HR: 1340h
AN: H43A-0959 [Abstracts]
TI: Uncertainty Assessment in Long-lead Drought Prediction Using GCMs Outputs
AU: * Karamouz, M
EM: Karampuz@ut.ac.ir
AF: School of Civil Engineering University of Tehran, Enqelab Ave., Tehran, 113654563, Iran
(Islamic Republic of)
AU: Nazif, S
EM: saranazif@yahoo.com
AF: School of Civil Engineering University of Tehran, Enqelab Ave., Tehran, 113654563, Iran
(Islamic Republic of)
AU: Rasouli, K
EM: Kabir.rasouli@gmail.com
AF: Engineering Department, Islamic Azad University- Science & Research branch, Poonak
sq., Tehran, 176571378, Iran (Islamic Republic of)
AB:
Drought is one of the major hazards that could cause excessive damages especially in arid and semiarid
regions. A study by international panel on climate changes (IPCC) showed that the frequency of drought is
increasing because of climate change impact. In this study certain scenarios on climate change that are included
in the outputs of the GCM models, are considered in order to evaluate climate change effects on the
characteristics of future drought events. For this purpose, different indices that reflect different aspects of drought
impacts are considered. These indices consider precipitation, water supply and soil moisture variations in the
drought periods. These indices are integrated through a hybrid index that is calculated based on drought
damages using Probabilistic Neural Network (PNN). The drought characteristics are then estimated using the
proposed algorithm over a one hundred year time horizon that the GCM outputs are available. For evaluation of
the uncertainties in the long lead drought prediction, one hundred ensemble data are generated using Statistical
Down Scaling Model (SDSM). Uncertainty analysis has been done by fitting probability distribution function to the
ensemble results of the drought characteristics prediction. A small basin located at the northwestern part of Iran
is used as the case study. The results of this study can be utilized by decision makers in the region to decide on
future development plans of the basin and for developing drought emergency plans.
DE: 1616 Climate variability (1635, 3305, 3309, 4215, 4513)
DE: 3275 Uncertainty quantification (1873)
SC: Hydrology [H]
MN: 2007 Fall Meeting