The Use oF Linear Perturbation Model for Real Time Flow Forecasting of the Blue Nile River System at Khartoum
The Use oF Linear Perturbation Model for Real Time Flow Forecasting of the Blue Nile River System at Khartoum
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Date
2015-05-03
Authors
Mohamed, Nada Shrieff Hassan
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Publisher
UOFK
Abstract
Flood is one of the most damaging natural disasters worldwide.
Flood problems lead to significant damages. In addition to loss of lives,
floods result in damages to ecosystem, properties, and poses risk to public
health. The unexpected occurrence of floods results in bigger amount of
damages and higher costs of rehabilitation than the predicted flood event.
Thus, the need for flood forecast especially flood early warning systems
is vital.
Along the Blue Nile River the floods have been the most common
form of natural disaster. In recent years the frequency of natural disasters
associated with extreme floods events were increased (e. g. 1988, 2003,
and 2007). The floods have negative impacts to Khartoum State. This
results mainly in loss of lives and properties. To combat or reduce such
impacts, two broad approaches can be used namely structural and non
structural. This work falls in the non structural approach. The main
objective of this study is to develop a model that is capable of issuing
forecast flows at Khartoum based on measured flows at Sennar, Dinder,
and Rahad with a suitable lead time.
The Linear Perturbation Model(LPM) was used as substantive
model. The model was calibrated using 11 years of data and verified
using 5years of data. The model was used in two forms namely
parametric and non parametric as well as in single input- single output
and multiple input-single output forms.
The calibrated models are then updated using both linear transfer
function (LTF)and autoregressive(AR) models with lead time of up to six
days. The model is then used for real time forecasting after calibration
and updating.
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Based on Nash – Sutcliffe efficiency criteria, the model
performance is judged and found very satisfactory in all its forms and
stages of uses. During the calibration period the model efficiencies are
94.2% and 95.5% for the cases of single input- single output and multiple
inputs – single output for Non-Parametric LPM respectively. The model
efficiencies during the verification period (R2) are 93.0% and 91.6% for
the cases of single input- single output and multiple inputs – single output
for Non-Parametric LPM respectively.
For the model in parametric form, (R2) is 99.73% during the
calibration period for single input case and 99.72% for multiple input.
While during the verification period of the parametric form the R2 are
99.76% and 99.75% for single and multiple input cases respectively.
The calibrated models in updating mode for six days lead time
provide efficiencies ranging from 99.5% to 96.5% for single inputsingle
output for non parametric case and 99.5% to 96.for multiple
input- single output for non parametric case. For the Parametric case the
model efficiencies ranging from 99.5% to 96.5% and 99.5% to 96.7 % for
single input and multiple inputs respectively.
It can be concluded that the flow at Khartoum can be forecasted to
an excellent degree using the flow at upstream station. It is also showed
that the effect of the Rahad and Dinder on flows at Khartoum is
negligible.
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Keywords
Use,Linear,Perturbation,Model,Real,Time,Flow,Forecasting,Blue Nile River,System