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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
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
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.