Shiva Saffarinia; Hirad Abghari; Mahdi Erfanian
Abstract
All water quality indicators have a definite answer for the water quality of the stations. The use of fuzzy inference system has eliminated the limitation of the definiteness of the answers and the lack of consideration of the parameters of water quality determination from the standards. In this paper, ...
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All water quality indicators have a definite answer for the water quality of the stations. The use of fuzzy inference system has eliminated the limitation of the definiteness of the answers and the lack of consideration of the parameters of water quality determination from the standards. In this paper, data from 1990-89 in 12 stations in the upper and lower range, Mahabad Reservoir Dam, and seven parameters of turbidity, electrical conductivity, chemical oxygen requirement, biochemical required oxygen, total hardness, ammonium and phosphate, Used. All data were received from the Regional Water Authority of West Azerbaijan Province. MATLAB software has been used to perform analyzes. The Mamdani model has been used for water quality classification and triangular membership functions for model inputs and outputs. The input membership functions are three and the output membership functions are five. From the World Health Organization standard and existing standards for the quality of surface water resources in Iran to determine the desired, acceptable and unacceptable range for input parameters as well as the operator and to define the rules of use and with the help of fuzzy inference system of water quality index (FWQI) development given. The SW9 station is the most polluted and the SW6 station is the least polluted. The results show that the fuzzy index is appropriate in estimating surface water quality in the study area.
mohsen kazemi; sadegh naji; Sadat Feiznia; Hassan Khosravi
Abstract
One of the strategies to achieve sustainable management of lakes and wetlands is change detection of lakes, wetlands and their surrounding landuses during the specific time periods. In this research, the satellite images from 1381 to 1394 applying geometric and atmospheric corrections were used in order ...
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One of the strategies to achieve sustainable management of lakes and wetlands is change detection of lakes, wetlands and their surrounding landuses during the specific time periods. In this research, the satellite images from 1381 to 1394 applying geometric and atmospheric corrections were used in order to monitor the changes of the Maharloo Lake level and its surrounding lands Image subtraction techniques, the principle component analysis (PCA) and fuzzy logic were used for providing the maps of landuse changes and drastically changes. The obtained results of Maharloo landuse changes showed that the lake water level has decreased 78 percent during 1381 to 1394. Reducing the lake water level, the landuses of bare and saline lands increased 46 and 58 percent respectively. The obtained results of the drastic changes showed that 82% of the changes have had the intensity between 50-100 percent. The most intensity of the changes with reduction of 22 percent was related to water body of Maharloo. The reduction of Maharlu Lake water level have different consequences therefore management planning is necessary to prevent its ecosystem degradation and Risks of reduced water levels in recent years.
ghobad rostamizad; ali salageghe; ali akbar nazari samani; jamal ghodoosi
Abstract
One of the types of water erosion and land degradation which causes imbalance, is the gully erosion phenomenon. Land degradation, a broken ecological balance of the land and landscape and risk of falling at biological resources in these areas, the study of the gully, is inevitable and necessary especially ...
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One of the types of water erosion and land degradation which causes imbalance, is the gully erosion phenomenon. Land degradation, a broken ecological balance of the land and landscape and risk of falling at biological resources in these areas, the study of the gully, is inevitable and necessary especially in the Darrehshahr Township. In this regard, Gully 36 number were selected in Darrehshahr area in the ilam province. To this end, were identified environmental factors, Physical - Chemical Soil properties, cover and hydrological properties of gullies tested using aerial photography, the digital maps and field operations. To determine the extent effect these factors on each of the gully geometry characteristics using fuzzy logic and information theory, the membership function and the weights of the membership function of each of the factors was calculated. Then relationship between the independent and dependent variables was obtained by using multivariate regression. Results of statistical analysis using multiple regression (stepwise method) revealed that length of gully with upstream area of the gully, top and bottom width and cross section of the Gully with basin elongation, deep gully with basin elongation and slope curvature, high of head Gully with local slope of the gully and steep walls of gully with percentage cover have a significant relationship. So could be concluded that characteristics of geometry gully in the study area would be a function of the upstream, basin elongation, curvature slope, Local slope of the gully head and the percentage of canopy cover catchment area of gully.
hossein norouzi; ataallah nadiri
Abstract
123
Groundwater system studies to understanding its behavior, requires the exploratory drilling wells, pumping test and geophysical experiments, which can carried out with most cost. For this reason, simulation of groundwater flows by mathematical and computer models, which is an indirect method to ...
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123
Groundwater system studies to understanding its behavior, requires the exploratory drilling wells, pumping test and geophysical experiments, which can carried out with most cost. For this reason, simulation of groundwater flows by mathematical and computer models, which is an indirect method to groundwater studies, is being spent a few costs. In this research, the efficiency of artificial neural network, fuzzy logic and random forest models has been investigated in groundwater level estimation of Boukan plain. Parameters of precipitation, temperature, flow rate and water level within time period of the previous month were used as input and the water table in each period were selected as output through monthly scale (2006-2017). To evaluating the performance of models, Correlation coefficient, root mean square error and coefficient of mean absolute error were used. The results showed that the Fuzzy Logic and Random Forest models are able to estimate water levels with acceptable accuracy. In terms of accuracy, fuzzy logic model with the highest correlation coefficient (0.96), lowest root mean square error (0.068 m0) and mean absolute error (0.056 m) was recognized as a best the model in the groundwater level prediction.
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.
M. Nabizadeh; A. Mosaedi; A. A. Dehghani
Abstract
River flow forecasting for a region has a special and important role for optimal allocation of water resources. In this research, for forecasting river flow process, Fuzzy Inference System (FIS) is used. Three parameters including precipitation, temperature and daily discharge are used for forecasting ...
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River flow forecasting for a region has a special and important role for optimal allocation of water resources. In this research, for forecasting river flow process, Fuzzy Inference System (FIS) is used. Three parameters including precipitation, temperature and daily discharge are used for forecasting of daily river flow of Lighvan River located in Lighvanchai watershed. For the initial preprocessing, the randomness of data was examined by return points test. Then, for determination of the optimum lags for input parameters, correlogram of data was considered. Finally to investigate the effects of temperature on river flow forecasting, the process were done for any months separately. Assessments of prediction by using various criteria such as Nash-Sutcliff coefficient showed that FIS model had high precision (CNS=0.9976) and low error (RMSE=0.0113) in prediction which shows that the FIS model can be employed successfully in river flow forecasting. Final assessment of the results was also revealed the effects of temperature on prediction in some months (April and December).
A. Salajegheh; A. Fathabadi
Volume 62, Issue 2 , October 2009, , Pages 271-282
Abstract
Correct estimation of suspended sediment transported by a river is an important practice in water structure design, environmental problems and water quality issues. Conventionally, sediment rating curve used for suspended sediment estimation in rivers. In this method discharge and sediment discharge ...
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Correct estimation of suspended sediment transported by a river is an important practice in water structure design, environmental problems and water quality issues. Conventionally, sediment rating curve used for suspended sediment estimation in rivers. In this method discharge and sediment discharge or concentration related using regression relation that generally is exponential model. Respect to uncertainty and nonlinear relation between discharge and sediment concentration, sediment rating curve has not enough efficiency for this purpose. In this study using Artificial Intelligent (Fuzzy Logic and Artificial Neural Network), suspended sediment in Karaj River was estimated. First, various neural network and fuzzy logic models established. For neural network and fuzzy logic, models with four neuron in hidden layers and FIS (Fuzzy Inference System) with four Gaussian membership functions, respectively were selected as the best structure. Finally, the results showed that fuzzy logic estimates the suspended sediment loud better than the other techniques and therefore is suggested for estimation of suspended sediment load.
B. Motamedvaziri; H. Ahmadi; M. Mahdavi; F. Sharifi; N. Javaheri
Volume 62, Issue 2 , October 2009, , Pages 283-298
Abstract
Estimation of river sediment load is one of the most important issues in design of hydraulic structures, investigating water quality, conserving fish habitat, estimating erosion and determining watershed management effects. There are two methods for estimating sediment load: empirical and hydrological ...
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Estimation of river sediment load is one of the most important issues in design of hydraulic structures, investigating water quality, conserving fish habitat, estimating erosion and determining watershed management effects. There are two methods for estimating sediment load: empirical and hydrological methods. Existence of numerous empirical methods for estimation of river sediment load and a wide range of calibration coefficients shows that a suitable analytical or empirical method does not yet exist to accurately estimate the sediment load. Also, hydrological methods are not able to recognize and separate the specific data measuring conditions and they can not show the temporal variation of sediment loads. In spite of these problems, nowadays, researchers are using Artificial Intelligence methods such as Fuzzy Logic. In this study, the measured suspended sediment load at hydrometric station of Sarcham located on Zanjanroud river is analyzed using USBR and FAO methods (common hydrological methods). Furthermore, suspended sediment load are estimated with a model developed based on Fuzzy Logic rules. In order to estimate suspended load using fuzzy method, one method named Supervised Fuzzy C- mean Clustering Method, is used. Then the results of hydrological and fuzzy methods are compared. The results showed that the temporal variation of sediment loads can be analyzed using a fuzzy method. Also the results obtained using the fuzzy method in comparison with the corresponding values obtained using the usual hydrological methods shows a better correlation with the observed values.
