نشریه پژوهش های نوین در مهندسی آب پایدار
پیاپی 2 (پاییز و زمستان 1401)

In this study, using the copula-based approach, the simulation of the flood discharge in the Karun River has been studied. In this regard, the flood in 11/30/2008 of the Karun River was used. Using the Nakagami and generalized Pareto marginal distributions, various copula functions were investigated, and the results showed the superiority of the Clayton copula with a parameter value of . According to Clayton copula and marginal distributions, the analysis of the frequency of occurrence of the pair variable of inflow and outflow hydrographs was carried out, and the results led to the presentation of a typical curve regarding the estimation of different values ​​of the outflow hydrograph corresponding to the values ​​of the inflow hydrograph. This curve can simulate the output values ​​of the hydrograph with different probability and based on the input values. Copula-based simulation, according to the conditional density of copula functions showed that the correlation coefficient of the simulated values ​​is 7% higher than the observed values. The accuracy and certainty of simulating the output values ​​of the hydrograph was also confirmed according to the violin plot. The results of this research showed that the copula-based simulation model has a high efficiency in simulating the output flow of the flood hydrograph. The results of the copula-based simulation, based on the root mean square error and Nash-Sutcliffe statistics, showed an error rate of 35.93 cubic meters per second and an efficiency of 0.96, respectively. The conditional density used in this research led to the presentation of a proposed equation regarding the simulation of the flood hydrograph outlet under the condition of the occurrence of the flood hydrograph inlet in the study area with an efficiency of 66%.

This research was conducted with the aim of investigating the snow cover changes in the northwest of Chaharmahal and Bakhtiari province (Kohrang region) in the second decade of the 21st century (2014 to 2020) and comparing it with the average snow cover in the last decade of the 20th century. For this purpose, the images of Landsat 5 and 8 satellites for  February from 2014 to 2020 and also four passes in the years 1991, 1995, 1997 and 2000 (to calculate the average snow cover of the last decade of the 20th century) were analyzed. The amount of snow cover was calculated using the normalized differential modified index of snow cover (NDSI) index. The results of the NDSI showed that the lowest amount of snow cover is 1363.8 square kilometers in 2018 and the highest is 4263.7 square kilometers in 2014., The results also showed that the amount of snow cover in the investigated years in the second decade of the 21st century decreased by 14% (in 2014) to 72.5% (in 2018) compared to the average snow cover in the last decade of the 20th century. The results of Mann-Kendal analysis of trend in snow height at the Kohrang station also indicate a significant decrease in snow height by 78 mm per year in January and 151 mm per year in February

Estimating runoff due to rainfall is a very important step in planning water resources, especially in watersheds without hydrometric stations. In this study, the rainfall-runoff simulation of Akhola station located in the Ajichai basin was discussed and the most suitable rainfall-runoff model was presented by using data mining methods and comparing their performance. For this purpose, the desired data (rainfall, discharge, temperature) for this study were received monthly from the water and meteorological organizations of the East and West Azerbaijan provinces. Random Forest and Artificial Neural Network data mining models were used for simulation. The comparison of observed monthly runoff values with monthly runoff estimated by models was done using evaluation criteria. In this study, CC values ​​(correlation coefficient) for test sets in the random forest model and artificial neural network were determined as 0.77 and 0.86, respectively. The analysis of the results showed that the ANN model has a higher performance and efficiency than the RF model for the Akhola station. Among other results of this research, we can mention the time series of rainfall and runoff of the station during the last 20 years. According to the obtained graphs, during these 20 years, there was no clear trend for precipitation in the Ajichai basin, and the time series graphs showed that the precipitation in these areas was fluctuating. But the time series for Ajichai discharge at Akhula station showed that a completely downward trend was recorded for the river water flow, which is the reason for the decrease of the discharge entering Lake Urmia and the lowering of the lake water level.

Precipitation is one of the basic elements of Hydrometeorological studies. Due to the limited number of rain-gauging stations and the lack of meteorological stations in highland area, the use of satellite rainfall products as an effective tool in predicting the regional spatial distribution of precipitation data has attracted the attention of researchers. But its disadvantage is the high estimation error of rainfall estimation, which requires accuracy evaluating before using. For this purpose, based on the rainfall data of 21 meteorological stations of Mazandaran province from 1998-2018, the performance of TRMM data and two interpolation methods of kriging and inverse distance weighting were investigated. The results showed that contrary to the proper correlation of TRMM data with observed data, this network has a high bias error. For example, in the case of annual rainfall data, the network bias error reached 70 mm, which is approximately 30% of the annual error. The modification coefficients of TRMM data were found between 0 and 2, that most of the coefficients were higher than one, which indicates the TRMM data in Mazandaran mostly has an underestimation error. The comparison of modified TRMM with the interpolation methods showed that using the modified network instead of interpolation methods in estimation of rainfall data reduces the mean square error of annual rainfall from 237 to 186 mm.

Indiscriminate extraction of groundwater resources as an essential resource for drinking purposes, especially in arid and semi-arid regions, threatens the quality of these resources. Low quality of groundwater because of infiltration of salt water into aquifers, affects human health, so evaluating groundwater quality is important. In this paper the results of evaluating groundwater quality for drinking purpose in birjand aquifer, located in South Khorasan province, by using the pollution index of groundwater (PIG), have been explained. In this study, the qualitative data of PH, TDS, Mg, Na, Ca, Cl, NO3, F, HCO3, SO4, K related to 20 wells for 2019-2020 were collected. In order to calculate the PIG, the parameter map was prepared using the appropriate interpolation method (Kriging and IDW) based on the RMSE and R2 in ArcGIS and the WHO standard was used as a guide. Due to the existence of local effects of various parameters and the existence of some dominant quality parameters in the samples, to increase the accuracy of the PIG model, the Analytical Hierarchy Method (AHP) was used to modify the weights and develop a local optimal index. The computed values of the revised pollution index map (LPIG), varied from 0.8 to 5.5, and divides the quality level of the aquifer into 5 classes with insignificant, low, moderate, high and very high pollution, It covers 9.7%, 15.5%, 35.9%, 23.9% and 1.15% of the area, respectively. A high pollution in the western and southwestern areas of the aquifer is attributed to agricultural activities in these areas.

Population increase, urbanization and consequently increase of impervious surfaces has caused an increase in the volume of urban runoff and this increase in volume causes problems in the runoff collection networks, which are one of the most important infrastructures for urban flood control. In this research, with the help of vulnerability and reliability indicators, the performance of the surface water collection network in the district 10 of Tehran Municipality was evaluated. In this regard, by using SWMM urban flood simulation model, the studied area was simulated hydraulically and hydrologically under the historical precipitation data of Mehrabad synoptic station, then by using vulnerability and reliability indicators, the performance of the network under the return period 2, 5 and 10 years were evaluated. The results indicate that the system vulnerability increases significantly with increasing the return period of the design. Also, the decrease in reliability of system by increasing return period indicates the increase of flood channels.

Uncertainty in the planned water demand and changes in the roughness values ​​of the pipes are among the common cases of unfavorable performance of water distribution networks. In this research, a model has been developed to optimize networks that have been implemented but need to be strengthened under conditions of uncertainty. In this model, the EPANET simulator model was combined with optimization genetic algorithm in MATLAB programming environment. In such a way that it is first created using the concept of fuzzy logic, fuzzy membership functions of the input parameters(nodal demand and pipe roughness coefficient), then by considering the relationship between demands and pressure head requirements at nodes and using (Gupta and Bhave 2007) impact method The fuzzy optimization model is converted to a deterministic model and finally, the diameter of the pipes that should be installed parallel to the existing pipes is obtained by using the genetic algorithm. The method created for a typical network from past researches is checked by changing the uncertainty level, the results indicated a 28% increase in the cost of the network with a 50% increase in considered uncertainties and a 7.5% decrease in cost by applying a tolerance of 0.75 meters in the desirable pressure head. The proposed method based on the genetic algorithm is completely suitable and creates a solution that provides the required pressures in the worst situation variables.

In crisis management, flood risk is one of the riskiest natural disasters that have to special look to it. One of the most important tasks in the field of flood mitigation and prevention of occurrence is zoning of potential flooding and classification of the flood risk. To prevent the occurrence of floods, it is necessary to identify areas having high potential for this phenomenon. Because the area of Ravansar is highly flood-producing and because of financial as well as physical damages caused by floods each year, we need to identify risk areas. The present study seeks to offer a method for zoning the flood-producing potentials of Ravansar. According to the research objectives, ArcGIS and AHP were used to investigate the flood-producing potential of study area. For this purpose, slope, elevation, NDVI, rain, distance from stream and land use as effective parameters in flooding in the studied were selected. After the experts familiar with the watershed completed the questionnaire, these parameters were weighted. Using the results of weighting, the flooding potential zoning map was then calculated. Based on the results flood hazard potential was zoned and finally, the was categorized into five classes based on flood hazard risk, southern part of Ravansar have been introduced as areas prone to flooding that are included respectively %24/8 and %21/6 of the area with low permeability and slow slope (0-5 degree), low altitude (1126-1508 m), near from the stream, low NDVI, high rain (814 millimeter) and urban land use to the other sectors.

Drought is a situation of lack of rainfall and an increase in temperature that can occur in any climate. Meteorological drought in the long term leads to the reduction of water resources through the reduction of surface and groundwater flows. Knowledge of the propagation time of meteorological droughts to hydrological and hydrogeological droughts is very important in managing and planning water resources. This study investigated the time delay of hydrological and hydrogeological droughts compared to meteorological droughts in the Nazlou Chay sub-basin in the west of the Lake Urmia basin. For this purpose, three drought indices SPI, SDI, and GRI were used based on 30-year rainfall and discharge data and 18-year piezometric data. The results showed that hydrological and hydrogeological droughts have a significant correlation with meteorological droughts in the study area. On the other hand, the time required for the propagation of meteorological drought to hydrological drought in the study area is 6 months on average, and the propagation time of meteorological droughts to hydrogeological droughts is 17 months. However, in the case of hydrological droughts, the precipitation factor explained a small percentage (15 percent) of the variance of the hydrological drought index, and therefore climatic factors other than precipitation (such as temperature), basin characteristics, or human factors contributed more to the changes in hydrological drought.

Plastic particles (microplastics and nanoplastics) are considered as an emerging pollutant and a serious threat to the environment which are distributed all over the world. The presence of plastic particles in various ecosystems, especially aquatic environments, is very life-threatening to diverse organisms. Therefore, it is urgently needed to find an effective treatment technology or to develop and improve conventional treatment technologies for the removal of microplastics and nanoplastics. So far, the scientific community has carried out some research on various options for treatment and removal of plastic particles. Currently, multiple technologies have been developed by researchers, including physical, chemical and biological, among which, few have shown good efficiency for removing microplastics and nanoplastics. Filtration technology has a various removal efficiency, but a relatively high cost due to membrane fouling and replacing new filters. The magnetic absorption and separation process is also considered as a simple removal method; however, the addition of absorbents may cause secondary pollution. Likewise, there is a similar problem of chemical residues in the chemical precipitation and oxidation techniques. In contrast, biodegradation technologies are often of a low degradation efficiency. In this review, major techniques for the removal of plastic particles and the mechanisms, efficiency, advantages, and disadvantages of these technologies have been discussed.

In recent years, the use of soil amendments with the aim of improving texture or increasing water capacity has become popular. This can affect the physical or chemical properties of the soil. In the present study, changes in electrical conductivity and soil permeability due to the addition of biochar and betonies were investigated. For this, 13 samples with two levels of 2% and 3% walnut wood biochar at two temperatures of 400°C and 600°C, were prepared, together with three levels of 2%, 5% and 10% bentonite and one soil sample without materials was used. The samples incubated for five months. The t-test was also used to check the difference between the samples. The results showed that both biochar and bentonite are able to significantly increase EC and decrease soil permeability. The average permeability value for samples with 2 and 3 percent biochar is a quarter of the permeability of soils without amendment. Adding bentonite to the soil reduced permeability such that the permeability of samples containing 10% bentonite (0.25 mm/min) was approximately ten times lower than that of the control sample (2.6 mm/ min). The electrical conductivity value in the samples with 10% bentonite is more than 4 times higher than in the soil without amendment, and in the samples with 2 and 3% biochar, it is on average about 2.3 times higher. Considering the increase in soil electrical conductivity, it is recommended to use biochar and bentonite with more accuracy.