3 Are Floods Getting Worse in the Ganges, Brahmaputra and Meghna Basins? 3.1 INTRODUCTION The Ganges, Brahmaputra and Meghna/Barak (GBM) river systems occupy about 175 million hectares (mha) of South Asia (Fig. 3.1) and supports more than 500 million people (Verghese and Iyer, 1993). They are unique in the world with respect to water and sediment supplies, channel processes, and instability. While the Brahmaputra ranks fourth among the largest rivers of the world with regard to mean annual discharge, the Ganges ranks thirteenth (Mirza, 1997). The estimated annual sediment yield of the Brahmaputra is 1,028 tons/km 2 , the highest among the world’s largest rivers. On the other hand, the sediment yield of the Ganges is only 502 tons/km 2 although its basin area is two times that of the Brahmaputra (Barua, 1994). The swinging and avulsion of the courses of the Ganges and Brahmaputra Rivers in recent history have significant influence on the morphology of their alluvial floodplains (Rahman, 1993; Brammer, 1996). They are characterized by high flows during the monsoon and low flows during the dry season. For example, the ratio of monsoon flow to dry season flow of the Ganges River at Hardinge Bridge in Bangladesh is 6:1 (Mirza and Dixit, 1997). The high flows often cause floods in many parts of these vast river basins. Sitting at the confluence of the three major rivers, Bangladesh (area 148,000 sq. km) is considered to be the most flood-affected country in the world followed by India. Every year, slightly over one-fifth of its land area becomes flooded and in extreme cases, more than two-thirds of the country is affected. In upstream India (area 3,280,000 sq. km), floods annually inundate an area larger than half of Bangladesh. Available information shows that in recent years, flood damage in Nepal, India and Bangladesh is increasing. Substantial increases in flood damage in Nepal during the 1980s were reported by the Asia Development Bank (ADB, 1991). For India, the Center for Science and Environment (CSE, 1992) reported that the annual flood damage had increased 40 times from the 1950s to the 1980s (Fig. 3.2). According to Mirza (1991a), compared to the 1960s and 1970s, flood damage in Bangladesh was the greatest in the 1980s (Fig. 3.3). These increases have largely been attributed to worsening flood events (increased river discharge and spatial extent) in the GBM basins in India and Bangladesh M. MONIRUL QADER MIRZA R. A. WARRICK N. J. ERICKSEN G. J. KENNY Reprinted with permission from Environmental Hazards 3 (2001), pp.37-48. Copyright © 2005 Taylor & Francis Group plc, London, UK (CSE, 1992; BBJTO, 1989; RBA, 1980; and Ives, 1991). These claims, do not, however, appear to be based on systematic analyses of relevant data. Therefore, this paper examines whether floods in the GBM basins are getting worse by applying statistical tests to: 1) the peak discharge data of the three rivers recorded at various stations in India, Nepal and Bangladesh; and 2) the flooded area data. The latter were used to determine changes in spatial severity of flooding in India and Bangladesh. Peak discharge recording stations and period of records are shown in Table 3.1. It is possible that the reported increases in flood problems are due to increased human activities in flood-prone areas. But that element of flood hazard is not the subject of this paper. Fig. 3.1 The Ganges, Brahmaputra and Meghna basins. Location of some discharge measurement stations have also been shown. Fig. 3.2 Flood damage in India during 1953-1999 (Source: CWC, 1989; ADRC, 2000a). 0 10000 20000 30000 40000 50000 1950 1960 1970 1980 1990 2000 Damage (in million rupees) Year 56 ARE FLOODS GETTING WORSE? Copyright © 2005 Taylor & Francis Group plc, London, UK Fig. 3.3 Flood damage in Bangladesh during 1954-1998 (Source: Mirza, 1991a; ADRC, 2000a). 3.2 HYDRO-METEOROLOGY OF THE GBM BASINS Of the three river basins, the Ganges is the largest. Its 109.5 mha basin area is distributed over China, Nepal, India and Bangladesh. The Ganges River rises South of the main Himalayan divide near Gangotri at a height of 4,500 m in the Uttar Pradesh (UP), India. In Nepal, India and Bangladesh, mean annual precipitation in the basin is 1,860 mm, 908 mm and 1,568 mm, respectively. Mean annual runoff of the Ganges River at Farakka, India and Hardinge Bridge, Bangladesh, is estimated to be 415 x 10 3 million cubic meters (mcm) and 352 x 10 3 mcm, respectively (Mirza, 1997). The highest annual peak discharge (80,230 m 3 sec -1 ) was recorded at Hardinge Bridge in 1998 (See Fig. 3.1 for the location of some of the stations referred to in this paper.) The Brahmaputra basin area is 58 mha. It is regarded as one of the world’s largest braided river systems in terms of discharge, sediment transport, and channel processes (JMBA, 1989). The river originates at an elevation of 5,150 m in a large glacier mass in the Kailash range of the Himalayas, very close to Manassarovar Lake. Mean annual precipitation in the basin area in India and Bangladesh is 2,500 mm and 2,400 mm, respectively. Mean annual runoff of the Brahmaputra at Pandu, India and Bahadurabad, Bangladesh is estimated to be 511 x 10 3 mcm and 643 x 10 3 mcm, respectively. The highest peak discharge was 98,600 m 3 sec -1 recorded at Bahadurabad in 1988. The Meghna/Barak basin is the smallest of the three basins, with an area of 8 mha. The headstream of the river in India is known as Barak and originates on the Southern slope of the mountain range to the North of Manipur, India. In Bangladesh, the river is known as Meghna and flows Southwest to meet the Padma (combined flow of the Ganges and Brahmaputra Rivers) at Chandpur. Mean annual precipitation of the basin in India and Bangladesh is 2,640 mm and 3,574 mm, respectively. Mean annual runoff of the Barak in India is 41 x 10 3 mcm (measured at Badarpurghat) (Kothyari and Garde, 1991). At Bhairab Bazaar in Bangladesh, the mean annual runoff is estimated to be 151 x 10 3 mcm. The highest peak discharge at Bhairab Bazaar was 19,900 m 3 sec -1 recorded in 1993. M. M. Q. MIRZA ET AL. 57 Copyright © 2005 Taylor & Francis Group plc, London, UK Table 3.1 Statistical properties of the peak discharge and flooded area data * non-random. River Station Period of Record Latitude (deg. N) Longitude (deg. E) Mean (m 3 sec -1 ) Coefficient of Variation (CV) Lag-1 Autocorrelation Coefficient Hardwar 1885-1971 29.58 78.10 6,639.00 0.47 - 0.42* The Ganges Farakka 1949-1980 25.00 87.91 56,516.00 0.17 + 0.05 Hardinge Bridge 1934-2000 23.06 89.03 51,184.00 0.18 + 0.22 The Kosi Barahkshetra 1948-1978 - - 10,190.00 0.44 - 0.18 The Brahmaputra Pandu 1955-1974 26.20 91.50 50,524.00 0.20 + 0.20 Bahadurabad 1956-1999 25.15 89.66 67,389.00 0.18 +0.03 The Meghna Bhairab Bazaar 1964-1998 24.03 59.98 14,072.00 0.19 - 0.23 The Surma-Meghna Kanairghat 1969-1993 - - 2,224.00 0.16 + 0.35 Flooded Area (mha) India Bangladesh 1953-1997 1954-1999 7.28 3.03 0.47 0.68 +0.17 +0.16 58 ARE FLOODS GETTING WORSE? Copyright © 2005 Taylor & Francis Group plc, London, UK 3.3 THE FLOOD PROBLEM Flooding of catastrophic proportions often occurs in the GBM river basins. Extreme precipitation in the monsoon, together with the physical settings of the river basins has caused many severe floods in the last few decades. Causes and characteristics of floods vary between the highlands in Nepal, the middle ground in India, and the flat deltaic terrain in Bangladesh. In Nepal, the flood problem is mainly restricted to the Terai region along the border it shares with India. Rivers in the Terai region are very unpredictable and cause heavy flood damage as a result of intensive downpours on the Southern slopes of the Siwalik Himalaya (SAARC, 1992). The high Himalayan Mountains of Nepal are affected by Glacier Lake Outburst Floods (GLOF). These floods do not cause much damage to human settlements because the upper mountainous areas are sparsely populated. In contrast, floods in the Terai occur regularly and cause considerable damage to densely populated floodplains. In India, floods in the Ganges region are caused by the following factors either singly or in combination: excessive precipitation, inadequate river channel capacity, obstruction in streams, inadequate waterways at confluences, human encroachments and lack of adequate drainage, failure of flood control embankments and deforestation (Rangachari, 1993; Chowdhury, 1989; Dhar and Nandargi, 1998). Similar factors cause floods in the Brahmaputra region, but they are compounded by local physiographic features. The region is interspersed with a large number of streams, flooding from which inundates the intervening narrow valleys. The riverbeds in some cases are higher than the surround- ing valley land. Therefore, any breach or spilling causes deep flooding in the valleys. The Brahmaputra region in India is highly prone to earthquakes and this often causes landslides. These seriously disturb the drainage system. The Barak region lies between the Khasi and Jaintia Hills in the North and Mizo Hills in the South. The river often overflows its banks inundating low areas on either side. There is a series of bowl-shaped depressions, locally known as “Haors”, which fill with floodwater. The gradient of the river is extremely flat and the outfall at the border with Bangladesh is congested. In recent years, the role of deforestation in the upstream areas in causing flooding in the downstream areas of the GBM basins has triggered interesting debates (BWDB, 1987; Carson, 1985; Thompson and Warburton, 1985; Hamilton, 1987; Hofer, 1998; Ives and Messerli, 1989; Messerli and Hofer, 1995; Rogers et al., 1989). BWDB (1987) indicated that deforestation in the upstream contributed significantly to the increased rates of sediment supply and accretion. However, the existing publications do not report any significant recent increase in the sediment load of the larger rivers and their tributaries, or in the magnitude of annual flooding and levels of river discharge (Ives and Messerli, 1989). Thompson and Warburton (1985) questioned the linkage between massive floods in the plains and land-use activities upstream in the Himalayas. However, they noted that there was some technical uncertainty encountered when analyzing the human components of erosion, flooding and shifting hydrological patterns. Hofer (1998) concluded that land-use changes in the Himalayas were not responsible for the floods far downstream in India and Bangladesh. In the aftermath of the devastating floods in Bangladesh in 1988, Rogers et al. (1989) remarked that there were no grounds for considering deforestation in the Himalayas as a significant cause of the flooding in the delta of the river system. Carson (1985:36) mentioned, “…Flooding and sedimentation problems in India and Bangladesh are a result of the geomorphic character of the rivers and man’s attempts to contain the rivers. Deforestation likely plays a minor, if any, role in the major monsoon flood events on the lower Ganges.” The role of deforestation in the sedimentation and flooding processes M. M. Q. MIRZA ET AL. 59 Copyright © 2005 Taylor & Francis Group plc, London, UK in South Asia is a highly contentious issue and it needs adequate scientific research and attention. Of the three countries affected by flooding in the GBM river basins, Bangladesh is the most vulnerable because of its geographic location, high monsoon cross-border flow, and the physiographic characteristics of its deltaic floodplains. Half of the country is under 12.5 m above the mean sea level (CBJET, 1991). Because of its flatness, floodwaters cannot drain quickly. The three rivers together may generate as much as 200,000 m 3 sec -1 of peak discharge. The problem becomes more complicated when the peak flow of each of the three rivers synchronises. In such a case, the flooded area may exceed 60% of the country (as occurred in 1988 and 1998), about three times the normally flooded area (Fig. 3.4). Although the river levels fall rapidly from September through November, water levels on adjoining floodplains fall more slowly because of low gradients, congested drainage, and substantial depression areas. The latter may stay submerged until December to January and some throughout the whole dry season (November to May). Floods cause considerable damage in the GBM basins and four main economic sectors - agriculture, housing, industry and transportation infrastructure are particularly vulnerable. Flood related damage puts considerable strain on the economies of the countries that share the GBM basins. This is particularly true in terms of diversion of resources for recovery activities and the loss in growth of Gross Domestic Products (GDP). For example, during the 1998/1999 fiscal year in Bangladesh, GDP growth declined to 4.6% from 5.2% of the previous year due to the devastating floods of 1998. Industry sector growth, however, decreased by 3.4% during the same period as a result of flood-induced disruptions in the manufacturing subsector (ADB, 2000). 0 20 40 60 80 100 120 1954 1961 1965 1969 1973 1977 1981 1985 1989 1993 1999 Ye ar Flooded Area (000 sq.km) Fig. 3.4 Flooded area in Bangladesh during 1954-1999 (Source: BWDB, 2000b). In Nepal, government statistics show an increasing trend in damage to public and private property from floods and landslides in recent years. The estimated damage to property increased from US$ 1.0 million in 1983 to US$ 100.0 million in 1989 (ADB, 1991). In India, out of the 34 mha of “flood-prone” area, some 23 mha are in the GBM basins. Fifteen Indian states and the union territory of Delhi lie in the basin. However, four states alone account for over two-thirds of the flood-prone area: Uttar Pradesh, Bihar, West Bengal and Assam (Rangachari, 1993). Data compiled by India’s Central Water Commission (CWC) show that during 1953-1987, the average area affected by floods was 60 ARE FLOODS GETTING WORSE? Copyright © 2005 Taylor & Francis Group plc, London, UK 7.66 mha (22.5% of the flood-prone area), of which 3.51 mha were cropped (CWC, 1989). Recent data published by the Ministry of Water Resources, Government of India shows that during 1953-1997 annual average flood affected area has declined to 7.42 mha (MWR, 2000) from that of the 1953-1987 average (Fig. 3.5). This is due to a decline in flooded area in the period 1987-1997. Available evidence indicates increasing flood damage in recent years in India. State governments estimated that flood damage in 1987 and 1988 was US$ 1.5 billion and US$ 2.5 billion, respectively (Rangachari, 1993). In 1953 it was 524 million rupees and remained around that level until the middle of the 1960’s when damage tracked upward (Fig. 3.2) (CWC, 1989). Fig. 3.5 Flooded area in India during 1953-1997 (Source: MWR, 2000). In Bangladesh, the area prone to floods in the GBM basin is 6.14 mha. This is 42% of the country’s geographical area. On an annual average, 20.5% of Bangladesh (3.03 mha) becomes inundated. The loss caused by floods in Bangladesh in a normal year is about US$ 175 million; but in extreme cases, the damage may exceed two billion dollars. The 1998 flood damage was the worst in history, totaling in the range of US$ 2 billion to 2.8 billion (ADRC, 2000a; MOFA, 1998). The industry and infrastructure sectors were worst hit, followed by agriculture (MDMR, 1998). The flood damage in Bangladesh for the period 1954-1998 is shown in Figure 3.3. Flood damage estimation methods in Nepal, India and Bangladesh only take into account the direct damage. Death, trauma, accidents, post-flood health and nutrition problems are not considered direct damage as their monetary valuations are unaccounted for. Almost every year, a significant number of people die due to floods. During 1953-1987, the annual average loss of human lives in India due to floods was 1,439 (CSE, 1992). In West Bengal, India 1,262 people had died and another 117 were reported missing during the devastating monsoon floods of 2000 (UNICEF, 2000). In Nepal, during the period of 1981-1999, a total of 5,453 people lost their lives with the highest, 2,307 people, in 1993 (ADRC, 2000a). In the catastrophic floods of 1998 in Bangladesh, the number of reported deaths was 1,050 (ADRC, 2000a). The number of deaths caused by floods in India, Bangladesh and Nepal is summarized in Table 3.2. Flood damage is an indicator of flood hazard, which in turn, is a function of potential flood events in relation to human use of flood-prone land. This includes activities aimed at alleviating the flood problem, such as embanking river channels and elevating floor levels of buildings. Thus, flood hazard effects (registered as property damage, social disruption, and human injury) rise or fall with changes in the parameters of the flood event 0 25 50 75 100 125 150 175 200 1953 1957 1961 1965 1969 1973 1977 1981 1985 1989 1993 1997 Ye ar Flooded Area (000 sq.km) M. M. Q. MIRZA ET AL. 61 Copyright © 2005 Taylor & Francis Group plc, London, UK (e.g., discharge and areal extent) or human use of flood-prone land (e.g., type and density), or both. In the wake of increasing flood damages in the GBM basins, special emphasis has been given to flood problems in both India and Bangladesh. The Government of India created the Rashtriya Barh Ayog (National Commission on Floods) in 1976. Devastating floods in India in 1987 led to the setting up of two committees to look into the problem (Rangachari, 1993; Mirza, 1991a). Bangladesh formulated a Water Master Plan in 1964 that recommended 59 flood control projects as a result of the consecutive floods of 1954 and 1955 (Mirza, 1991b). However, from the mid-seventies to the late-eighties, flood control received little attention in Bangladesh. In response to the devastating flood of 1988, Bangladesh carried out 28 studies under the “Flood Action Plan (FAP)” during the period 1989-1995. All of these efforts were based on the claim by government (as well as non-government agencies) that floods in the GBM basin areas were getting worse (CSE, 1992; BBJTO, 1989; RBA, 1980; Ives, 1991). As floods are generally accompanied by over bank spilling, assessment of peak discharges in the major rivers is the best way to determine whether changes in flood events have occurred or not. In order to detect changes, Cumulative Deviation, Worsley Likelihood Ratio, Kruskal-Wallis and Mann-Whitney U tests (Annex 3.1) were applied to the peak discharge series of the three rivers. Similar tests were also applied to the flooded areas in India and Bangladesh to see if there were associated changes in the spatial (areal) extent of flooding. Table 3.2 Number of deaths due to floods in India, Bangladesh and Nepal during the period 1953-2000 Year India Bangladesh Nepal 1953 37 1954 279 112 60 1955 865 129 1956 462 1957 352 1958 389 1959 619 1960 510 1961 1,374 1962 348 117 1963 432 30 1964 690 1965 79 1966 180 39 1967 355 1968 3,497 221 276 1969 1,408 1970 1,076 87 350 1971 994 120 1972 544 50 1973 1,349 427 1974 387 1,987 1975 686 62 ARE FLOODS GETTING WORSE? Copyright © 2005 Taylor & Francis Group plc, London, UK Table 3.2 Continued Source: India: 1953-1987 (CWC, 1989) and 1988-1999 (ADRC, 2000a). Death toll for 2000 was taken from (ADRC, 2000b; UNICEF, 2000). Bangladesh: ADRC, 2000a except for 1954, 1955, 1962, 1968, 1970 and 1974 (Islam, 2000). Nepal: until 1999 (ADRC, 2000a.). Figure for 2000 was taken from ADPC, 2000. 3.4 THE DATA Annual peak discharge data for the Ganges, Brahmaputra and Meghna Rivers were collected from UNESCO (1976), IAHS-AISH (1984), Bangladesh Water Development Board (BWDB) (1995, 2000a), French Engineering Consortium (FEC) (1989a), Raghunath (1985) and Nepal Water Conservation Foundation (NWCF, 1996). Flooded area data were collected from the Central Water Commission (CWC, 1985), Ministry of Water Resources (MWR, 2000) and BWDB (1993, 2000b). The periods of records of the collected peak discharge data for various rivers and stations varied, as shown in Table 3.1, but fall within the period 1885 to 2000. For India, flood damage data were collected from the Central Water Commission (CWC, 1989) and Asian Disaster Reduction Center (ADRC, 2000a). Flood damage data for Bangladesh were taken from Mirza (1991a) and Asian Disaster Reduction Center (ADRC, 2000a). Two observations were missing in the peak discharge data series for the Ganges River. One observation was missing for each of the Farakka (1969) and the Hardinge Bridge (1971) sites. These were filled by determining the correlation coefficient and then applying Year India Bangladesh Nepal 1976 1,373 103 1977 11,316 13 1978 3,396 17 130 1979 3,637 1980 1,913 655 1981 1,376 750 1982 1,573 92 1983 238 245 186 1984 1,661 1,200 200 1985 1,804 300 46 1986 1,200 150 22 1987 1,835 3,680 358 1988 2,050 2,379 27 1989 1,097 180 1990 203 231 25 1991 1,024 450 51 1992 572 15 1993 1,862 366 2,307 1994 2,845 43 1995 1,479 900 140 1996 1,506 55 768 1997 2,526 179 1998 2,131 1,050 311 1999 500 48 170 2000 2,159 100 144 M. M. Q. MIRZA ET AL. 63 Copyright © 2005 Taylor & Francis Group plc, London, UK the method of Salinger (1980). 1 Similarly, one observation was also found missing for each of the Pandu (1964) and the Bahadurabad (1971) sites for the Brahmaputra River. These were also filled by the method applied for the missing data of the Ganges River. For the Meghna River at Bhairab Bazaar, four observations (1977-1980) were missing. These missing observations were filled by applying the precipitation-peak discharge regression model (Mirza, 1997). 2 Errors involved with the discharge measurement, processing and storage of data are not generally reported and documented. Standard equipment, methods and specifications are being used in discharge and water level measurements in Nepal, India and Bangladesh. However, in Bangladesh, due to changing bed forms, velocity measurements from non-anchored boats and inaccurate measurement of depths for current meter may cause ≤10% and ≤15%-20% uncertainty in discharge and water level measurements, respectively (Sir William Halcrow and Partners, 1991; FAP 24, 1993). The magnitudes of errors in the measurement of discharge and water levels in India and Nepal are not known. But, due to similar characteristics of river channels, they are assumed to be the same as those of Bangladesh. Statistical properties of the peak discharge data are shown in Table 3.1. Annual peak discharge of the Ganges River at Hardwar is found to be highly variable, followed by the Kosi River at Barahkshetra. The almost equal coefficients of variation of the Brahmaputra, Meghna and Surma-Meghna Rivers indicate that they drain the catchment areas with similar characteristics. Lag-1 autocorrelation coefficient was determined using the equation shown below. This coefficient is used to determine the presence of “persistence” in the data. A negative value of r 1 is indicative of marked high frequency (i.e. short-period) oscillations. On the other hand, positive values indicate Markov linear type persistence (Mirza et al., 1998). The presence of this type of persistence in a peak discharge series means that a large (or small) peak discharge for one year is more likely to be followed by a large (or small) for the next year: where X i is annual peak discharge at year i, n is the sample size, and is mean peak discharge. The randomness of the series can be tested to identify presence of trend or cycle using the one-tail 95% confidence limit of the Gaussian distribution (Mitchell et al., 1966). The 1 The missing observation for one year was calculated using the ratio of the mean peak discharge of the two stations with a missing record to the adjacent data-possessing station multiplied by the peak discharge of that year. 2 The regression model for estimating annual peak discharge is Q p = -10531 + 3.41*P1 + 5.69* P2 (R 2 = 87%). Where P1 is average precipitation in the North Assam meteorological sub-division and P2 is the average precipitation in the South Assam meteorological sub-division and Bangladesh part of the basin. test value () r t 1 is computed from: 64 ARE FLOODS GETTING WORSE? Copyright © 2005 Taylor & Francis Group plc, London, UK [...]... (-) No Change Change (+) No Change Change (-) No Change Change (+) No Change No Change No Change Change (+) No Change Kruskal-Wallis Mann-Whitney Change (-) Change (+) Change (+) No Change Change (-) No Change Change (+) No Change Change (+) No Change No Change No Change Change (-) No Change No Change No Change Change (-) No Change Change (+) No Change Change (+) No Change No Change Change (-) ARE... Lowlands and Delta? Assumptions and Facts Mountain Research and Development 7 (3) (1987), pp.25 6-2 63 Hofer, T.: Do Land-Use Changes in the Himalayas Affect Downstream Flooding? Traditional Understanding and New Evidences In: Kale, V S (Editor), Flood Studies in India, Geological Society of India, Bangalore, 1998, pp.11 9-1 41 IAHS-AISH: World Catalogue of Maximum Observed Floods IASH-AISH Publ No 1 43, ... of Bangladesh - The Embankment Issue Water Nepal 2(2 /3) (1991b), pp.2 5-2 8 Mirza, M M Q.: Modeling the Effects of Climate Change on Flooding in Bangladesh, Unpublished D.Phil Thesis International Global Change Institute (IGCI), University of Waikato, Hamilton, New Zealand, 1997 Mirza, M M Q and Dixit, A.: Climate Change and Water Resources in the GBM Basins Water Nepal 5(1) (1997), pp.7 1-1 00 Mirza, M... Meghna - The Kosi The Bhahmaputra The Surma-Meghna The Meghna b Flooded Area India Bangladesh Cumulative U Deviation Change (-) No Change Change (+) No Change Change (-) No Change Change (+) No Change Change (+) No Change No Change Change (-) Note: The shaded rows denote locations within the border of Bangladesh Copyright © 2005 Taylor & Francis Group plc, London, UK Worsley Likelihood Ratio Change (-) ... change was detected in the Brahmaputra basin Only the Worsley Likelihood Ratio test identified an increase in the Meghna basin in India In Bangladesh, Cumulative Deviation and the Mann-Whitney U tests indicated decreases in the flooded areas in Bangladesh Overall, the results do not indicate any conclusive change in the peak discharge or flooded area time series within Bangladesh (Table 3. 3) However, at... Frequency and Risk Analysis in Hydrology Water Resources Publications, Fort Collins, USA, 1988 Kothyari, U C and Garde, R J.: Annual Runoff Estimation for Catchments in India Journal of Water Resources Planning and Management 117(1) (1991), pp. 1-1 0 Master Plan Organization (MPO): National Water Plan Ministry of Irrigation, Water Development and Flood Control, Dhaka, 1986 Messerli, B and Hofer, T.: Assessing... People living in, or associated with these at threat floodplains draw their livelihood from them Such activities include agriculture, industries, public infrastructure, and commercial outlets For example, during the 1950s and 1960s, India’s cultivated area increased from about 119 mha in 195 0-1 951 to 141 mha in 197 0-1 971 Since then, it has remained relatively stationary, although in some areas it intensified... (peak discharge and flooded area) must be responsible for the increase in flood damage (Figs 4.2 and 4 .3) recorded for countries within the GBM basins Two main factors have been identified as possible contributors to the record of increasing flood damage: (i) improvement in flood damage assessment techniques; and (ii) increases in human settlement in flood-prone areas 3. 7.1 IMPROVEMENT IN FLOOD DAMAGE... lived in the GBM basins in Nepal (4%), India (75%) and Bangladesh (20%) Most of them dwelt on floodplains susceptible to annual floods In India, the number of people affected by the average annual floods rose from 16 million to 53 million in the 30 -year period leading up to the late 1980s (CSE, 1992) In Bangladesh it has increased from 13 million to 38 million for the same period This translates into... Ganges, Brahmaputra and Meghna Rivers? Firm evidence of a long-term regional trend in area-averaged precipitation is yet to be found Mooley and Parthasarathy (19 83) examined above- and below-average annual precipitation extremes between 1871 and 1980 for 36 0 precipitation stations all over India, except for the Northern mountainous districts They included the Gangetic Plain, Bengal and Assam in their analysis . No Change No Change No Change No Change Pandu Change (-) Change (-) Change (-) Change (-) The Bhahmaputra Bahadurabad No Change No Change No Change No Change The Surma-Meghna Kanairghat Change. Change No Change No Change Change (+) Change (+) No Change No Change Change (+) No Change No Change Bangladesh - Change (-) No Change No Change Change (-) 66 ARE FLOODS GETTING. Discharge Hardwar Change (-) Change (-) Change (-) Change (-) The Ganges Farakka No Change No Change Change (+) No Change Hardinge Bridge Change (+) Change (+) Change (+) No Change The Kosi