Research article · 2023 · Full text
International Journal of Geography Geology and EnvironmentFlood damage scenario: A comparative study of the 2004, 2007 and 2017 floods of Bihar
Volume 5(1) · Pages 205–210 · DOI: 10.22271/27067483.2023.v5.i1b.168 ↗
Research areasFlood Risk Assessment and ManagementHydrology and Drought AnalysisAgricultural risk and resilience
Abstract
Author-writtenFloods as a disaster is quite synonymous in the state of Bihar and in that context, a relative assessment of the 2004, 2007 and 2017 floods could be hatched out. The disaster management authority of the state has a regular monitoring and updated climate change goals with respect to flood management. But the 2007 flood was highly intensive with 1287 human deaths with a maximum in Darbhanga district while Araria recorded second highest deaths in 2017. The most affected by crop damage was the district of Samastipur in 2007 among the three years. Data processing through GIS mapping provides inundation damage. In all the year’s flow of Gandak, Kosi and Bagmati was very high above danger mark. Though in recent years pre-emptive measures are engaged like early warning systems, riparian buffers, wetland rejuvenation and the like.
Summary
Source-checkedPlain-language reading of the full paper, prepared with AI and checked against the text. Each point links to the authors' own words.
Why it matters
- Bihar is highly susceptible to flooding due to its location on the Ganga floodplains and its tropical monsoon climate. View evidence ↗
- Approximately 73.06% of Bihar's land area (6.9 million hectares) is flood-affected, representing about 17.2% of all flood-prone areas in India. View evidence ↗
- The high density of people in flood-prone areas leads to significant annual financial and infrastructural losses in the state. View evidence ↗
The question
- The study aims to compare major floods across different years to identify challenges and suggest measures to reduce the loss of life and property. View evidence ↗
What they did
- The researchers used simulated data derived from Bihar's state disaster management statistics for the years 2004, 2007, and 2017. View evidence ↗
- GIS mapping was employed to process data and determine the extent of inundation damage. View evidence ↗
What they found
- The 2004 flood affected 20 districts in North Bihar, covering over 2.772 million hectares and impacting 21.3 million people. View evidence ↗
- The 2007 flood was particularly intensive, resulting in 1,287 human deaths (highest in Darbhanga district) and affecting 18,832 villages. View evidence ↗
- In 2017, 815 human lives were lost, with Araria recording the second highest number of deaths. View evidence ↗
- Samastipur district suffered the highest crop damage in 2007, followed by Muzaffarpur in 2004. View evidence ↗
- Unlike previous years, the 2017 floods also impacted southern districts, including Nawada. View evidence ↗
- The Gandak, Bagmati, and Kosi rivers overflowed in every season studied; additionally, the Ganges swelled in 2007, causing deaths in Patna. View evidence ↗
What it means
- The authors conclude that deaths have significantly decreased along the Kosi and Mahananda rivers, indicating the success of the Government's Roadmap 2030. View evidence ↗
- The authors recommend reviving traditional water management practices, such as ahar, pynes, and ponds, and building reservoirs to store flood water. View evidence ↗
- The authors note that implementing large anti-flood sluices would require extensive technical feasibility studies and could be hindered by the state's poverty. View evidence ↗
Visual summary
3 visualsIllustrations explain the paper; charts are replotted from the paper's own table values.
River Overflow Patterns
AI-generated conceptual illustration (The river basins of Bihar, India, featuring the Ganges, Kosi, Bagmati, and Gandak rivers flowing through a flat alluvial). It explains the idea and does not show study data.
View source evidence ↗
2017: Human lives lost vs Public Property Damaged...
Replotted from Table 2 (page 5) of the original paper. Every bar is the paper's own table value.
View source evidence ↗
Livestock lost: 2004 vs 2007 vs 2017
Replotted from Table 2 (page 5) of the original paper. Every bar is the paper's own table value.
View source evidence ↗Figures & tables
From the original paper
Table 1
Table 1
Figure 1
Table 2
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Figure 6Introduction
In the list of natural disasters, floods have made a remarkable benchmark from devastation to vulnerability throughout the Indian subcontinent. In India, twenty-three of the thirty-six states and Union Territories in the country are subjected to floods and 40 million hectares of land, roughly one-eighth of the country's geographical area, is prone to floods (NIDM, 2014) [8] . Bihar being situated on the Ganga floodplains streamlined by its various tributaries with a tropical monsoon climate is quite prone to floods. "About 6.9 out of 9.4 million hectares comprising 73.06 per cent of the state is flood affected which accounts for approximately one-sixth (17.2%) of the flood-prone area in India" (Kansal et al., 2017; Sinha, et al., 2012) [4, 11] . This implies that the number of persons hit by flood per unit area in Bihar is quite large and the state incurs a huge loss both financially and infrastructurally every year. The floods in Bihar during the South West Monsoon 2004, 2007 (July to September) and 2017 to a certain extent portray yet another familiar picture of the State's vulnerability to recurrent floods and is a grim reminder of the extensive devastations and disruption caused by floods. The focus of this study is to highlight on the practical problems, dilemmas and challenges and to suggest measures for reducing the loss of life and property due to major floods in a comparative process among the four years.
Literature review
Flood is a state of hydrological extreme of high water level in a stream channel or on bank that results in inundation of land that isn't ordinarily submerged. Generally, it occurs in event of heavy showers and becomes a disaster once it causes loss to lives, livestock and livelihood. In this scenario, the state of Bihar has a recurring series of floods every year. Ironically enough the state faces flood and drought situations equally due to rainfall variability with differences in rainfall distribution spatially as it is situated on the crossroads of wet eastern coastal region and dry continental regions of the western plains. So, the Government has classified the type of floods, in the following. Class I: Flash floods-floods occurring due to rainfall in Nepal, lead time is short (8 hours), receding of flood waters is fast. Class II: River floods-lead time 24 hours, receding of flood waters is 1 week or more. Class III: Drainage congestion in river confluence-lead time more than 24 hours, lasting full monsoon season (i.e., receding of flood water takes 3 months). Class IV: Permanent water-logged area." (BSDMA, 2023)
Study area
The state of Bihar is located in the eastern part of the country between 24°20'10" to 27°31'15" North latitude and 82°19'50" to 88°17'40" East longitude with a population of
Analysis
This damage analysis shows that the mid Northern plain of the state is the most affected area in floods almost every year as the gradient of the slope dips quite suddenly allowing huge sediment flow but a huge velocity of the stream during a substantial downpour especially during the summer monsoon when there is a sudden release of waters from the upper catchment areas of Nepal and as the sluggishness increases in the downslope the water holding capacity decreases and as many rivers have the channel rerouting tendency like Kosi they overflow through even the embankments. With the anthropogenic influence in the levees the population become more vulnerable. A huge deforestation and poor drainage are also the primary reasons to it. In 2004, Darbhanga has recorded the greatest number of deaths and after the 2 nd maximum number of deaths has been recorded in 2007 floods in Samastipur followed by Araria in 2017 floods. Crop damage is highest in Samastipur in 2007 followed by Muzaffarpur in 2004.
In 2017 southern districts such as Nawada was also inflicted. Gandak, Bagmati and Kosi rivers overflowed every flood season and in 2004 and 2017 along with these Budhi Gandak and Mahananda rivers added. In 2007 there was a swell in the Ganges also causing deaths in Patna as well. Though various mitigation measures can be taken such as revival and maintenance of traditional practices of ahar, pynes and ponds system or reservoirs for diverting and storing flood water and making use of the same for multipurpose activities including irrigation, restoration of water tables etc. Larger involvement of senior citizens from the local areas can be encouraged who have better understanding and knowledge about the system. For this, major river-based GIS mapping would be required. Besides the bed of the rivulets and tributaries would have to be properly structured and meticulously maintained. It is believed that the Ganges cause erosion on the side of its left bank only and almost all its tributaries excepting Jamune, Karmnasa, Sone, Punpun and Kiul rivers merge in Ganges from its right bank side. In the process a lot of sediments gets deposited on the right side creating narrow streams within the bed. If Large anti-flood sluices across the rivers are built then a controlled release of water in the Ganges will take place, and a considerable level of water would be maintained in the tributaries as well which requires a lot of studies and technical feasibility periods adding to the endowing poverty of the state. The state also incurs huge losses of agricultural crops, inundation of waters to fresh areas, livestock losses and even human deaths. All the 2004, 2007 and 2017 floods were quite devastating in the history of Bihar floods affecting mainly the districts of Madhubani, Darbhanga and Samastipur doubling with the effects of climate change. It is noteworthy that the number of deaths has significantly reduced on the banks of major flood prone rivers like Kosi and Mahananda showing Government's roadmap 2030 is building back better as well as involving local bodies at those districts in the lines of Sendai Framework (BSDMA, 2015) [1] of 2015. So, with the adoption of mitigation measures, technical advancements and participation in all levels can help reducing the vulnerabilities faced now.
Conclusion
Conclusion
Figures and tables from the paper
| Sl. No | Category | Area (ha) |
|---|---|---|
| 1. | Forest land | 6,76,400 |
| 2. | Land under misc tree, groves | 2,11,709 |
| 3. | Current fallow | 2, 56,783 |
| 4. | Other fallow | 6,87,570 |
| 5. | Cultivable waste | 79,319 |
| 6. | Net area under cultivation | 56,05,798 |
| 7. | Barren land & permanent pasture | 5,03,381 |
| 8. | Areas under non-agriculture use | 13,95,340 |
| Total | 94,16,300 |
Table text extracted from the original PDF; superscript letters are shown inline. The original table image is below.
View original table image
| Year | Winter rain | Summer rain | South-west monsoon | North-west monsoon | Total (Rainfall in mm) |
|---|---|---|---|---|---|
| 2000 | 0.40 | 101.70 | 994.10 | 10.00 | 1106.20 |
| 2001 | 20.90 | 83.70 | 908.20 | 192.20 | 1208.00 |
| 2002 | 48.90 | 66.80 | 896.90 | 33.20 | 1045.80 |
| 2003 | 19.20 | 93.00 | 767.60 | 128.90 | 1008.70 |
| 2004 | 23.70 | 41.40 | 906.10 | 60.10 | 1031.30 |
| 2005 | 0.10 | 89.50 | 777.60 | 30.20 | 897.40 |
| 2006 | 0.10 | 88.97 | 925.86 | 27.77 | 1042.69 |
| 2007 | 28.34 | 76.40 | 1360.85 | 40.49 | 1506.08 |
| 2008 | 30.61 | 61.78 | 1081.27 | 19.31 | 1195.97 |
| 2009 | 0.09 | 98.22 | 699.17 | 71.13 | 868.61 |
| Average | 17.23 | 80.4 | 932.06 | 61.33 | 1091.08 |
Table text extracted from the original PDF; superscript letters are shown inline. The original table image is below.
View original table image
References
6 in the original paper- Kansal M, Kumar P, Kumar A. Impacts of flood and its management: A case study of Bihar. International Journal of Advanced Research. 2017;5(3):1695-1706.
- Kumar S, Sahdeo A, Guleria S. Bihar Floods: 2007. New Delhi: National Institute of Disaster Management; c2007.
- Madhuri Tewari HR, Bhowmick PK. 'Livelihood vulnerability index analysis: An approach to study vulnerability in the context of Bihar', Jàmbá: Journal of Disaster Risk Studies. 2014;6(1):127, 13 pages.
- Mishra DK. The Bihar Flood Story. Economic and Political Weekly. 1997;32(35):2206-2217.
- OCHA. India: Situation report -Bihar floods; c2004. Retrieved from Relief web: https://reliefweb.int/report/india/india-situation-reportbihar-floods-13-jul-2004
- Tripathi G, Pandey AC, Parida BR, Kumar A. Flood Inundation Mapping and Impact Assessment Using Multi-Temporal Optical and SAR Satellite Data: A Case Study of 2017 Flood in Darbhanga District, Bihar, India. Springer Nature; c2020.