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Sunday, 09 October 2022
Dr Mohammed Basheer
Knowledge Exchange Fellow – The University of Manchester
Alexander von Humboldt postdoctoral research fellow –
Humboldt-Universität zu Berlin
NEXUS GAINS
Multiobjective optimization of dam
operation and irrigation development
on the Blue Nile in Sudan
2
Presentation outline
Presentation outline
Introduction
Objectives
Step1: simulate
Step2: search
Step3: deliberate
Conclusions
1
2
3
4
6
5
3
1- Introduction
 The Blue Nile is one of the main
tributaries Nile and contributes
around 60% of the mean annual
flow.
 Large-scale irrigated agriculture
is practiced on the Blue Nile in
Sudan.
 The Blue Nile Basin in Sudan will
soon enter a new era with the
construction and operation of
the Grand Ethiopian Renaissance
Dam (GERD).
4
 Study area Extends over the
Blue Nile Basin from the Grand
Ethiopian Renaissance Dam
(GERD) to Khartoum.
 Includes three dams:
 GERD
 Roseires Dam
 Sennar Dam
1- Introduction
5
 Existing irrigation schemes
 Gezira and Managil
 North West Sennar
 Suki Minor pump schemes
 Rahad 1
 Gunied
 Planned irrigation schemes
 Kenana 1
 Kenana 2
 Kenana 3
 Kenana 4
 Roseires
 Dinder South
 Dinder North
 Rahad 2 South
 Rahad 2 North
1- Introduction
6
2- Objectives
(1) Develop a river
system simulation
model
(2) Search for
efficient plans
(3) Deliberate the
search outcomes
 How to plan dam
operations and
irrigation
expansion?
 A three-step
iterative process
7
3- Step1: simulate
21 inflow, abstraction,
and reservoir nodes
33 river flow
sequences
8
 The model was calibrated over the
period 1985-2000 and over validated
from 2001-2016.
 Model performance was assessed based
on historical observed flow data at three
locations: Roseires Dam, Sennar Dam,
and Khartoum Gauge
 Model performance ranking was
assessed according to the criteria
published in: Stern, M., Flint, L., Minear, J., Flint, A.,
Wright, S., 2016. Characterizing changes in streamflow and
sediment supply in the Sacramento River Basin, California, using
hydrological simulation program—FORTRAN (HSPF). Water 432,
1–21. https://doi.org/10.3390/w8100432.
3- Step1: simulate
9
Location Performance metric
Calibration Validation
(1985-2000) (2001-2016)
Metric
value
Ranking
Metric
value
Ranking
Roseires Dam
MEP 2.76 Excellent 7.14 Excellent
NSE 0.95 Excellent 0.92 Excellent
R2 0.95 Excellent 0.92 Excellent
Sennar Dam
MEP 18.59 Good 29.66 Fair
NSE 0.9 Excellent 0.87 Excellent
R2 0.91 Excellent 0.87 Excellent
Khartoum Gage
MEP 20.74 Good -13.52 Very good
NSE 0.83 Very good 0.86 Excellent
R2 0.84 Very good 0.88 Excellent
 The model showed predominantly very good to excellent
performance in the calibration and validation periods
3- Step1: simulate
10
4- Step2: search
 The simulation model was connect
to a multiobjective evolutionary
algorithm to search for plans.
Simple multi-objective example
for selecting a restaurant
11
 Seven optimization objectives:
1. Maximise GERD’s mean annual energy
2. Maximise Roseires’ mean annual energy
3. Maximise Sennar’s mean annual energy
4. Maximise mean annual irrigation water
use in irrigation expansion in Sudan
5. Maximise mean annual irrigation water
use in existing irrigation in Sudan
6. Maximise mean annual irrigation water
use by Wheat in irrigation expansion in
Sudan.
7. Maximise mean annual municipal water
use in Sudan
4- Step2: search
12
 Decision variables:
1. GERD operating rules
2. Roseires operating rules
3. Sennar operating rules
4. Cropping pattern in irrigation
expansion in Sudan.
 Six crops are considered for
irrigation expansion:
 Wheat
 Cotton
 Groundnuts
 Sorghum
 Sugarcane
 Sunflower
4- Step2: search
13
 Parallel coordinates
plot of the Blue Nile
system performance
under efficient
designs of dam
operating rules and
cropping patterns in
new irrigation.
 Two designs are
highlighted (thick
lines) focusing on
specific performance
metrics.
4- Step2: search
14
 Each highlighted efficient design (from the previous slide)
implies and package of dam operating rules.
4- Step2: search
Collaborative interactive stakeholder
assessment
 Deliberate trade-offs
 Negotiate, agree on
interventions
15
Loucks, D.P., van Beek, E., 2017. Water resource systems planning and
management: An introduction to methods, models, and applications, Advances
in Water Resources. Springer. https://doi.org/10.1016/0309-1708(81)90046-4
5- Step2: deliberate
16
6- Conclusions
 Multi-objective optimization can help design
efficient dam operating rules and cropping patterns
for new irrigated areas.
 System performance objectives should be balanced
when selecting a package of interventions.
 Other constraints such as crop rotations should be
considered in the deliberation process.
Thank you for
your attention!

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Mohammed Basheer - Blue Nile Cascade Dam Operation

  • 1. Sunday, 09 October 2022 Dr Mohammed Basheer Knowledge Exchange Fellow – The University of Manchester Alexander von Humboldt postdoctoral research fellow – Humboldt-Universität zu Berlin NEXUS GAINS Multiobjective optimization of dam operation and irrigation development on the Blue Nile in Sudan
  • 2. 2 Presentation outline Presentation outline Introduction Objectives Step1: simulate Step2: search Step3: deliberate Conclusions 1 2 3 4 6 5
  • 3. 3 1- Introduction  The Blue Nile is one of the main tributaries Nile and contributes around 60% of the mean annual flow.  Large-scale irrigated agriculture is practiced on the Blue Nile in Sudan.  The Blue Nile Basin in Sudan will soon enter a new era with the construction and operation of the Grand Ethiopian Renaissance Dam (GERD).
  • 4. 4  Study area Extends over the Blue Nile Basin from the Grand Ethiopian Renaissance Dam (GERD) to Khartoum.  Includes three dams:  GERD  Roseires Dam  Sennar Dam 1- Introduction
  • 5. 5  Existing irrigation schemes  Gezira and Managil  North West Sennar  Suki Minor pump schemes  Rahad 1  Gunied  Planned irrigation schemes  Kenana 1  Kenana 2  Kenana 3  Kenana 4  Roseires  Dinder South  Dinder North  Rahad 2 South  Rahad 2 North 1- Introduction
  • 6. 6 2- Objectives (1) Develop a river system simulation model (2) Search for efficient plans (3) Deliberate the search outcomes  How to plan dam operations and irrigation expansion?  A three-step iterative process
  • 7. 7 3- Step1: simulate 21 inflow, abstraction, and reservoir nodes 33 river flow sequences
  • 8. 8  The model was calibrated over the period 1985-2000 and over validated from 2001-2016.  Model performance was assessed based on historical observed flow data at three locations: Roseires Dam, Sennar Dam, and Khartoum Gauge  Model performance ranking was assessed according to the criteria published in: Stern, M., Flint, L., Minear, J., Flint, A., Wright, S., 2016. Characterizing changes in streamflow and sediment supply in the Sacramento River Basin, California, using hydrological simulation program—FORTRAN (HSPF). Water 432, 1–21. https://doi.org/10.3390/w8100432. 3- Step1: simulate
  • 9. 9 Location Performance metric Calibration Validation (1985-2000) (2001-2016) Metric value Ranking Metric value Ranking Roseires Dam MEP 2.76 Excellent 7.14 Excellent NSE 0.95 Excellent 0.92 Excellent R2 0.95 Excellent 0.92 Excellent Sennar Dam MEP 18.59 Good 29.66 Fair NSE 0.9 Excellent 0.87 Excellent R2 0.91 Excellent 0.87 Excellent Khartoum Gage MEP 20.74 Good -13.52 Very good NSE 0.83 Very good 0.86 Excellent R2 0.84 Very good 0.88 Excellent  The model showed predominantly very good to excellent performance in the calibration and validation periods 3- Step1: simulate
  • 10. 10 4- Step2: search  The simulation model was connect to a multiobjective evolutionary algorithm to search for plans. Simple multi-objective example for selecting a restaurant
  • 11. 11  Seven optimization objectives: 1. Maximise GERD’s mean annual energy 2. Maximise Roseires’ mean annual energy 3. Maximise Sennar’s mean annual energy 4. Maximise mean annual irrigation water use in irrigation expansion in Sudan 5. Maximise mean annual irrigation water use in existing irrigation in Sudan 6. Maximise mean annual irrigation water use by Wheat in irrigation expansion in Sudan. 7. Maximise mean annual municipal water use in Sudan 4- Step2: search
  • 12. 12  Decision variables: 1. GERD operating rules 2. Roseires operating rules 3. Sennar operating rules 4. Cropping pattern in irrigation expansion in Sudan.  Six crops are considered for irrigation expansion:  Wheat  Cotton  Groundnuts  Sorghum  Sugarcane  Sunflower 4- Step2: search
  • 13. 13  Parallel coordinates plot of the Blue Nile system performance under efficient designs of dam operating rules and cropping patterns in new irrigation.  Two designs are highlighted (thick lines) focusing on specific performance metrics. 4- Step2: search
  • 14. 14  Each highlighted efficient design (from the previous slide) implies and package of dam operating rules. 4- Step2: search
  • 15. Collaborative interactive stakeholder assessment  Deliberate trade-offs  Negotiate, agree on interventions 15 Loucks, D.P., van Beek, E., 2017. Water resource systems planning and management: An introduction to methods, models, and applications, Advances in Water Resources. Springer. https://doi.org/10.1016/0309-1708(81)90046-4 5- Step2: deliberate
  • 16. 16 6- Conclusions  Multi-objective optimization can help design efficient dam operating rules and cropping patterns for new irrigated areas.  System performance objectives should be balanced when selecting a package of interventions.  Other constraints such as crop rotations should be considered in the deliberation process.
  • 17. Thank you for your attention!