عنوان مقاله [English]
For water resources management in dry areas that rely on dams and surface water storage, the use of Drought Early Warning System (DEWS) with the hydrological indicator that capability to deal with the drought and water shortage are very useful and it also prevents the reducing of water reserves.In this research, it is tried to develop a drought early warning system, relying on effective component in reservoir management. The developed drought early warning system consists of five essential elements, namely, (1) Drought monitoring, (2) Prediction and uncertainty analysis of water consumption in the future, (3) Calculation of an index for drought alert (4) Risk and uncertainty analysis and (5) Policy Making for Drought Management that used in Zayandeh-Rud dam. To design this system, at the first stage the inflow was predicted by using Artificial Neural Networks (ANNS) in a period of 6-months with considering the relevant uncertainty and difference of probability levels. Also drought conditions were categorized in five levels by using of historical data (1983-2005) of reservoir water storage and using Self Organizing Feature Map (SOFM). The levels arenone, slightly severe, fairly severe, severe and very severe. Then a drought alert index was calculated with current drought monitoring conditions of reservoir and water consumption measuring in a 6-month forecast period. Based on the results of calculated index, warning of different levels of green status (normal condition) to red status (severe condition) with relevant uncertainty and different confidence levels was determined. In the next step, a nonlinear optimization model was used to determine optimum reduction of demands for maximum reservoir incomes. Finally, the performance of this system and its role in reducing the severity of the drought has been studied in the period of 1998-2001 as a severe drought in the study region.Results showed that the developed DEWS can alert droughts with overall accuracy of about 75%[r1] . Furthermore, it can determine the optimal water release in different management scenarios. So this system can be an effective tool for water resources management in areas that rely on dams.
[r1]It is mentioned as 75% in text. Which one is true?