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S. Shaeri Karimi M. Yasi S. Eslamian 《International Journal of Environmental Science and Technology》2012,9(3):549-558
Environmental flow assessment and maintenance are relatively new practices, especially in developing countries. This paper describes the desktop assessment of environmental flows in a river with insufficient data on ecological features and values. In this study, the potential environmental flows in a typical river reach of the Shahr Chai River in Iran were investigated using a newly developed hydrological method (flow duration curve (FDC) shifting) and Global Environmental Flow Calculator software. This approach uses monthly flow data to develop an environmental FDC and to generate flow requirements corresponding to different features of the river ecosystem. Results were compared with those from four alternative hydrological methods: the desktop reserve model (DRM), Tennant, low-flow index, and flow duration curve analysis (FDCA). Comparisons of these methods indicated that to maintain the basic function of the river ecosystem, the river flows should be managed within an acceptable environmental level. The predictions from the Tennant method and the low-flow index (7-day low flow with a 10-year return period), and from the FDCA (for flows exceeding 90?% of occurrence) are not as reliable as those from the FDC shifting technique and DRM. Comparative results indicate that a minimum flow rate of 1.2?m3/s (equivalent to 23?% of the natural mean annual runoff, or flow with 80?% occurrence depicted from the FDC) is required for the Shahr Chai River to run toward the internationally recognized Urmia Lake in Iran. 相似文献
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Ahmad Nicknam Reza Abbasnia Yasser Eslamian Mohsen Bozorgnasab Ehsan Adeli Mosabbeb 《Journal of Earth System Science》2010,119(3):383-396
We determine the source parameters for 2003 (Mw 6.5) Bam, Iran, earthquake using an empirical Green’s function summation approach
to model ground motions recorded by two strong motion stations at approximately 45 km epicentral distance. We introduce a
genetic algorithm technique to optimize the fit to observed elastic response spectra. The proposed genetic algorithm technique
allows us to explore the sensitivity of the results to multiple source parameters, including hypocenter location, focal mechanism
(Strike and Dip), P-wave velocity in depth, fault dimension and rupture and healing velocities. 相似文献
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Density currents are caused by a difference in density,though low,of an entering fluid with the ambient fluid.This type of current is two-phased and found on riverbeds or in reservoirs behind dams,and is nonlinear in nature,complex,and sensitive to initial conditions.Fractal geometry is used as a powerful tool for studying complex natural phenomena.Using experimental studies and changes in inlet current conditions,the fractal and multi-fractal analyses of the interface between the density current and the ambient fluid were done.In addition,a search was made to find a possible connection between the nonlinear patterns.According to the results,with an increase in the inlet discharge and inlet density of the current the fractal dimension decreased.Further,the smaller the range of the singularity spectrum diagram was,i.e.,the more it was less than 0.34,the lower the system's tendency was to be multi-fractal,and the system sensitive to large local changes.In the interface between the density current and the ambient fluid,using the fractal dimension-based Richardson number could improve experimental data by 12.4%.Moreover,with an increase in the Richardson number,the Reynolds number of the current decreased.Further,upon considering the fractal dimension,the Reynolds number improved by 23%and a good correlation with a coefficient of determination of 0.76. 相似文献
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Gaur Shishir Mishra Aryan Gupta Anurag Jain Arihant Dave Apurve Eslamian Saied Dwivedi S. B. Graillot Didier 《Water Resources》2021,48(4):565-575
Water Resources - Predicting the Suspended Sediment Load (SSL) of the river is a very significant and challenging task. Being a non-linearity in the SSL data, it requires a non-linear method to get... 相似文献
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Hasanzadeh Saray Marzieh Eslamian Seyed Saeid Kl&#;ve Bj&#;rn Gohari Alireza 《Theoretical and Applied Climatology》2020,140(1):115-127
Theoretical and Applied Climatology - This study examined the effect of different attributes on regionalization of potential evapotranspiration (ETp) in Urmia Lake Basin (ULB), Iran, using the... 相似文献
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ABSTRACTThe trends in hydrological and climatic time series data of Urmia Lake basin in Iran were examined using the four different versions of the Mann-Kendall (MK) approach: (i) the original MK test; (ii) the MK test considering the effect of lag-1 autocorrelation; (iii) the MK test considering the effect of all autocorrelation or sample size; and (iv) the MK test considering the Hurst coefficient. Identification of hydrological and climatic data trends was carried out at monthly and annual time scales for 25 temperature, 35 precipitation and 35 streamflow gauging stations selected from the Urmia Lake basin. Mann-Kendall and Pearson tests were also applied to explore the relationships between temperature, precipitation and streamflow trends. The results show statistically significant upward and downward trends in the annual and monthly hydrological and climatic variables. The upward trends in temperature, unlike streamflow, are much more pronounced than the downward trends, but for precipitation the behaviour of trend is different on monthly and annual time scales. Furthermore, the trend results were affected by the different approaches. Specifically, the number of stations showing trends in hydrological and climatic variables decreased significantly (up to 50%) when the fourth test was considered instead of the first and the absolute value of the Z statistic for most of the time series was reduced. The results of correlations between streamflow and climatic variables showed that the streamflow in Urmia Lake basin is more sensitive to changes in temperature than those of precipitation. The observed decreases in streamflow and increases in temperature in the Urmia Lake basin in recent decades may thus have serious implications for water resources management under the warming climate with the expected population growth and increased freshwater consumption in this region.
Editor Z. W. Kundzewicz; Associate editor Q. Zhang 相似文献
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Neda?Yousefi Saeed?Reza?KhodashenasEmail author Saeid?Eslamian Zahra?Askari 《Arabian Journal of Geosciences》2016,9(4):321
Predicting behavior and the geometry of the channels and alluvial rivers in which the erosion and sediment transport are in equilibrium is one of the most important topics in river engineering. Various researchers have proposed empirical equations to estimate stable river width (W). In this research, empirical equations were examined and tested with a comprehensive available data set consisting of 1644 points collected from 29 stable rivers in various parts of the world. The data set covers a wide range of flow conditions, river geometry, and bed sediments. This data set is classified in two groups (W < 600 m and W ≥ 600 m) for presenting the new models. The new linear and nonlinear multivariable equations were fitted to these two groups, and the best models were selected by preliminary tests and diagnostic determined for each group. The determination coefficient of these models ranged from 0.87 to 0.96. The results show that the models presented in this paper are more accurate with respect to the previously presented models. In the second part, “Artificial neural networks,” perceptron was used and a new methodology for estimating stable channel width was developed. Comparison of the statistical methods presented in this paper and the results of perceptron neural network revealed preferential recent method. 相似文献
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Regional flood frequency analysis (RFFA) was carried out on data for 55 hydrometric stations in Namak Lake basin, Iran, for the period 1992–2012. Flood discharge of specific return periods was computed based on the log Pearson Type III distribution, selected as the best regional distribution. Independent variables, including physiographic, meteorological, geological and land-use variables, were derived and, using three strategies – gamma test (GT), GT plus classification and expert opinion – the best input combination was selected. To select the best technique for regionalization, support vector regression (SVR), adaptive neuro-fuzzy inference system (ANFIS), artificial neural network (ANN) and nonlinear regression (NLR) techniques were applied to predict peak flood discharge for 2-, 5-, 10-, 25-, 50- and 100-year return periods. The GT + ANFIS and GT + SVR models gave better performance than the ANN and NLR models in the RFFA. The results of the input variable selection showed that the GT technique improved the model performance. 相似文献
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