Streamflow drought severity analysis by percent of normal index (PNI) in northwest Iran

The streamflow drought is the most important type of drought due to the high dependence of many activities on surface water resources. The streamflow drought severity was identified by the percent of normal index (PNI) in the western basins of the Lake Urmia located in northwest Iran. The streamflow records were obtained from 14 hydrometric stations for the period October 1975–September 2009. The temporal trends of the streamflow drought severity were detected by the parametric Student’s t test and the nonparametric Mann–Kendall and Sen’s tests. The worst streamflow droughts at almost all the stations occurred in 1999–2000 and 2000–2001. The streamflow drought severity based on the PNI increased during the last 34 years. The results also indicated that the temporal dependency of time series had a dominant role in detecting trend by the parametric Student’s t test.     

Strong ground motion simulation of the 2003 Bam, Iran, earthquake using the empirical Green’s function method

The 2003 Bam, Iran, earthquake caused catastrophic damage to the city of Bam and neighboring villages. Given its magnitude (M _w ) of 6.5, the damage was remarkably large. Large-amplitude ground motions were recorded at the Bam accelerograph station in the center of Bam city by the Building and Housing Research Center (BHRC) of Iran. We simulated the Bam earthquake acceleration records at three BHRC strong-motion stations—Bam, Abaraq, and Mohammad-Abad—by the empirical Green’s function method. Three aftershocks were used as empirical Green’s functions. The frequency range of the empirical Green’s function simulations was 0.5–10 Hz. The size of the strong motion generation area of the mainshock was estimated to be 11 km in length by 7 km in width. To estimate the parameters of the strong motion generation area, we used 1D and 2D velocity structures across the fault and a combined source model. The empirical Green’s function method using a combination of aftershocks produced a source model that reproduced ground motions with the best fit to the observed waveforms. This may be attributed to the existence of two distinct rupture mechanisms in the strong motion generation area. We found that the rupture starting point for which the simulated waveforms best fit the observed ones was near the center of the strong motion generation area, which reproduced near-source ground motions in a broadband frequency range. The estimated strong motion generation area could explain the observed damaging ground motion at the Bam station. This suggests that estimating the source characteristics of the Bam earthquake is very important in understanding the causes of the earthquake damage.     

Modelling the effects of porous media deformation on the propagation of water-table waves in a sandy unconfined aquifer

This paper examines the influence of porous media deformation on water-table wave dispersion in an unconfined aquifer using a numerical model which couples Richards’ equation to the poro-elastic model. The study was motivated by the findings of Shoushtari et al. (J Hydrol 533:412–440, 2016) who were unable to reproduce the observed wave dispersion in their sand flume data with either numerical Richards’ equation models (assuming rigid porous media) or existing analytic solutions. The water-table wave dispersion is quantified via the complex wave number extracted from the predicted amplitude and phase profiles. A sensitivity analysis was performed to establish the influence of the main parameters in the poro-elastic model, namely Young’s modulus (E) and Poisson’s ratio (ν). For a short oscillation period (T?=?16.4 s), the phase lag increase rate (k _i) is sensitive to the chosen values of E and ν, demonstrating an inverse relationship with both parameters. Changes in the amplitude decay rate (k _r), however, were negligible. For a longer oscillation period (T?=?908.6 s), variations in the values of E and ν resulted in only small changes in both k _r and k _i. In both the short and long period cases, the poro-elastic model is unable to reproduce the observed wave dispersion in the existing laboratory data. Hence porous media deformation cannot explain the additional energy dissipation in the laboratory data. Shoushtari SMH, Cartwright N, Perrochet P, Nielsen P (2016) The effects of oscillation period on groundwater wave dispersion in a sandy unconfined aquifer: sand flume experiments and modelling. J Hydrol 533:412–440.     

MLP-based drought forecasting in different climatic regions

Water resources management is a complex task and is further compounded by droughts. This study applies a multilayer perceptron network optimized using Levenberg–Marquardt (MLP) training algorithm with a tangent sigmoid activation function to forecast quantitative values of standardized precipitation index (SPI) of drought at five synoptic stations in Iran. The study stations are located in different climatic regions based on De Martonne aridity index. In this study, running series of total precipitation corresponding to 3, 6, 9, 12, and 24?months were used and the corresponding SPIs were calculated: SPI3, SPI6, SPI9, SPI12, and SPI24. The multilayer perceptrons (MLPs) for SPIs with the 1-month lead time forecasting, were tested and validated. Four different input vectors were considered during network development. In the first model, MLP constructed by importing antecedent SPI with 1-, 2-, 3-, and 4-month time lags and antecedent precipitation with 1- and 2-month time lags (MLP1). Addition of antecedent North Atlantic Oscillation or antecedent Southern Oscillation Index with 1-month time lag or both of them to MLP1 led to MLP2, MLP3, and MLP4, respectively. The MLP models were evaluated using the root mean square error (RMSE) and the coefficient of determination (R ²). The results showed that MLP4 had a higher prediction efficiency than the other MLPs. The more satisfactory results of RMSE and R ² values of MLP4 for 1-month lead time for validation phase were equal to 0.35 and 0.92, respectively. Also, results indicated that MLPs can forecast SPI24 and SPI12 more accurately than the other SPIs.     

Modelling flow and sediment trapping upstream and within grass buffer strips

Grass buffer strips impact the hydrology of flow and consequently the fate of sediment. A complex process‐based model is developed to predict flow characteristics as well as sediment deposition and transport upstream, and within grass strips. The model is capable of estimating the proportion and amount of different sediment particle size classes in the outflow. The modified Green–Ampt equation was used to simulate infiltration. Gradually varied flow and kinematic wave approximation were used to model flow characteristics upstream and within grass strips. The GUEST model approach has been modified in order to use its basic approaches in sediment transport module in grass strips. Model predictions agree well with the results of two sets of controlled experiments. The bias, coefficient of model efficiency and the root mean squared error of the modelled efficiency of grass strips in reducing sediment concentration were 0.93–0.99, 0.58–0.99 and 8.9–12.7, respectively. The sensitivity analysis showed that the initial soil moisture and flow rate are the most sensitive parameters in predicting runoff loss. Increasing the slope steepness and flow rate dramatically decreases the efficiency of grass strips in reducing sediment concentration and mass. Copyright © 2015 John Wiley & Sons, Ltd.     

A dynamic prediction model for time-to-peak

A simplified empirical equation is developed for widespread prediction of dynamic catchment response time. This model allows for time-to-peak prediction to evolve from static, lumped models, thereby providing a single value for any storm within a given catchment, using a single set of input parameters, that can be applied to a dynamic model, thus accounting for the variability between storm sizes and catchment moisture conditions. These dynamic prediction methods are translated to North America for the first time. This allows the concepts and prediction methods for catchment response time prediction previously established for the United Kingdom (UK), to be translated to a simple empirical equation for use in North America, through the use of selected study areas in Canada and the United States. This reconfigured model is statistically successful in both the UK and North America and allows for a straightforward implementation of dynamic time-to-peak prediction. Further, the reconfigured model introduces the use of a runoff coefficient (R_c) to encompass historical catchment wetness, increasing the ease of incorporating antecedent moisture condition into predictions.     

Estimating design probable maximum precipitation using multifractal methods and comparison with statistical and synoptically methods case study: Basin of Bakhtiari Dam

The probable maximum precipitation which is defined as the maximum precipitation at a particular location for a given duration is used as a design criterion for major dams. The assumptions of deterministic consideration and an upper limit to probable maximum precipitation have been repeatedly criticized by hydrologists. Nowadays, multifractal method which strongly contains physical bases can be used to improve the probable maximum precipitation. In this research, the universal multifractal model was used to estimate the design probable maximum precipitation for specified exceedence probability in basin of Bakhtiari Dam, southwest Iran, and its results were compared with statistical and synoptically methods. The results revealed that the return period of statistical and synoptically probable maximum precipitation, estimated for the different durations, are about 10⁹ and 10³–10⁴ years, respectively; also, over periods ranging from 1 to 7 days, the ratios of design probable maximum precipitations, estimated based on multifractal method for return period of 10³–10⁹ years, to statistical and synoptically probable maximum precipitation estimates ranged from 0.61 to 1.1 and 1.33 to 2.37, respectively. These results indicated that the multifractal method can be used to reasonably estimate the probable maximum precipitation.     

完整岩石在不同尺度上的屈服

对完整岩石力学机制的研究有助于更好地理解与屈服有关的应力-应变关系。屈服准则研究方法包括基于实验数据分析和基于微观力学的研究。屈服数学理论的研究目标是对应力和应变关系的理论描述和对弹塑性界限的识别。本文主要研究完整岩石在不同尺度上的屈服。从Weibull理论可知,岩石强度随尺度增大而减少,这已经通过单轴压缩强度（UCS）的Hoek-Brown方程得到证实。然而,围压能改变岩石强度及屈服。因此,本文利用直径为50mm和96mm的圆柱形砂岩样品在不同围压作用下的压缩实验来研究不同尺度下的岩石屈服,从实验中提取不同尺度下的屈服初始点并描述屈服面,最终给出简单数学形式的屈服准则。     

The survey of climatic drought trend in Iran

Drought is one of the most important natural hazards in Iran. Therefore, drought monitoring has become a point of concern for most of the researchers. In the present study, the changes and trend of drought was surveyed, under the current global climate changes, by non parametric Mann–Kendall statistical test for 42 synoptic stations at different places of Iran. Standardized Precipitation Index (SPI) was calculated to recognize the drought condition at different time scales (3, 6, 9, 12, 18 and 24 months’ time series) for analyzing the drought trend in the recent 30 years. The obtained results have indicated a significant negative trend of drought in many parts of Iran, especially the South-East, West and South-West regions of the country. According to the results, although some parts of Iran such as North (around the Caspian Sea) and Northeast show no significant trend but in other parts of country, the severity of drought has increased during the last 30 years.