2nd APWS IMPAC‐T Session (2013/5/18)
Development of the integratedDevelopment of the integrated water resources model
Kenji TanakaWater Resources Research Center
Disaster Prevention Research Institute, Kyoto University JapanKyoto University, Japan
Motivation for model development1. How the hydrological cycle in watershed will be
Motivation for model development
affected due to external disturbance such asclimate change?
2. How the hydrological cycle in watershed will beaffected due to the alteration of land surfaceaffected due to the alteration of land surfacecondition such as deforestation, urbanization?
3. What kind of watershed is strong/ feasible/sustainable under climate change ?
4. Human activity (flood control, irrigation, release f h t) i l i t t t f dof heat) is also an important part of energy and
water cycle.
Goal of IMPAC‐TT l t
Real time simulation Flood protection
Flooded area
Inundation model
TelemetryNumerical weather predictionReal time reanalysis Climate scenarios
Climate change
H08 model(NIES/UT)Meteorological data River discharge
Reservoir storage
R i l
Geographical data
Reservoir release
Irrigation requirementSiBUC model
(KU)
New reservoir operation New reservoir?
Irrigation requirement
Water resources management
River planning Reservoir management
Integrated Water Resources ModelWater Cycle YieldCrop Growth
Crop Dynamics
Human EffectsCrop calendarLAI
Land Surface IrrigationSoil moisture
SIMRIW(Horie,1985)
Soil moisture
Stream flow
SiBUC (Tanaka,2004) SiBUC (Tanaka,2004)Intake & drainage
Dam operationStream flow
Outflow demand
p
Kinematic waveOutflow & Inflow
Discharge Newly developed
Land Surface (SiBUC)Land Surface (SiBUC)Grid box is divided intothree landuse categories
Simple Biosphere including Urban Canopy
1.Broadleaf‐evergreen trees2.Broadleaf‐deciduous trees3 Broadleaf and needle leaf treesg
1. Green Area2. Urban Area
3.Broadleaf and needle leaf trees4.Needle leaf‐evergreen trees5.Needle leaf‐deciduous trees6 Short vegetation/C4 grassland3. Water Body 6.Short vegetation/C4 grassland7.Broadleaf shrubs with bare soil8.Dwarf trees and shrubs9 F l d ( i i d)
Land Surface Irrigation
Crop calendarLAI
YieldCrop Growth
Modeling…
9.Farmland (non‐irrigated)10. Paddy field (non‐irrigated)11. Paddy field (irrigated)
Land Surface
Stream flow
Irrigation
SiBUC (Tanaka,2004) SiBUC (Tanaka,2004)
Soil moisture
Runoff
Intake & drainage
Damoperation
12. Spring wheat (irrigated)13. Winter wheat (irrigated)14. Corn (irrigated)Stream flow
Kinematic wave
Runoff
Outflow & InflowDischarge
Dam operation
developed
( g )15. Other crops (irrigated)
Green area model(SiB)( )• Prognostic variables
temperature (canopy, ground, deep soil)p ( py g p )interception water (canopy, ground)soil wetness (surface, root zone, recharge)
• Time invariant parametergeometrical parametergeometrical parameteroptical parameterphysiological parametersoil physical propertiessoil physical properties
• Time varying parameter (LAI etc.)estimate from satellite data
• Physical processesPhysical processesradiative transferinterception losssoil hydrologycanopy resistancecanopy resistancetranspirationturbulent transfer,snow, freezing/melting,… etc., g g,
I i tiIrrigationCrop calendarLAI
YieldCrop Growth
Land Surface IrrigationSoil moisture
Intake & drainage
Modeling…
Basic concept is to maintain soilStream flow
SiBUC (Tanaka,2004) SiBUC (Tanaka,2004)
Kinematic wave
Runoff
Intake & drainage
Discharge
Dam operation
developed
Basic concept is to maintain soil moisture/water depth within appropriate ranges for optimal Kinematic wave
Outflow & InflowDischarge developedappropriate ranges for optimal
crop growth.Application to wheat corn soyApplication to wheat, corn, soy bean, cotton etc…New water layer is added to treatNew water layer is added to treatpaddy field more accurately.
Water control in farmland
Soil moisture
Days
Water control in paddy field
Water depth
Days
Water maintain level for each growing stageCrop type Growing stage 1st 2nd 3rd 4th 5th
Spring Periods(%) 23 14 14 14 35p gwheat Soil wetness 0.70 0.60 0.80 0.80 0.55
Winter Periods(%) 25 20 22 13 20wheat Soil wetness 0.70 0.70 0.80 0.80 0.55
CornPeriods(%) 8 48 6 14 24
CornSoil wetness 0.75 0.65 0.70 0.75 0.65
RiPeriods(%) 25 13 33 13 16
Rice Water depth (mm)
20-50 none 20-60 moistening intermittent
Periods(%) 3 26 16 28 27soy bean
Periods(%) 3 26 16 28 27Soil wetness 0.75 0.65 0.65 0.70 0.65Periods(%) 4 21 13 26 36
cottonPeriods(%) 4 21 13 26 36Soil wetness none 0.5 0.55 0.55 0.5
Chart by required water for cultivation in China
Producing Crop Calendar from NDVI analysis
Time series NDVI represents growth of land surface
B0 (430‐470nm)B2 (610‐680nm)B3 (780‐890nm)MIR (1580‐1750nm)
vegetation.To find parameter to describe
f l dtimings of planting and harvesting.
Double Crop NDV
I
Growing periodhead headparameter
0.4
0.6
0.8
1
cnN
DVI
Double Crop
NDVI
NDVIfn
-0.2
0
0.2
0.4
12/3111/19/17/15/13/11/1
NDVI
, cn
time
NDVIst
Double cropland in India-0.2
12/3111/19/17/15/13/11/1
Date headplant harvest
Statistical crop calendar product (MIRCA 2000)
Statistical crop calendar products (country scale, monthly)
half data for calibrating parameter, half data for validation
NDVI Product (Spot Vegetation)Estimated date
Good
allowable
Statistical month
Global crop calendar generated by NDVIC l d d t (S k t l 2010)Crop calendar product (Sacks et al., 2010)
Advantage over previous products
High spatial resolutionHigh temporal resolutionHigh temporal resolutionReliability in countries where no statistics available
Satellites are observing surface!
Annual IWR (Irrigation Water Requirement) [mm/yr]
Annual IWR for each grids are
1000
100
im [G
t]
Model
Annual IWR for each grids are aggregated into country, then compared with AQUASTAT
10
1
With
draw
al S
im
0.1
0.0110001001010.10.01
W
Withdrawal AQUASTAT [Gt]
AQUASTAT※ Using irrigation efficiency (Doll et al., 2002)
Crop calendarLAI
YieldCrop Growth
River Land Surface Irrigation
SiBUC (Tanaka,2004) SiBUC (Tanaka,2004)
Soil moisture
Intake & drainage
Modeling…RiverStream flow
Kinematic wave
Runoff
Outflow & InflowDischarge
Dam operation
developed
: the grid which have largest catchment
: the grid flow into from upper grid: the grid flow into from upper grid
mesh size of model
data resolutionChannel length
Actual channel network
D A MD A Min fQ
66.6505
disc
harg
e
order
floodQ lowQ
1 Flood Protection OperationFlood discharge, normal dischargeoufQ
1. Flood Protection Operation
flood inf floodbase
Q Q QQ when
Q else
Disc. Peak‐cut Operation
2. Water Supply Operation
normQ else floodQ
max ,ouf base reqQ Q Q Demand from downstreamTime
Crop calendarLAI
YieldCrop Growth
C Land Surface Irrigation
SiBUC (Tanaka,2004) SiBUC (Tanaka,2004)
Soil moisture
Intake & drainage
Modeling…CropStream flow
Kinematic wave
Runoff
Outflow & InflowDischarge
Dam operation
developedS I M R I WkLAI Empirical
f f
Simulation Model for Rice‐Weather relations
max
1 exp ( ) 1 jj j f cf
LAILAI LAI A K T T
LAI
LAIkSS )1()1(1Solar
LAI growth Empiricalequation
LAImkrrSSs )1(exp)1(1 00
C C for1 DVI 2C(1 B) DVI 2
CSDW Carbon
Solarabsorption
Cs C(1 B)1Bexp
, DVI 2t
for2 DVI 3
,ssj CSDW Carbon
production
hi h & l t t t fl i tWhY high & low‐temp. stress at flowering stage Particle swarm optimization (PSO) was used to calibrate parameters.
WhY h Yield Harvest Index Dry weight
Seasonal Change (Asia)
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Water Balance check①WB② PREC
P E win② PREC③ EVAP④ R
ΔSWQsfwin
wout④ ROFF
⑤ TWS⑥ delTWS Qg
wout
⑥ delTWS
i
Qg
iTWS (Total water storage)=Soil moisture + surface water (snow)
catchment, , ,i t i t i tRoff Qsf Qg
, , , , ,i t i t i t i t i t iWB P E Win Wout S
Water Balance(Mekong & Chao Phraya)
What produces the difference pbetween flood and non flood year?
Please see Mr. Kotsuki’s Poster
1800
Need for high quality data
1200
1400
1600
1800
400
600
800
1000
Full(C2)Average value depends on data
0
200
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
Limit(C2)used (selected)
割 降 量 違 がS ll diff i i f ll1割の降雨量の違いが1.5倍の流量過大となる
Small difference in rainfall makes large difference in runoff
Anomaly Correlation analysis (Quality check) Daily data Monthly data
( missing < 6 days) var1monMonthly rainfall climatologyMonthly rainfall climatology
( at least 5years ) varclim
Anomaly = (var1mon – varclim)/varclimAnomaly = (var1mon – varclim)/varclim
X : monthly rainfall anomaly at each stationY f thl i f ll lY : area average of monthly rainfall anomalyCorrelation between X and Y
3
1.5
2
2.5
0
0.5
1
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
‐1.5
‐1
‐0.51 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
Integrated Water Resources model (H08)1. Simulate both natural water
cycle and human water activitiesHanasaki et al., 2006, J. of Hydrol.Hanasaki et al. ,2008a,b, HESSHanasaki et al., 2010, J. of Hydrolcycle and human water activities
at daily basis2. Open source software
, , y
2. Open source software
Land Surface processRiver RoutingRiver RoutingEnvironmental flowWater withdrawalCrop GrowthReservoir Operation
Effectiveness of new operation rule pto mitigate flood and drought risk
Please see Miss Cherry’s Poster
Summary and ConclusionSummary and Conclusion• Integrated water resources model is developed.Integrated water resources model is developed.Land Surface, Irrigation, River, Dam, CropGl b l di ib i f l d f• Global distribution of land surface parameters are produced. Especially, crop calendar is produced from time series analysis of satellite data (NDVI).( )
• Quality of rainfall data is very important for b tt t f tbetter management of water resources.
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