فصلنامه مهندسی منابع آب
پیاپی 54 (پاییز 1401)

Assessment of groundwater quality and quantity variation in drought and semi-drought region are of most interest especially in Iran. This research is going to analysis salinity reasons by ground water quality mapping in the Khafr plain.

To do this the principal components of water quality extracted in spring and autumn seasons. Then Spline, IDW and Kriging interpolation techniques were fitted and evaluated for mapping. Finally, the best model was determined and ground water quality mapped using principle components.

Kriging recognized as the best model for autumn. The first component with high coefficients on TH, K, Mg, Ca, SO4, TDS, EC showed maximum values in the center and eastern south of the region. For the second component (SAR, Cl, Na) maximum values observed at the eastern south as well. The third component (PH) increased from center to the north and western north and decreased from center to the south and eastern south, and for the Forth (HCO3) maximum observed at the north and minimum in the eastern south. Spline method recognized as the best model in spring season. The first component (SAR, Cl, Na) showed maximum values in the eastern south of the region. The second (Th, Mg, Ca) maximum values observed at the center and the third component (PH) maximums in the west. Forth component (HCO3) maximum valued observed in the center and western north. Finally, the reasons of spatial and temporal variation of the components analyzed.

Rainfall and runoff process is one of the main phases of the hydrological cycle and is simulated using hydrological models to examine the relationship between rainfall and runoff. The accuracy of the runoff estimation depends on the input parameters of the hydrological model including the sub-basins Curve Number (CN), Initial abstraction (Ia) and Lag time (Lt).

In this study, to more accurately estimate the simulated discharges computing through the hydrological model HEC-HMS in Mahabadchay watershed, the input parameters were calibrated. For this purpose, two evolutionary algorithms including Particle Swarm Optimization (PSO) and Simulated Annealing (SA) were used. In each iteration, the basin hydrological parameters are estimated using optimizer and given to the simulator. Afterwards, simulations are made. The Root Mean Square Error (RMSE) was used as objective function. The AutoIt software was used to automatically couple the optimization algorithms with HEC-HMS model. The rainfall-runoff data related to the 5 events of year 1387 were used to calibrate and validate the optimal parameters.

The results showed PSO convergence speed is more than SA algorithm in finding optimal objective function value and calibrating the hydrological parameters including CN, Ia, and Lt. Also, the optimal computed hydrograph found by SA algorithm had good agreement with that of by PSO one. Considering the results, it is concluded that the hydrologic parameters of watersheds without data can accurately be estimated by linking optimization and hydrologic models.

Density current is one of the factors influencing the transfer of sediments to reservoirs of dams. One of the practical methods to control sediments is to build an obstacle in the path of these currents.

In this laboratory research, the behavior of the Density current under the effect of cylindrical obstacles made of wood with a diameter of 1.5 cm and a height of 30 cm (more than the height of the body of the Density current) was evaluated. Therefore, by considering variables such as floor slope, concentration and discharge, the values of the density current head were determined. Machine learning algorithms such as adaptive neural fuzzy inference system and artificial neural network were used to model the results.

Based on the results, the density salt flow head was modeled using machine learning algorithms such as adaptive fuzzy neural inference system and artificial neural network and the performance of these two methods were compared. The results showed that machine learning algorithms are useful in modeling the density salt flow head. And the regression of the adaptive neural fuzzy inference system for the training and test data was 0.99 and the regression of the artificial neural network was 0.94 and 0.91, respectively.

By comparing the two methods, it was found that the adaptive neural-fuzzy inference system is more effective in modeling the percent reduction of the head of Density current than the feed-forward artificial neural network method.

Impulsive waves (i.e., tsunamis) can be generated by sudden displacements of volumes of water induced by earthquakes, landslides, and volcanic eruptions, impacts of asteroids and gradients of atmospheric pressure.

we present a new method for numerically modelling landslide-generated tsunamis in OpenFOAM® by using a new approach based on the Overset mesh technique. This technique, which is based on the use of two (or more) numerical domains, is new in the coastal engineering field and appears to be extremely powerful to model the interaction between a moving body and one or more fluids. Indeed, the accurate resolution around the moving body (i.e., body-fitted approach), guaranteed by this method, and offers a great advantage to study the momentum exchange between the body and the water.

The results have been presented for the dimensionless distance and the normalized geometry of the landslide in the range 5 to 7, 1 to 2, respectively. These numbers have been normalized by the aid of the height of the landslide (a). According to the results of simulations, the tsunamis process is divided into three stages, which were analyzed in details with considering the interactions between the solid and the water reservoir.

The expansion of industries in the world, the limitation of resources and the increasing consumption of water have led researchers to pay more attention to wastewater treatment than in the past. Wastewater treatment is done in order to stabilize the produced organic matter, reuse water and solid materials resulting from wastewater treatment, and also to be able to discharge the waste water into the environment and protect the environment.

This research has been investigated with the method of biological treatment information modeling using fuzzy logic. One of the cost-effective methods for purifying the sanitary wastewater of the refinery is modeling using the fuzzy logic method. Fuzzy inference systems are a popular computing framework based on the concept of fuzzy sets, if-then rules, and fuzzy reasoning. This category of systems has a successful application in the fields of automatic control, data classification, decision analysis, expert systems, time series prediction, robotics and pattern recognition. In this research, MATLAB R2012 software has been used for fuzzy logic modeling by Mamdani method. Information obtained from the tables in the article "H.A. Hegazi. 2013".

By examining all the diagrams and models, we found that the modeling done is reliable and can be used to obtain the results of other experiments without conducting experiments. Also, the best operating conditions can be called rice husk adsorbent concentrations of 50, 60, 60, 60, 60, for the removal of Fe, Pb, Cd, Cu and Ni metals. For the ash absorbent, the absorbent concentrations of 60, 60, 60, 50, and 60, respectively, were called optimal absorbent concentrations for metals. Also, among the two absorbents, rice husk is a better absorbent. The accuracy of the model was reached around 95% and proved the reliability of the model. It can also be concluded that ash and rice husk worked very well as natural absorbents and the removal efficiency was up to 90%.

Due to rapid expansion of population, there is an increase in the number of water users. As a result, optimal water allocation has become a pivotal issue. System dynamics is a suit methodology for simulating and representing of water availability in complex condition and impacts of water resources usage over time. In this study, a dynamic water allocation model within Vensim GUI was developed for the agricultural and environmental water resources of Khamiriza catchment.

The model consists of two separate sections; the first part is a water balance module which is designed to provide surface water and groundwater simulations; the other part is a water allocation sub-model. After the development of the model, the water balance simulation optimized by optimizing the surface water and groundwater against observed data.

The water use policy includes the conjunctive use of groundwater and surface water to meet drinking, industrial, agricultural, and environmental demands. The results suggest that under current situation the quantity of available surface and groundwater could be insufficient to meet the demands of different sectors within the basin. Therefore, a scenario containing improved irrigation efficiency and 30% of the land in fallow may lead to the allocation vulnerability.

The results of this application indicate that system dynamics can be considered as an innovative tool in the planning and allocating water resources. Moreover, conjunctive use of groundwater and surface water resources may lead to a better water allocation policy.

Desiccation of Urmia Lake in the last two decades and saline dust emission from its dry bed has become an environmental crisis in the northwest of Iran. The main purpose of this study is the modeling of the deposition rate, transport pathway and emission height of saline dust over Urmia Lake based on near surface winds.

In this regard, observed severe winds around the lake were analyzed. Subsequently, by matching of strong winds with MODIS satellite AOD products, a number of dust storms generated over Urmia Lake were selected and then storm generation date and location determined. In next step the HYSPLIT model was run in forward mode for 18 hours. To assess the model results, its outputs were compared with synoptic maps.

Results showed that although strong winds are possible from all directions, but the prevailing directions are from the south, southwest and north respectively. Modeling results showed that saline dust diffusion is possible in all directions, and also transporting pathway, deposition rate and mixed layer height of saline dust can be different in terms of surface winds characteristics and especially upper levels atmospheric currents. Based on the results the emission path of the salt dust is more in line with upper levels winds, and raising particles may be emitted a distance of ~200 kilometers in 18 hours. Eventually, raising top height of saline particles could up to 4000 meters according to the intensity of ascending fluxes.

Rainfall-runoff modeling is considered one of the important methods in the study of hydrology and environmental management, especially in urban areas, in which sudden floods lead to significant financial and human losses. Thereupon, various models have been developed for urban flood simulation, among which selecting the best, is of significant consideration in the literature.

Runoff peak flow and hydroghs measured in three nodes of an urban drainage network were applied for both spatial and temporal evaluation of the SWMM hydrological model in EPA SWMM, ASSA and Bently SewerGEMS V8i softwares. Other rainfall-runoff models also evaluated were SCS TR-55, SCS TR-20, Rational, Dekalb Rational, Santabarbara UH models (in ASSA software) and SCS UH model (in SewerGEMS V8i software). The models were calibrated considering the measurements during three precipitation events, and then validated by the measured data of three other events. The Nash-Sutcliffe coefficient along with the BIAS coefficient, the Coefficient of Determination and the Root Mean Square Error were used as the efficiency indicators.

The measured runoff peak flow and hydrograph were most compatible with those simulated by SWMM models of EPA SWMM, SewerGEMS V8i and ASSA softwares, respectively. Regarding the results of the partial parameter and the Spearman correlation coefficient methods, model outputs were most sensitive to the percentage of impervious areas, equivalent width, roughness coefficient of impervious areas, the depth of depression of impervious and pervious areas, the percentage of impervious areas without surface storage and the curve number, respectively. The model was not sensitive to the roughness of the permeable areas. The results suggest EPA SWMM as the software with more reliable simulation results for runoff management projects in the study area and urban basins alike.