Response of River Flow Regime to Various Climate Change Scenarios in Ganges-Brahmaputra- Meghna Basin

Rajib Kamal; M. A. Matin; Sharmina Nasreen

doi:doi:10.11648/j.wros.20130202.12

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Response of River Flow Regime to Various Climate Change Scenarios in Ganges-Brahmaputra- Meghna Basin

Rajib Kamal, M. A. Matin, Sharmina Nasreen

Published in Journal of Water Resources and Ocean Science (Volume 2, Issue 2)

Received: 19 May 2013 Published: 10 June 2013

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Abstract

The potential climatic variability over Ganges-Brahmaputra-Meghna (GBM) basin like alterations in precipitation and temperature are expected to have a significant impact on the natural flow regime of its rivers. The Lower Meghna River, being a major drainage outlet of the basin, is likely to be affected by such variability and hence its response to climate can be studied through the use of plausible scenarios of climate change. In this study, an artificial neural network (ANN) model, based on future climate projections of HadCM3 GCM, was constructed to examine the potential changes in the river flow regime assuming that climate tend to change as per the SRES scenarios A1B, A2 and B1. The results showed a trend of increasing monsoon flows for these scenarios during the periods of 2020s, 2050s and 2080s with a projected shift in the seasonal distribution of flows. Examining the monthly projected flows for different scenarios and comparing with the observed condition, it was found that the peak flow may increase 4.5 – 39.1% in monsoon and the dry period low flows may drop by 4.1 – 26.9% indicating high seasonality as a result of climate change. Due to seasonal variation of precipitation and temperature, i.e., excess precipitation in monsoon and lack of precipitation along with higher temperature in the dry season, the flood peaks are likely to shift towards earlier months and the rate of change of flows during the rising and recession of flooding would be much higher compared to current state of the river. These results also indicate the exacerbation of flooding potential in the central part of Bangladesh due to the largest increase of peak flows during monsoon.

Published in	Journal of Water Resources and Ocean Science (Volume 2, Issue 2)
DOI	10.11648/j.wros.20130202.12
Page(s)	15-24
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2013. Published by Science Publishing Group

Keywords

Climate Change, GBM Basin, Lower Meghna River, Flow Regime

References

[1]	B. Malmqvist and S. Rundle, "Threats to the Running Water Ecosystem of the World", Environmental Conservation, vol. 29, pp. 134–153, 2002.
[2]	IPCC, "Climate Change 2007: The Physical Science Basis", Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change[Solomon, S., D. Qin, M. Manning, Z. Chen, M. Marquis, K.B. Averyt, M. Tignor and H.L. Miller (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 2007.
[3]	C. A. Gibson, J. L. Meyer, N. L. Poff, L. E. Hay and A. Georgakakos, "Flow Regime Alterations Under Changing Climate in Two River Basins: Implications for Freshwater Ecosystems", River Research and Applications, vol. 21, pp. 849–864, 2005.
[4]	F. H. Verhoog, "Impact of Climate Change on the Morphology of River Basins", Proceedings of the Vancouver Symposium, IAHS, Publ. no. 168, 1987.
[5]	CCC, "Impact Assessment of Climate Change and Sea Level Rise on Monsoon Flooding", Report Prepared by Climate Change Cell, DoE, MoEF; Component 4b, CDMP, MoFDM, Dhaka, 2009.
[6]	M. R. Chowdhury and N. Ward, "Hydro-Meteorological Variability in the Greater Ganges–Brahmaputra–Meghna Basins", International Journal of Climatology, vol. 24, pp. 1495–1508, 2004.
[7]	Ministry of Water Resources (MoWR), "Hydro-Morphological Dynamics of the Meghna Estuary", Report Prepared by DHV Consultants, Bangladesh Water Development Board, Bangladesh, 2001.
[8]	A. K. Gain, W. W. Immerzeel, F. C. Sperna-Weiland and M. F. P. Bierkens, "Impact of Climate Change on the Stream Flow of Lower Brahmaputra: Trends in High and Low Flows Based on Discharge Weighted Ensemble Modeling", Hydrology and Earth System Sciences Discussion, vol. 8, pp. 365–390, 2011.
[9]	M. Q. Mirza, R. A. Warrick, N. J. Ericksen, and G. J. Kenny, "Trends And Persistence in Precipitation in The Ganges, Brahmaputra and Meghna River Basins" Hydrological Sciences, vol. 43, no 6, pp. 845-858, 1998.
[10]	N. Nakicenovic et al., "Emissions Scenarios", Special Report of Working Group III of the Intergovernmental Panel on Climate Change, Cambridge University Press, Cambridge, UK and New York, NY, USA, 2000.
[11]	T. Mitchell and P. Jones, "An Improved Method of Constructing a Database of Monthly Climate Observations and Associated High-Resolution Grids", International Journal of Climatology, vol. 25, pp. 693-712, 2005.
[12]	United States Geological Survey (USGS), "HYDRO1k Elevation Derivative Database – Asia", Distributed by the Land Processes Distributed Active Archive Center (LP DAAC) located at the USGS EROS Data Centre, from http://LPDAAC.usgs.gov, 2001.
[13]	O. Kii, "River Flow Modeling Using Artificial Neural Networks", Journal of Hydrologic Engineering, vol. 9, no. 1, pp. 60–63, 2004.
[14]	J. S. Wu, J. Han, S. Annambhotla and S. Bryant, "Artificial Neural Networks for Forecasting Watershed Runoff and Stream Flows." Journal of Hydrologic Engineering, vol. 10, no. 3, pp. 216–222, 2005.
[15]	X. Chen,J. Wu and Q. Hu, "Simulation of Climate Change Impacts on Streamflow in the Bosten Lake Basin Using an Artificial Neural Network Model", Journal of Hydrologic Engineering, vol. 13, no. 3, pp 180-183, 2008.
[16]	ASCE Task Committee, "Artificial Neural Networks in Hydrology I." Journal of Hydrologic Engineering, vol. 5, no. 2, pp. 115–123, 2000.
[17]	ASCE Task Committee, "Artificial Neural Networks in Hydrology II." Journal of Hydrologic Engineering, vol. 5, no. 2, pp. 124–137, 2000.
[18]	M. A. Matin and R. Kamal, "Impact of Climate Change on River System", Proceedings of the International Symposium on Environmental Degradation and Sustainable Development (ISEDSD-2010), Dhaka, Bangladesh, pp.61-65, 2010.

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APA Style

Rajib Kamal, M. A. Matin, Sharmina Nasreen. (2013). Response of River Flow Regime to Various Climate Change Scenarios in Ganges-Brahmaputra- Meghna Basin. Journal of Water Resources and Ocean Science, 2(2), 15-24. https://doi.org/10.11648/j.wros.20130202.12

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ACS Style

Rajib Kamal; M. A. Matin; Sharmina Nasreen. Response of River Flow Regime to Various Climate Change Scenarios in Ganges-Brahmaputra- Meghna Basin. J. Water Resour. Ocean Sci. 2013, 2(2), 15-24. doi: 10.11648/j.wros.20130202.12

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AMA Style

Rajib Kamal, M. A. Matin, Sharmina Nasreen. Response of River Flow Regime to Various Climate Change Scenarios in Ganges-Brahmaputra- Meghna Basin. J Water Resour Ocean Sci. 2013;2(2):15-24. doi: 10.11648/j.wros.20130202.12

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@article{10.11648/j.wros.20130202.12,
  author = {Rajib Kamal and M. A. Matin and Sharmina Nasreen},
  title = {Response of River Flow Regime to Various Climate Change Scenarios in Ganges-Brahmaputra- Meghna Basin},
  journal = {Journal of Water Resources and Ocean Science},
  volume = {2},
  number = {2},
  pages = {15-24},
  doi = {10.11648/j.wros.20130202.12},
  url = {https://doi.org/10.11648/j.wros.20130202.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.wros.20130202.12},
  abstract = {The potential climatic variability over Ganges-Brahmaputra-Meghna (GBM) basin like alterations in precipitation and temperature are expected to have a significant impact on the natural flow regime of its rivers. The Lower Meghna River, being a major drainage outlet of the basin, is likely to be affected by such variability and hence its response to climate can be studied through the use of plausible scenarios of climate change. In this study, an artificial neural network (ANN) model, based on future climate projections of HadCM3 GCM, was constructed to examine the potential changes in the river flow regime assuming that climate tend to change as per the SRES scenarios A1B, A2 and B1. The results showed a trend of increasing monsoon flows for these scenarios during the periods of 2020s, 2050s and 2080s with a projected shift in the seasonal distribution of flows. Examining the monthly projected flows for different scenarios and comparing with the observed condition, it was found that the peak flow may increase 4.5 – 39.1% in monsoon and the dry period low flows may drop by 4.1 – 26.9% indicating high seasonality as a result of climate change. Due to seasonal variation of precipitation and temperature, i.e., excess precipitation in monsoon and lack of precipitation along with higher temperature in the dry season, the flood peaks are likely to shift towards earlier months and the rate of change of flows during the rising and recession of flooding would be much higher compared to current state of the river. These results also indicate the exacerbation of flooding potential in the central part of Bangladesh due to the largest increase of peak flows during monsoon.},
 year = {2013}
}

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TY  - JOUR
T1  - Response of River Flow Regime to Various Climate Change Scenarios in Ganges-Brahmaputra- Meghna Basin
AU  - Rajib Kamal
AU  - M. A. Matin
AU  - Sharmina Nasreen
Y1  - 2013/06/10
PY  - 2013
N1  - https://doi.org/10.11648/j.wros.20130202.12
DO  - 10.11648/j.wros.20130202.12
T2  - Journal of Water Resources and Ocean Science
JF  - Journal of Water Resources and Ocean Science
JO  - Journal of Water Resources and Ocean Science
SP  - 15
EP  - 24
PB  - Science Publishing Group
SN  - 2328-7993
UR  - https://doi.org/10.11648/j.wros.20130202.12
AB  - The potential climatic variability over Ganges-Brahmaputra-Meghna (GBM) basin like alterations in precipitation and temperature are expected to have a significant impact on the natural flow regime of its rivers. The Lower Meghna River, being a major drainage outlet of the basin, is likely to be affected by such variability and hence its response to climate can be studied through the use of plausible scenarios of climate change. In this study, an artificial neural network (ANN) model, based on future climate projections of HadCM3 GCM, was constructed to examine the potential changes in the river flow regime assuming that climate tend to change as per the SRES scenarios A1B, A2 and B1. The results showed a trend of increasing monsoon flows for these scenarios during the periods of 2020s, 2050s and 2080s with a projected shift in the seasonal distribution of flows. Examining the monthly projected flows for different scenarios and comparing with the observed condition, it was found that the peak flow may increase 4.5 – 39.1% in monsoon and the dry period low flows may drop by 4.1 – 26.9% indicating high seasonality as a result of climate change. Due to seasonal variation of precipitation and temperature, i.e., excess precipitation in monsoon and lack of precipitation along with higher temperature in the dry season, the flood peaks are likely to shift towards earlier months and the rate of change of flows during the rising and recession of flooding would be much higher compared to current state of the river. These results also indicate the exacerbation of flooding potential in the central part of Bangladesh due to the largest increase of peak flows during monsoon.
VL  - 2
IS  - 2
ER  -

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Author Information

Rajib Kamal

Department of Water Resources Engineering, Bangladesh University of Engineering and Technology, Dhaka, Bangladesh
M. A. Matin

Department of Water Resources Engineering, Bangladesh University of Engineering and Technology, Dhaka, Bangladesh
Sharmina Nasreen

Bangladesh Water Development Board, Dhaka, Bangladesh

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APA Style

Rajib Kamal, M. A. Matin, Sharmina Nasreen. (2013). Response of River Flow Regime to Various Climate Change Scenarios in Ganges-Brahmaputra- Meghna Basin. Journal of Water Resources and Ocean Science, 2(2), 15-24. https://doi.org/10.11648/j.wros.20130202.12

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ACS Style

Rajib Kamal; M. A. Matin; Sharmina Nasreen. Response of River Flow Regime to Various Climate Change Scenarios in Ganges-Brahmaputra- Meghna Basin. J. Water Resour. Ocean Sci. 2013, 2(2), 15-24. doi: 10.11648/j.wros.20130202.12

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AMA Style

Rajib Kamal, M. A. Matin, Sharmina Nasreen. Response of River Flow Regime to Various Climate Change Scenarios in Ganges-Brahmaputra- Meghna Basin. J Water Resour Ocean Sci. 2013;2(2):15-24. doi: 10.11648/j.wros.20130202.12

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@article{10.11648/j.wros.20130202.12,
  author = {Rajib Kamal and M. A. Matin and Sharmina Nasreen},
  title = {Response of River Flow Regime to Various Climate Change Scenarios in Ganges-Brahmaputra- Meghna Basin},
  journal = {Journal of Water Resources and Ocean Science},
  volume = {2},
  number = {2},
  pages = {15-24},
  doi = {10.11648/j.wros.20130202.12},
  url = {https://doi.org/10.11648/j.wros.20130202.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.wros.20130202.12},
  abstract = {The potential climatic variability over Ganges-Brahmaputra-Meghna (GBM) basin like alterations in precipitation and temperature are expected to have a significant impact on the natural flow regime of its rivers. The Lower Meghna River, being a major drainage outlet of the basin, is likely to be affected by such variability and hence its response to climate can be studied through the use of plausible scenarios of climate change. In this study, an artificial neural network (ANN) model, based on future climate projections of HadCM3 GCM, was constructed to examine the potential changes in the river flow regime assuming that climate tend to change as per the SRES scenarios A1B, A2 and B1. The results showed a trend of increasing monsoon flows for these scenarios during the periods of 2020s, 2050s and 2080s with a projected shift in the seasonal distribution of flows. Examining the monthly projected flows for different scenarios and comparing with the observed condition, it was found that the peak flow may increase 4.5 – 39.1% in monsoon and the dry period low flows may drop by 4.1 – 26.9% indicating high seasonality as a result of climate change. Due to seasonal variation of precipitation and temperature, i.e., excess precipitation in monsoon and lack of precipitation along with higher temperature in the dry season, the flood peaks are likely to shift towards earlier months and the rate of change of flows during the rising and recession of flooding would be much higher compared to current state of the river. These results also indicate the exacerbation of flooding potential in the central part of Bangladesh due to the largest increase of peak flows during monsoon.},
 year = {2013}
}

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TY  - JOUR
T1  - Response of River Flow Regime to Various Climate Change Scenarios in Ganges-Brahmaputra- Meghna Basin
AU  - Rajib Kamal
AU  - M. A. Matin
AU  - Sharmina Nasreen
Y1  - 2013/06/10
PY  - 2013
N1  - https://doi.org/10.11648/j.wros.20130202.12
DO  - 10.11648/j.wros.20130202.12
T2  - Journal of Water Resources and Ocean Science
JF  - Journal of Water Resources and Ocean Science
JO  - Journal of Water Resources and Ocean Science
SP  - 15
EP  - 24
PB  - Science Publishing Group
SN  - 2328-7993
UR  - https://doi.org/10.11648/j.wros.20130202.12
AB  - The potential climatic variability over Ganges-Brahmaputra-Meghna (GBM) basin like alterations in precipitation and temperature are expected to have a significant impact on the natural flow regime of its rivers. The Lower Meghna River, being a major drainage outlet of the basin, is likely to be affected by such variability and hence its response to climate can be studied through the use of plausible scenarios of climate change. In this study, an artificial neural network (ANN) model, based on future climate projections of HadCM3 GCM, was constructed to examine the potential changes in the river flow regime assuming that climate tend to change as per the SRES scenarios A1B, A2 and B1. The results showed a trend of increasing monsoon flows for these scenarios during the periods of 2020s, 2050s and 2080s with a projected shift in the seasonal distribution of flows. Examining the monthly projected flows for different scenarios and comparing with the observed condition, it was found that the peak flow may increase 4.5 – 39.1% in monsoon and the dry period low flows may drop by 4.1 – 26.9% indicating high seasonality as a result of climate change. Due to seasonal variation of precipitation and temperature, i.e., excess precipitation in monsoon and lack of precipitation along with higher temperature in the dry season, the flood peaks are likely to shift towards earlier months and the rate of change of flows during the rising and recession of flooding would be much higher compared to current state of the river. These results also indicate the exacerbation of flooding potential in the central part of Bangladesh due to the largest increase of peak flows during monsoon.
VL  - 2
IS  - 2
ER  -

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