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In this paper, an integrated drought management scheme (IDMS) is developed for the Aharchay River Basin, located in northwestern Iran. This region is located in a semiarid region and has experienced considerable drought damage in recent years. Therefore, application of the proposed IDMS could greatly help to mitigate drought damage. The developed IDMS includes different tools and models needed for drought management. The utilized tools are classified into four groups, as follows: (1) data collection and validation, (2) rainfall-runoff prediction, (3) reservoir operation, and (4) drought analysis and monitoring. Future rainfall and runoff are projected using two computer models. Optimal reservoir operation is determined using a Bayesian stochastic genetic algorithm and Bayesian stochastic dynamic programming. These models are capable of incorporating new data of reservoir inflow and expert opinion in decision-making. For reservoir operation in drought conditions, hedging rules are also developed based on a mixed-integer nonlinear programming model. The hedging rules conserve water and adjust the operation in dry periods. Different drought indexes, including the standardized precipitation, surface water supply, and Palmer drought severity indexes, in addition to the hybrid drought index, which considers the socioeconomic aspects of drought, are used for drought evaluation. The socioeconomic aspects of drought are incorporated in drought management, utilizing an optimization model for land-use planning. The water pricing as a demand management tool for drought conditions is employed to measure drought impacts and usage efficiency of the limited available water resources. Based on drought characteristics in the study region, a drought warning scheme is also developed based on the drought monitoring data. To investigate the applicability of the proposed scheme, the future conditions of the basin hydroclimatic conditions are evaluated considering climate change impacts. To integrate these tools, a decision support system (DSS) package is developed, which includes different analytical modules needed for drought monitoring and management. The results show the significant value of integrated drought management schemes to identify and investigate the impacts of drought, and reduce the socioeconomic and environmental predicaments in the study region. [ABSTRACT FROM AUTHOR]

Flood is one of the most calamitous natural disasters that causes extensive property and life damages across the world. It however, could be a blessing due to its special natural water resources recharging value. By simulating the magnitude of probable floods considering the anthropogenic and natural effects and implementing contingency plans, their damages could be reduced. In this paper, the General Circulation Model (GCM) climate change scenarios are employed to simulate future floods. The GCM scenarios include simulation of climatic signals of the future considering green house gas emission forces. In this study a statistical downscaling model (SDSM) has been applied for rainfall downscaling to provide regional results from GCM outputs. Then, a rainfall-runoff model called HEC-HMS has been employed to estimate runoff in the region. The maximum simulated rainfall for each year that is of high enough potential to cause flood, is introduced into the rainfall-runoff model to simulate the plausible hydrograph of the flood. The proposed procedure is applied to the Kajoo River basin in South Baloochestan region, south-east of Iran. [ABSTRACT FROM AUTHOR]