mahboobeh moatamednia; ahmad nohegar; arash malekian; maryam saberi anari
Abstract
One of the most important of hydrological computing in ecosystem is estimation of the relationship between rainfall and runoff. So that investigation occurred processes in it and the estimate of important outputs such as flood and sediment is considered one the most important mission of a watershed project. ...
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One of the most important of hydrological computing in ecosystem is estimation of the relationship between rainfall and runoff. So that investigation occurred processes in it and the estimate of important outputs such as flood and sediment is considered one the most important mission of a watershed project. Because of variable spatial and temporal characteristics of incident in the water cycle and the nonlinear relationship and uncertainties, none of the statistical and conceptual models are able to be a better and capable model for that. But today using nonlinear networks as intelligent system for forecasting such complicated event can be efficient and effective in many problems of ecology. For this aim it is used variables such as precipitation, temperature, evartanspiration, relative humidity and discharges in daily scale over 42 years period and assessment 62 different suggested structures for surveying river flow in Amame representative watershed. For comparison it used Multi Layer Perceptoron (MLP) and Radial Basis Function (RBF).The results show that out of 6000 available models for estimation river flow model number 54 with 8-9-8-1 network structure and 8 types of input variable such as precipitation (Pt), precipitation with two lags (Pt-1 and Pt-2), temperature (Tt), evartanspiration (ETt), relative humidity (Rht), and discharge with two lags (Qt-1 and Qt-2) with Multi Layer Perceptoron method has the best function. The error of model was 0.03, 0.18 and 0.04 in training and 0.02, 0.14 and 0.02 for testing stage for MSE, RMSE and MAE, respectively.
majid kazemzadeh; arash malekian
Abstract
One of the most important dynamic ecosystems is river, awareness of spatio-temporal water quality changes of which is necessary. In this research, we studied the spatiotemporal water quality changes using three techniques of Cluster analysis (CA), Discriminant analysis (DA) and Principal Component analysis ...
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One of the most important dynamic ecosystems is river, awareness of spatio-temporal water quality changes of which is necessary. In this research, we studied the spatiotemporal water quality changes using three techniques of Cluster analysis (CA), Discriminant analysis (DA) and Principal Component analysis (PCA) in the Aji-Chai watershed over 1981-2010. Applying clustering, we identified three homogeneities clusters. Stations which were labeled in the first cluster showed that they are located in the upstream of Aji-Chi River. In comparison with other stations, these stations showed better water quality and the lowest changeability. DA methods significantly determined the three functions which described about 73.50, 20.30 and 3.40% of total variances. In the other word, in general three functions described the 97.20% of the total variances. Also the DA methods revealed the HCO-3, SAR, Na+, SO42- and Ca2+ were the most important parameters affecting upon water quality, based on which it's possible to seperate homogenous clusters. Finally, the results of PCA showed that the first two factors were the most important factors of water quality changes in the Aji-Chai River Watershed. These factors described about 78.75 and 14.71% of the variances, respectively.
mohammad moazami; Sadat Feiznia; Majid Khayyat Kholghi; Arash Malekian
Abstract
Hydraulic conductivity is an important parameter for controling water flow through porous media. Hence, accurate estimation of this parameter is important for evaluating flow exchange between surface water and groundwater. In this study, 12 empirical formulae based on grain-size and 4 infiltration equations ...
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Hydraulic conductivity is an important parameter for controling water flow through porous media. Hence, accurate estimation of this parameter is important for evaluating flow exchange between surface water and groundwater. In this study, 12 empirical formulae based on grain-size and 4 infiltration equations were used for estimating hydraulic conductivity on 3 sites in Jarmeh flood spreading system, Khuzestan Province. Results were evaluated using measured hydraulic conductivity by double rings infiltrometer. The results of the empirical formulae showed that 9 formulae were overestimated or underestimated and 3 formulae were close to measured values. Hazen formula gave the largest overestimation and Slitcher formula gave the largest underestimation and Shepherd formula is the best one. Generally, empirical formulae applicability requires the calibration of C coefficients. The results of the infiltration equations showed that all of 4 equations estimated hydraulic conductivity appropriately and there are no significant differences between them. Among the equations, Kastiakov and Green-Ampt were the best.
fatemeh maghsoud; Arash Malekian; Mohsen Mohseni Saravi; Omolbanin Bazrafshan
hossein mohammad asgari; shahram khalighi sigarodi; Parviz Irannejad; Hassan Ahmadi; Arash Malekian
Abstract
Aerosol impact on people health, social and economic activities, land and water ecosystems and meteorological parameter. The GOCART scheme was evaluated for simulating PM10 in this study. GOCART was run into WRF model as a host model. Reanalysis data from FNL for every 6 hour was used for initial conditions. ...
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Aerosol impact on people health, social and economic activities, land and water ecosystems and meteorological parameter. The GOCART scheme was evaluated for simulating PM10 in this study. GOCART was run into WRF model as a host model. Reanalysis data from FNL for every 6 hour was used for initial conditions. One domain and two nests were used to cover region from West Africa till East Asia, Iran and Khuzestan Province. Primary results shown that the model overestimate surface moisture and the results was weak for simulating PM10 ,so we modified surface moisture using welting point of soil texture in desert region for summer. In addition, erodibility index was defined using surface moisture and threshold wind velocity and coefficient of this index modified using Tir and Day PM10 data at 1387. Results of modified model were compared with observed data in environmental station in Ahwaz for one week from 25, 3,1388 till 31,3,1388. Statistical analyses shown that, GOCART has a good capability for simulating PM10.
Maryam Moradnezhadi; Arash Malekian; Meghdad Jourgholami; Ali Ghasemi
Abstract
24 hour precipitation distribution pattern and its relationship to short-term rainfall is an important issue in hydrology studies such as in flood simulation and in design of hydraulic structures. Accordingly, this study made an attempt to investigate the relationship between daily precipitation and ...
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24 hour precipitation distribution pattern and its relationship to short-term rainfall is an important issue in hydrology studies such as in flood simulation and in design of hydraulic structures. Accordingly, this study made an attempt to investigate the relationship between daily precipitation and hourly and minute precipitation using data from rain gauge station of Nowshahr in a coastal-forest region in north of Iran. The patterns of daily rainfall temporal distribution were examined using Pilgrim and Huff techniques. Finally, the obtained regional pattern using statistics were analyzed to evaluate absolute percent relative error, mean absolute error, root mean squared error and mean square error. Results of the relationship between 24 hour precipitation and 5 and 30 minutes and 1, 2, 3, 6, 9, 12, and 18 h rainfall showed that in all cases an exponential relationship can better explain this relationship than linear regression equations and logarithmic relations. Study of the rainfall temporal distribution pattern showed that in all extracted 24 hour events, the highest rainfall occurred in the lower quartile and in all rainfall events constant decrease in rainfall intensity occurred from the moment it started till it ended so that no fluctuation was observed in precipitation over time signaling that rainfall intensity would increase again. The results indicated that in similar areas, l SCS-type IA model could show reasonably better estimation in comparison with other models.
bahram choubin; SHahram KHalighi Sigaroodi; Arash Malekian
Abstract
Predicting climate trends, especially forecasting rainfall, provides managers of different fields withsuitable tools so that considering these predictions; they can devise future-state policies. At thisstudy, after selecting the most effective climate indices applying PCA method, the effects of largescaleclimate ...
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Predicting climate trends, especially forecasting rainfall, provides managers of different fields withsuitable tools so that considering these predictions; they can devise future-state policies. At thisstudy, after selecting the most effective climate indices applying PCA method, the effects of largescaleclimate signals in seasonal rainfall of basin Maharlu - Bakhtegan were investigated bothsimultaneously and by delay through statistical methods (Pearson correlation and cross-correlationcoefficient) and by applying stepwise regression model, regression equation for forecasting rainfallwas offered. The results showed that in cross-correlation between the time series of SPI (dependentvariable) at time (t) and climate signals (independent variable) at time (t-k), only SOI indexconcurrently has a significant relationship with rainfall, whereas, most of indices turned significantwith standardized precipitation index with different lag times. In season to season study of thesignals with the standard precipitation index using Pearson's correlation coefficient it was found thatclimate signals of spring and summer are not significantly correlated with SPI. Representationcoefficients (R2) and standardized regression effect (Beta) in stepwise regression model showed thatsimultaneous and with season to season delays signals (for example: SPI index of autumn with fourprevious seasons indexes) at method Pearson correlation have higher relationship with seasonalstandardized precipitation index than the cross-correlation in time (t-k), (which signals of allseasons given is delay together with than SPI of all seasons) show.
Arash Malekian; Mahsa Mirdashtvan
Abstract
Nowadays, with the increasing exploitation of groundwater resources, optimal use of these resources is more and more necessary. geostatistical methods can be used to assess and monitor the quality of groundwater resources. Hashtgerd Plain is the case study of this investigation. In this study firstly, ...
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Nowadays, with the increasing exploitation of groundwater resources, optimal use of these resources is more and more necessary. geostatistical methods can be used to assess and monitor the quality of groundwater resources. Hashtgerd Plain is the case study of this investigation. In this study firstly, by using data from qualitative data which were harvested from 41 Piezometric wells, different qualitative parameters were evaluated, then by using the geostatistical methods such as: Kriging, Co-kriging and IDW the best model for mapping for aquifer quality classification was selected. Results showed that most of the indicators are better simulated by Co-kriging method, based on mutual evaluation and RMSE. The parameters of SAR and EC were selected in order to determine the irrigation water quality parameters according to Wilcox diagram. Based on these two parameters by using ArcGIS v.10 software zoning maps were prepared. Results showed that 99% of the aquifer is classified in the category of good quality irrigation water (C2S1) and 1% level in the aquifer is classified as middle class (C3S1) based on Wilcox diagrams. The results of the study can be used in aquifer management and irrigation management in the agricultural purposes.
Khaled Osati; Ali Salajegheh; Mohammad Mahdavi; Paul Koeniger; Kamran Chapi; Arash Malekian
Abstract
Within the climate change debate and its probable impacts on water resources systems, design and operation of management plans based on the assumption of stationary hydrology may cause serious challenge to accurately predict future supplies. Therefore this case study is trying to assess trend in hydroclimatic ...
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Within the climate change debate and its probable impacts on water resources systems, design and operation of management plans based on the assumption of stationary hydrology may cause serious challenge to accurately predict future supplies. Therefore this case study is trying to assess trend in hydroclimatic variables of Karkheh Rivers upstream by applying modified Mann-Kendall trend test on long term daily time series of temperature, precipitation and discharge. Temperature variables are mostly showing meaningful increasing trends but observed changes in assessed stations were not spatially uniform for precipitation. Streamflow variables depict a decreasing trend, though more noticeable in base flows. Decreasing trend is meaningful for annual discharge median in Holailan at 90% confidence level. Total yearly precipitation, number of precipitation days and number of days with precipitation equal to, or greater than, 10 mm/d show the most correlation with stream flow variables. Comparing monthly discharge with temperature and precipitation variables in the studied gages indicates a time-delay in system response to inputs. This may related to snowmelt contributions or contributions of water into streams after passing through different hydrological pathways such as groundwater. Some parts of streamflow changes, especially about base flows, is not completely verified by precipitation changes and can be attributed to changes in temperature or another factors such as groundwater overexploitation.
Fatemeh Salari; Mehdi Ghorbani; Arash Malekian
Abstract
Water resources local governance can is one of the most influential collaborative approach in the water resources management. Social monitoring of local stakeholders plays an important role in planning, resources management and water efficient governance. Therefore to achieve this goal, social network ...
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Water resources local governance can is one of the most influential collaborative approach in the water resources management. Social monitoring of local stakeholders plays an important role in planning, resources management and water efficient governance. Therefore to achieve this goal, social network analysis has been considered as an approach of analysis of the relationship among local stakeholders, in order to sustainable management of water resources. This study aims to social monitoring in local stakeholders network using social network analysis in Razin watershed located in Kermanshah province. This work based on social network analysis approach as method with emphasis on trust and collaboration ties and quantitative and mathematical indicators on the macro-level of local stakeholders network (Density, Centralization, Reciprocity and Geodesic Distances). The results showed that the level of social capital in the village has been measured weak. The degree of reciprocity indicator for trust and collaboration ties and the stability of network is weak. Also the level of correlation between trust and collaboration is 37 percent. The results of the mean geodesic distance on the basis of trust and collaboration ties showed that circulation velocity of trust and collaboration is moderate to low. Can be concluded on the basis of the results, weak social capital and low union between stakeholders, makes reduce circulation of trust and collaboration and therefore local governance of water resources in the region is challenged
ali shahbazi; Shahram khaliqi sygarodi; Arash Malekian; Ali Salajegheh
Abstract
In order to decrease the risks associated with the management of urban watersheds, the use of proper methods is an essential task to estimate the runoff with a high degree of confidence. Time of concentration is one of factors that impacts on peak discharge and runoff volume. The objective of this study ...
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In order to decrease the risks associated with the management of urban watersheds, the use of proper methods is an essential task to estimate the runoff with a high degree of confidence. Time of concentration is one of factors that impacts on peak discharge and runoff volume. The objective of this study is to select the best method among the empirical formulas for estimating the time of concentration. In this study, for determination of actual time of concentration, the field method based on measuring the travel time by using floating-object method was employed. To select the best empirical formula of the time of concentration, the statistical criteria including percentage Relative Error (RE), Root Mean square error (RMSE), Average percentage Relative Error (RME), Nash - Sutcliffe criteria (NS) and determination coefficient were used. Then, differences among the estimations obtained from empirical equations were compared with the actual values. The results of this study based on comparison of the relative error in each interval showed that in the reach No. 2, empirical formulas of California, Chow, Carter and Federal Aviation, with percentage error of 2.7, 2.9, 4.4 and 4.4 have showed the best estimation, respectively. The equation proposed by Kirby with percentage error of 1 in the reach No. 3, the equation of Ventura with percentage error 8.5 in the reach No. 9 and the equation of rational hydrograph with percentage error 4.8 in the reach No. 10 have showed the best estimates. Therefore, it is recommended to use the empirical formula that has the lowest percentage of error for areas with features similar to the studied reaches. In general, the results show that only rational hydrograph method in all of the reaches has the lowest error and then provides the most proper estimates compared than others.
Arash Malekian; Mahrou Dehbozorgi; Amir Houshang Ehsani; Amir Reza Keshtkar
Abstract
Consecutive droughts in Sistan and Baloochestan province cause water resources restriction and this isa very significant problem for this region. In this study, in order to forecast the drought cycle in 9climatological stations in the province, we used Artificial Neural Networks. The input data wereaverage ...
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Consecutive droughts in Sistan and Baloochestan province cause water resources restriction and this isa very significant problem for this region. In this study, in order to forecast the drought cycle in 9climatological stations in the province, we used Artificial Neural Networks. The input data wereaverage of annual rainfall data in all stations and also deciles precipitation index, which the first 30years from 1971 to 2000 used for training the network and the last 8 years from 2001 to 2008 forsimulating it. The network consists of Multilayer Perceptron (MLP) and Back Propagation Algorithm(BP) and also sigmoid transfer function. Number of Neurons in hidden layer was 10 with 1-10-1structure and was calculated based on the lowest RMSE. Then drought prediction was done in neuralnetwork with the trained algorithm and without using actual and observed data in 2009 to 2012.Results showed that, the network was able to simulate and forecast DPI index with 97% regressionand average RMSE error less than 5%. According to drought indices, results showed that the droughtwill have an increasing trend in all stations in this region in 2009 to 2011. Therefore, by using thismethod, drought can be predicted in later years without any need to have actual meteorological dataand also can be used in water resources management, drought management and climate changes.
Morteza Dehghani; Hosein Ghasemi; Arash Malekian
Abstract
Nowadays, watershed management practices are undertaken based on selective criteria and/or a specific purpose such as a decrease in flood risk, soil erosion and the like. In this respect,fuzzy logic has the ability to manage a wide range of options for decision making. This researchaimed to use the fuzzy ...
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Nowadays, watershed management practices are undertaken based on selective criteria and/or a specific purpose such as a decrease in flood risk, soil erosion and the like. In this respect,fuzzy logic has the ability to manage a wide range of options for decision making. This researchaimed to use the fuzzy logic theory to priorities watershed management practices consideringtime and budget constraints in catchments with high sediment production and flood risk. Thisresearch was carried out in the Foorg watershed of Darmian town with an area of 11137 ha. Allparameters related to soil erosion and flood risk were determined using the standard methods.Fuzzy score for each mentioned factor was then determined. Finally watershed managementpractices using the fuzzy theory and GIS were prioritized.
