WATER AND WASTEWATER
Year:2009 | Volume:20 | Issue:1 (69)|Papers Count:12

The widespread activities in water resources exploitation and use require sound research programs on planning and management of conjunctive use of surface and ground-water. Conjunctive management is a suitable approach for the imbalanced water resources distribution and related constraints in using surface water. In this paper, a multi-objective model is developed to maximize the minimum reliability of the system and to minimize the costs due to failure to supply water, aquifer storage, failure to cope with reservoir capacity, and prioritizing water allocations. The non-dominated sorting genetic algorithm (NSGA-II) is used to present the optimal trade-off between the objectives. The sequential genetic algorithm (SGA) is also applied in order to be compared with the NSGA-II model. The results show that the NSGA-II model can considerably reduce the computational cost of the conjunctive use models in comparison with the SGA optimization model. The obtained trade-off curve shows that a slight increase in reliability leads to much higher system costs. The weighted single objective SGA model results verify the optimal trade-off obtained from NSGA-II model and show the optimality of the allocated discharges.

River flow forecast has of long been the focus of attention due to its wide applications in water-related sciences. Development of new models and advanced techniques will bring about drastic changes in the estimation of this dynamic and nonlinear system. In this research, feed-forward Artificial Neural Network (ANN) was used to predict monthly flow. Given the numerous flow forecast variables used in the present study, identification of variables effective in the network was necessary to help obtain improved results. For this purpose, we modeled the flow using the Principal Component Analysis (PCA) technique that reduces the number of input variables to include only the ones effective in ANN (PCA-ANN). PCA was first employed to reduce the number of input variables whereby 18 original variables were changed to 18 new components and the first 8 in the best model were then selected as network inputs. In addition, wavelet transformation was used for preprocessing input variables in the network to develop a model for flow forecasting (WNN). Comparison of the results obtained from the three models (ANN, PCA-ANN, and WNN) indicated the positive effect of preprocessing by wavelet and PCA on input variables. Another finding of the study was that the proposed model (PCA-ANN) had a simpler network architecture, faster training speed, and more satisfactory predicting performance in comparison with ANN and WNN models.

In recent decades, river quality management has received enormous attention by researchers as an important water resources management issue. The main reason for this is saving in wastewater treatment costs by optimal allocation of the assimilative capacity of the river system to dischargers. Regarding the unidirectionality of the river flow toward the lowest level, the Trading Ratio System (TRS) and Bayesian Networks are utilized in this paper to develop new, real-time operating policies for discharge permit trading in rivers. TRS is used in a Monte Carlo Analysis to provide the required data for training and validating a Bayesian Network (BN). The trained BN are then used for real time river water quality management to provide probability distribution functions of treatment levels and trading discharge permit policies. The methodology is successfully applied to a case study and its results are compared with those of the TRS. The comparisons show the usefulness of the methodology as a cost-effective and probabilistic decision-making tool in real-time river water quality management.

Iran is located in an arid and semi-arid region and will be joining the 'Thirsty States' by 2025. However, water use efficiency and water services seem to be low and inadequate, as they do not match the emerging conditions of water scarcity. As part of the research efforts required addressing the problems in this area, this paper endeavors to use a simple, efficient, precise, and practical method for determining the income and price elasticity of the domestic drinking water demand. The household income in this method is replaced by a good, measurable substitute index which is the household land and building areas. Log-log functions are presented for different blocks for the statistical period 2001- 2004. Correlation coefficients obtained were above 40% in all the functions. The average income elasticity ranged from 0.704 to 0.411 for the first to the fifth blocks, respectively. This shows that water is a necessary and non-substitutable commodity in the household portfolio. The price demand elasticity was estimated using the modified Pollak-Wales method, price variations over two different time periods, and income elasticity over the statistical period. The price elasticity value varied from - 0.3 to -0.01 for the second to fourth blocks, respectively. This indicates the inelasticity or low elasticity of water for current prices.

The nanophotocatalytic process using nano-structured semiconductors is one of the techniques used for the destructive oxidation of organic compounds such as dyes. The photocatalytic oxidation of Reactive Orange 16 aqueous solution, applied in the textile industry, was assessed by UV ray irradiation in the presence of TiO2 nanoparticles. It was found that the photons required for the process were completely absorbed when TiO2 concentration reached 0.4 g/L. Degradation of paint decreased with increasing TiO2-concentration. It is suggested that at very high concentrations, the active points on ions are covered and the number of radicals like 'OH will, therefore, decrease on the surface of catalysts. Another explanation for this state of affairs is that UV screening may have the same function. The negative action of anions may be explained by the reaction of positive cavities accomplished by hydroxyl radicals with anions. This reaction can be described as corrosive for 'OH and hVB+, which can prolong the process of color removal. The TiO2 in an acidic environment has a positive charge (pH<6.8); therefore, there exists an electrostatic adsorption between the positive charge of TiO2 and anionic colors. pH is a very important factor because it affects the electrostatic charge of the photocatalyst ions as well as the surface of the semiconductor particles. The mineralization of RO 16 dye was reported by measuring the initial and final COD (Chemical Oxygen Demand) values of the solution irradiated under optimized conditions. The results showed that the nanophotocatalytic process has a tremendous capability in enhancing the mineralization of RO16.

The purpose of this study was to conduct an experimental investigation of decolorization of effluents by the electrocoagulation method. Removal of Eriochrome black T from solution in a batch system was investigated using different voltages (10, 20, 30 volt), electrodes (Al, Fe), electrode distances (2, 4 cm), electrolysis times (0 to 30 min.), and pH levels (3.5, 7, 11). Experimental results showed that removal efficiency depended on electrolysis time and applied current. The experiments carried out at 30V and pH=3.5 further revealed that color removal efficiencies of Fe and Al electrodes over a period of 30 minutes were 96% and 86%, respectively.

Shahid Mahallati Wastewater Treatment Plant was selected for installing a UV disinfection unit to investigate its gennicidal effect on microbial removal. Low pressure mercury lamps were used to generate gennicidal ultraviolet radiation (UV-C). The UV system was operated over a period of 6 months that included both warm and cold seasons. A maximum UV disinfection efficiency of 14.4m3/h was recorded for the system on the basis of design criteria within turbidity ranges of 9 to 32 NTU. The minimum UV dose applied in the UV unit was 40000 m W.s/cm2 and the highest bacterial density in the UV unit influent was 5.6*10 . Effluent total coli form or fecal coliform enumerationafter exposure to UV ray showed the microbial density decreasing from four logs, or 99.99%, to as high as six logs, or 99.9999% removal efficiency, under different conditions. Effluent microbial densities in terms of total and fecal coliforms were below 1000MPN/I00mL and 400MPN/100mL, respectively. These values comply with wastewater discharge or cultural irrigation standards according to Iran Department of Environment. From our results, it IS concluded that UV disinfection may be an effective technique for wastewater disinfection in Iranian wastewater treatment plants.

Groundwater overdraft is one of the main reasons of land subsidence. Differential subsidence leads to earth fissures and damages to structures, roads, railroads, pipelines, irrigation canals, and sewage networks. In order to simulate land subsidence due to groundwater overdraft, a fully coupled finite element consolidation model was developed. Formulation of finite element was based on Biot three-dimensional consolidation theory. Land subsidence studies in Rafsanjan City were conducted by collecting and analyzing data on geology, geophysics, hydrology, soil properties, and observed land subsidence. Due to lack of sufficient experimental data about different soil profiles, land subsidence monitoring and back calculation were used in several spots to obtain the necessary data for use in other places. A computer model was finally developed to predict the subsidence of the city and its effects on the sewage network were studied.

Nowadays, optimization techniques such as Genetic Algorithms (GA) have attracted wide attention among scientists for solving complicated engineering problems. In this article, pumping test data are used to assess the efficiency of GA in estimating unconfined aquifer parameters and a sensitivity analysis is carried out to propose an optimal arrangement of GA. For this purpose, hydraulic parameters of three sets of pumping test data are calculated by GA and they are compared with the results of graphical methods. The results indicate that the GA technique is an efficient, reliable, and powerful method for estimating the hydraulic parameters of unconfined aquifer and, further, that in cases of deficiency in pumping test data, it has a better performance than graphical methods.