Considering the importance of climate change and its effect on drought and the spatial and temporal extent of this phenomenon, the purpose of this study is to investigate the effect of climate change on the characteristics of the drought phenomenon. On the other hand, since drought has many aspects and studying different aspects of it for better decision making is necessary, multivariate analysis of climate and hydrology can lead to this meaning. Since the most trusted future scenarios in climate change studies are Atmosphere-Ocean General Circulation Models (AOGCMs), the output of these models has been the basis of climate change studies after spatial downscaling. A multi-model ensemble scenarios framework is used to improve the reliability of the climate change impact assessment by considering the main sources of uncertainties. The probabilistic bounded range multi-model ensemble method, which includes maximum number of GCMs, is used to project climate variables for the near future period. To consider extremes, the projection of future series has been carried out by climate generators to model extremes changes better. With the use of Monte Carlo in producing a large number of future series and considering the appropriate criteria, the best series has been chosen. For the definition and characterization of drought by indices, a comprehensive survey of data existence, index applicability and goals in water resources operation is needed. In this article and towards an applicable standardized index in the conjunctive use of water resources, nonparametric functions used to achieve integration and applicability. The status of water resources is calculated via integration of climatic water balance and available hydrologic water by multivariate nonparametric function to obtain integrated drought index (IDI). This index describes the status of hydrologic cycle in a region. In this study, the Zayandehrud River Basin is selected as the case to study climate change and drought. The most important river of centeral Iran passing thourgh it and its head water flows to Zayandehrud Dam. This dam has a key role in streamflow regulation for downstream demands in the basin. With the index tool to determine the condition of the subbasins, dam resource reoperation is followed by the purpose of the minimum drought intensity. Reoperation of dam was determined under three managemet method of hedging (Hdg), operation policy (OP) and all variable (AV) by using WEAP. Thess way of operation resulted in good and excellent demands supply reliability, minimum surface storage increase of 100 million cubic meters (MCM), storage increase of aquifers by 400 MCM at least, balanced storage or decrease of ground water depletion in comparison with the past. Baseline and Meta (supply and demand management) scenarios were defined for a 10 year period and an Adaptive Network-based Fuzzy Inference System (ANFIS) is used to generate synthetic natural flows considering outputs of climate change as inputs to mitigate drought intensity under climate change by regulating dam releases using beforementioned management methods. Demands supply is done in an excellent level. Negative reservoirs water balance reached 1100 MCM in baseline scenario. But better supply and storage is resulted in meta scenario when final surface storage is increased 200 MCM in volume and ground water sorage is balanced. Keywords: Multivariate Analysis, Climate Change, Meteorological Drought, Hydrological Drought, Integrated Drought Index (IDI), Nonparametric Functions, Reoperation.