Journal of Water Resources Engineering
Year:2017 | Volume:10 | Issue:33 |Papers Count:8

Population growth and shortage of energy warrant optimal utilization of our limited resources. Pumping stations typically run on electrical energy and economical use of the energy is desirable. Serial pumping stations are often required when the pipeline is long, or when the designed pumping head is too large to be handled by the existing single pumps. The greatest energy price reduction can be obtained by careful scheduling of pumping operation. Here, a pump operation schedule is represented as a string of binary values with each bit representing pump on/off status during a particular time interval, and pump optimal scheduling problem is coded as a problem of finding the best binary string, which results in the least energy price. In this study, a GA (genetic algorithms) based simulation-optimization model has been developed for the optimal scheduling of serial pumping stations. The model integrates GA optimizer and EPANET 2 hydraulic network solver in MATLAB. The proposed model is applied to find the optimal pump operation schedule of the Shiraz water conveyance system from the Doroudzan Reservoir in an ordinary day of the year. The results showed that the total energy cost in the optimal operation was 29% less than average in an ordinary day. Comparison between the optimal operation program and the previous studies indicated the model’s robustness.

The AQUIPRO method was used to assess aquifer vulnerability using the operating water well logs. The AQUIPRO model is a parameter/factor weighting system for rating the pollution potential of aquifers. This method uses the water depth in well, as well as the clay and partial clay thickness in a well, to generate pollution potential scores. In this model, aquifer protection increases as the AQUIPRO vulnerability scores increase and ground water pollution potential decreases. Logs of 30 wells with chemical analyses of nitrate concentrations in these wells were used to determine the ground water pollution potential of Ajabshir Aquifer, East Azerbaijan. Theoretically, low AQUIPRO pollution potential scores should have more frequent occurrences of ground water contamination events than areas with high AQUIPRO scores with similar land-use, well construction, and well densities. The relative AQUIPRO scores were compared with the nitrate concentration in ground water. The results indicated that wells containing more nitrate showed a decrease of AQUIPRO vulnerability scores. The average nitrate-N concentrations within each relative AQUIPRO vulnerability scores category were also compared. The results indicated that as the relative AQUIPRO (R2= 0.97) vulnerability scores increase, the mean nitrate concentrations also increase. Accordingly, comparison of the AQUIPRO method with the distribution of nitrate, and comparison of average nitrate concentrations in the every classification and relative AQUIPRO vulnerability scores confirmed the accuracy and validity of the method in the region.

Density current is produced due to a density contrast with the ambient fluid. This density difference can result from dissolved solids, suspended materials, temperature, etc. Density jumps significantly influence the characteristics of the gravity currents and the ambient fluid (e.g., velocities and concentrations). In this paper, the density jump is studied analytically by considering the bed roughness and entrainment ratio. For both smooth and roughened beds, a generalized relationship was obtained for estimating the conjugate depth ratio as a function of the upstream densimetric Froude number, the entrainment ratio, and the relative roughness. Moreover, various equations for calculating the maximum possible value of the relative roughness, the minimum possible value of the prejump densimetric Froude number, and the maximum possible value of the relative roughness were proposed. The minimum possible value of the conjugate depth ratio was determined. It was found that both the conjugate depth ratio and the length of the roller zone decrease as the bed roughness increases. Moreover, as the entrainment ratio increases, the ratio may also decrease, or may initially increase and then decrease. Finally, a relationship was obtained for estimating the minimum possible value of the obstacle height as a function of the conjugate depth ratio.

Armoured breakwaters are important hydraulic structures as they protect the non-rocky against erosion. As the berm width affects the run-up height, therefore, its determination is of almost importance. It is interesting to note that most researchers have studied the berm recession thus ignoring the wave run-up. Therefore, this study enhances our understanding of these vital structures. As a whole, 350 numerical models were developed to investigate the relationships of the linear wave run-up over the armoured breakwaters to the berm width employing the Flow-3D software. The main variables in this study were berm width, wave height, wave period, the seaside slope of the breakwater, and the distance to the static water surface. It was observed that the numerical results were close to those of the analytical results with a correlation coefficient of 96%. A 45% increase in the berm width decreased the wave run-up height by 36%. Furthermore, a 67% increase in the wave height resulted in a 53% increase in the wave run-up height, and a 53% increase in the period resulted in a 36% increase in the wave run-up height. To sum up the stability, an optimum performance of breakwaters is determined by their berm widths.

Tide induced head fluctuation has been considered by many researchers in coastal areas. In this paper, a numerical solution has been developed for an inhomogeneous multi-layered aquifer. This aquifer system comprises an unconfined aquifer on the top, a semi-confined aquifer at the bottom, and an aquitard between them. This coastal aquifer is bounded by coast in longitudinal direction; the coastal boundaries are parallel to each other. The results showed that the amplitude of unconfined aquifer head increases with increase of leakage, however, the amplitude of head fluctuation decreases in the semi-confined aquifer. In addition, the results of analytical solution, the head fluctuation in unconfined aquifer decreases with increase of dimensionless storage coefficient, however, it is almost constant in confined aquifer. Also, increase of dimensionless transmissivity increases the groundwater head fluctuation in both aquifers. Temporal head fluctuation illustrated that time lag has not significant changes, and is greater for semi-confined aquifer with respected to confined aquifer. Comparison between numerical and analytical solutions showed that there is little difference between.

Nowadays, along with an increase in water needs, there is no balance between water demand and water supply in most regions of the country. Therefore, planning an appropriate policy to strike a balance between a declining water supply and an increasing demand to prevent a crisis is of utmost importance. The use of optimization methods in this context can be useful. Evolutionary algorithm methods are known as appropriate methods in this regard, and their suitable performance have been reported. Biogeography-based optimization (BBO) is a new evolutionary algorithm which its high performance in some aspects has been proved. The main objective of this study was to assess the performance of BBO in water resources management for the first time. Firstly, BBO was used for finding optimal points of three benchmark function including Sphere, Rosenbrock, and Bukin6; secondly, it was applied for an optimal operation of the Karon4 Reservoir with the aim of hydropower generation. In order to evaluate the performance of BBO, in addition to this method, the genetic algorithm (GA) and the nonlinear programming (NLP) were employed. The results of benchmark function showed that BBO delivered a better performance than the GA in finding the optimal points of three functions. Moreover, BBO reached an optimal solution with a higher degree of accuracy. In operation of the Karon 4 Reservoir, the results also indicated the high efficiency of BBO in extracting optimal operational policies in such circumstances; the objective function value of BBO at the best performance was 1.223, and, that for GA was 1.535. Furthermore, the global optimal solution obtained from NLP for this problem was 1.213.

Precipitation is known as one of the most important factors in a hydrologic cycle. Hence, an accurate knowledge of rainfall data, which are usually gathered through a group of rain gauges, is necessary for any hydrologic simulation on a watershed. Therefore, a rain gauge network design, including determination of an optimum number of stations, is one of the fundamental concerns in any hydrologic study. Several indexes are employed to express accuracy of a rain gauge network. Among the indexes, entropy is one of the well-used concepts, which is utilized to assess the accuracy of the data collected by any rain gauge network. In earlier studies, entropy-based equations were used assuming normality of rainfall data. This assumption may have led to inaccuracy in results. In this study, the validation of the supposition was checked by the actually observed (non-normal) monthly precipitation data of 24 rain gauges in the Province of Fars, Iran. A traditional rain gauge network design based on the entropy concept and the actually observed data was used. The designed network compared with a procedure in which the Box-Cox transformation is used to normalize primary data. The results indicate that the priority of selected stations changes drastically, and entropy growth rate decreases, as the number of the rain gauge stations whose transformed data are used increased.

In this study, some interpolation methods were evaluated for estimating groundwater depth in the Iranshahr- Bampour Plain during 2003, 2007 and 2012 in the months of May and October. Data used belonged to 42- 48 wells scattered across the study area. The methods used contained geostatistical approaches of Ordinary Kriging (OK) and Universal Kriging (UK), and deterministic approaches of Inverse Distance Weighting (IDW), Radial Basis Function (RBF) and Local Polynomial Interpolation (LPI). The performance of the prediction methods was evaluated through cross-validation with comparison criteria of determination coefficient (R2), root mean square error (RMSE) and mean bias error (MBE). The statistical analysis showed a high variance and coefficient of variation of groundwater depth and an increase in the average depth to groundwater during bygone years especially during 2003-2007 period. Directional semivariograms were calculated to find out the drift direction. UK method, with the first and second-order polynomials as drift, and different semivariogram models was examined. According to cross-validation results, the best geostatistical method for estimating groundwater depth was OK (with spherical semivariogram) for 1382 and 1391, and UK with J-bessel semivariogram model and second and first drift orders, respectively, for May and October 2007. Moreover, the cross-validation results indicated that LPI, with RMSE equal to 6.94, 5.87 and 8.65 m, respectively, for May 2003, 2007 and 2012, and 6.86, 6.54 and 8.68 m, respectively, for October 2003, 2007 and 2012 is the best method of interpolation among others. The generated maps of groundwater depth revealed a drop in depth to groundwater; therefore, an occurrence of water crisis over the study region during the recent years. Therefore, it is necessary to consider some management scenarios including exploitation control and alteration of crop pattern and irrigation systems for an optimum use of water resources and achieving a sustainable agriculture across the region.