فهرست مطالب meysam vadiati

In this research, clustering of a hydrochemical data set from Sarab plain aquifer using Fuzzy C-Means (FCM) and Hierarchical Cluster Analysis (HCA) techniques have carried out and its application in delineation of hydrochemical facies has studied. The statistical clusters are analyzed for spatial coherence and confirming that the clusters have a hydrogeological corresponding to aquifer hydrochemical facies. Groundwater samples using the optimizing the number of the classes and fuzziness exponent using the fuzzy c-mean were grouped into four classes. The data set including 49 water samples and 12 hydrochemical variables form the study area have used. Results from both approach produced cluster centers that can be used in order to identify the physical and chemical processes creating the variations in the hydrochemistry variation of study area. The FCM method is potentially useful in establishing hydrochemical facies distribution. The results showed that the clustering scheme for partitioning water chemistry samples into homogeneous groups produced by FCM method is an important tool for the determination of aquifer hydrochemical facies and the FCM method is more capable to investigate threshold data rather than HCA method that variation is sharp and abruptly.

Nowadays, groundwater quality change and salinization of water resources is a major hazard to developing of agriculture, particularly in dry lands like Iran. In this study, the application of Fuzzy Set theory to evaluate quality of groundwater was studied. In recent years, artificial intelligence methods have adjusted to spot uncertainty in environmental problems. Fuzzy Logic is one of the popular methods for decision making in complex and uncertain environments. In this study, the 49 groundwater samples of Sarab plain in 2014 that analyzed in Hydrogeology laboratory of Tabriz University was used. Values of irrigation indices including the Sodium Absorption Ratio, Permeability Index, the Kelley Ratio, Magnesium Adsorption Ratio, Residual Sodium Bicarbonate, Dissolved Sodium Percentage and Electrical Conductivity as an indicator of total dissolved solids in water are used in this research. Based on Fuzzy Water Quality Model, the groundwater quality is classified in three categories desirable, acceptable and unacceptable. Results showed 41 Samples come in desirable category with certainty level of 65 to 83 percent and 26 samples classified in the acceptable category whose certainty level ranged from 37 to 65.4 percent and the remaining three samples were in rejected category with the maximum certainty level of 23.4 percent.

In recent years, the new methods for assessment of groundwater resources quality have been developed extensively. In this research, the application of Entropy Theory to evaluate groundwater quality for drinking purposes is shown. In rural regions, the groundwater resources are the main source of drinking water. Also, the source of drinking water in Sarab plain is groundwater resources. The Entropy method was used, in order to prevent the individual judgments on determination weight of the parameters used in Water Quality Index Method. In this study, for evaluating Sarab Plain groundwater quality for drinking purposes through entropy weighted method, 12 groundwater parameters affecting the quality of drinking water, including bicarbonate, sulphate, chloride, calcium, magnesium, sodium, potassium, lithium, fluoride, nitrate, sillies and electrical conductivity, were used. Results showed that chloride had the highest impact on water quality of Sarab plain aquifers. Potassium, sodium and nitrate are the most unstable parameters among the studied parameters. The results showed 53 and 18 percent of groundwater samples were classified in group one and two respectively.

Analysis the flow in unsaturated soil is very complicated and is dependent on two nonlinear functions K(h) and θ(h) which are the nonlinear functions of soil hydraulic behavior. There are various methods for estimation of soil hydraulic parameters which using the infiltration test is one of them. In this study, the collected data from disk infiltrometer experiment (pressure head and cumulative water infiltration) used for estimation and optimization of soil hydraulic parameters by applying HYDRUS-2D software. The estimations done by inverse solution and Van Genuchten-Mualem model used for hydrodynamic assessing of soil sample. In addition, it is assumed that there is no hysteresis in soil sample and porous media is completely homogenous and isotropic. The silt loom soil sample with 20.7 cm in length and diameter equal to 20.7 cm selected for this experiment. The recorded data in 150 hours used as experimental observations in inverse solution of problem and the soil hydraulic functions estimated. Model ran in two discrete part, using pressure head and cumulative infiltration respectively, and results were compared. Results show that using the pressure head in depth 4 cm cannot lead to precise estimation of soil hydraulic parameters. Using the cumulative infiltration show the successiveness of this part of experiment in inversely estimation of parameters.

Coastal aquifers comparing noncoastal aquifers, are faced to natural hazards more rapidly due to incorrect managements (Bear et al. 1999). Aquifer’s vulnerability to various pollutants or intrusion of saline water to coastal aquifers have been studied by several researchers so far (Chachadi et al., 2002 Cardona et al., 2004). Overlay models are produced to overlay physical indicator maps and weight them (NRC, 1993). There is a high potential in applying methods based on spatial analysis, in hydrogeological studies. Assessment of natural hazards due to over-extraction of groundwater in Urmia coastal aquifer is the aim of this study which can leadto evaluating of groundwater quality fluctuations in coastal aquifer and also salt water intrusion in coastal aquifer. Study area is Urmia plain coastal aquifer. This plain is bounded from North, East, South and West by Zola chai and Kherkhere chai watersheds, Urmia Lake, Gadar Chai watershed and boundary mountains of Iran and Turkey respectively. Present study focused on, utilization of overlaid natural hazards substantial evaluation groundwater over extraction indices spatial models method, using Geographical Information System (GIS). Flow chart of the Methodology of present study is depicted in figure Fig 1. Methodology flowchart of present study Drawdawn is meaningless?? “Counductivit “is wrong “conductivity” is true. Six parameters that have crucial importance in hazards caused by groundwater over-extraction and groundwater quality depletion subsequently, have chosen upon to literature review, various studies and authors expertise (Nobr et al, 2007 Hammouri and El-Naqa 2008). Weights and ranks were indicated base on experimental results or authors judgment and experts knowledge in similar studies and statistical methods. Used indices final weights were determined as below: Total dissolved solid (TDS) (1), discharge of water wells (2), hydraulic conductivity (1), Aquifer thickness (1.5), Water table depletion (3), Distance from lake shore (1.5). Weight of every layer is given to layers ranks. Final map was determined and areas with low, moderate, high and very high vulnerability was ranked eventually considering the vulnerability amounts importance. Fig 2. Final map of Spatial Analysis of Natural Hazards in the aquifer of Urmia region The results of this study revealed that natural hazard’s rates in Urmia Lake coastline due to salt water intrusion and also in aquifer central part is very high, which caused by groundwater over-extraction. Final map shows the areas with low vulnerability has covered 191 square kilometer (about 20 percent of the study area). In these areas groundwater extraction is low and the thickness of aquifer is also negligible. Areas with moderate and high vulnerability contain 353 (37 percent) and 119 (13 percent) square kilometer respectively. In the coastal and central parts of the plain, groundwater extraction is so high and of course features the very high vulnerability that covers 30 percent and 280 square kilometer of the study area.

In recent years, fuzzy-logic-based methods have adjusted to spot uncertainty in environmental problems. In the present study, a methodology based on Fuzzy Inference Model to assess river water quality is used. The potential application of the fuzzy model has been tested with a case study. Therefore, a data set collected from seventeen stations through the Karoon River from 2008 t0 2009 has been used. The most important parameters are affecting the river quality of water such as DO, BOD5, NO3-, Cl-, EC has been used. Using Fuzzy Inference Model, the river water quality classified in three categories; Good, Moderate and Poor. Results showed that fuzzy inference model is able to indicate water quality variations in different seasons. Therefore, this methodology develops as a suitable and alternative tool to be used in developing effective water management plans.