JWSS - Journal of Water and Soil Science

The goal of this study was to evaluate tannic acid as a coagulant in turbidity removal. Tests were designed using Taguchi method and carried out on the synthetic and natural turbid samples. In order to optimize turbidity removal by tannic acid, seven factors including pH, coagulant dosage, rapid mixing rate, slow mixing rate, slow mixing time, sedimentation time and initial turbidity were investigated. The results revealed that in optimum conditions,  tannic acid could n remove up to 71 percent of synthetic turbidity and 66 percent of natural turbidity; also, tannic acid showed more coagulation activity in the lower initial turbidities. ANOVA analysis showed that initial turbidity and slow mixing time were the most important parameters in the turbidity removal by tannic acid. In general, this study showed that tannic acid was capable of removing turbidity and could be used instead of common coagulants in the preliminary treatment.

Urban and industrial wastewaters are considered as the most contaminant of surface water. Entrance   of these pollutants to the river reduces the concentration of dissolved oxygen and aquatic life will be threatened. So, one of the main qualitative characteristics of water resources management is the concentration of dissolved oxygen. The base of the   developed model in this investigation is the convection- diffusion equation in soil. Terms of production and decay of dissolved oxygen were added to this equation. The final equation was discretized using the finite difference method with the implicit scheme. With applying the initial and boundary conditions, the equation set was solved by the Thomas algorithm. The calculations were done by programming in the MATLAB software. For the calibration and validation of the model, data obtained from two reaches of Zayanderoud River, including steel melt and Mobarakeh Steel factories, were used. The temporal and spatial variations of the dissolved oxygen were plotted and compared with the real data and the results of the MSP and CSP models. The results showed that the concentration of the dissolved oxygen could be well predicted through solving convection-diffusion equation with introducing two terms for the decay and production of oxygen. The comparison between the results of the model and two other models showed that the model led to better results in comparison to the MSP and CSP models.

Detergents are the main organic pollutants in the industrial and domestic wastewater. Electro-chemistry methods are advanced purification methods developed with high efficiency features. The goal of this study was to investigate the possibility of using electrocoagulation and the complementary flocculation process to achieve the highest removal efficiency of the detergent COD. So, with iron electrode, synthetic samples at the concentrations of 500, 750 and 1000 mg/l (with COD of 217, 268 and 370 mg/l, respectively) and with the initial pH levels of 5, 7.3 and 9 were tested. Variable parameters during the electrocoagulation process included the current duration at 3, 5 and 10 minutes, and the current density was at 4, 10, 16 and 22 mA/cm². The primary results showed that in the optimum conditions, the coagulation process and complementary flocculation could reduce the sample’s COD with an initial concentration of detergent (500 mg/l) from 217 mgO₂/l to 81.30 mgO₂/l. The electrocoagulation method could reduce the chemical oxygen demand to below the standard limit of environmental discharge (200 mgO₂/l) and compensate for the possibility of the irrigation of green spaces due to water shortages.

Nowadays, environmental pollutions especially water pollution is increasingly developing. One of the problems of entering the pollutants to rivers is reduction in the concentration of river dissolved oxygen. In order to manage the water resources, amount of dissolved oxygen should be predicted. This study presents a novel equation for simulating the concentration of river dissolved oxygen by adding the oxygen production and consumption in the river factors to equation for transmission-diffusion of minerals in the soil. The resultant equation was separated in finite differential method and by using implicit pattern. Calculations were done by encodings in MATLAB software. In order to calibrate and confirm the dissolved oxygen model, data derived from Zayanderood River around Zob-Ahan factory of Isfahan and Mobarakeh Steel Complex was used. By using some data, coefficients of model were determined. Analyzing the sensitivity of model coefficients showed that aeration constant (K_r) had the most effect on predicting the model. Since depends on hydraulic parameters of river, sensitivity of depth and pace of river was studied and finally depth of river was introduced as the most sensitive variable.

In this study, the effect of some soil parameters on the life forms and total aboveground net primary production (ANPP) in meadow rangelands in Fandoghlou region of Namin county in Ardabil Province were investigated. ANPP in 180 plots of 12 by harvesting and weighting method were measured. Eighteen soil samples were collected along transects. Some physical and chemical attributes of the soil were measured by standard methods. The relationship between these parameters and ANPP was performed using multivariate regression (enter) method. To determine the effects of important soil parameters on ANPP variation, principal component analysis (PCA) was used. The results of regression analysis showed that electrical conductivity (EC), magnesium (Mg), spreadable clay (WDC), volumetric moisture content (VM), organic carbon (OC), soluble potassium (KS), exchangeable potassium (Kexch), sodium (Na) and phosphorus (P) were the effective parameters on the life forms and total ANPP (p<0.01). The accuracy of obtained equations for grasses, forbs and total ANPP were calculated 79, 76 and 70%, respectively. Moreover, results of PCA showed that soil parameters justify 84.52 percent of total ANPP variation and in comparison, with regression results with 28% it provides better results.

Today, one of the biggest challenges facing the world is the lack of water, especially in the agricultural sector. In this research, we investigated the effects of irrigation method and deficit irrigation with the urban refined effluent on biomass, grain yield, yield components and water use efficiency in single grain crosses 704 maize. This research was carried out in a randomized complete block design with two irrigation systems (furrow irrigation (F) and drip irrigation (T)) and three levels of deficit irrigation treatments of 100 (D₁), 75 (D₂) and 55 (D₃) percent of water requirements in three replications, in 2017, at the collage of Abourihan Research field, University of Tehran, in Pakdasht County. The results showed that the highest yield of biomass was 2.426 Kg m^-2 for full drip irrigation treatments; also, there was no significant difference between D₁ and D₂ treatments. The highest grain yield was 1.240 kg m^-2 for the complete drip irrigation treatment. The highest biomass water use efficiency was obtained for the treatment of 75% drip irrigation, which was equal to 5.3 kg per cubic meter of water. Therefore, a drip irrigation system with 75% water requirement is optimal and could be recommended.

In this study, we used the ARIMA time series model, the fuzzy-neural inference network, multi-layer perceptron artificial neural network, and ARIMA-ANN, ARIMA-ANFIS hybrid models for the modeling and prediction of the daily electrical conductivity parameter of daily teleZang hydrometric station over the statistical period of 49 years. For this purpose, the daily data for the 1996-2004 period were used for model training and data for the 1996-2006 period were applied for testing. In order to verify the validity of the fitted ARIMA models, the residual autocorrelation and partial autocorrelation functions and Port Manteau statistics were used. PMI algorithm were   then used to model and predict electrical conductivity for selecting the effective input parameter of the neural fuzzy inference network and the artificial neural network. The daily parameters of magnesium (with two days delay) and sodium (with one day delay), heat (with one day delay), flow rate (with two months delay), and acidity (with one day delay) were obtained with the lowest values of Akaike and highest values of hempel statistics as the input of the neural fuzzy inference network and the artificial neural network for modelling daily electric conductivity predictions; then predictions were made. Also, models evaluation criteria confirmed the superiority of the ARIMA-ANFIS hybrid model with the trapezoidal membership function and with two membership numbers, as compared to other models with a coefficient of determination of 0.86 and the root mean square of 29 dS / m. Also, the Arima model had the weakest performance. So, it could be applied to modeling and forecasting the daily quality parameter of the tele Zang hydrometer station.

The upcoming climate change has become a serious concern for the human society. These changes, caused and aggravated by the industrial activities of the international community and the increase in the concentration of greenhouse gases in the atmosphere, are seen as a threat to the food security and environment. Temperature change and precipitation are studied in the form of different probabilistic scenarios in order to have an outlook for the future. The present study was conducted to address the effects of climate changes on temperature and precipitation in Qazvin plain in the form of five AOGCMs including Hadcm3, CSIRO-MK3, GFDL, CGCM3 and MICROC3.2, and 3 greenhouse gas emission scenarios of A1B, A2 and B1, based on different possible scenario combinations in the next 30 years, 2021-2050 and 2051-2080 (near and far future). On basis of the study results, all 4 target stations, on average, will have experienced a change between two ratios of 0.5 and 1.4 of  the observed precipitation period  by the end of 2050, and the mean temperature will have had a change  between -0.1 to 1.6 °C, relative to the observed period.  By the end of 2080,  the  precipitation will also have fluctuated between the two proportions of 0.5 and 1.7 times of the observed precipitation period and the mean temperature will touch an increase between 0.6 and 2.6 °C. Both SPI and SPEI indices suggest the increment in the number of dry periods in the near and far future. However, the total number of negative sequences differed considering the 3, 12 and 24-month intervals at the stations level. Given the SPEI index, as compared to the base period, the total negative sequences of drought and number of dry periods will increase at 3 stations of Avaj, Bagh-Kowsar and Shahid-rajaei-powerhouse and decrease at Qazvin station in the future; however, SPI gives different results, such that  for Bagh-Kowsar, there will be an increase in both total negative sequences of drought and number of dry periods, as  compared to the baseline period; three other stations will have more dry periods, specifically, but less total negative sequences. The results reported that the drought events would become severe, and the wet events would become extreme in the future.

Splash (raindrop) erosion plays an significant role in soil loss, especially in arid and semi-arid regions with poor vegetation. In this paper, by analyzing the pattern of rainfalls that occurred during 26 years in four basins located in Semnan County, their effect on the pattern of eroded sediments from the basin was investigated. Sedimentary layers from the sampling of retarding reservoir sediments in 2017 were related to the corresponding precipitations. Due to the occurrence of the highest amount of rainfall in each quarter of rainfall, rainfall hyetographs were divided into four categories. Cumulative precipitation curves with similar quartiles were drawn in one shape and compared with sediment curves and vice versa taking into account the physical characteristics of the basin. The results showed that the Aliabad basin (with less slope and more elongation) with an effective quarter of type 3 had the highest similarity in precipitation and sediment patterns. Also, the Western Soldereh basin (with the highest slope and the least elongation) with an effective quarter of type 2 had the least similarity in precipitation and sediment patterns. The results indicate the vital role of rainfall patterns on the resulting sediment patterns, which show up to 85% similarity.