Optimal Management of Surface Water Resources by WEAP: Considering Bayesian Approach under Climate Change Conditions

Document Type : Research Paper

Authors

1 M.Sc. Student, Dept. of Civil Engineering, Univ. of Qom

2 Assistant Professor, Department of Civil Engineering, University of Qom

Abstract

In this research, the effect of climate change phenomenon on optimal management of water resources in Khorramabad basin was investigated. The developed hybrid model based on the Bayesian approach was used for this purpose. So that initially the output of AOGCM models under the A2 emission scenario during the baseline period 1971-2000 and the future period 2040-2069 were downscaled and 100 examples of the downscaled monthly probability distribution function of the temperature and rainfall were produced based on the weighting method, using the Monte Carlo method and SIMLAB Software. The results indicated that the future long-term monthly average temperature would increase between 1.93 to 3.7 oC. The rainfall will increase in some months and decrease in another months. The rainfall variations in the basin under scenario A2 during the period 2040-2069 will be in the range of -17.29 and 1036.04 percent as compared to the baseline. Then, by introducing the future temperature and precipitation of the hybrid model into the calibrated and verified IHACRES, the future runoff will be achieved. The results showed a decrease in future runoff rates relative to baseline values. This reduction would be 4.33 % for the A2 scenario during the period 2040-2069. Finally, different scenarios were investigated by WEAP model and the amounts of water allocation at the baseline and climate change periods were compared. It was found that the seasons (such as summer) in which the water demand and consumption are increased, there would be an unmet demand (failure period) and this situation will be intensified in climate change condition. As the amount of annual unmet demand will be equal to 0.17×106 m3 and for the A2-2040-2069 scenario, it will be increased by 87% and equal to 1.33×106 m3 as compared to the baseline.

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References

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Iranian Journal of Soil and Water Research
Volume 50, Issue 2
March and April 2019
Pages 495-504

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