Journal of Applied Research in Water and Wastewater
Volume:9 Issue: 1, Winter-Spring 2022

Zoning of flood hazards in a dam catchment plays an essential role in water resources planning and management. In the present study, nine lithogenic and anthropogenic parameters including slope, elevation, curve number, distance to river, rainfall, geology, soil texture, Normalized Difference Vegetation Index (NDVI) and land use are used to achieve a flood hazard map in downstream of Sabalan dam basin in Ardabil province, Iran. After categorizing the criteria, the layers were weighted by two multi-criteria decision making (MCDM) methods including analytic hierarchy process (AHP), and analytic network process (ANP). The results showed that among the factors affecting flood formation in the study basin by AHP method were the elevation and slope factors with the weights of 0.31 and 0.18 respectively, have the highest effect; however, curve number and distance to river factors with the weights of 0.04 and 0.02 have the lowest effect. Similarly, in the ANP method, the elevation and slope factors with the weights of 0.30 and 0.21 respectively, have the highest effect and the curve number and distance to river factors with the weights of 0.02 and 0.006 have the lowest impact on flood hazard potential in the study area. The results obtained in this study can be useful in achieving sustainable management of water resources.

Widespread use of pesticides and herbicides, and the contamination in river, lake and sea waters have been become a major environmental concern in recent years. A common example of such herbicides is atrazine and its derivatives, which have been widely used in recent years to control pests in agriculture and improve food production and meet the needs of the global population, which is increasing year by year. Most analytical methods are used to determine pesticides and herbicides in the environment which are usually highly reliable and sensitive, but they are often very complex and require advanced tools, and measurements should be performed directly in a lab. Atrazine electrochemical biosensors based on enzymatic biosensors, immunosensors, and aptasensors are reviewed in this study. For atrazine detection by enzymatic biosensors, tyrosinase commonly is used. Phenols and atrazine are the substrates and inhibitor of this enzyme, respectively. These enzymatic biosensors are based on sensing of decreasing current in the presence of atrazine. Immunosensors based on the analyte size generally categorized into two detection methods including competitive and noncompetitive that both of them were used for atrazine detection. The several aptamer sequences were used for atrazine aptasensing that could detect it in nano and picomolar concentrations.

In this paper, the flow in the vicinity of rectangular side orifices placed in main channels is estimated by means of the FLOW-3D model. To reconstruct the flow free surface, the volume of fluid (VOF) approach is utilized. In addition, the standard k-ε and RNG k-ε turbulence models are employed to predict turbulence flow. According to the results obtained from the numerical modeling, the RNG k-ε turbulence model has higher accuracy than the standard k-ε. The analysis of the numerical modeling results proved that this model forecasts the discharge coefficient of side weirs with suitable accuracy. On the other hand, the mean absolute percent error (MAPE) is calculated equal to 12.204%. Also, the maximum pressure is simulated near the main channel bed. Moreover, the minimum pressure is estimated near the flow free surface. Regarding the numerical simulations, the maximum turbulence energy state occurs near the inlet of the side orifice and by increasing the side orifice dimensions the flow field turbulence energy value increases.

Water shortages and pollution are so severe that the last decade has been called the international decade for water. In water treatment plants, coagulation and flocculation are used to remove turbidity. This study examined the use of naturalcoagulants and its efficiency compared with existing coagulants. Response surface methodology was used to design the experiments. Type of coagulant and coagulant aid, as well as pH, were considered important factors during experiments. Results of the tests indicate that pH has a significant impact on turbidity removal. The combination of chitosan and polyaluminum chlirode reduces water turbidity effectively. A combination of polyaluminum chlirode (7.6 mg/L) and chitosan (9.28 mg/L) at pH= 8.52 removed 99.85 % of the turbidity. Accordingly, the combined use of polyaluminum chlirode and chitosan reduced the amount of material and enhanced turbidity removal.

Reference Evapotranspiration (ETo) counted as the main factor for assessing the amount of water, needed for crops as well as for the planning of water resources management. Several techniques, methods, and equations have been used for computing ETo. Thus, required weather data sets are the main challenge for evaluating this factor. FAO Penman-Monteith is the most popular technique to determine the ETo. The FAO 56-PM equation requires accurate weather data like air temperature, humidity, solar radiations, and wind speed. Unfortunately, not all these data are possible to reach easily on the station's side. Therefore, FAO 56 recommended another equation namely Hargreaves-Samani (HS) equation when sufficient weather data may not be available to estimate ETo by FAO56-PM. In the context of this, this study aimed to estimate ETo using the HS equation. For this purpose, historical annual, seasonal, and monthly temperature and wind data were collected from 1981 to 2020 using ‘The Prediction of Worldwide Energy Resources (POWER)’ web portal. It is concluded that the HS method in conjunction with the POWER datasets and spatially mapping with IDW interpolation gave reliable and accurate results of ETo. This technique gives an idea of water losses in a district and demonstrates a trend of historical annual, seasonal, and monthly ETo.

Pollution from industrial effluents is more diverse and complex than municipal wastewater due to the use of thousands of new chemical compounds in industry every year. Subsequent introduction of small quantities of these compounds into water streams through industrial effluents has complicated water pollution problems and posed many challenges in removing contaminants from water. The purpose of the present study was to remove phenol contaminants from the effluent of petrochemical wastewater treatment plants using advanced photochemical oxidation method (ultraviolet/hydrogen peroxide/ozone) in a laboratory scale. The experiments were performed using UVC light, 30 % H2O2 as oxidizer and phenol (100 mg/L). The effective parameters studied in phenol removal included pH, H2O2concentration, solution temperature and UVC irradiation time. The experimental results showed an increase in phenol removal efficiency with increasing H2O2 concentration up to 400 mg/L while decreasing with increasing oxidizerconcentration to 500 mg/L, thus suggesting a concentration of 400 mg/L as the optimal value. Using a flow rate of 200 mg/L of ozone for 80 min, by optimizing other conditions, increased the phenol removal efficiency by 98 %. The phenol removal efficiency was much higher at acidic conditions than at alkaline and neutral ones. The phenol content decreased significantly with increasing contact time. In other words, prolonged contact time increased the phenol removal efficiency in the tested sample. The highest phenol removal efficiency (75.7 %) occurred at the pH value of 4 and the phenol removal efficiency in the sample decreased with increasing pH value. Prolonged contact time caused more phenol concentration to be removed from the test sample, so that 69.8 % of the phenol concentration in the sample was reduced. The results of this study showed that advanced oxidation reduced the phenol content in the analyzed sample. To conclude, the advanced oxidation methods can be useful in the process of treating petrochemical wastewater andeffluent of units containing toxic aromatic compounds such as phenol.

This study aimed to determine the performance of polyculture constructed wetlands compared with monocultures and to monitor plant type influence in treating wastewater. Four pilot scales were used and planted with three plant kinds (Phragmites Australis, Cyperus Papyrus, and Scirpus). Three of them were monoculture systems, and the last one was a polyculture system with all these plants. The filters had identical sizes and the same density. After seven days of retention time, results showed that the pH obtained was around neutral ranging from 6.91 to 7.32; the electrical conductivity increased significantly and it was between 4.47-5.47 mS/cm. Removal efficiencies of phosphate, ammonium, nitrite, and chemical oxygen demand were between 75.29-79.90%, 91.27-92.51 %, 83.33-86.32%, and 84.61-88.52%, respectively. Papyrus filter had the higher removal efficiencies in most of these parameters, and the polyculture system didn’t increase the filter performance; however, the differences between these filters were not significant, except for the electrical conductivity.

The goal of this study was to check the climatological, hydrological, hydrogeological, topographical, and also vegetation cover situation of the wetland by using the google earth engine cloud system and calculation of current and future hydrological water balance of the wetland. For this purpose, data from TRMM, MODIS, Terra, LANDSAT, GRACE, and ALOS satellites were used. The results showed that GEE has a lot of potential and application for preparing time series and monitoring areas where little information is available about its past situation. According to the rainfall of 1.1333 mm3, surface runoff of 12.20 mm3, and evapotranspiration of 13.875 mm3 in the wetland area, the water balance of the wetland is -0.452 mm3. This amount indicates the volume of water that the wetland has based on climatic and hydrological relations. This amount will be equal to 1.4 mm3 in 2040, which shows that the wetland condition will improve in the future.

Water pollution caused by heavy metals due to the increasing growth of industries is very worrying. Among heavy metals, evaluating the effect of silver (Ag) toxicity and its challenges on human and environmental health is very important and fundamental. This paper, for the first time, assessed the ability of palm leaf ash (PLA) as a biosorbent to reduce the amount of water-soluble Ag cations from water. To do so, the effect of adsorbent amount, contact time, initial concentration of Ag ions, pH of the solution, and the temperature was evaluated on the adsorption process. The adsorption process was more consistent with the Freundlich isothermal model and the pseudo-second-order model was in better agreement with experimental data. The results of the experiments showed that the removal percentage of Ag ions and adsorption capacity was accrued from 91.84 to 99.94% and from 25.89 to 52.771 mg/g with increasing pH from 3 to 8 respectively and the enthalpy of the adsorption process (ΔH) was 6996.36 j/mol. Furthermore the removal efficiency of Ag at the initial concentration was obtained at 99.7%, Therefore, it can be concluded that cheapness, and abundance and high sorption capacity are the main advantages of this adsorbent.

In this study, using vine copulas and tree sequences, dependence analysis of groundwater quality variables (Total hardness (TH), Sodium adsorption ratio (SAR), Sodium percentage (Na %) and magnesium (Mg)) was performed. For this purpose, the tree sequence of vine copulas including regular vine (R-vine), independent version of R-vine, also Gaussian version of R-vine, Gaussian independent version of R-vine, canonical vine (C-vine), independent version of C-vine, drawable vine (D-vine) and independent D-vine were evaluated independently in pairwise variables analysis. The study results of dependence structures and tree sequences of Vine copulas showed that among the studied copulas, the performance of the independent C-vine was 3.8 % better than R-vine and 0.25 % (insignificant and negligible) better than D-vine. The tree sequences provided by independent C-vine preserve correlation of pairwise variables until the last tree. In the last tree of independent C-vine, edge correlation of Mg, Na % | TH, and SAR reaches zero. Due to the proper performance of D-vine in dependence analysis of the studied variables, this copula is introduced as the selected copula.

In this study, using vine copulas and tree sequences, dependence analysis of groundwater quality variables (Total hardness (TH), Sodium adsorption ratio (SAR), Sodium percentage (Na %) and magnesium (Mg)) was performed. For this purpose, the tree sequence of vine copulas including regular vine (R-vine), independent version of R-vine, also Gaussian version of R-vine, Gaussian independent version of R-vine, canonical vine (C-vine), independent version of C-vine, drawable vine (D-vine) and independent D-vine were evaluated independently in pairwise variables analysis. The study results of dependence structures and tree sequences of Vine copulas showed that among the studied copulas, the performance of the independent C-vine was 3.8 % better than R-vine and 0.25 % (insignificant and negligible) better than D-vine. The tree sequences provided by independent C-vine preserve correlation of pairwise variables until the last tree. In the last tree of independent C-vine, edge correlation of Mg, Na % | TH, and SAR reaches zero. Due to the proper performance of D-vine in dependence analysis of the studied variables, this copula is introduced as the selected copula.

Flood is inherently an uncertain phenomenon and the certainty and credibility of flood forecasting and warning systems will cause errors regardless of the sources of uncertainty. Extreme rainfall events are one of the most important input data to rainfall-runoff models, which always have uncertainty. Considering this issue the uncertainty of the design flood hydrograph can be investigated for different return periods. In this research first to simulate the flood hydrograph the HEC-HMS model was calibrated and validated based on the hourly flood hydrographs recorded at the basin outlet. Historical data were collected on the 24-hour maximum rainfall of Gharesoo Basin stations with 30-year statistics and the affected basins were identified. Then in each station 30 series of 30 years of artificial data with a maximum 24-hour rainfall were produced. For each of these produced stochastic series the best statistical distribution was fitted and in each series extreme values with a return period of 25 50 100 and 1000 years were calculated. Finally in each return period by combining 30 different amounts of rainfall obtained from stochastic series, the uncertainty bandwidth of the flood hydrograph was obtained during this return period. The results indicated that the highest predicted peak discharge for different return periods was between 1.2 and 1.7 times the historically recorded discharge during that return period. Generally the maximum discharge of different return periods was between 1.5 and 3 times the minimum discharge