فصلنامه مهندسی منابع آب
پیاپی 59 (زمستان 1402)

The sharp decrease in rainfall has reached the peak of drought conditions in Fars province, so that the discharge of all rivers in Fars province has decreased between 70 to 100 percent, and due to the limitation of renewable water resources, there is a need for optimal and sustainable use of existing water resources. All reservoirs of dams in Fars province are necessary.

The main purpose and methodology of this research is to design a mathematical planning model for the optimal allocation of water resources of selected dams in Fars province, in order to net advantage of the system on the planning horizon that issues such as time period, reliability level, course currents, number of dams and consider some scenarios. Accordingly, the objective function of the model seeks the maximum advantage obtained for dams based on the parameters set with three indices of scenario, dam and time period.

At first, this model was considered for 5 users (dams) with 4 different scenarios in 10 monthly time periods, in which case the value of the objective function reached 39863110. Then, in order to analyze the sensitivity of the results and show the change of the optimal answer depending on the dimensions of the problem, the model was implemented for 10 users (dams) with 8 different scenarios in 20 monthly time periods in which the value of the objective function reached 82944240. Therefore, with the increase of the dimensions of the problem, a significant increase in the amount of the objective function and the optimal allocation of water resources of the selected centuries occurs in Fars province. Therefore, due to water shortages and recent droughts in Fars province, it is necessary to pay attention to sustainable and equitable development in planning the allocation of water resources and taking into account various indicators simultaneously.

It is essential to optimize repair, reconstruction and rehabilitation programs of urban water distribution networks for the correct use of limited water resources. The aim of the present study is to implement and compare two artificial intelligence methods to predict the burst rate of water pipes.

In this article, dataset of the pipe bursts in Joopar water network from 2012 to 2017 has been collected. The parameters for predicting of pipe failure includes: material, age, diameter, water pressure and installation depth, and the correlation coefficient of these parameters with the failure rate has been investigated. In order to predict the failure rate, convolution neural network with support vector machine (RCNN-SVR) and fuzzy regression based on c mean clustering (FCMR) have been used. To compare the performance of these two methods, the criteria such as Root-Mean Squared Error (RMSE), Index Of Agreement (IOA), Mean Absolute Percentage Error (MAPE), and coefficient of determination (R2) have been used.

According to the evaluations, RCNN-SVR method compared to FCMR method shows excellent results. Also, the correlation between age and failure rate in asbestos pipes is high and in polyethylene pipes this value is positive but low. The correlation coefficient between pressure and failure rate is also positive for both pipe types.

Soil is an important and effective factor in the emergence and formation of any natural ecosystem and the physical properties of the soil are of considerable importance in determining the characteristics and use of soil. Soil physical properties as part of soil variables have significant effects on runoff production in different watersheds.

In this study, in order to determine the type of relationship between runoff production and physical properties of soil in different land uses of Gachsaran Formation deposits, a part of Kuhe Gach watershed of the Izeh city with an area of ​​1202 hectares was selected. Then, sampling of runoff production at 6 points with 3 replicates and at different rainfall intensities of 45, 60 and 70 mm/hour in three land uses of the range, residential area and agricultural lands with the help of the rain simulator was done. And the same number of runoff sampling, sampling of physical properties of soil such as clay, silt, sand, very fine sand and moisture content was performed. In this study, the relationship between production runoff and soil physical properties in different uses of Gachsaran Formation was determined using univariate regression. SPSS and EXCEL software were used for statistical analysis. 

The results showed that in total, in Gachsaran Formation and in all three range, agricultural and residential land uses and in all three intensities of 45, 60 and 75 mm/hour, very fine sand and moisture were showed the highest of negative relationship with runoff production and silt was showed the highest of positive relationship with runoff production.

Despite the consensus among all experts that water bankruptcy will be the main development challenge in Iran for the coming decades which can threat Iran's regional development and food security; there is still no integrated water-economy-environment index system for allocation of water resources in Iranian provinces. Therefore, the purpose of this study was to investigate the effects of regional water resource allocation in integrated water-economy- environment index on the economic growth of Iranian provinces.

After determining the integrated regional water-economy-environment index based on the recent theoretical and empirical literature, the integrated regional index was estimated for water resource allocations in 31 Iranian provinces using fuzzy comprehensive evaluation method and improved entropy approach. About 55 data titles were collected from various databases including Provincial and National Statistical Yearbooks, Statistical Centre of Iran, Ministry of Industry, Mine and Trade, Agricultural Statistical Yearbook, Agricultural Technical Research Institute. Finally, the effect of regional water resource allocations in water-economy-environment index on economic growth of Iranian provinces was estimated during the period from 2012 to 2018 using Generalized Method of Moments (GMM) approach.

Estimation of the total index with 5 main components revealed that Gilan, Mazandaran, Chaharmahaal & Bakhtiari and Khuzestan provinces can be suggested as the most suitable provinces to implement domestic virtual water strategy. The final results proved that policy making for implementation of virtual water strategy should be conducted regionally and individually based on the status of each province in water-economy-environment components of regional integrated index. Finally, the results of the study indicated that integrated regional water-economy-environment index had a positive and significant effect on economic growth of Iranian provinces.

Effective management in metropolitan planning of urban green space water resources is very important due to the rapid growth of urbanization and the limitation of water resources. The purpose of this research is multi-objective optimization and management of treated wastewater allocation using dynamic system models for urban green space irrigation in Shiraz metropolis.

The factors affecting the supply of water resources and irrigation of the green spaces of Shiraz city have been simulated and according to that, the consumption forecast and the number of available resources and the allocation optimization have been presented. Also, in the current research, effective factors in the current and future conditions that can affect the proposed model have been taken into consideration, and two scenarios have been applied, including increasing the efficiency of green space irrigation and the use of treated wastewater.

The results showed that increasing the efficiency of irrigation through management of transfer, storage and distribution of water and also irrigation at the right times has a much greater effect compared to the use of purified wastewater in order to reduce the extraction of limited resources. In such a way, by increasing the irrigation efficiency by 40% and 50%, respectively, 14% and 39% of water shortages will be solved.

The simulation results showed that in order to achieve the stability of the system, a combination of scenarios of reducing per capita water consumption in green spaces, increasing irrigation efficiency, using purified wastewater and dry landscaped spaces should be considered in the development of urban spaces.

An artificial neural network (ANN) is a powerful data-driven tool capable of learning the linear and nonlinear relationships governing different systems. However, determining the best-performing algorithm in terms of convergence speed and accuracy for a particular problem is still a fundamental challenge for users of artificial neural networks.

We investigated the most effective algorithm among widely used processes to simulate and estimate nonlinear water quality parameters. For this purpose, we constructed 42 models combining artificial neural network topology (single or multilayer) and training processes. The quality parameters’ data acquired at 107 wells throughout the aquifer of Qorveh-Dehgolan plain were used for training (data from 1996 to 2013) and to test (data from 2014 to 2016) each model.

The results showed that artificial neural networks with a hidden layer that benefits from the optimal number of neurons could simulate the aquifer behavior with high accuracy and in less time. Also, increasing the number of hidden layers while increasing the response accuracy increases the number of optimal network neurons and the duration of the problem analysis. Finally, artificial neural networks based on the Broyden-Fletcher-Goldfarb (BFG) method had the highest efficiency in simulating aquifer behavior, although the performance of the Levenberg Marquart (LM) method is very close to BFG. BFG is more efficient than LM due to its lower Mean Square Error and Standard Deviation (3.46 and 3.09, respectively).