Floodplain Planning Based on Statistical Analysis of Tilpara Barrage Discharge: a Case Study on Mayurakshi River Basin 1
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CAMINHOS DE GEOGRAFIA - revista on line http://www.seer.ufu.br/index.php/caminhosdegeografia/ Instituto de Geografia ufu ISSN 1678-6343 Programa de Pós-graduação em Geografia FLOODPLAIN PLANNING BASED ON STATISTICAL ANALYSIS OF TILPARA BARRAGE DISCHARGE: A CASE STUDY ON MAYURAKSHI RIVER BASIN 1 Vibhash Chandra Jha Department of Geography, Visva-Bharati University [email protected] Haraprasad Bairagya Department of Geography, Visva-Bharati University [email protected] ABSTRACT Floods in the West Bengal are responsible for colossal loss of human life, crops, and property. In recent years, various measures of flood control and management have been adopted. However, flooding in such rivers like Brahmani profoundly challenges flood-hazard management, because of the inadequacy of conventional data and high spatio-temporal variability of floods. To understand flood hazards and environmental change it is imperative that engineers and hydrologists utilize historical and paleoflood records to improve risk analyses as well as to estimate probable maximum flood on rivers such as these in a highly flood-prone region(Parkar,2000). The flood frequency analysis, probable peak discharge analysis, its return period analysis and floodplain zoning based on ancillary data will help better management of flood in the Mayurakshi River basin situated in the districts of Birbhum and Murshidabad. Keywords: Flood Frequency, Gamble’s Method, Return Period, Floodplain zoning. INTRODUCTION Flood is such a natural phenomenon that is uncontrollable and, to some extent, unpredictable .It seems to be strange and mysterious too. Man has been toiling for ages to control flood, but all in vain. Man must acquaint himself with the characteristics of floods if he is to control them. Floods vary as the weather differs from month to month and year to year. The first step in becoming better acquainted with flood is to measure them. When this has been done and record is available for a long period of time, analytical studies will provide a better understanding of the phenomenon (CHOW, 1964). The rivers of the south-eastern part of the Indian Peninsula are monsoonal in nature. These rivers are subjected to severe floods during the monsoon season. In the last few decades, several large- magnitude floods (peak floods between 10,000 and 80,000 m 3/s) have been recorded. In general, floods caused by precipitation from Bay of Bengal depressions include the peak flood of record. Analyses of the systematic, historical, and paleoflood records indicate that, in recent decades, the frequency of high-magnitude floods has increased significantly. Hydraulic estimates reveal that high flows are capable of bedrock erosion and transportation of coarse material (KRON, 2005). Owing to its barrage discharge from Tilpara the river Mayurakshi plays an important role to create flood devastation in the districts of Birbhum and Murshidabad. It helps to create stagnation of water and more flood duration at Hijol (a large marshy land) area also. Amongst the different measures of flood, flood frequency analysis is indispensable for floodplain planning, management and to protect the human civilization from flood disaster for ever. 1 Recebido em 12/06/2012 Aprovado para publicação em 20/09/2012 Caminhos de Geografia Uberlândia v. 13, n. 43 out/2012 p. 326 –334 Página 326 Floodplain planning based on statistical analysis of Tilpara Vibrash Chandra Jha Barrage discharge: a case study on Mayurakshi river basin Haraprasad Bairagya LOCATION The Mayurakshi River is a tributary of the Bhagirathi River. The Mayurakshi originates from Dumka District in Jharkhand and then flows through Birbhum district, bisecting Suri subdivision (ROY, 1985). It then flows through Murshidabad district, where it joins the Dwarka River. The Tilpara Barrage is located in 3kms away from Suri town. It is a hill stream with beds full of pebbles and yellow clay. Figure 1 : Study area. Table 1: At a glance Tilpara Barrage. TILPARA BARRAGE Location Near Suri, District Birbhum on the river Mayurakshi Total Catchment Area including the catchment of 5067sq. km. Massanjore Dam Width Between Abutments 308.84 m Number of Weir Bays 7 (Width 18.29 m Each) + Under Sluices 8 (Width 18.29 m Each) Linear Water Way 274.39 m Optimum Pond Level 64.33 m Design Upstream Water Level 64.33 m Design Discharge 8,495 cumecs Canal Discharge 99.11 cumecs Length of Main Canal a) Left 16.62 km b) Right 22.53 km Irrigable Area a) Kharif 2,26,629 Ha b) Rabi 20,250 Ha Birbhum, Murshidabad & Burdwan Maximum Irrigation Achieved a) Kharif 2,20,730 Ha b) Rabi 8,150 Ha c) Boro 25,400 Ha Source: wbiwd.gov.in/irrigation_sector/major/ stats /mayurakshi _stats .htm Caminhos de Geografia Uberlândia v. 13, n. 43 out/2012 p. 326 –33 4 Página 327 Floodplain planning based on statistical analysis of Tilpara Vibrash Chandra Jha Barrage discharge: a case study on Mayurakshi river basin Haraprasad Bairagya Plate 1: Tilpara Barrage. FLOOD FREQUENCY ANALYSIS OF MAYURAKSHI RIVER BY GUMBLE’S METHOD Chow et al . (1951) has shown that most frequency – distribution functions applicable in hydrologic studies can be expressed by the following equation known as the general equation of hydrologic flood frequency analysis : XT =X¯ +K. Sd Where, XT = value of the variate X of a random hydraulogic series with a return period T, X¯ = mean of the variate, Sd= standard deviation of the variate, k= frequency factor which depends upon the return period, T and the assumed frequency distribution. The commonly used frequency distribution function for the prediction of extreme flood values is the Gumble’s method. This extreme flood value distribution was introduced by Gumble (1941) and is commonly known as Gumble’s distribution .It is the most widely used probability distribution function for extreme values in hydrologic studies and meteorological studies for the prediction of flood peaks, maximum rainfall, maximum wind speed etc. Gumble defined a flood as the largest of the 365 daily flows and the peak annual series of flood flows (SUBRAMANYA, 1999 ). The general formula for the prediction of extreme flood values and its probability of occurrence, is given by Gumble as below: Qp = Q¯ +K. Sd n-1 Where Qp =Probable Peak Discharge, Sd n-1 =Standerd Deviation of the sample size N = √∑ (Q¯ -Q) ²/ √N-1 Q¯ = Average Flood discharge, K =Frequency factor expressed as K =Yt-Y¯ n/Sn In which Yt = reduced variate, a function of T and is given by Yt = - [In.In T/T-1] Or, Yt= -(0.834+2.303LogLogT/T-1) Yn = reduced mean, a function of sample size N. Sn= reduced standard deviation, a function of sample size N Caminhos de Geografia Uberlândia v. 13, n. 43 out/2012 p. 326 –33 4 Página 328 Floodplain planning based on statistical analysis of Tilpara Vibrash Chandra Jha Barrage discharge: a case study on Mayurakshi river basin Haraprasad Bairagya The value of Yn and Sn is given in Gumble’s extreme value distribution table (table 2 and 3): Table 2: Reduced mean Yn in gumble’s extreme value distribution (Sample Size N). N 0 1 2 3 4 5 6 7 8 9 10 .4952 .4996 .5053 .5070 .5100 .5128 .5157 .5181 .5202 .5520 20 .5236 .5252 .5268 .5283 .5296 .5309 .5320 .5332 .5343 .5353 30 .5362 .5371 .5380 .5388 .539 6 .5402 .5410 .5418 .5424 .5430 40 .5436 .5442 .5448 .5453 .5458 .5463 .5468 .5473 .5477 .5481 50 .5485 .5489 .5493 .5497 .5501 .5504 .5508 .5511 .5515 .5518 Table 3: Reduced standard deviation Sn in Gumble’s extreme value distribution. N 0 1 2 3 4 5 6 7 8 9 10 .9496 .9676 .9833 .9971 1.0095 1.0206 1.0316 1.0411 1.0493 1.0565 20 1.0628 1.0696 1.0754 1.0811 1.0864 1.0915 1.0961 1.1004 1.1047 1.1086 30 1.1124 1.1159 1.1193 1.1226 1.1255 1.1285 1.1313 1.1339 1.1363 1.1388 40 1.1413 1.1436 1.1458 1.1480 1.1499 1.1519 1.1538 1.1557 1.1574 1.1590 50 1.1607 1.1623 1.1638 1.1658 1.1667 1.1681 1.1696 1.1708 1.1721 1.1734 Source: S.K.Garg (2007), pp.461-168 FLOOD FREQUENCY AND PEAK DISCHARGE ANALYSIS OF RIVER MAYURAKSHI BY GUMBLE’S FORMULA AT TILPARA Massanjore dam highly influences the discharge of Tilpara Barrage. The water is reduced form the dam and it is stored in the barrage according to its need. So mainly Tilpara barrage controls the flood condition of the entire basin. Here peak annual flood flow collected from Tilpara gauge station is taken into consideration as in the table 4. Table 4: Flood frequency analysis by Gumble’s formula in river Mayurakshi at Tilpara Barrage. YEAR Annual Peak Order(m) Q¯-Q (Q¯-Q)² Frequency Max Probable Discharge in (T=N+1/m) Flood(in%)P= cumec(Q) 100/T 1959 6678.8 1 -5657.3 32001649 25 4 1956 5405.3 2 -4383.8 19217702.44 12.5 8 1971 2122.5 3 -1101 1212201 8.3 12 1968 1273.5 4 -252 63504 6.25 16 1957 1174.5 5 -153 23409 5 20 1955 1047.1 6 -25.6 655.36 4.16 21.6 1963 962.2 7 59.3 3516.49 3.57 28.01 1977 912.9 8 108.6 11793.96 3.125 32 1974 872.57 9 148.93 22180.14 2.78 35.97 1975 848.23 10 173.27 30022.49 2.5 40 1958 622.6 11 398.9 159121.21 2.274 43.98 1961 549 12 472.5 223256.25 2.08 48.07 1973 422.18 13 599.32 359184.46 1.92 50.76 1970 325.45 14 696.05 484485.6 1.79 55.87 1969 254.7 15 766.8 587982.24 1.67 59.8 1967 232.06 16 789.44 623215.51 1.56 64.1 1965 226.4 17 795.1 632184.01 1.47 68.03 1972 141.5 18 880.00 774400 1.39 71.94 Caminhos de Geografia Uberlândia v.