IUKWC Workshop Nov16: Developing Hydro-climatic Services for Water Security – Session 1 – Item 1 - P_Mujumdar

Hydromet Forecasts and
Projections : Some Recent
Applications
Pradeep Mujumdar
Indian Institute of Science
Bangalore

Applications of…
 Medium Range Weather Forecasts for Irrigation Water
Management
 Climate Change Projections for Developing Adaptive
Responses - Water Resources Systems
 Near-Real-Time Forecasts for Urban Floods
29 November
2016
India UK Water Centre

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Discharger 1
Discharger 2
Discharger n
Inflow
Regulated
d/s flow
Reservoir
A Typical Water Resource System
 Power
Discharger ..
Non Point Source
Pollution
Municipal
Water
Supply
Groundwater
Reservoir
Recharge
Rainfall
Evaporation
74%
5%
6%
3%
1% 2%
9%
Water Requirements for Different
Uses - INDIA
Irrigation
Domestic
Industries
Power
Navigation
Environment/Ecology
Evaporation
Source : Ministry of Water Resources,
Irrigation
GW Pumping

Cr.#1
Cr.#2
Cr.#3
Cr.#4
Conveyance
System
Reservoir
Inflow
Rainfall
Evaporation
Soil Moisture
Irrigated Area
Evapotranspiration
Cr :
Crop
A Typical Surface Water Irrigation System
29 November 2016India UK Water Centre

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Grid Longitude Latitude
1 E75030’ N130
2 E75030’ N13030’
3 E75030’ N140
4 E75030’ N14030’
5 E75030’ N150
6 E760 N130
7 E760 N13030’
8 E760 N140
9 E760 N14030’
10 E760 N150
11 E76030’ N13030’
12 E76030’ N140
13 E76030’ N14030’
14 E76030’ N150
15 E770 N150
 Forecasted Rainfall Data (National Centre for Medium Range Weather Forecasting)
• Grid 0.50 Latitude and 0.50 Longitude
• Forecasts from 20 Ensemble Members based on 20 Perturbed Initial Conditions
• The forecast length is 240 hours i.e., Day1 through Day10 at 1day interval
Bhadra Reservoir Command Area

• The National Centre for Medium Range Weather Forecasting
(NCMRWF ) regularly provides forecasted rainfall data at
0.5 degree resolution
• The NCMRWF Global Ensemble Forecast System (NGEFS)
rainfall forecasts are available for the 20 ensemble
members.
• The forecasts from 20 ensemble members are obtained
based on the 20 perturbed initial conditions. The forecast
length is 240 hours i.e., Day1 through Day10 at 1day
interval.
RAINFALL FORECASTS
INFLOW FORECASTS
First order Non Stationary Markov Model

Figure 4.5: Comparison of variations in Forecasted Rainfall (mm) with Actual
Rainfall (mm) for (a) Grid 1, (b) Grid 3, and (c) Grid 7 (Data from National Centre
for Medium Range Weather Forecasting, 2013)

Satellite Soil Moisture Data
• ESA CCI (European Space Agency Climate Change Initiative) daily global merged soil
moisture data with a spatial resolution of 0.250
• Fuzzy Gridded Soil Moisture Class Intervals of Crops 𝑴 = 𝒎 𝟏
𝟏
, 𝒎 𝟐
𝟏
, … 𝒎 𝑪
𝟏
, 𝒎 𝟏
𝟐
, 𝒎 𝟐
𝟐
… , 𝒎 𝑪
𝒏 𝒈
• Study Area (1 degree x 1 degree) consists of Three Grids
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Crop Production Function
–System performance measure
–Response of the crop yield to water supply during
intraseasonal periods.
–A function of evapotranspiration deficits occurring
during the growth stages of the crop.
 
NS
1s
c
max
c
a
c
scm ])sET/ET-1(ky-1[)(y/y
Crop Season
s=1 s=2 s=3 s=4 s=5
1. Establishment 2. Vegetative 3. Flowering 4. Yield Formation 5. Ripening

0 (1-d)(f - w) (f - w)
1.0
AET
PET
AVAILABLE SOIL MOISTURE
AET-PET RELATION
• Optimum crop growth occurs when AET = PET
• Soil moisture may be depleted upto a certain level
(governed by the soil moisture depletion factor, d), with AET
still equal to PET.

Period t Period
t+1
RAINt + IRAt ETa
t
m
t
n
t+1
Dt
Dt+1
DDPt
Soil Moisture Balance
0
n
t+1 Dt+1 = m
t Dt + RAINt + IRAt - Eta
t - DPt + 0 D
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Increasing root depth from
period to period

Climate Change: Hydrologic Projections

Mahanadi river basin
TIKARPAR
A
SANKARA
SEORINARAY
AN
BASANTP
UR
PENDRARO
AD
BAIKUNTHP
UR
RAIPUR
PHULBANI
BURLA
820 840830
200
850
210
870860810
INDIA
190
HIRAKUD
DAM
R.S. DAM
MAHANADI BASIN MAP
220
230
1
5 6
2 3
4
87
Downscaling
locations
Downscaling to daily precipitation at eight locations
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Mahanadi River Basin - Streamflow
29 November
2016
Predictand:
Monsoon Streamflow
of Mahanadi River at
Hirakud Dam
Predictors
2m Surface Temperature
Geopotential Height at 500 hP
Specific Humidity
Mean Sea Level Pressure
Hirakud Dam
River Mahanadi
Chiplima power
house
Burla power
house
Inflow to Hirakud reservoir
Irrigation release
Bay of Bengal
Power generation
capacity: 347.5 MW, Firm
power: 134 MW

Streamflow Projection : Downscaling Model
validation
Independent testing : Trained on 1959-1989 data, tested on 1990-2005 data
Study area 15o N to 25oN, 80oE to
90oE
Training data NCEP/NCAR reanalysis
data from 1959-2005
Monsoon monthly
mean inflow data at
Hirakud for years
1959-2005
Projection data GCMs: CGCM2, GISS,
MIROC3.2
Scenarios : A1B, A2,
B1
Large-scale
predictors
2m surface air
temperature, mean
sea level pressure
(MSLP), 500 hPa
geopotential height
and surface specific
humidity
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2016
Projections for future monsoon inflows to
Hirakud Reservoir
Range of projected future flow duration curves at Hirakud
Reduction in
‘normal’ (middle
level) flows

29 November
2016
Projected Irrigation Water Demand :
CGCM2; A2 ; Source : Asokan and Dutta
(2009)
Projected Peak and Average Discharge;
CGCM2; A2; Source : Asokan and Dutta
(2009)
Flood Storage
Live Storage
Hydropower
Irrigation
Dam

Mean monthly hydropower
0
50
100
150
200
250
300
350
Jan F eb Mar Apr May Jun Jul Aug S ep Oct Nov Dec
Month
Meanpowergenerated(MW)
C urrent S OP
1959-2005
MIR OC 3.2 B 1
with S OP
MIR OC 3.2 B 1
with P olicy 1
MIR OC 3.2 B 1
with P olicy 2
MIR OC 3.2 B 1
with P olicy 3
0
50
100
150
200
250
300
350
Jan F eb Mar Apr May Jun Jul Aug S ep Oct Nov Dec
Month
Meanpowergenerated(MW)
C urrent S OP
1959-2005
C GC M2 A1B
with S OP
C GC M2 A1B
with P olicy 1
C GC M2 A1B
with P olicy 2
C GC M2 A1B
with P olicy 3
Adaptive policies for (a) MIROC3.2 B1 scenario and (b) CGCM2 A1B scenario for 2045-65
using SDP optimization showing recovery of mean monthly power generated.
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Reservoir operation under
adaptive policies
R ule C urve at Hirakud for adaptive policies
178
180
182
184
186
188
190
192
194
1-Jul 1-Aug 1-S ep 2-OctDate
Reservoirlevel(m)
C urr rule curve
min
C urr rule curve
max
2045-65 rule
curve min
2045-65 rule
curve max
MIR OC 3.2 B 1
2045-65 P olicy
1
MIR OC 3.2 B 1
2045-65 P olicy
2
MIR OC 3.2 B 1
2045-65 P olicy
3
Reservoir operation under MIROC3.2 B1 scenario: Current and projected rule
curve versus mean elevations obtained for adaptive policies.
• Adaptive policies have a higher reservoir elevation in August than that permitted by the corresponding rule
curves
• Policy 2 and Policy 3 which progressively increase the weightage assigned to power reliability result in
progressively higher elevations
• Increased risk of flooding since higher elevations breach the flood control rule curve for 2045-65 scenerios
29 November
2016

URBAN FLOODS
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Flood mapping
Flood management decision
support system
Flood characterization and
management
Flood hazard maps Public participation
Sensors in
pilot study
area
Communication systems
Meteorological Forecasts
Implementation on ground
Hydro-meteorological Data
in real time
Hydrologic models and lab setup
Climate change impacts
Historical data analysis
Adequacy analysis of storm
water drains
0.25 0.5 1 3 6 12 24
0
20
40
60
80
100
120
140
160
180
Duration (hours)
Intensity(mm/hr)
50
100
150
200
250
300
350
400
450
500
Historical
REA
A1
BC1
BC1M
BNU
CAN
C4
CMS
CN5
CM60
FG2
FS2
GF2G
GF2M
HADC
HADE
IN4
IPCL
IPCM
MI5
MIEC
MIE
MPI
MRI
NEM
Returnlevel(mm/hr)
RCP 8.5 Scenario, 10 Y Return period
0 50 100 150 200 250 300
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
Water Level Data for 10th November 2015
WaterlevelaboveDatum(m)
Time(min)
123 6 12 18 24 36 48
0
10
20
30
40
50
60
70
Duration
Intensity(mm/hr)
Non-stationary
Stationary
Laboratory setup
2D overland flow modelling
LiDAR
Survey
Value addition
Controlled Watershed
BBMP
http://civil.iisc.ernet.in/~pradeep/index_files/Page353.htm
Outreach
29
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2016
India UKWater Centre

Bangalore BBMP (800 Sq KMs)
1 TRG at every 8sq km & TWS at every 100sq km
Raingauage&Weathersensors
100- Telemetric Rain Gauges
8- Telemetric Weather stations

Near Real-time Rainfall Forecasts
from SAC Ahmedabad
 SAC uses WRF model - once the boundary conditions are
set in WRF model ,
 the weather parameters such as Wind speed, wind
direction, Relative humidity, and temperature from
KSNDMC from 8 Telemetric Weather sensors within BBMP
area is pushed to WRF model through FTP.
 At 12.30PM everyday, KSNDMC receives rainfall forecast
for next 12hr, 24hr, 36hrs,48hr ,60hrs& 72 hrs,
 Every day WRF model receives the actual weather
parameters through FTP from KSNDMC and the forecast
is updated for next 3 days.

29 November
2016
Rain Forecast map Actual rainfall map
8:30 hrs of 20th July 2016 To 8:30hrs of 21st July 2016

Overall System Architecture for
Flood Management System- Bangalore City Pilot implementation
SCADA/HMI- Human Machine Interface
Level/Flow Sensor with GSM/GPRS Modem
Rain Sensor with GSM/GPRS Modem
GSM/GPRS
Network
To the Hydraulic
Model/Weather
Model
Server (SCADA/ HMI) Control Room for
Centralized Data
Acquisition
Rain
Sensor1
Rain
Sensor2
Flow
Sensor1
Level
Sensor1
Level
Sensor2
Flow
Sensor2
Rain
Sensor3
The total number of Rain, Level, Flow sensors are indicative only
Bangalore City Zone Map
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Flood Forecasts

Concluding Remarks
 Medium range weather forecasts are useful in
updating irrigation schedules; especially useful in
increasing water use efficiencies.
 It is possible to derive adaptive policies for
hydropower generation, flood control and
irrigation water supply as a response to climate
change.
 Real-time rainfall forecasts are useful in integrated
urban flood management
29 November
2016

IUKWC Workshop Nov16: Developing Hydro-climatic Services for Water Security – Session 1 – Item 1 - P_Mujumdar

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IUKWC Workshop Nov16: Developing Hydro-climatic Services for Water Security – Session 1 – Item 1 - P_Mujumdar