IRAN-WATER RESOURCES RESEARCH
Year:2010 | Volume:6 | Issue:3 (18)|Papers Count:10

Procedures of extraction, refinement, transmission and consumption of oil have a high pollution potential to soil, air, and water resources. The leaking of oil into the ground and toward the groundwater resources is a common phenomenon in pollution studies. Regarding the considerable oil resources in Iran, the groundwater pollution is a major issue due to different oil-based pollutants in the main source of drinking and agricultural water. Methyl Tertiary Butyl Ether (MTBE) which is toxic and very soluble in water is one of the most common oxygenated compounds used in producing lead-free gasoline in Iran and many other countries. The parametric study of the factors which affect the biodegradation and transport of MTBE is very important. In this study the most important biodegradation models are reviewed. BIOSCREEN as an analytical and BIOPLUME as a numerical model based on finite difference approximation are among these models.As the case study, the geochemical field data is used for one of the gasoline stations in Tehran (gasoline station no.25 next to Ameneh Nursery) to predict the fate of MTBE in groundwater resources in the vicinity of the station. This is performed based on the biogeochemical properties of the soil and the groundwater including the soil density, soil adsorption, and groundwater velocity. The concentrations of dissolved oxygen, nitrate, sulfate, and iron are also considered as electron acceptors. The result of the study showed that the electron acceptors have a considerable effect on MTBE biodegradation. The results also indicated that the model outputs are in good agreement with the field data and can be used as a good tool for the prediction of natural biodegradation of petroleum products in groundwater.

Small hydropower plants can have an important role in energy generation. Upper catchments are normally proper locations to construct such plants, but they usually have snowy regimes and the availability of data is usually a problem. This paper is an attempt to simulate snowmeltrunoff with SRM and ANNs in the relatively small catchment of Sardabrood in northern Iran with scarce data. In the next step, effects of errors resulting from the streamflow simulation on the estimated hydropower energy potentials is investigated.For the SRM model, a snow covered area is needed. This is met by the images of the AVHRR sensor of NOAA satellites for the years 1999 and 2000. In case of ANNs, the networks are trained with 1 year- (1999 using stations in the region) and 3 year- (1997 to 1999 using stations of the region and nearby) observed data. Year 2000 is used for verification.The results have shown that if ANNs get trained with 3-year data, it performs better than SRM. Both methods have problems in high flow simulations. Duration-Curve method and Sequential Streamflow Routing method are applied to simulate electricity generation, based on the results of runoff simulations. The RETScreen software and a program developed in this research are implemented for this purpose.The comparisons suggested better performance of SRM in the equal time periods (1999 and 2000) and subsequently better energy generation prediction. ANNs with 3 years training have closer results to SRM. Although runoff simulated with SRM have better performance in energy generation. This is because of better simulation of runoff in the operational ranges of the turbines.

Fuzzy evaluation presents a certainty level for the acceptability of water for drinking purposes based on prescribed standards of various organizations and perception of the experts. In this study, fuzzy set theory was applied for decision making on the suitability of certain groundwater resources for drinking purposes based on chemical quality.The quality of water was expressed in indefinite environment of monitored data and prescribed standards given in a nonprobabilistic sense. From the 9 cities in Esfahan Province, 29 groundwater samples that were collected from the drinking water wells are used in this study. These samples were analyzed for 11 chemical parameters. But, finally 9 parameters were used for evaluation of drinking water quality. The results showed that 10 water samples were in the “desirable” category with a certainty level of 84-97%, 9 samples were in the “acceptable” category with a certainty level of 50-100%, and 10 samples were in the “nonacceptable” category with a certainty level of 50-95%.Furthermore, about 65% of the samples were in the “desirable” or “acceptable” categories for drinking purposes.

In river with non-regular cross sectional area or with turbulent flow, it is not possible to measure flow by usual methods. The tracing method is used in such circumstances.This method is applied in two ways: constant rate injection for small streams and slug injection for greater flows. These methods are based on tracer dilution in a stream. In this study a new equation is presented for discharge determination using constant rate injection in the laboratory and nonlinear regressions. Sodium chloride is used in this experiment as a tracer. This method is double-checked in the field.Experimental and field results confirm accuracy of the new equation.

Evaporation is one the most important climatic parameters in water resources management. This parameter depends on many other climatic factors and plays an important role in arid and semiarid regions. In this study, 14 weather stations were selected in arid areas in central and southern parts of Iran. The climatic historical data including cloudiness, maximum and minimum temperatures, the differences between maximum and minimum temperatures, mean relative humidity, wind speed, and some other factors were provided.An Attempt was made to determine the most important factors affecting evaporation by using Factor Analysis (FA).Then, by conducting Cluster Analysis (CA) through Minitab software, homogeneous regions were separated. Taking advantages of multiple regressions in each region, the relationship between climatic factors and evaporation on the basis of monthly routine was maintained. The verification and evaluation of derived regression equations was calculated using MAE or RMSE statistics. At the end, through applying the geo-statistic technique (Kriging) on calculated evaporation data of investigating stations, the monthly coevaporation map for each homogeneous region was drawn and the resultant histograms were analyzed.The results show factor analysis is an appropriate method for determining the relative importance of climatic parameters affecting evaporation. Also, division of a vast region to small subdivisions using cluster analysis increases the precision of derived evaporation equations. Results showed that the multiple regressions may be used in calculation of evaporation and consequently potential evaporation with great confidence. Utilization of geo-statistic technique is a proper approach for estimating potential evaporation in low or no data areas.

Recently a lot of attention has been directed to advanced techniques of reservoir operation. The continuous evolution of the information technology (software and hardware) and the development of new techniques including soft computing, intelligent techniques, and evolutionary algorithms created a good environment for reality-based methods and tools. From the Theoretical point of view, modeling a system requires explicit mathematical relationships between inputs and outputs (variables). Since these relations are unknown in many systems, developing such an explicit model is very difficult. In this case, soft computing methods that are based on imprecise conditions and evolutionary algorithms provide capabilities in defining many nonlinear systems and identifying control issues. One of these heuristic selforganization methods is Group Method of Data Handling (GMDH) that produce increasingly complex models during the performance evaluation of input and output sets. Based on GMDH, in this research we have developed a model for the operation of reservoirs in the Tehran-Karaj plane including Lar, Latian and Karaj reservoirs. The GMDH is selected for reservoir operation based on the sufficiency of sampling, characteristics of reservoir in the region of study, and suitability of this technique in the data driven systems.Results of modeling showed high performance of GMDH in reservoir operation.

The Hamoon Lakes are located in the Sistan Basin, in south eastern Iran. Among the most unstable water bodies of the world, these lakes experience great annual fluctuations. The Hamoon wetlands, with unique ecological values, is a protected site under the Ramsar Convention.In this paper, the temporal-spatial relationship between the surface water potential and the stability of Hamoon and Godzereh water bodies has been analyzed for the periods of 1972-2004. Based on the Hirmands' inflows, mainly Parian and Sistan rivers, this analysis was conducted using the remote sensing information. (Landsat MSS, TM and ETM+ sensors images and LISS1 and LISS2 sensors of IRS images) The depths of water, the area of the lakes, and the vegetation of the Sistan Basin were analyzed and interpreted based on these images (two images per yes) using principle components of satellite visual interpretation.The results suggested that the temporal-spatial stability of Hamoons mainly depends on the Hirmand inflow.It is known that the Hirmand Hamoon Lake is more unstable than other water bodies in the basin. The Puzak Lake is more stable. It should be stated that in hydrological drought events the response of the hyper saline Godzereh lake is very gradual.Analyzing the Topax/Poseiden Jason satellite data, the variation of the Puzak Hamoon during the critical long period of droughts is evaluated.Irrevocable changes have occurred in land cover, due to the shallow depths and excessive dependence on the Hirmand inflow and operation of upper reservoirs (Kajaki and Arghandab dams in Afghanistan).It is shown that a long period of normal discharge is needed for hydro-ecological balances and compensation of losses in this vulnerable ecosystem.

In this research, the effects of a number of environmental factors such as pH, sunlight, temperature, salinity, free chlorine, and adsorption in porous media are evaluated on the applicability of selected groundwater tracers. Tracers from different categories as fluorescent dye tracers (uranine, eosin and rhodamine-B), chemical salts (NaCl and KCl), and non fluorescent dye tracer (KMnO4) have been tested in the laboratory. The results showed that uranine losses its florescence in acid environments, while in alkaline conditions its florescence increases. The results also showed that due to photochemical decay, if subjected to sunlight, eosin is the most unstable tracer. KMnO4 turns to brown under sunlight and high temperature conditions and may lose its usefulness as a tracer. Results also confirmed that the fluorescence intensity of rhodamine-B decreases as temperature and/or salinity increases. Uranine and eosin showed high resistance against high temperature and high salinity conditions. An important factor in groundwater tracing is adsorption of tracer in porous media environment. Our research showed that rhodamine-B would easily be adsorbed to fine grain porous media while uranine and eosin high resist against adsorption.KMnO4 is also easily adsorbed. Chlorine used in drinking water treatment is strongly oxidizing even in low concentrations and can lead to the elimination of fluorescence of uranine, eosin and rhodamine-B.

The main objective in calibration of conceptual Rainfall- Runoff models is to find a set of optimal model parameters that provide the best fitness between the observed and the estimated flow hydrographs. These models are general, but when there is a lack of data, their application will be too difficult. In basins without data using the synthetic unit hydrograph for calculation of design flood is inevitable.Recently, it is shown that the use of the heuristic algorithms in combinational optimization problems is very suitable. In this research, two different algorithms, Univariate-Gradient as a classic optimizer, and Genetic Algorithm as a throughout optimizer, were used for calibrating snyder, Clark, and SCS unit hydrograph models in HEC-HMS software. The flood of Bahman 14-18, 1371 (Shamsi Calendar) in Dejgan station, Mehran River, Hormozgan Province, was used in this study.Results showed that the combination of GA and Snyder method is appropriate for forecasting the basin characteristics.The basin characteristic can be obtained using this method, observed hydrograph, and fitness function. “AutoIt” software was used for automated running of simulation and optimization.