فصلنامه مهندسی منابع آب
پیاپی 53 (تابستان 1401)

Local scouring that occurs due to human construction of structures in the course of rivers flow can lead to erosion of the river's bottom and threatens to change the natural flow of the river. One of the indirect methods of reducing scouring is the use of protective structures.

In this research, the effect of protective sheet length on the scour depth reduction of cylindrical base was investigated.

The results of the experiments showed that the laying of protective plates could reduce the scour depth to 69.50%. Also, the best relative length (the length of the protective plate to the width of the bridge base, L / b) of the protective plates is equivalent to one, and with the increase in the length of the protective plates, the effect of the plate length on the scour depth reduction was reversed, so that reducing the scour depth for the relative length of 5.0 and 2 are respectively, 50% and 60% more than the control (without protective plates), and in all experiments, the relative depth of scour has increased with increasing the flow rate.

Volumetric delivery of water by installing smart water meters on the agricultural wells could be an effective action for proper use of water and increase the water productivity. In recent years, the smart water meters were used at Arsenjan plain in Fars province for volumetric water delivery.

In this study, the applied water and the water productivity in some of the Arsenjan plain farms and gardens were evaluated. Twelve farms were selected for each of the three products; winter wheat, tomato and pomegranate. Well discharge, crop yield, volume of applied water was measured using smart meters. The actual values were also measured. The values of irrigation water productivity and total water productivity was calculated. The differences between applied water and some water requirement scenarios were compared using t-test.

Results showed that the values of applied water and discharge in the smart meters were 21 and 25 percent less than the actual measured values, respectively. Therefore, the performance accuracy of the studied smart water meters was low. The average irrigation water productivity of wheat, tomato and pomegranate was 0.93, 7.75 and 1.44 kg/m3, respectively. The average applied water in the studied farms and gardens were 43 percent more than the required values estimated by Penman-Montieth method. Finally, it was suggested that in order to improve the performance of smart meters, the calibration of these meters should be considered more carefully.

Streamflow simulation is one of the most important issues in the field of hydrology and water resources. Forecasting of runoff in future periods can determine the rate of flooding and also the increasing and decreasing trend of river discharge. There are various methods to simulate or predict runoff rates, including statistical methods, rainfall-runoff models and artificial intelligence. In this study, three models consisting of neural network, IHACRES and linear regression were used to estimate runoff in Tashk-Bakhtegan basin and evaluated using statistics such as correlation coefficient, coefficient of determination and other error indices. The results showed that runoff and precipitation have a non-linear relationship and therefore, the linear regression model cannot be trusted to estimate runoff. The results also showed that, in general the neural network model due to the nonlinear relationship between precipitation and runoff compared to the other two models have good performance in estimating monthly runoff in Tashk-Bakhtegan basin.

Investigating the spatial variability of runoff and its influencing factors to provide solutions to reduce it is very important. In recent years, many theoretical and field studies have evaluated the spatial production of runoff as heterogeneous.

In this study, to investigate the affecting factors in runoff production of the slope main aspects (northern, southern, eastern, and western) of the Gachsaran and Aghajari formations were selected a part of the Gach Kuhe and Margha watershed in Izeh city. For this purpose, a rain simulator was used in both formations at 16 points with 3 replications at rainfall intensities in 1 and 1.25 mm/min. Also, soil factors of Gachsaran and Aghajari formations such as percentages of gravel, sand, silt and clay, pH, soil salinity, moisture, calcium carbonate, organic matter, and sodium content were investigated. SPSS 17 and EXCEL 2007 software were used for statistical analysis.

The most important factors affecting runoff production were identified using multivariate regression. The results showed that runoff production in Aghajari Formation is more dependent on soil chemical properties, but runoff production in Gachsaran Formation is more dependent on soil physical properties.

Density current is one of the most important factors in the sedimentation process of dams. Increased sediment will reduce dam storage capacity and makes significant challenges for relevant engineers. Therefore, understanding the dynamics of density fluids and related sediment patterns is very efficient for dam reservoir management.

The purpose of this study was to create an intelligent model with appropriate adaptation to laboratory data so that, it can be used in future designs with different variables. Therefore, in this study, the percentage of reduction of density salt current head under the influence of trapezoidal permeable obstacles (aggregates with a diameter of 1 cm), taking into account variables such as discharge, slope, concentration and height of obstacles in laboratory.

Based on the results, the density salt current head was modeled using the artificial neural network feed-forward method and the classical multivariate regression method, and the performance of these two methods was compared. The results showed that the intelligent feed neural network intelligent method in modeling the percentage reduction of density salt current head is significantly superior to the multivariate regression method so that the training, calibration and test regression values ​​ are 0.99, 0.98 and 0.98 were obtained for neural network and 0.92, 0.91 and 0.91 for multivariate regression, respectively.

The performance of the artificial neural network is much better than the multivariate regression method.

Water conflict is a major challenge that, if left unmanaged, will become a security issue. Although tensions over water have increased, conflicts over shared water resources are more likely to happen. The study aimed to investigate water conflict and its management strategies among farmers.

The descriptive-survey research method was used. The data-gathering tool was the questionnaire, which its validity was verified through face validity. The study population included farmers who used shared water wells to provide water for agriculture (N=478). Using Cochran's formula, the sample size was 214 farmers who were selected by the simple random sampling method. Data were analyzed using SPSS software.

The results showed that “drought” and “increasing number of farmers”, with an average score of 3.56 and 3.45, respectively on a scale of 1 to 5, are considered as the main causes of agricultural water conflict. From the farmers’ view, the priority for reducing water conflicts was the participation of farmers in managing water wells and negotiating with farmers around the water. On a scale of 13 to 65 with an average of 38.51, the perceived agricultural water conflict was at the medium level. By increasing farm distance from the well, area of agricultural rental land, and annual income from non-agricultural activities, the perception of agricultural water conflict increased. However, by increasing owned agricultural land area and agricultural income, the perception of agricultural water conflict decreased. The main strategy used by farmers to manage agricultural water conflict was “control”, in which coercion and force are used to manage conflict. The “problem-solving” and “avoidance” strategies were the second and third priorities, respectively.

Scouring depth due to dam break flows as one of the important engineering problems can be investigated numerically by means of an appropriate multiphase model. Smoothed Particle Hydrodynamic (SPH) model is a Lagrangian Mesh-free based method that has been introduced to solve such complicated flows.

A Multiphase version of this model is modified in this study to predict scouring depth after dam break flows. At first, the introduced model is validated via comparing the results with experimental data and it is confirmed that the model can well predict turbulent multiphase flows. Then, the performance of a scour protection structure with different length and heights is simulated against dam break flow to find an optimum geometry for this structure.

Based on the results, it is concluded that the effect of structure height on scour reduction is more sensible than the effect of structure length. In contrast to the structure length, a small edge at the end of the protective structure can efficiently decrease the final scoured depth. However, there exists an optimum height with the best performance. A too high scour protection structure can even result in a higher scouring depth than an unprotected case. Therefore, it is necessary to use a protection structure with an appropriate height and the introduced model can be utilized as a helpful tool to check the required performance of this structure.

The main problem downstream of hydraulic structures, such as weirs, is scouring and movement of bed materials.  The piano key weirs (PKW) is one the types of weirs. Due to the fact that the geometric shape of the weir affects the condition of the downstream scour, therefore in this study, the downstream scouring of the piano key weirs with a trapezoidal geometric shape is studied. In this paper, the scour profile and the rate of change were compared with the change in the lateral wall angle of the weir.

For this purpose, four experimental models of this type of weirs were made and these models were tested in a laboratory flume at different flow rates. Also, to investigate the effect of tail water depth on scour profiles, one of the models was investigated at three different tail water depths.

The results of scouring characteristics showed that in trapezoidal piano key weirs, the maximum depth of the hole is created under the output key and by increasing the discharge and decreasing the tail water depth, the geometric dimensions of the scour hole increase in trapezoidal models. Also, in trapezoidal piano key weirs, by increasing the side wall angle of the weir, the geometric dimensions of the scour hole are reduced. In all flows, by increasing every 3 degrees of the side wall angle of the piano key weir, maximum scour hole depth on average, 5%, Spatial position distance, maximum scour hole depth and scour hole span length, respectively, and it decreases by 8% and 3% on average. Also, when Frd>65% is, this difference becomes insignificant and there is not a significant difference in the shape of the scour hole for PKW models.

Recent droughts and over-harvesting of wells have caused a drop in the level of underground water resources in many plains of the country. This research was conducted in order to investigate and provide corrective methods for determining the permissible hours of pumping agricultural wells in the Asadabad plain of Hamedan.

In this research, the cultivated area of horticultural and agricultural products was prepared during a 5-year period. The water requirement of different crops for the Asad-Abad plain was extracted from the National Water Document and the gross irrigation requirement was calculated by considering the average irrigation efficiency of the plain. By dividing the gross irrigation requirement by the maximum three-month hydromodule, the allowed hours of well operation per month were calculated. The calculations were done considering the main plants of the cultivation pattern and the total plants of the cultivation pattern in order to influence the cultivation pattern.

The average number of annual pumping hours for the Asadabad Plain, taking into account the average hydromodule of three months (June, July and August), was calculated as 3455 hours, which is about 15% more than the hours considered in the Asadabad Plain. The effect of annual changes in the cultivation pattern on the number of working hours of the wells was significant at the 5% probability level. The results of two modified methods of calculating pumping hours caused an increase of 26 to 33% in the annual working hours of wells, which is closer to the existing reality.