An investigation of trends in precipitation volume for the last three decades in different regions of Fars province, Iran

Under condition of climate changes as global warming, monitoring and detecting trend of precipitation volume is essential and will be useful for agricultural sections. Considering the fact that there were not enough research related to precipitation volume, this study aimed to determine trends in precipitation volume, monthly and annually in different regions of Fars province for the last three decades (33?years period; 1978–2010). Fars province is located in arid and semi-arid regions of Iran, and it plays an important role in agricultural production. Inverse distance weighting interpolation method was used to provide precipitation data for all regions. To analyze the trends of precipitation volume, Mann–Kendall test, Sen’s slope estimator, and 10-year moving average low-pass filter (within time series) were used. The negative trends were identified by the Sen’s slope estimator as well as Mann–Kendall test. However, all the trends were insignificant at the surveyed confidence level (95%). With regards to the application of 10-year moving average low-pass filter, a considerable decreasing trend was observed after around year 1994. Since one of the most important restrictions in agricultural development of the Fars province is lack of sufficient water resources, any changes onward to lack of sufficient precipitation impose impressive pressure and stress on valuable resources and subsequently agricultural production.     

近14 a也门降水异常的气候特征

利用1990-2003年也门7个测站降水资料，在分析近148也门降水季节变化特征的基础上，着重分析了也门夏季降水的年际变化特征。结果表明，也门降水异常的季节变化明显，异常在4-9月最大，尤其是7-9月，异常峰值所在月呈现出较明显的提早趋势；近148也门夏季降水呈现出增加的趋势，90年代末该趋势加大；近148也门夏季降水存在38和78左右的显著振荡周期。     

Comparison of artificial neural network and multivariate linear regression methods for estimation of daily soil temperature in an arid region

Soil temperature (T _S) strongly influences a wide range of biotic and abiotic processes. As an alternative to direct measurement, indirect determination of T _S from meteorological parameters has been the focus of attention of environmental researchers. The main purpose of this study was to estimate daily T _S at six depths (5, 10, 20, 30, 50 and 100?cm) by using a multilayer perceptron (MLP) artificial neural network (ANN) model and a multivariate linear regression (MLR) method in an arid region of Iran. Mean daily meteorological parameters including air temperature (T _a), solar radiation (R _S), relative humidity (RH) and precipitation (P) were used as input data to the ANN and MLR models. The model results of the MLR model were compared to those of ANN. The accuracy of the predictions was evaluated by the correlation coefficient (r), the root mean-square error (RMSE) and the mean absolute error (MAE) between the measured and predicted T _S values. The results showed that the ANN method forecasts were superior to the corresponding values obtained by the MLR model. The regression analysis indicated that T _a, RH, R _S and P were reasonably correlated with T _S at various depths, but the most effective parameters influencing T _S at different depths were T _a and RH.     

Consolidation of inelastic clays under rectangular cyclic loading

This paper presents a semi-analytical solution for one dimensional consolidation problem of inelastic clays under cyclic loading considering the effect of the change of the consolidation coefficient of the soil layer. Due to change of the consolidation coefficient, and time-dependant loading, Terzaghi's theory would not be applicable in cyclic conditions. In this research, a method based on the time variable exchange along with the superimposing rule is employed to overcome these shortcomings. Changes in the consolidation coefficient are applied in the solution by modifying the loading and unloading durations introducing a Virtual Time. Based on the superimposing rule a set of continuous static loads in specified times are used instead of the cyclic load in the transformed time space. Each full cycle of loading is replaced by a pair of static loads with different signs. Based on the Terzaghi's theory the pore-water pressure distribution and the degree of consolidation are calculated for each static load and the results are superimposed. A set of laboratory consolidation tests under cyclic load and numerical analysis are performed in order to verify the presented method. The numerical solution and laboratory tests results showed the accuracy of the presented method.     

Seismic evaluation of rocking structures through performance assessment and fragility analysis

Numerical studies have been conducted for low- and medium-rise rocking structures to investigate their efficiency as earthquake-resisting systems in comparison with conventional structures. Several non-linear time-history analyses have been performed to evaluate seismic performance of selected cases at desired ground shaking levels, based on key parameters such as total and flexural story drifts and residual deformations. The Far-field record set is selected as input ground motions and median peak values of key parameters are taken as best estimates of system response. In addition, in order to evaluate the probability of exceeding relevant damage states, analytical fragility curves have been developed based on the results of the incremental dynamic analysis procedure. Small exceedance probabilities and acceptable margins against collapse, together with minor associated damages in main structural members, can be considered as superior seismic performance for medium-rise rocking systems. Low-rise rocking systems could provide significant performance improvement over their conventional counterparts notwithstanding certain weaknesses in their seismic response.