. From the graph, it can be predicted that in every 50 and 100 years this district would have a rainfall of 390 mm and 410 mm or more respectively (Figure 8). Due to heavy shower 316

8 Table 2: Rainfall frequency analysis (Weibul s method) of West Tripura District Year Maximu m rainfall (mm) Maximum rainfall in descendin g order (X m ) Rank (m) Return Period T r = n+1 = 46 m m Exceedence probability P (X m )= 1 = m T r 46 Percent probability P= 1/T r X Source: Calculated by the researcher 317

9 Figure 7: Exceedence probability of rainfall of the West Tripura District. Source: Prepared by the researcher on the basis of rainfall data provided by the Dept. of Agriculture, Govt. of Tripura. of small duration (24 hours), all storage capacities will become satisfied as a result of which excessive amount of water spread over the surrounding area and inundated lower catchments of the river basins of this district. Figure 8: Rainfall Frequency Curve showing rainfall of 50 and 100 years return period (390 and 410mm respectively). Source: Prepared by the researcher on the basis of rainfall data provided by the Dept. of Agriculture, Govt. of Tripura. Not only the intensity (24 hours rainfall) of rainfall is responsible for high discharge but also the duration of rainfall is responsible for it which creates flood in this district. Figure 9 shows that there is a positive relation between monsoon rainfall and monsoon discharge (r= +0.70) of the Haora River. That means, in almost every year monsoon rainfall (May to October) give 318

10 rise to high discharge which escalates the chances of flood. Thus, it can be inferred that high rainfall, both intensity and duration, is helpful for prediction of flood occurrence. Figure 9: Correlation between monsoon rainfall and monsoon discharge of the Haora River in West Tripura District. Source: Prepared by the researcher on the basis of rainfall data provided by the Dept. of Agriculture, Govt. of Tripura and restricted discharge data. 5. Conclusion From the above discussion it is clear that rainfall is the most important causative factor of flood. Though the study shows decreasing trend of rainfall (Figure 5) but still flood risk is increasing due to rapid increase in population. About 390mm and 410mm or more rainfall in 50 and 100 years return period respectively will be more hazardous for this district. Therefore, as it is not possible to reduce the rainfall, but flood risk reduction is possible through proper land use planning of the Haora and Lohar floodplains and changing the cropping pattern. Moreover, nowadays everybody has mobile phone. By downloading the AccuWeather apps the people could get weather forecast, i.e. the chances of occurrence of heavy rainfall etc. and accordingly they could prepare themselves to move to the higher places for shelter. 6. References 1. Abrahams A.D., Pearsons, A.J. and Wainwright, J., (1995), Effects of vegetation on inter rill runoff and erosion, Walnut Gulch, Southern Arizona. Geomorphology 13, pp Beven, K.J., (2001), Rainfall-runoff modelling. The primer. Wiley, Chichester. 3. Borga, M., Dalla Fontana, G. and Vezzani, C., (2005), A regional rainfall depth Duration frequency equations for an alpine region, Department of land and agro 319

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