hamid hosseyni marandi; mohammad mahdavi; hasan ahmadi; baharak motamed vaziri; abdolali adelpour
Abstract
Abstract Common causes for groundwater quantity and quality changes are infiltration through the seasonal floodwater, effects of the artificial recharge projects and adjacent aquifers, and groundwater extraction for deferent uses. However, recognizing the impact of their contributions to these changes ...
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Abstract Common causes for groundwater quantity and quality changes are infiltration through the seasonal floodwater, effects of the artificial recharge projects and adjacent aquifers, and groundwater extraction for deferent uses. However, recognizing the impact of their contributions to these changes can be often challenging. Still, to understand the changes, monitoring groundwater level and several chemical factors are taken into consideration. Certain problems of course can complicate the analysis of the observations; for instance, insufficient data and manually prepared and measurement intervals can degrade the accuracy of such observations. In this paper, device-measured daily time series of Electrical Conductivity (EC), Temperature (T) and Groundwater Head (GH) are analyzed. The main purpose is to evaluate the groundwater changes and its relation to the processes on the aquifer surface in an arid region. Two wells (PZ2 and W20) with 1,200m distance from each other selected and installed a sensitive device for recording the groundwater level, temperature and salinity fluctuations. Time series of changes from December 2012 to July 2013, were analyzed. Groundwater head in PZ2 showed a decline but in W20 showed a minor rise. Salinity variations were different and were 15.3mS/cm in PZ2 and 1.7mS/cm in W20. The backdrop of increased salinity in the surface layers of groundwater in PZ2 identified and showing a correlation between groundwater head and salinity fluctuation with 83.5% R squire.
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.
