This study analyzed the annual streamflow of Karkheh River in Karkheh river basin in the west of Iran for flood forecasting using stochastic models. For this purpose, we collected annual stremflow (peak and maximum discharge) during the period from 1958 to 2015 in Jelogir Majin hydrometric station (upstream of Karkheh dam reservoir). A time series model (stochastic model or ARIMA) has three stages consists of: model identification, parameter estimation and diagnostic check. Model identification was done by visual inspection on the Autocorrelation and Partial Autocorrelation Function. Three types of ARIMA(p,d,q) models (0,1,1), (1,1,1) and (4,1,1) suggested for the studied series. The suggested model parameters were computed using the Maximum Likelihood (ML), Conditional Least Square (CLS) and Unconditional Least Square (ULS) methods. In model verification, the chosen criterion for model parsimony was the Akaike Information Criteria (AIC) and the diagnostic checks include independence of residuals. The best ARIMA model for this series was (4,1,1), with their AIC values of 88.9 and 77.8 for annual peak and maximum streamflow respectively. Forecast series up to a lead time of ten years future (2006 to 2015) were generated using the accepted ARIMA models. Model accuracy was checked by comparing the predicted and observation series by coefficient of determination (R2). Results show that the ARIMA model was adequate for the flood analysis in Karkheh River and the forecast of the series in short time at future.

This study presents a new hybrid framework based on the multi-criteria decision making in order to rank the potential site layout locations by consideration of the cost and safety criteria in the Mehr Construction Project in Tehran, Iran. To this end, all of the criteria in selecting suitable potential locations are extracted from the research literature and the most effective ones, which are matched with existing conditions in Tehran are considered based on the opinion of experts,. Then, the proper locations for site layout are determined as the potential alternatives and ranked by experts based on the structure. According to the data collected from the questionnaires, the weights of the selected criteria are calculated using Best Worst Method (BWM) and the final ranking of the locations is performed using two Gray Relational Analysis and VIKOR methods. The computational results indicate that both VIKOR and GRA methods yield the same ranking. However, a method with higher reliability should be used to select the best potential location of construction site layout. Therefore, the sensitivity analysis of final outputs on the parameters existing in VIKOR and GRA methods is used in order to rank the alternatives and select the best approach. According to the computational results, the GRA method provides higher robustness compared with the VIKOR method. Accordingly, the ranking obtained from the GRA method is employed as the final solution in implementing the case study. .

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Stochastic models (time series models) have been proposed as one technique to generate scenarios of future climate change. Precipitation, temperature and evaporation are among the main indicators in climate study. The goal of this study is the simulation and modeling of climatic parameters such as annual precipitation, temperature and evaporation using stochastic methods (time series analysis). The 40-year data of precipitation and 37-year data of temperature and evaporation at Jelogir Majin station (upstream of Karkheh dam reservoir) in western of Iran has been used in this study and based on ARIMA model, The auto-correlation and partial auto-correlation methods, assessment of parameters and types of model, the suitable models to forecast annual precipitation, temperature and evaporation were obtained. After model validation and evaluation, the Predicting was made for the ten future years (2006 to 2015). In view of the Predicting made, the precipitation amounts will be decreased than recent years. As regards the mean of annual temperature and evaporation, the findings of the Predicting show an increase in temperature and evaporation.

It is obvious that providing drinking water in cities, especially in metropolises such as Tehran, as a political-socialeconomic center of the country is important. During the last decades, climatic changes, the decrease of raining, the increase of water harvesting from groundwater as well as the increase of population have intensified the importance of water in Tehran. Therefore, every change from water consumption to collecting, purifying and storing drinking water in the city reservoirs is highly critical. In the present study, the causes of delay in such projects have been determined based on experts' opinions about several concrete implemented reservoirs obtained by questionnaire and the related literature. Given to three classes pertained to such projects (employer, consultant and contractor), an initial questionnaire was provided to poll the experts' opinions and distributed among the sample of the study. In this regard, 45 Likert-scale questionnaires were equally distributed among three population; after gathering, the items with higher mean scores were selected for the main questionnaire (totally, 17 items). Using AHP method, the most important factors were identified and ranked through Expert choice Software. As the research findings revealed, failure of employer to pay to contractor timely, failure to obtaining the necessary permissions by employer before noticing to contactor to proceed, and uncertainty and buying project site by employer are the most important factors respectively.