With respect to the necessity of comprehensive studies on drought and also high damages that caused by drought, this research studied the meteorological and hydrological droughts. In this study, Lighvan, Navroud and Seqez basins with different climates were selected. We used monthly data of stream flow, precipitation and evaporation from 1992 to 2016 for the study of drought phenomena. The aim at this study is to analyze the SPI and SPEI for determination of dry and wet meteorological periods and use of the SSI for the exploration of hydrological drought. The analysis of drought characteristics such as intensity and duration in three areas with different climates shows that the climate change has a major impact on the characteristics of the droughts. The relations between the duration and severity of drought have been more accurate in the period of 9 months in the Navroud watershed basin. The most significant events are SPI-9 with the duration of 57 months and the severity of 34.7, SPEI-9 with the duration of 34 months and the severity of 28.09 and SSI-9 with the duration of 41 months and the severity of 30.2. According to the obtained equations in different time periods, it was resulted that the highest accuracy was observed in the relationship between the meteorological and hydrological drought characteristics in the watershed basin of Seqez for a period of 6 months. The results show that in all three basins, the correlation between the meteorological and hydrological drought is significant at the level of 99%. Results show that hydrological and meteorological droughts in Navroud and Lighvan basins have a significant correlation with 48-month periods and in the Seqez basin with 12- and 24-month periods, and the relations between hydrological droughts and meteorological droughts were obtained using the nonlinear linear models (polynomial, exponential and logarithmic). The good R2 between the duration and severity of SPI-9 and SSI-9 is 0.8 and 0.92, respectively, for polynomial equations. The maximum determination coefficient of duration and severity of SPEI-9 and SSI-9 is 0.72 and 0.82, respectively, using polynomial equation. The application of several indices indicating different components of the hydrological cycle integrates many factors that affect and trigger droughts, and thus can help in providing a wider realization of the characteristics of droughts on various water sections.
River flow estimation using records of past time series is importance in water resources engineering and management and is required in hydrologic studies. In the past two decades, the approaches based on the artificial neural networks (ANN) were developed. River flow modeling is a non-linear process and highly affected by the inputs to the modeling. In this study, the best input combination of the models was identified using the Gamma test then MLP-ANN and hybrid multilayer perceptron (MLP-FFA) is used to forecast monthly river flow for a set of time intervals using observed data. The measurements from three gauge at Ajichay watershed, East Azerbaijani, were used to train and test the models approach for the period from January 2004 to July 2016. Calibration and validation were performed within the same period for MLP-ANN and MLP-FFA models after the preparation of the required data. Statistics, the root mean square error and determination coefficient, are used to verify outputs from MLP-ANN to MLP-FFA models. The results show that MLP-FFA model is satisfactory for monthly river flow simulation in study area.
The increase in negative effects of fossil fuels on the environment has forced many countries to use renewable energy sources, especially wind energy. Wind speed is the most important parameter of the wind energy. Probability distributions are useful for estimating wind speed because it is a random phenomenon. This study analyzes wind speed frequencies using wind data from Tabriz synoptic station in Iran. Four different distributions are fitted to the maximum annual wind from station, and parameters of the distributions are estimated using the method of maximum likelihood and the method of moments. Calculations are performed with Mathematica, a computer algebra system developed by Wolfram Research. The advantage of using this software is that the symbolic, numerical, and graphical computations can be combined and that all quantities can be accurately calculated; in particular, there is no need to resort to any approximate methods for the calculation of quantiles. There is a ready-to-use command for calculating quantiles from distributions that are built in Mathematica, while for other distributions they can be easily and accurately calculated by inverting the cumulative distribution functions or by solving nonlinear equations where the inversion is not possible. The best distribution is selected based on the root mean square error (RMSE), the coefficient of determination (R2), and the probability plot correlation coefficient (PPCC). The results indicate that the best performance can be obtained by the Gamma distribution
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