Journal of Water Resources Engineering
Year:2012 | Volume:5 | Issue:13|Papers Count:10

One of the best ways, to prevent groundwater resources from contamination, is identifying the aquifer vulnerability areas, and monitoring groundwater quality spatial variations to manage the groundwater exploitation and the land usage. In this research, for the first time, the aquifer vulnerability map of Gachsaran Emamzadeh Jaafar, located in South of Kohgiloyeh and Boyrahmad province, is evaluated using DRASTIC model. Investigating of hydro geological parameters impact on aquifer vulnerability, and the results of sensitivity analysis, using both the map removal and single parameter methods, indicate that the zone (I) has the most significant impact on the vulnerability index. Based on the DRASTIC results, about 4.2, 56.2 and 37.0 % of Emamzadeh Jaafar aquifer have high, moderate, and low vulnerability, respectively, and the vulnerability of 2.6% of the areas is negligible. Since the high vulnerability areas is covered upstream of the aquifer, entrance of any contaminants can be distributed in groundwater flow direction.In addition, the potable groundwater variations map, prepared based on GWQI index, and the result from its comparing with the Schaller diagram, shows that 1.6, 83.4 and 12.1 percentages of groundwater resources in Emamzadeh Jaafar aquifer have excellent, good and bad quality. In general, the groundwater quality of most area is good, except in North West part of the aquifer, which has poor groundwater quality due to flowing through the evaporated Gachsaran formation.

By entering flow into a bend, the flow will be affected by two forces of transverse pressure and centrifugal in which the helicoidally flow is developed. Such pattern is the main cause of erosion in outer bank and sedimentation in inner bank. Many measures have been developed which can modify the flow pattern and therefore reduce erosion. The W-weirs is among such measures. In the present paper, by measuring three components of flow velocities with and without presence of W-weir, variation of flow patterns and shear stress distribution in a 90 degree sharp bend have been investigated. The analyses of data show more uniform flow upstream of the weir and also reveal that the effect of transverse and centrifugal forces are modified in such a way that the secondary flow is diminished. The shear stress distribution upstream of the weir is more uniform in comparison to the case of no weir. The results show that shear stress in outer bank is reduced and in inner bank increased. The results show that for the case of no weir, the shear stress for Froude number of 0.17 and 0.40 in 30-degree location are 1.19 and 5.47, respectively. For the case in which a Weir exists, these values are reduced to 1.16 and 4.07, respectively.

Rivers flow forecasting has special importance in surface water management, especially in agricultural planning and risk reduction of floods and droughts. In recent years, studies have shown the superiority of time-series forecasting models based on artificial intelligence, such as artificial neural networks (ANN) and genetic programming (GP). In this paper, continuous and discrete historical flow records are used for Saeed-Abad monthly river flow forecasting in East Azarbaijan province, Iran. Auto regressive moving average with exogenous inputs (ARMAX), ANN, and GP models are used and compared to each other. Coefficient of determination (R2) and root mean square error (RMSE) are used to evaluate the performance of the aforementioned models. Results show that for the two methods, the GP model is more effective than ARMAX and ANN in terms of accuracy. For continuous time-series forecasting, GP is a more precise model (R2 = 0.7 and RMSE = 0.172) than either ANN (R2 = 0.627 and RMSE = 0.193) or ARMAX (R2 = 0.595 and RMSE = 0.243). For discrete time-series forecasting, the superiority of the GP model is evident in almost all months. Moreover, results indicate that discrete monthly time-series forecasting method is superior to the continuous monthly time-series forecasting method.

Drought phenomenon, during its occurrence, affects on groundwater resources, which have been less taken into consideration. In this research, the extent of meteorological drought vulnerability in Fasa and adjacent areas using Standardized Precipitation Index (SPI) at monthly, seasonally and yearly scales during the period of 1978-2009, and the hydro geological droughts in this area using Groundwater Resource Index (GRI) during the period of 1994-2010 have been studied. The results show that the GRI values have a decreasing trend with occurrence of high levels of hydro geological droughts in groundwater resources in years 2003, 2008 and 2009. To investigate the dependence of groundwater quantity/quality to meteorological drought phenomenon, the correlation coefficient between the mean values of groundwater levels, GRI and Standardized Electrical Conductivity Index (SECI) with SPI on different time scales, with and without time delay, was calculated for the period of 1993-2009. The results show that, the SPI index, in 48-month time scale without time delay (SPI-48), has a strong correlation (at 99 percent meaning level) with groundwater levels, GRI and SECI, which confirms the directly affected of groundwater (quantitatively and qualitatively) by drought. The regression of groundwater levels with SPI-48 indicates that approximately 56% of groundwater levels’ variances are related to SPI and 44% is by other factors. In addition, the regression analysis between SECI and groundwater levels and SPI-48 shows that approximately 46% of SECI variances are related to the amounts of groundwater and 54% is by other factors. There is no linear correlation, at 95 and 99 percent meaning level, between SECI and SPI-48.

Hydrologic response of hillslopes is affected by their geometric characteristics including the profile curvature. In the previous studies, in order to investigate the effect of profile curvature, a single equation (Evans’ equation, 1980) was used to produce convex and concave hillslopes corresponding response of which were compared. In this paper, first, it is shown that in the previous studies the convex and concave hillslopes were not equivalent and comparable. Next, some criteria for producing pairs of equivalent hillslopes are suggested. Based on these criteria a new profile model is derived. Evans’1980 profile model with the new one can be employed in producing pairs of comparable hillslopes .Finally; the equilibrium time equations and the dimensionless equations corresponding to the rising limb of the resulting hydrographs for equivalent hillslopes are derived and compared. The results showed that time to equilibrium for concave slope is shorter than that of convex slope. In addition, ignoring slope variation in the determination of time to equilibrium in convex slopes may potentially cause an underestimation by up to 25%. Time to equilibrium for concave slopes is close to that of straight slopes. Thus, the error due to assuming a uniform slope is negligible for this case.

Impact of precipitation changes on ground water level was investigated by analyzing the relationship between monthly rainfalls recorded in the past and water levels in observation wells in the plain of Shiraz. Approximately 86% of the wells have a positive correlation with rainfall and changes in rainfall, causes groundwater level changing toward each other. With the establishment of cross correlation between the changes in monthly rainfall in Shiraz station with the average groundwater level in Shiraz plain during the years 1372-1386, it was observed that monthly rainfall in Shiraz station affect the average monthly groundwater level about 1 month later. Therefore, maximum and minimum groundwater level is achieved with 1-month delay after reaching the maximum and minimum on monthly rainfall.

Seydan-e-Farough plain is one of the Marvdasht’s plains. The area of the considered plain is 369 square kilometer that 204 square kilometer of that is mountainous and 165 square kilometer is plain. In this study, nonlinear mathematical programming approach was applied for determination of optimal depth of agricultural wells with objectives of decreasing excavation and pumping costs. To determine the optimum depth of excavation wells it was assumed that farmers allow re-drilling wells and withdrawal of water to achieve the first discharge in the absence of the aquifer water balance. Data was collected from 1640 agricultural wells in Seydane-e-Farough plain and was analyzed with GAMS software. The results showed that lifting water from wells is justified with excavation of wells to the altitude 138 meters. Excavating the well to depth of 138 meters, Well discharge and pump altitude were quantified 9.81 liter per second and 112.32 meters. Besides, the optimal cultivation area for each crop regarding to guarantee the agricultural water required is determined in case of excavation of present wells. At the end, optimized consumption management and illegal well exploitation prevention is suggested.

Iran encounters climatic variations as located in 25-40 North latitudes. If atmospheric events like rain, drought and flood predicts correctly it would affect significantly on natural hazard control and water resources and agriculture planning. One of the most important factors in climatic variation is the sea surface temperature (SST) which is effective on the amount of rain. In this research, the relation between the Persian Gulf and Red sea’s SST and the fall and winter rain of three synoptic stations in Khuzestan province in Iran during years 1965- 2010 is detected by means of a data mining technique called association rules. Data mining is an advanced tool for regional water authorities to carry out research on databases and detect the hidden patterns and procedure of events and clarify their future manners, and make better decisions. In this study, drought and wet year events are defined according to Standardized Precipitation Index (SPI). The coincident and individual effects of Persian Gulf and Red sea’s SST on these events are analyzed using a time series data mining algorithm called ARSS. The new algorithm (ARSS) is developed to find the relations between atmospheric and climatic indices in a different manner than classic statistical hydrology. Results show that coincident use of Persian Gulf and Red sea’s SST enables us to find more relations than the separate use of them. The ARSS algorithm can also predict the neutral condition with most confidence in future, though its ability to predict the moderate drought and extreme wet conditions is mentionable.