Download Dr. P P Mujumdar

Sustainable Water Management
in India: Implications of Climate
Change
Pradeep Mujumdar
Indian Institute of Science
Bangalore, India
Outline
Introduction
◦ Water Resources of India
◦ Sustainability Issues
Climate Change Impacts
◦ Scale Issues and Uncertainties
◦ Impacts on streamflow, agriculture demands and urban floods
Impacts of Landuse Change
Concluding Remarks
03 December 2016
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India - Water Requirements for Different Uses
Population (Millions)
India - Population
1800
1600
1400
1200
1000
800
600
400
200
0
2%
1581
9%
2%
1333
3%
1157
Irrigation
Domestic
Industries
Power
Navigation
Environment/Ecology
Evaporation
6%
846.3
5%
361
73%
Source : Ministry of Water Resources,
1951
1991
2010
2025
2050
75-80% of Annual Rainfall During
Monsoon Season
Year
All India Average Water Availability
700
3500
1150
3008
Availability(m3 /person/year)
All India Ave. Water
3000
2500
Evaporation
Infiltration
2000
Surface-Runoff
1500
1283
938
1000
814
687
2150
500
Distribution of Precipitation (source : Central
Ground Water Board, 1965)
0
1951
03 December 2016
1991
2010
2025
2050
YearIWSA NATIONAL CONFERENCE
Source : Ministry of Water Resources,
3
India
Source for the map:
www.mapsofIndia.com
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Surface Water Resource
S.N.
River Basin
Water Resource( Cu Km)
As per CWC 1993
1
Indus
2
Ganga - Brahmaputra - Meghna
2a
As per NCIWRDP
1999
73.31
73.31
Ganga
525.02
525.02
2b
Brahmaputra
537.24
629.05
2c
Meghna
48.36
48.36
3
Subarnarekha
12.37
12.37
4
Brahmani – Baitarani
28.48
28.48
5
Mahanadi
66.88
66.88
6
Godavari
110.54
110.54
7
Krishna
78.12
69.81
8
Pennar
6.32
6.32
9
Cauvery
21.36
21.36
10
Tapi
14.88
14.88
11
Narmada
45.64
45.64
12
Mahi
11.02
11.02
Source : 1.Reassessment of Water Resources Potential of India – CWC, Publication 6/93
2.Major River basins of India – An overview – CWC, 50/89
3.Report of Irrigation Commission (1972) – (Vol.III; Part I & II), Ministry of Irrigation & Power.
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Contd.
S.N.
River Basin
Water Resource (Cu Km)
As per CWC 1993
As per NCIWRDP
1999
13
Sabarmati
3.81
3.81
14
West Flowing Rivers of Kachchh, Saurashtra and
15.1
15.1
15
West Flowing Rivers of South of Tapi
200.94
200.94
16
East Flowing Rivers Between Mahanadi and Godavari
17.08
17.08
17
East Flowing Rivers Between Godavari and Krishna.
1.81
1.81
18
East Flowing Rivers Between Krishna and Pennar.
3.63
3.63
19
East Flowing Rivers Between Pennar and Cauvery.
9.98
9.98
20
East Flowing Rivers south of Cauvery
6.48
6.48
21
Area of North Ladakh not draining into Indus
0
0
22
Rivers draining into Bangladesh
8.57
8.57
23
Rivers draining into Myanmar.
22.43
22.43
24
Drainage areas of Andaman, Nicobar and Lakshadweep
0
0
Total
1869.37
1952.87
Say
1870
1953
Source : 1.Reassessment of Water Resources Potential of India – CWC, Publication 6/93
2.Major River basins of India – An overview – CWC, 50/89
3.Report of Irrigation Commission (1972) – (Vol.III; Part I & II), Ministry of Irrigation & Power.
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Ground Water Resource
1.
2.
3.
Total replenishable ground water resource
Provision for domestic, industrial and other
uses
Available ground water resource for
irrigation
432 Km3
71 Km3
361 Km3
4.
Utlisable ground water resource for
irrigation
(90 % of the Sl. No.3)
325 Km3
5.
Total utilizable ground water resource
(Total of Sl. No. 2 & 4)
396 Km3
Source: Ground Water Resources of India, CGWB, 1995.
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Human Induced Hydrologic
Change
Changing patterns of precipitation, streamflow,
evapotranspiration, and hydrologic extremes of floods
and droughts due to anthropogenic climate change
Change in streamflow, evapotranspiration,
groundwater recharge and other hydrologic
components due to rapidly changing landuse.
Significantly altered flow regimes because of
construction of dams and other hydrualic structures
Shrinking aquifer storages
due to excessive pumping
of groundwater
Change in hydrologic regimes due to large scale
irrigation and interbasin transfer of water
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National Water Problem
- India
◦ Extremely low efficiency
of water use, particularly
in agriculture sector
◦ Frequent floods and
droughts – lack of
capacity to forecast and
develop responses.
◦ Contaminated rivers and
groundwater
Source for map : www.mapsofindia.com03 December 2016
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National Water Problem
- India
Indiscriminate use of groundwater;
subsidised/free electricity to farmers
 Decreasing per capita availability of
water; Inaccessibility of safe drinking
water and sanitation to a large number
of people;
Rapid urbanisation with little scope
for increasing infrastructure; limited
water availability for urban sustenance
in most cities.
Lack of adequate quality and quantity
of data and trained manpower to arrive
at informed decisions at
regional/riverbasin/local levels.
Climate change likely to aggravate
the situation.
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Inflow
Rainfall
Evaporation
Reservoir
Irrigation

Power
Discharger 1
Regulated
Non Point Source
d/s flow
Pollution
Discharger 2
Recharge
GW Pumping
Groundwater
Reservoir
Discharger ..
Municipal
Water
Supply
Discharger n
A Typical Water Resource System
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Increasing Temperatures
◦ Evapotranspiration
◦ Water Quality
Change in Precipitation Patterns
◦ Streamflow; Water availability
◦ Intensity, Frequency and Magnitude
of Floods and Droughts
◦ Groundwater Recharge
Rise in Sea Levels
◦ Inundation of coastal areas
◦ Salinity Intrusion
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Fig. Source: ww.engr.uconn.edulanboG229Lect111SWIntru.pdf
Climate Change – Hydrologic Implications
Hydrologic Processes
in a Catchment
Source: http://hydrogeology.glg.msu.edu/research/active/modeling-and-monitoring-hydrologicprocesses-in-large-watersheds
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Source: University Corporation for Atmospheric Research (UCAR)
Distributed hydrologic models
Simulate Streamflow,
Evapotranspiration, Soil
Moisture, Deep percolation,
Detention Storage and other
surface water processes
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Ground Water Model
Two dimensional, unsteady flow in an isotropic, homogeneous,
unconfined aquifer

h

h
h
(T ) 
(T )  S y
 QP  QR
x x y y
t
h
Ground water level (m)
T
Sy
Transmissivity m2/day
Specific yield
QP
pumping rate per unit area m3/day/m2
QR
Recharge rate per unit area m3/day/m2
x and y Cartesian coordinates in plan
t
time in days
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Flow
specified
h
T
0
n
No flow across boundary
(e.g., dykes)
h
T
q 0
n
Head specified across
boundary
Boundary Conditions
n is the outward normal direction
q is the outflow rate per unit length, in m3/day/m
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Dissolved Oxygen Depletion
(From: Environmental Science: A Global Concern, 3rd ed. by W.P
Cunningham and B.W. Saigo, WC Brown Publishers, © 1995)
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Climate Change: Water Sustainability Issues
•Water availability
•How do water fluxes vary on catchment scale
in response to global climate events?
•Water Demands
•Evapotranspiration - Irrigation Demands
•Municipal and Industrial Demands
•Ecological and Environmental Demands
•Impacts on Water Quality
•Change in frequency and magnitude of
extreme events (floods and droughts)
•Delays in onset of monsoon:
•Impact on Agriculture
•Salinity Intrusions & Coastal flooding
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Source for the map:
www.mapsofIndia.com
19
Global Climate Models (GCMs)
Source for figures :
Google images;
Source for text :
Wikipedia
03 December 2016
Climate models are systems of differential equations based on the
basic laws of physics, fluid motion, and chemistry. To “run” a model,
scientists divide the planet into a 3-dimensional grid, apply the basic
equations, and evaluate the results. Atmospheric models calculate
winds, heat transfer, radiation, relative humidity, and surface
hydrology within each grid and evaluate interactions with
neighboring points.
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Climate Change Scenarios
IPCC (2001)
Scenarios are alternative images of how the future might unfold and are an
appropriate tool with which to analyze how driving forces may influence future
emission outcomes.
The scenarios
are updated
once in about
4-5 years in
the
Assessment
Reports of
IPCC . The
AR5 scenarios
are expressed
in the form of
Representative
Concentration
Pathways
(RPCs).
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Need for Downscaling
Source: Xu Chong-Yu, Water Resources Management 13: 369–382, 1999.
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Challenge:
Quantification and
Reduction of
Uncertainties
Impact Assessment
Climate Change Projections
(precipitation, temperature,
radiation, humidity)
Topography, Landuse/Land Cover ; Soil
characteristics; Other
catchment data
Downscaling
Projections
Hydrologic Model
Possible Future Water
Resource Scenarios at River
Basin Scales (Water Availability,
Adaptive Responses
Water Demand, Soil Moisture,
03 December 2016
Infiltration,
Groundwater Recharge etc)
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Sustainable Water Management

Sustainable water resource systems
are those designed and managed to
fully contribute to the objectives of
society, now and in the future, while
maintaining their ecological,
environmental, and hydrological
integrity (ASCE, 1998; UNESCO, 1999)
•Sustainability is intimately related to various measures of risk
and uncertainty about a future we cannot know, but which we
can surely influence
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Sustainability Measures
Reliability of Meeting Future Demands
◦ How often does the system ‘Fail’ to deliver?
Resiliency
◦ How quickly can the system recover from failure?
For most water resource systems, time at which failure occurs, is also
a vital indicator
Productivity Index
◦ How good will be the crop yield?; How much power? How
much drought-proofing? --over a long future
Vulnerability of the system
◦ Effects on environmental integrity (e.g., long term effects
on salinity d/s of a reservoir in a coastal region; water
quality; impacts on eco-systems); Losses due to failure
(e.g., crop failures, damages due to drought);
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Climate change effects in the Colorado river basin
Source: Christensen et al. (2004), Climatic Change 62, 337–363
Naturalized: effects of water
management removed
Colorado River basin with 1/8degree VIC routing network
and major system of reservoirs
Drainage Area : 6,30,000 sq. km; Serves 7 states; 12 major reservoirs – water supply, hydropower
and flood control ; 70% runoff from Snow pack; Average Annual Runoff : 18.6BCM
Variable infiltration capacity (VIC) model
• Driven by gridded precipitation, temperature and wind time series at 1/8-degree spatial resolution
and daily temporal resolution
• Simulates snow accumulation and melt, soil moisture dynamics and evapotranspiration, as well as
surface runoff and baseflow
• Processes routed through a grid-based flow network to simulate streamflow at selected points
within the03basin
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Climate change effects in the Colorado river basin
Downscaled temperature and precipitation from Parallel Climate Model
(PCM) – 105 year simulations
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Source: Christensen et al. (2004), Climatic Change 62,
337–363
HIST : Historical (observed) : 1950-1999
CTRL : Control Climate Simulation (1995 greenhouse gas levels)
BAU: Business as usual scenario for periods 1–3: 2010–2039, 2040–
2069 and 2070–2098
27
Climate change effects in the Colorado river basin
Source: Christensen et al. (2004), Climatic Change 62, 337–363
Mean monthly
hydrograph for
simulated historic,
control, and BAU period
1–3 simulations
Periods 1–3: 2010–2039, 2040–2069 and 2070–
2098
Current demands in the basin are not much lower than the mean flow. A mere 10%
reduction in mean annual flow has major implications for the reservoir system
performance; Reliability of a reservoir system decreases rapidly as the demands
approach the mean flow;
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Indian River Basins
•NATCOM Project – Response to UNFCCC*
•Source : Gosain et al (2006)
•HadRM 3 results at 0.44 0 scale ; IS92a scenario
◦ Climate variables used :
◦ Precipitation, temperature, solar radiation, wind speed, and relative humidity.
◦ River basins divided into sub-basins, each of size around 500010000 sq.km
◦ SWAT model used to simulate runoff and evaporation.
* United Nations Framework Convention on Climate Change
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Basin
Scenario
Mahanadi Control
GHG
Brahmani Control
GHG
Ganga
Control
GHG
Godavari Control
GHG
Cauvery Control
GHG
Narmada Control
GHG
Tapi
Control
GHG
Krishna
Control
GHG
Pennar
Control
GHG
Mahi
Control
GHG
Luni
Control
GHG
Sabarmati Control
GHG
03 December 2016
Rainfall
mm
1269.5
1505.3
1384.8
1633.7
678.2
736.4
1292.8
1368.6
1309.0
1344.0
937.5
949.8
928.6
884.2
1013.0
954.4
723.2
676.2
655.1
539.3
317.3
195.3
499.4
303.0
Change
w.r.t.
control
18.6
18.0
8.6
5.9
2.7
2.4
-4.8
-5.8
-6.5
-17.7
-38.4
-39.3
Total
Runoff
mm
612.3
784.0
711.5
886.1
113.0
115.1
622.8
691.5
661.2
650.4
353.4
359.4
311.2
324.9
393.6
346.9
148.6
110.2
133.9
100.0
15.5
6.6
57.0
16.6
As
proportion Actual ET
of rainfall mm
(%)
48.2
613.5
52.1
674.1
51.4
628.8
54.2
698.8
16.7
542.1
15.6
583.5
48.2
624.1
50.5
628.3
50.5
601.6
48.4
646.8
36.3
586.8
37.8
556.6
33.5
587.9
36.7
529.3
38.9
585.0
36.4
575.6
20.6
556.7
16.3
551.7
20.4
501.0
18.5
422.7
4.9
316.5
3.4
207.3
11.4
433.1
5.5
286.0
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Control : 1981-2000; GHG : 2041-2060
As
proportion
of rainfall
(%)
48.3
44.8
45.4
42.8
79.9
79.2
48.3
45.9
46.0
48.1
60.3
58.6
63.3
59.9
57.7
60.3
77.0
81.6
76.5
78.4
99.7
106.1
86.7
94.4
Gosain et al (2006)
30
Downscaling & uncertainties of the GCM outputs to the river
basin scales
Challenge:
Quantification and
Reduction of
Uncertainties
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Mahanadi River Basin - Streamflow
Hirakud Dam
Predictand:
Predictors
2m Surface Temperature
Geopotential Height at 500 hPa
Specific Humidity
Mean Sea Level Pressure
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Monsoon Streamflow
of Mahanadi River at
Hirakud Dam
32
Projections for future monsoon inflows to
Hirakud Reservoir
Reduction in
‘normal’ (middle
level) flows
Range of projected future flow duration curves at Hirakud
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Projected Peak and Average Discharge;
CGCM2; A2; Source : Asokan and Dutta
(2009)
Projected Irrigation Water Demand :
CGCM2; A2 ; Source : Asokan and Dutta
(2009)
Flood Storage
Dam
Live Storage
Hydropower
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Irrigation
34
Rule curve at Hirakud for adaptive policies
194
192
Reservoir level (m)
Curr rule curve min
190
Curr rule curve max
188
SDP 2045-65
186
Adaptive policy 1
Adaptive policy 2
184
Adaptive policy 3
182
SDP 1959-2005
180
178
1-Jul
1-Aug
1-Sep
2-Oct
Date
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Advances in Water Resources (2010)
Rule curve for adaptive policies
Impacts on Irrigation Water
Demands
India - Water Requirements for Different Uses
2%
9%
2%
3%
Irrigation
Domestic
Industries
Power
Navigation
Environment/Ecology
Evaporation
6%
5%
73%
Source : Ministry of Water Resources,
Source for figure : http://eoedu.belspo.be/en/applications/evapcontexte.asp?section=4.1
Factors affecting Crop Evapotranspiration
•Air Temperature
•Net Radiation
•Wind Speed
•Vapour Pressure
•Relative Humidity
•Soil Moisture
•Type of Crop
•Season of Crop Growth
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Study Area
100 N to 200 N and 70 0 E to 80 0 E
Observed data
NCEP/NCAR reanalysis monthly data
from 1948 -2009 (62 years) 2.50 x 2.5 0
IMD daily gridded rainfall data of
resolution 0.50 X 0.50 from1971 to
2005.
GCM Outputs: Global Climate Variables
Statistical Downscaling: Principal
Component Analysis, Canonical
Correlation Analysis
Projections of Local / Regional Variables
(Rainfall, Relative Humidity, Wind Speed,
Maximum and Minimum Temperatures)
Evapotranspiration Model
(Relative Humidity, Wind Speed,
Maximum and Minimum Temperatures)
GCM data
Projections of Potential
Evapotranspiration
Projections of
Rainfall
Irrigation Demand
Bhadra Command
Area
03 December 2016
Large-scale
Predictors
Predictands
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MIROC3.2 medium resolution of 1.125
x 1.125 deg, from Climate System
Research (CCSR, Japan) with SRES A1B
scenario from 2001 to 2100
Precipitation flux, precipitable water,
surface air temperature at 2m, mean
sea level pressure, geopotential height
at 500 mb, surface U-wind, surface Vwind, specific humidity at 2m, surface
relative humidity, surface latent heat
flux, sensible heat flux, surface short
wave radiation flux, surface long wave
radiation flux
Rainfall, maximum and minimum
temperatures, wind speed, relative
humidity
38
Bhadra Command
Area
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Hydrological Processes (2012)
Monthly Reference Evapotranspiration for Bhadra Command
Area Estimated from MIROC 3.2 GCM Output with A1B
Scenario
Projected Annual
Water Requirements Sugarcane
Paddy
25
Irrigation Water
Requirement (M.cu.m)
Irrigation Water
Requirement (M.cu.m)
30
25
20
15
10
5
0
1
2
3
4
5
6
7
8
20
15
10
5
0
9
1
2
3
4
Location
Permanent Garden
7
8
9
8
9
20
10
Irrigation Water
Requirement (M.cu.m)
Irrigation Water
Requirement (M.cu.m)
6
Semidry Crops
12
8
6
4
2
0
5
Location
1
2
3
4
5
6
7
8
9
15
10
5
0
Location
Present
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2020-2044
1
2045-2069
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3
4
5
6
7
Location
2070-2095
40
Climate Change Impacts on Urban Floods
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2016
41
Effects of Urbanization – Hydrographs
Source: Boase, 2007
03 December 2016
URBAN DEVELOPMENT Alters the
hydrology of a region; rainfall –
runoff relationships get affected;
quicker and higher peak flows
occur
42
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Urban Heat Islands Increase
Rainfall Rates around cities
by 48-116 % (NASA)
Winds Interact with Urban-induced Convection
to Produce Downwind Rainfall
Causes of Heat Island:
•Materials of construction:
Concrete, asphalt etc
•Lack of vegetation (lack of
evapotranspiration to effect
cooling)
•Waste energy (e.g., from
air conditioners, cooling
systems etc)
•Air pollution
•Tall buildings block
surface heat from radiating
into the relatively cool
night sky
Source : http://www.gsfc.nasa.gov/topstory/20020613urbanrain.html
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Bangalore City – Change in the IDF
Relationships
Comparison of IDF for return period of 10 years
100
Rainfall Intensity (mm/h)
90
80
90.174
1969-2003
1969-1986
76.789
1987-2003
70
60
62.672
59.653
53.898
50
43.471
40
33.651
30
26.968
20
19.124
15.25
9.5709
17.45
10
0
1
2
6
12
24
Duration (hours)
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How do the short
duration, high
intensities of rainfall
respond to the
climate change?
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Urban Flooding
Likely changes in IDF
(Intensity-DurationFrequency)
relationships due to
climate change
03 December
2016
45
Toronto
Source : Simonovic,
2005
Precipitation Intensity (mm/hour)
95
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2090
90
85
2050
80
75
1985
70
65
60
55
50
10
20
30
40
50
60
70
Extreme precipitation recurrence time (Years)
03 December
2016
80
46
Bangalore City : GCMs Used
Procedure
CMIP 5 Ensemble
Downscaling (Daily
Scale) Rainfall
Stochastic
Disaggregation
Hourly and Subhourly Rainfall
Intensity
Ensemble
Averaged
Projections
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Model Name
ACCESS1_0
BCC-CSM1-1
BCC-CSM1-1-M
BNU-ESM
CanESM2
CCSM4
CMCC-CMS
CNRM-CM5
CSIRO-MK3-6-0
FGOALS-G2
FGOALS-S2
GFDL-CM3
GFDL-ESM2G
GFDL-ESM2M
GISS-E2-R
HadGEM2-CC
HadGEM2-ES
INMCM4
IPSL-CM5A-LR
IPSL-CM5A-MR
MIROC5
MIROC-ESM-CHEM
Latitude
12.5 N
12.55 N
12.89 N
12.55 N
12.55 N
12.7225 N
12.1 N
11.9 N
12.12 N
12.55 N
12.4 N
13 N
13.14 N
13.14 N
13 N
12.5 N
12.5 N
12.75 N
12.31 N
12.6 N
11.9 N
12.55 N
Longitude
76.875 E
78.75 E
77.6 E
78.75 E
78.7 E
77.5 E
76.8 E
77.34 E
76.875 E
78.75 E
75.9 E
78.75 E
76.25 E
76.25 E
76.25 E
76.87 E
76.875 E
78 E
78.75 E
77.5 E
78.75 E
78.75 E
Abbreviation
A1
BC1
BC1M
BNU
CAN
C4
CMS
CN5
CM60
FG2
FS2
GF3
GF2G
GF2M
GISS
HADC
HADE
IN4
IPCL
IPCM
MI5
MIEC
Climate Scenarios
RCP 4.5, RCP 8.5
RCP 2.6, RCP 4.5, RCP 6.0, RCP 8.5
RCP 2.6, RCP 4.5, RCP 6.0, RCP 8.5
RCP 2.6, RCP 4.5, RCP 8.5
RCP 2.6, RCP 4.5, RCP 8.5
RCP 2.6, RCP 4.5, RCP 6.0, RCP 8.5
RCP 4.5, RCP 8.5
RCP 4.5, RCP 8.5
RCP 2.6, RCP 4.5, RCP 6.0, RCP 8.5
RCP 2.6, RCP 4.5, RCP 8.5
RCP 2.6, RCP 4.5, RCP 6.0, RCP 8.5
RCP 2.6, RCP 6.0
RCP 2.6, RCP 4.5, RCP 6.0, RCP 8.5
RCP 2.6, RCP 4.5, RCP 6.0, RCP 8.5
RCP 4.5
RCP 4.5, RCP 8.5
RCP 2.6, RCP 4.5, RCP 6.0, RCP 8.5
RCP 4.5, RCP 8.5
RCP 2.6, RCP 4.5, RCP 6.0, RCP 8.5
RCP 2.6, RCP 4.5, RCP 6.0, RCP 8.5
RCP 2.6, RCP 4.5, RCP 6.0, RCP 8.5
RCP 2.6, RCP 4.5, RCP 6.0, RCP 8.5
MIROC-ESM
12.55 N
MPI-ESM-LR
MRI-CGCM3
NorESM1-M
12.12 N
12.89 N.
12.31 N
78.75 E
MIE
RCP 2.6, RCP 4.5, RCP 6.0, RCP 8.5
78.75 E
77.62 E
77.5 E
MPI
MRI
NEM
RCP 2.6, RCP 4.5, RCP 6.0, RCP 8.5
RCP 2.6, RCP 4.5, RCP 6.0, RCP 8.5
RCP 2.6., RCP 4.5, RCP 6.0, RCP 8.5
03
December
2016
47
Bangalore City : Projected change in the IDF Relationship :- CMIP5
models with AR5 scenarios (85 simulations)
CMIP 5 Ensemble
Downscaling (Daily
Scale) Rainfall
Stochastic
Disaggregation
Hourly and Subhourly Rainfall
Intensity
Ensemble
Averaged
Projections
IWSA National Conference
03
December
2016
48
Hydrologic models and lab setup
Implementation on ground
Historical data analysis
180
160
140
120
100
80
60
Meteorological Forecasts
40
20
0
0.25
0.5
1
3
Duration (hours)
6
12
24
Climate change impacts
RCP 8.5 Scenario, 10 Y Return period
60
450
400
Intensity(mm/hr)
50
350
300
250
200
Non-stationary
Stationary
40
Controlled Watershed
Hydro-meteorological Data
in real time
70
500
Return level (mm/hr)
30
20
150
Water Level Data for 10th November 2015
100
1
10
0.9
50
123
6
12
18
24
36
48
0.8
Duration
Water level above Datum (m)
MRI
MPI
NEM
IN4
MI5
MIE
IPCL
MIEC
IPCM
FS2
FG2
HADE
HADC
CN5
GF2M
CMS
CM60
GF2G
A1
C4
BC1
CAN
REA
BNU
0
BC1M
Historical
Intensity (mm/hr)
LiDAR
Survey
Sensors in
pilot study
area
Value addition
2D overland flow modelling
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
0
50
100
150
200
250
300
Time(min)
Flood mapping
Communication systems
Adequacy analysis of storm
water drains
Public participation
Flood hazard maps
Laboratory setup
IWSA National Conference
49
BBMP
Flood characterization and
management
Outreach
Flood management decision 03
Decem
support system
ber
http://civil.iisc.ernet.in/~pradeep/index_files/Page353.htm
2016
8:30 hrs of 20th July 2016 To 8:30hrs of 21st July 2016
Rain Forecast map
IWSA National Conference
Actual rainfall map
03 December 2016
50
Overall System Architecture for
Flood Management System- Bangalore City Pilot implementation
Server (SCADA/ HMI)
To the Hydraulic
Model/Weather
Model
Control Room for
Centralized Data
Acquisition
GSM/GPRS
Network
Bangalore City Zone Map
Flow
Sensor2
Rain
Sensor3
Rain
Sensor2
Level
Sensor2
Flow
Sensor1
SCADA/HMI- Human Machine Interface
Level/Flow Sensor with GSM/GPRS Modem
IWSA National Conference
Rain Sensor with GSM/GPRS Modem
Rain
Sensor1
Level
Sensor1
03
December
2016
The total number of Rain, Level, Flow sensors are indicative only
51
Isolating the impacts of land use and climate change on
streamflow
IWSA National Conference
03
December
2016
52
Upper Ganga Basin
53
Location of Upper Ganga Basin
 The Upper Ganga Basin (UGB) is located in northern India with geographical
coordinates of 25 30'N to 31 30'N latitude and 77 30'E to 80 E longitudes.
 The catchment area of the basin is 95,593 sq. km, covering parts of Uttarakhand and
Uttar Pradesh states of India.
IWSA National Conference
03
December
2016
 Average annual rainfall over the UGB varies from 500 mm to 2500 mm.
Methodology : Data
1. Topographic Data: Soil Map – NBSS & LUP
DEM – ASTER DEM
2. LU Information: Processed Landsat imageries for the years 1973,
1980, 2000 and 2011
3. Meteorological data: rainfall (P), maximum temperature (Tmax),
minimum temperature (Tmin) and wind speed (W) for the period
1971-2005 at daily time scale
4. Future Climate Projections: Procured from CORDEX South Asia
group at daily scale for six Coupled Model Intercomparison Project
5 (CMIP5) for RCP 4.5 and RCP 8.5 scenarios
5. Observed Discharge (Qobs): Procured for two locations:
Bhimgodha (1987-2011) and Ankinghat (1977-2009) at monthly
scale
 Data corresponding to various diversion channels is also procured from
CWC and added to the observed (regulated) flow - converting the
observed streamflow to virgin flow
0.5° × 0.5° grids in the UGB
IWSA National Conference
03
December
2016
54
Temporal LULC Analysis: Change Location Map
Scrub to
crop land
Barren to
crop land
IWSA National Conference
03
December
2016
55
Hydrologic Modelling
 Carried out at IISc, Bangalore and
Imperial College, London
 IISc :
 Setting
up
the
Variable
Infiltration
Capacity
(VIC)
hydrologic model at 0.5 degree
resolution over the Upper Ganga
basin
 Evaluating the effect of land use
and climate on hydrological
regime of the basin using VIC
model.
Canopy
Layer 1
(0 – 10 cm)
Layer 2
(10 – 40 cm)
Layer 3
(40 – 100 cm)
P
Ec Et
E1
Land-cover
classes
Qd
W1
Q12
I
Q23
W2
W3
Qb
P = Precipitation
Et = Evapotranspiration
Ec = Canopy Evaporation
E1 = Baresoil Evaporation
Qd = Direct Runoff
I = Infiltration
Q12 = Gravity flows layer 1
to 2
Q23 = Gravity flows layer 2
to 3
W1, W2, W3 = Water
content in
respective layers
Qb = Subsurface Flow
 Isolating the individual impact of
land use and climate change on
streamflow
 Climate change is the dominant
contributor to the observed
streamflow changes
IWSA National Conference
03
Hydrologic
impacts
of LULC and climate
56
December
2016
Summary Measures for Upstream Region – Future
Projections
Resolution of IMD data: 0.5 0.5
Resolution of downscaled IIT-B data:
0.25 0.25
Resolution of cordex data: ~0.44
0.44
03 December Rainfall
2016
IIT-B
(monthly)
CORDEX-CSIRO
(monthly)
Mean Observed Discharge ( X ) = 769.8 cumecs
Std Dev Observed Discharge ( ) = 793.1 cumecs
Projected Discharge (cumecs)
RCP 4.5
RCP 8.5
RCP 2.6
(2006-2099)
(2006-2099)



Model Name X
X
X
ACCESS1.0
1340.5 1026 1398.6 1096.6
CCSM4
1001.4 954.1 1408.6 1112.1
CNRM-CM5
1369.5 1036.5 1377.8 1101.9
GFDL-CM3
1230.3 941.9 1352.8 1080.8
MPI-ESM-LR
1386.1 1074 1430.9 1159.6
NorESM-M
1338.3 1021.4 1492.1 1144.6
RCP 2.6
RCP 4.5
RCP 8.5
(2010-2099)
(2010-2099)
(2010-2099)
BCC
880.3 896.0 868.7 611.4 870.9 602.3
CCCMA
874.9 894.0 896.0 632.2 879.7 610.8
IPSL
876.6 835.9 894.0 623.3 908.3 620.3
MIROC
845.3 880.0 835.9 560.1 859.8 590.9
NorESM
886.9 1041.4 880.0 605.1 896.1 613.7
Mean (cumecs)
Std. Dev. (cumecs)
Ensemble
(2010-2099)
1086.8
865.4
did not change
significantly
in future while discharge shows increase
IWSA
National Conference
57
Observations – Upper Ganga Basin
Climate is the dominant contributor to
streamflow across all the regions.
LU contribution is observed to be
minimal – streamflow is moderately to
highly sensitive to changes in urban
land for all the three regions, however
the spatial extent of urban area is very
less.
IWSA National Conference
03
December
2016
58
River Water Quality Response to
Climate Change
03 December 2016
IWSA NATIONAL CONFERENCE
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Case Study
03 December 2016
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Schematic Diagram of River
Shimoga City Sewage
Tunga
Shimoga
4
4
5
MPML VISL
3
3
Bhadra
Lakavalli
1
1
5
6
Honnali City Sewage
2
Harlahalli
6
2
Kumudavathi
7
Tunga -Bhadra River
7
Honnali
BhadravathiCity
16
8
Head Water Flow
Point Load
8
9
Kuppelur
Reach
Reach End point
Check point
MPM VISL HPF 03 December 2016
15
12
9
14
Harihar City Sewage
10
13
11
10
11
12
13
HP
14
Dhavangere
City Sewage
Byladahalli
Haridra
Mysore Paper Mill
Vishveshwaraya Iron and Steel Limited
Harihara Poly Fibers
IWSA NATIONAL CONFERENCE
61
Hypothetical Climate Change Scenarios
Alteration of climatic variables, covering all possibilities, e.g., change in
temperature and precipitation independently or in combination.
Scenario no.
Temperature Increase
(oC)
Streamflow Change
03 December 2016
1
2
3
4
5
6
1o
1o
1o
2o
2o
2o
0%
0
% 10% 20%
20% 10%
IWSA NATIONAL CONFERENCE
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Water Quality Response to Hypothetical
Scenarios using QUAL2K
Changes in DO level in response to
change in streamflow for a given
temperature change
03 December 2016
Changes in River Water Temperature in
response to change in streamflow for a
given Air temperature change
IWSA NATIONAL CONFERENCE
63
Statistical Downscaling : Selection of
Predictnad Variables
Input Variables to a water quality model
 Streamflow
 Water Temperature
Variables for a Water Temperature Model
River temperature is mainly controlled by
ambient atmospheric conditions (e.g. Edinger et
al.,1974; Ward,1985; Wu,1992; and Stefan and
Preud’homme,1993)






Predictand Variables Selected
1.
2.
3.
4.
5.
6.
7.
Streamflow
Average Air Temperature
Maximum Temperature
Minimum Temperature
Dew Point Temperature
Average Wind Speed
Relative Humidity
Average Air Temperature
Relative Humidity
Wind Speed
Dew Point Temperature
Solar Radiation
 Maximum Temperature
 Minimum Temperature
Effluent loadings and Diffuse Sources are assumed as unchanged in the future.
03 December 2016
IWSA NATIONAL CONFERENCE
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Check Point 10
7.00
6.72
6.06
5.50
5.55
5.00
4.50
4.89
4.00
3.50
present
2010-2040 2040-2070 2070-2100
03 December 2016
Dissolved Oxygen mg/L
Dissolved Oxygen mg/L
Check Point 1
6.50
6.00
Jl of Hydrology (2012)
DO Levels at various Check Points
7.00
6.50
6.00
5.50
5.99
5.39
5.00
4.50
5.15
4.51
4.00
3.50
present
IWSA NATIONAL CONFERENCE
2010-2040 2040-2070 2070-2100
65
(D&A) of
human-induced climate
change
Fingerprint of human-induced climate change searched for, in observations
‘Detection’ of climate change is ‘the process of demonstrating that climate or a
system affected by climate has changed in some defined sense, without
providing a reason for that change’.
‘Attribution’ is ‘the process of evaluating the relative contribution of multiple
causal factors to a change or event with an assignment of statistical confidence’.
Source : IPCC, (2007)
03 December 2016
IWSA NATIONAL CONFERENCE
66
Mahanadi river
basin
Research Issue
Addressed :
Whether the observed
change is due to
natural variability or is
due to external
forcings
Monsoon (JJAS) precipitation at 8 IMD locations, and accumulated monsoon
streamflow at Hirakud dam considered
03 December 2016
IWSA NATIONAL CONFERENCE
67
Water Resources Research, 2012
D&A results: Signalstrengths
Monsoon streamflow
The ensemble-averaged signal strengths (S values) from each model run (dots) and their 95% confidence
intervals (bars) are shown. The observed signal strength (Sobs) with its 95% confidence interval,
considering the multi-model ensemble-averaged ANTH fingerprint is shown in black. The GCMs for
which the ANTH signal strength is inconsistent in sign with the observed signal strength are marked in
cyan and those for which the ANTH signal strength is consistent with the observed signal strength are
marked in blue.
03 December 2016
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Concluding Remarks
Physical understanding of hydrologic systems
should be used for sustainable management of
water resources systems
It is possible to derive adaptive policies for
conjunctive use of surface and groundwater,
hydropower generation, flood control and water
quality control as a response to climate change.
03 December 2016
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