INTRODUCTION TO YANQI BASIN CASE STUDY (CHINA) · INTRODUCTION TO YANQI BASIN CASE STUDY (CHINA)...
Transcript of INTRODUCTION TO YANQI BASIN CASE STUDY (CHINA) · INTRODUCTION TO YANQI BASIN CASE STUDY (CHINA)...
INTRODUCTION TO YANQI BASIN CASE STUDY (CHINA)
Wolfgang Kinzelbach, Yu LiETH Zurich, Switzerland
Outline
• Study area- Hydrological regime- Problems - Sustainability in Yanqi
• Distributed numerical model
• Box model
• Multi-objective evolutionary algorithm
• Homework
2
Study Area
3
The Yanqi Basin (China)
Lake Bosten
Irrigation area
Kaidu River
damKongqueRiver
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The Yanqi Basin (China)
Hydrological RegimePrecipitation 74 mm/year (Switzerland 1500 mm/year)
PET 1400 mm/year
Elevation 4000 to 1046 m.a.s.l from north to south
Inflow by rivers 133 m3/s
Irrigation abstraction 37 m3/s
Evaporation by lake 57 m3/s
Flow to downstream 39 m3/s
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Land use
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Irrigation oasis
Salt marsh
Lake
Die-off of fish
Soil salinization
Groundwater table rise due to irrigation
Drying up of „green corridor“
Degradation of reed belt
Decline of water level in lake
Increase of salinity in lake
The problems….
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Before 1983: One natural lake After 1983: Building of dam and operation as reservoir
Some more views
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Water balance of lake: 1958-2008
disc
harg
e (1
08m
3 /a)
Safe lake level
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Water balance of basin (average 1950-2000) in m3/s
Unproductive evaporation
Savings in irrigation water
Reduction ofevaporation of lake
Bosten Lake
Resources tobe harnessed
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• Lake Bosten- Water quality: TDS lower than 1000 mg/l
- Lake level in the secure range between 1045.5 and 1048 m.a.s.l
- Increased flow to the downstream to sustain its agricultural development and prevent die-off of the green corridor
• Soil:- Salt concentration of irrigated soils should be stabilized at acceptable level
(assume 6000 mg/l)
• Groundwater- No deterioration of quality (salinity, agrochemicals)
- Groundwater level around the lake should be higher than lake level in order to prevent a reversal of groundwater flow
• Measures must be economically acceptable for farmers
What does sustainability mean in Yanqi Basin?
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Mechanism of soil salinization
Irrigation water (salt)
Salts from irrigation water
water vapour
water, salts
without drainage à accumulation of salts
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Mechanism of soil salinization
Irrigation water (salt)
without drainage à accumulation of saltsGroundwater table rise, capillary rise, mobilization of salts, high evaporation and salt deposition
water, salts
Salts from irrigation water Groundwater table rise
Natural recharge
Salts (not mobilized)
irrigated
Irrigation water (salts)
Salt (mobilized)
Salts (deposited at surface)
water vapour
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• Water saving irrigation- drip irrigation, plastic mulching
• Use of groundwater to lower groundwater table- reduce phreatic evaporation and thus salinization
• Diversion of saline water to evaporation ponds in the desert
• Reduction of agricultural area- Return to a more natural system
• Renovation of irrigation channels to reduce water transport losses- Increase efficiency
• Maintenance of drainage channels to flush salts out
Possible measures contributing to the goal of sustainability
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• Cost increase – pumping energy, drip equipment
• Groundwater pumping– Risk of over-exploitation
• Drip irrigation: accumulation of salts– requires flooding every 3 to 4 years to remove residual salts
• Drainage efficiency: difficult to raise
• Opposition to reduction of agricultural area
• Unknown: climate risk
Challenges
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Groundwater Pumping (initiated by World Bank project)
Pumping keepsgroundwater table belowthe extinction depth:no capillary rise
maximum pumping rate =Initial phreatic evaporation rate
Risks:
- Over-explotation- Recirculation in a deep
cone of depression
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Groundwater Pumping (initiated by World Bank project)
Pumping keepsgroundwater belowthe extinction depth:no capillary rise
maximum pumping rate =Initial phreatic evaporation rate
Risks:
- Over-explotation- Recirculation in a deep
cone of depression
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Distributed Numerical Model
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Data sources available
58 years of observations!
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Numerical model of Yanqi Basin:
• River flow : Saint Venant equation, 1D, simulating the lake as a set of river channels with wide cross-section
• Transpiration : Kristensen and Jensen method
• Unsaturated flow : Richards’ equation, 1D,van Genuchten’s formula
• Saturated flow : flow equation, 3D
Ø Software: MIKESHE/MIKE11
Parameters:
Collected+Calibrated
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ü Period: 1958---2008
ü Model discretization: - horizontal: 500m x 500m, 169 x 370 cells- vertical: 4 aquifer layers and- unsaturated zone: 0.05m to 2m from top to bottom
ü Manual calibration: results acceptable on the basis of different kinds of observations
Considerable computation time
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Numerical model of Yanqi Basin:
Selected results from distributed model(500 m grid)
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Reduced numerical model:
Consecutive coarsening of grid
ü Parameters of coarsened grid: average values from sub grids.
ü Coupling parameters (drain and river): effective parameters (modified based on mass conservation)
500 m by 500 m 1 km by 1 km 2 km by 2 km
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Results reduced numerical model:
Now use model in predictive mode to evaluate management scenarios
üS0_basin: Business-as-usual scenario: randomly generates one 50 years’ time series with hydrological characteristics of historical data.
üS1_basin: Salt deposit scenario: Transfer all drainage discharge from the irrigated area to the desert.
üS2_basin: Drip irrigation scenario: One third of agricultural land is assumed to adopt the new technology within the prediction time horizon. 10% of irrigation water is saved and drip irrigation water is supplied from groundwater.
üS3_basin: Reduced agricultural area scenario plus introduction of drip irrigation: reducing cultivated land by 20% andapplying drip irrigation in one third of farm land from groundwater.
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Coping with uncertainty
• Parameter uncertainty (including correlation of parameters)
• Uncertainty of hydrology• Both can be taken into account by ensemble method
(Monte Carlo method)• Many model runs with an ensemble of realizations of
the model with different parameter combinations and hydrologic sequences instead of one single model run
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Prediction: Ensemble average results
Lake level Discharge to downstream
Salt accumulated in soil zone Lake salinity
Kept constant by pumpingexcess water to downstream
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28IfU, BAUG, ETHZ
Example for ensemble outputs of Scenario S1:
Salt mass accumulation in soil
Lake TDS
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Fresh water
Predictive uncertainty (time horizon 50 years)
Lake dischargeSalt mass stored in soil
TDS of lake
SustainabilityGo for a combinationof salt disposaland watersaving
Soil salinity: Salt disposal moreefficientLake salinity:Drip irrigation moreefficient
Limit
Thesis Li Ning
(108t)
Conclusions
Ø A distributed 3D flow and transport model is constructed using MIKESHE/MIKE11 with the grid size of 500 m by 500 m. Running this numerical model is too time consuming, so a reduced but still adequate numerical model with the grid size of 2 km by 2 km is obtained by consecutive coarsening of the grid of the finer model.
Ø The coarser model is used in an ensemble approach to cover prediction uncertainty.
Ø All 3 strategies lead with some probability to a sustainable situation. The strategy of delivering the salt flux from the drain system to the desert instead of returning it to the lake is the most robust.
Ø The uncertainty of the scenarios does not yet include the uncertainty of climate change. The latter may be small because all rivers are dammed in the upstream.
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Box Model
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BostenLake
Kaid
uRi
ver
A Schematic View of the System (water balance)
Aqu
ifer
crop fieldin
flow
into
lake
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BostenLake
diversion
pumpingKa
idu
Rive
r
A Schematic View of the System (water balance)
Aqu
iferriver infiltration
crop field
crop consumption
inflo
w in
to la
ke
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BostenLake
river infiltration
diversionseepage
pumping
surfa
ce d
rain
age
Kaid
uRi
ver
A Schematic View of the System (water balance)
Aqu
ifer
inflo
w in
to la
ke
crop field
crop consumption
Phreatic evaporation
evaporation
outflow
exfilt
ratio
n
34
BostenLake
diversion
surfa
ce d
rain
age
Kaid
uRi
ver
A Schematic View of the System (water balance)
inflo
w in
to la
ke
crop field
crop consumption
evaporation
outflow
river infiltration
seepage
pumping
Aqu
ifer Phreatic evaporation
exfilt
ratio
n
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river infiltration
seepage
pumping
Aqu
ifer Phreatic evaporation
exfilt
ratio
n
river infiltration
diversionseepage
pumpingKa
idu
Rive
r
A Schematic View of the System (water balance)
Aqu
ifer
crop field
crop consumption
Phreatic evaporation
BostenLake
surfa
ce d
rain
age
inflo
w in
to la
ke
evaporation
outflow
exfilt
ratio
n
36
BostenLake
surfa
ce d
rain
age
inflo
w in
to la
ke
evaporation
outflow
exfilt
ratio
n
BostenLake
diversion
surfa
ce d
rain
age
Kaid
uRi
ver
A Schematic View of the System (salt balance)
inflo
w in
to la
ke
crop field
crop consumption
outflow
river infiltration
seepage
pumping
Aqu
ifer
Soil capillary
rise
washout
exfilt
ratio
n
37
river infiltration
seepage
pumping
Aqu
ifer
Soil capillary
rise
washout
exfilt
ratio
n
river infiltration
diversionseepage
pumpingKa
idu
Rive
r
A Schematic View of the System (salt balance)
Aqu
ifer
crop field
crop consumption
Soil capillary
rise
washout
BostenLake
surfa
ce d
rain
age
inflo
w in
to la
ke
outflow
exfilt
ratio
n
38
BostenLake
surfa
ce d
rain
age
inflo
w in
to la
ke
outflow
exfilt
ratio
n
• Install the Matlab Runtime Environment corresponding to your operating system
• Double click the executable file (.exe) to open the program
• Type values in the box to define inputs
• Click “calculate” to run the model. Results and figures are stored in the “Results” folder
How to Run the Program
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Interfaceput your own numbers in the left panel to define your decisions
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Interfacesee final performance on the right
panel
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Check state-variables in “Results” folder
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Homework
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■ Try with box model program by:– Changing water allocation scheme– Changing irrigation scheme (i.e., methods and area)– Changing cropping scheme– Changing simulation horizon
■ Play 20 times with 20 years horizon, check the performance of the your decisions based on following criteria:
– Salt concentration in Bosten Lake no higher than 1000 mg/l– Bosten Lake level stays in between 1045.5 and 1048 m.a.s.l– Salt concentration in soil layer is not higher than 6000 mg/l– On average, the aquifer water table is higher than the lake level to
prevent reversal of groundwater flow;
■ Collect all resulted “.csv” files into a folder named as “”, and send it to instructor
Tasks
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■ Get a feel for box model by:– Changing water allocation scheme– Changing irrigation scheme (i.e., methods and area)– Changing cropping scheme– Changing simulation horizon
■ Play 20 times with 20 years’ time horizon, check the performance of your decisions based on the following criteria:
– Salt concentration in Bosten Lake no higher than 1000 mg/l– Bosten Lake level stays in between 1045.5 and 1048 m.a.s.l– Salt concentration in soil layer is not higher than 6000 mg/l– On average, the aquifer water table is higher than the lake level to
prevent reversal of groundwater flow;
■ Collect all resulted “.csv” files into a folder named as “”, analyze, describe your findings in words. Send calculation results to instructor
Goals
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Salt concentration in Bosten Lake no higher than 600 mg/l
Bosten Lake level stays in between 1045.5 and 1048 m.a.s.l
Salt concentration in soil layer is not higher than 4000 mg/l
On average, the aquifer water table is higher than the lake level to prevent reversal of groundwater flow;
Optimizing our decisions
Criteria
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Optimizing our decisions
min{ salt concentration in lake }
min{ salt concentration in soil}
max{ aquifer head – lake level }
max{ net profit }
constraint{ 1045 < lake level [m] <1048 }
Criteria Objective
Salt concentration in Bosten Lake no higher than 600 mg/l
Bosten Lake level stays in between 1045.5 and 1048 m.a.s.l
Salt concentration in soil layer is not higher than 4000 mg/l
On average, the aquifer water table is higher than the lake level to prevent reversal of groundwater flow;
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Results Monte-Carlo simulation
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Performance: 1 objective
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Performance: 2 objectives
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Performance: 2 objectives
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Question: can you see conflict of objectives ?
Performance: 2 objectives
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a 1-D Pareto front
Performance: 3 objectives
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Performance: 4 objectivesDifference between aquifer head and lake level
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Parallel coordinate plotsm
inim
izatio
n
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Parallel coordinate plots
each Y-axis is an objective
min
imiza
tion
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Parallel coordinate plotseach line represents a solution
min
imiza
tion
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Parallel coordinate plots
two lines intersecting each other reveals a “conflict” m
inim
izatio
n
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Parallel coordinate plots
screening out unacceptable performances
min
imiza
tion
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Multi-objective optimization with MOEA
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Initialize Population
Evaluate
Selection
Crossover
Mutation
Termination Criterion
Create New Population
Solution Set
smar
t gue
ss
A typical flowchart of genetic algorithm
Q1: how to perform the smart guess Q2: how to ensure the gradual
improvement of the solution
Multi-objective Evolutionary Algorithm (MOEA)
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Initialize Population
Evaluate
Selection
Crossover
Mutation
Termination Criterion
Create New Population
Solution Set
smar
t gue
ssMulti-objective Evolutionary Algorithm (MOEA)
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A “population” is a group of possible solutions
a1
b1
c1
a2
b2
c2
a3
b3
c3
a4
b4
c4
Initialize Population
Evaluate
Selection
Crossover
Mutation
Termination Criterion
Create New Population
Solution Set
smar
t gue
ssMulti-objective Evolutionary Algorithm (MOEA)
63
A “population” is a group of possible solutions
a1
b1
c1
a2
b2
c2
a3
b3
c3
a4
b4
c4
y1 y2 y3 y4
y2 > y4 > y1 > y2
Initialize Population
Evaluate
Selection
Crossover
Mutation
Termination Criterion
Create New Population
Solution Set
smar
t gue
ssMulti-objective Evolutionary Algorithm (MOEA)
64
A “population” is a group of possible solutions
a1
b1
c1
a2
b2
c2
a3
b3
c3
a4
b4
c4
y1 y2 y3 y4
y2 > y4 > y1 > y2
Initialize Population
Evaluate
Selection
Crossover
Mutation
Termination Criterion
Create New Population
Solution Set
smar
t gue
ssMulti-objective Evolutionary Algorithm (MOEA)
65
“cross-over” operation
a2
b2
c2
a4
b4
c4
a2
b4
c2
a4
b2
c4
Initialize Population
Evaluate
Selection
Crossover
Mutation
Termination Criterion
Create New Population
Solution Set
smar
t gue
ssMulti-objective Evolutionary Algorithm (MOEA)
66
a2
b2
c2
a4
b4
c4
A2
B2
C2
A4
B4
C4
“mutation” operation
+ ∆ - ∆’
Three-objective Test Problem■ Heuristic method: flexibility for stochastic problems with unknown gradients
■ Search balances convergence and diversity
Multi-objective Evolutionary Algorithm (MOEA)
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Reed, Patrick M., et al. "Evolutionary multiobjective optimization in water resources: The past, present, and future." Advances in water resources 51 (2013): 438-456.
Approximated Pareto Front with NSGAII
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Acceptable solution with parallel plot
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Solution A
Solution B
Acceptable solution with parallel plot
Question: if the inflow from Kaidu River is changing in future, are the solutions still acceptable ?
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Solution A
Solution B
Robustness Based Assessment
objective
scenario
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Robustness Based Assessment
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scenarios
objective
acceptablethreshold
Success
Failure
Robustness Based Assessment
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objective
acceptablethreshold
scenarios
Success
Failure
The robustness under changing inflow rates
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Solution A:
Acceptable performance = 31%
Solution B:
Acceptable performance = 0 %
With inflow changing by 20%
The robustness under changing inflow rates
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Solution A:
Acceptable performance = 51%
With inflow changing by 10%
Solution B:
Acceptable performance = 0 %
Conclusion: Solution A is more robust!
THANK YOUfor your attention
Follow our project on: http://www.ifu.ethz.ch/projects/china-groundwater-management-project.html 76