impact of climate change on precipitation characteristics of brahmaputra basin

58 Pages·2012·0.74 MB·English

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IMPACT OF CLIMATE CHANGE ON
PRECIPITATION CHARACTERISTICS OF
BRAHMAPUTRA BASIN

A Study Report

By

SHYAMAL KUMAR DEKA
Research Scholar

PROF. ARUP KUMAR SARMA
B.P.Chaliha Chair Professor for Water Resources

DEPARTMENT OF CIVIL ENGINEERING
INDIAN INSTITUTE OF TECHNOLOGY GUWAHATI
JULY 2011
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DOCUMENT CONTROL AND DATA SHEET

Report Title : Impact of Climate Change on Precipitation
Characteristics of Brahmaputra Basin

Publication Date : July, 2011

Type of Report : Technical Report

Pages and Figures : 57 Pages, 31 Figures and 8 Tables

Authors : Shyamal Kumar Deka
Post Graduate Student, IIT Guwahati
E mail: [email protected]

Arup Kumar Sarma
Professor, IIT Guwahati
Email: [email protected]

Originating Unit : Indian Institute of Technology Guwahati,
Guwahati, Assam, India

Security Classification : Restricted

Distribution Statement : Among concerned only

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ABSTRACT
The climate of North-Eastern region of India is depicted by its extreme
humidity. Its most distinguishing feature being the abundant rainfall between March
and May at a time when rain in other India is at its minimum. Along with ample
precipitation in this part of the country is the associated water induced disasters. These
problems may worsen because of impacts of global climate change. Changing climate
may have significant impacts on the quality and quantity of water that is available and
accessible. The consequent social, economic, livelihood and environmental
implications in the Himalayan region are of immediate concern.
The present study has been taken up to quantify the impact of the climate
change on the precipitation characteristics of Brahmaputra Basin. Considering the
variation of precipitation in the entire basin, two stations have been selected based on
their contrasting features and also on the availability of data. One of the sites is
Gerukamukh rainfall station in the Subansiri river basin at Arunachal Pradesh which is
located on the upper reach of the basin in India. The other site is the rainfall station at
Guwahati which is situated at the lower reach of the basin having considerable flatter
terrain.
In this study the Large-scale predictor variables obtained from the National
Centre for Environmental Prediction (NCEP) reanalysis data and observed
meteorological station data are used to develop and validate a Statistical downscaling
model for establishing a statistical relationship between the data. Using this
downscaling model the possible future scenarios of temperature and precipitation
variations are generated using large-scale predictor variables obtained from the Global
Climate Model (GCM) outputs. Downscaling has been carried out by statistical
approaches using ASD (Automated Statistical Downscaling) model. The statistical
model uses the HadCM3 daily weather data under A2 scenario to determine the
precipitation and temperature variations at a specific site.
The result shows decrease in precipitation in the early monsoon period and
marginal increase in precipitation in the late monsoon period in the future. The future
series generated by temperature model has produced up to 1.80C rise in the maximum
temperature averaged over month. In the process of model development, it was
experienced that the selection of predictors plays an important role in future series
generation through downscaling of GCM. (cid:1)
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CONTENTS

Page No
Chapter 1 Introduction 01 – 04

1.1 Impact of climate change
1.2 Impact of climate change on water resources
1.3 Brahmaputra River system
1.4 Organisation of the report

Chapter 2 Climate Modelling 05 – 07

2.1 Types of climate model
2.2 Downscaling

Chapter 3 Literature Survey 08 – 11

3.1 Global Climate Change
3.2 Climate change and water resources
3.3 Statistical Downscaling approaches
3.4 Dynamical Downscaling approaches
3.5 Conclusion

Chapter 4 Methodology 12 – 14

4.1 Study area
4.2 General Circulation model used
4.3 Downscaling technique used

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Chapter 5 Precipitation & Temperature model for station at 15 – 24
upper reach of Brahmaputra basin

5.1 Data used and Selection of predictors
5.2 Model calibration and validation(cid:1)
5.3 Future data generation

Chapter 6 Precipitation & Temperature model for station at 25 – 40
lower reach of Brahmaputra basin

6.1 Selection of predictors
6.2 Calibration and validation(cid:1)of model
6.3 Future data generation

Chapter 7 Analysing data trends 41 – 46

Chapter 8 Conclusion and Future work 47 – 48

References

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LIST OF FIGURES

Fig 5.1: Gerukamukh site in the Subansiri river basin
Fig 5.2: Calibration and validation of Temperature model using NCEP data
Fig 5.3: Validation of Temperature model using GCM data
Fig 5.4: Calibration and validation of Precipitation model using NCEP data
Fig 5.5: Validation of Precipitation model using GCM data
Fig 5.6: Comparison of present and future (generated) Temperature
Fig 5.7: Comparison of present and future (generated) Precipitation
Fig 6.1: Guwahati station along with four neighboring grid points
Fig 6.2: Calibration and validation of precipitation model for CASE 1 : 250 N – 900E
Fig 6.3: Calibration and validation of precipitation model for CASE 2 : 250 N – 93.750E
Fig 6.4: Calibration and validation of precipitation model for CASE 3: 27.50N–900E
Fig 6.5: Calibration and validation of precipitation model for CASE 4: 27.50N–93.750E
Fig 6.6: Calibration and validation of precipitation model for CASE 5 : 260N–91.350E
Fig 6.7: Comparison of observed and future Precipitation CASE1: 250N–900E
Fig 6.8: Comparison of observed & future Precipitation CASE2: 250N–93.750E
Fig 6.9: Comparison of observed & future Precipitation CASE3: 27.550N–900E
Fig 6.10: Comparison of observed & future Precipitation CASE4: 27.550N–93.750E
Fig 6.11: Comparison of observed & future Precipitation CASE5: 260N–91.350E
Fig 7.1: Trend in Annual observed rainfall
Fig 7.2: Trend in January observed rainfall
Fig 7.3: Trend in February observed rainfall
Fig 7.4: Trend in March observed rainfall
Fig 7.5: Trend in April observed rainfall
Fig 7.6: Trend in May observed rainfall
Fig 7.7: Trend in June observed rainfall
Fig 7.8: Trend in July observed rainfall
Fig 7.9: Trend in August observed rainfall
Fig 7.10: Trend in September observed rainfall
Fig 7.11: Trend in October observed rainfall
Fig 7.12: Trend in November observed rainfall
Fig 7.13: Trend in December observed rainfall
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LIST OF TABLES
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Table 5.1: Ansari Bradley test and correlation for Temperature model
Table 5.2: Ansari Bradley test and correlation for precipitation model
Table 5.3: List of Predictors finally adopted for Gerukamukh
Table 6.1: Correlation & Ansari-Bradley test at Lat-Long : 250N – 900E (CASE1)
Table 6.2: Correlation & Ansari-Bradley test at Lat-Long : 250N – 93.750E (CASE 2)
Table 6.3 : Correlation & Ansari-Bradley test at Lat-Long : 27.50 N – 900E (CASE3)
Table 6.4: Correlation & Ansari-Bradley test at Lat-Long : 27.50 N – 93.750E (CASE4)
Table 6.5: Correlation & Ansari-Bradley test at Lat-Long : 260 N–91.350E (CASE5)

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CHAPTER 1 : INTRODUCTION

Climate change has been defined by the United Nations Framework Convention
on Climate Change 2007 as, “a change of climate which is attributed directly or
indirectly to human activity that alters the composition of the global atmosphere and
which is in addition to natural climate variability observed over comparable time
periods”.
Climate change is caused by greenhouse gases which trap the outgoing
radiations and leads to increasing of the earth’s temperature. Carbon Dioxide and Water
Vapour are mainly responsible for increasing the temperature. The artificial gases
responsible for greenhouse effect are Carbon dioxide (CO ), Methane (CH ),
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Chlorofluorocarbons (CFC), Nitrous Oxide (NO ) and others. After Industrialization
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CO has been significantly increasing and is the major greenhouse gas. The artificial
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greenhouse gases that are causing global warming are produced from the burning of
fossil fuels. Paddy fields, swamps and marshes are the sources of emission of Methane.
Gases such as CFCs, HFCs and PFCs enter the atmosphere through their use in air
conditioning, refrigeration, propellants etc.
The world wide emission of greenhouse gases has been rising since
industrialization. The increase of CO since 1940 follows exponential growth. With
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such a rate of emission, amount of CO in the atmosphere is likely to be doubled in the
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near future. The developing countries like India and China is also adding to the amount
of CO as the demand for energy has increased.
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1.1 THE IMPACTS OF CLIMATE CHANGE
The Intergovernmental Panel on Climate Change has identified five key areas to
be influenced from increasing temperature. They are Water, Agriculture, Ecosystems,
Health and Coastlines. The rising temperature will lead to intensification of the
hydrological cycle. The result may be in dryer dry seasons and wetter rainy seasons.
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The Changing climate will lead to decline in the Agricultural yield as many of the
varieties of crop would not be able to survive such a climate. However, some colder
region of the world may become better for sustaining crops.
Increasing temperature will also have significant impacts on the availability of
water as well as the quality and quantity of water. The global warming causes melting
of glaciers which will increase flood risk during the rainy season, and strongly reduce
dry-season water supplies. Higher temperatures expand the range of some dangerous
vector-borne diseases, such as malaria. The rising of sea levels resulting from melting
ice will also lead to salt water contamination of groundwater supplies, thus threatening
the quality and quantity of freshwater.

1.2 IMPACT OF CLIMATE CHANGE ON WATER RESOURCES

In the future, water is the resource that will have a profound effect of climate
change. Global warming will alter the water distribution, thus there will become more
water, but not everywhere. Climate change is expected to increase the severity and
frequency of weather-related natural hazards such as storms, heavy rainfall, floods, and
droughts.
The increasing global warming will accelerate the hydrologic cycle, altering the
rainfall and eventually the runoff. The rainfall pattern will be considerably changed.
Warm air can hold more moisture and increases the evaporation of surface moisture
which tends to increase the precipitation. Monsoon rainfall can vary leading to flood as
well as drought.
Developing countries like India has already understood the impact of climate
change which will be induced as a result of maintaining economic growth and
requirement of energy to sustain such a growth.

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The future impacts of climate change, identified by the Government of India’s
National Communications (NATCOM) in 2004 include:
• Decreased snow cover, affecting snow-fed and glacial systems such as
the Ganges and Brahmaputra. 70% of the summer flow of the Ganges comes
from meltwater
• Erratic monsoon with serious effects on rain-fed agriculture, peninsular
rivers, water and power supply
• Drop in wheat production by 4-5 million tones, with even a 1ºC rise in
temperature
• Rising sea levels causing displacement along one of the most densely
populated coastlines in the world, threatened freshwater sources and mangrove
ecosystems
• Increased frequency and intensity of floods. Increased vulnerability of
people in coastal, arid and semi-arid zones of the country
• Over 50% of India’s forests are likely to experience shift in forest types,
adversely impacting associated biodiversity, regional climate dynamics as well
as livelihoods based on forest products.
1.3 BRAHMAPUTRA RIVER SYSTEM
The Brahmaputra is one of the largest rivers of the world. Its sources are near
Mansarovar in a great glacier mass in the Kailash range of Himalayas. The river flows
through a length of 1600 km in Tibet, over 160 km in Arunachal Pradesh, 720 km in
Assam and rest in Bangladesh. It has a length of 2880 km and width as high as 18 km.
The Himalayas acts as a climate divide. In winter, it serves as a barrier to the
intense cold continental air flowing southwards and in monsoon months, the moist rain
bearing winds are forced up the mountains to deposit their moisture. The South West
Monsoon, which enters Assam and adjoining area around the end of May and
beginning of June establishes firmly over the entire North East India by June end.
During the monsoon season a low pressure region develop and extends from the
seasonal low over Rajasthan to the Bay of Bengal. This monsoon axis oscillates about
its normal position to the north and south during this season. When it moves north,
towards the foothill of Himalayas, the rainfall over Assam increases.
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