مجله پژوهش آب ایران
پیاپی 49 (تابستان 1402)

Evaporation from water levels is one of the most important processes in meteorology and hydrology. Optimum use of available water resources is necessary due to the high costs of water storage in the dams. Every year, it is evaporate millions of cubic meters of fresh water from the dam’s water. On the other hand, evaporation from the pan helps to estimate the amount of the plant water requirement in areas where there is no lysimeter information. A wide variety of methods can be used to measure or estimate water use by plants. The evaporation pan method is a simple, inexpensive, and readily understandable way to estimate irrigated crop water use. It also requires little attention and can provide farmers with reliable estimates of plant water use. Pans provide a measurement of the integrated effect of radiation, wind, temperature, and humidity on the evaporation from an open water surface. The pan has proved its practical value and has been used successfully to estimate water use by observing the evaporation loss from a water surface and applying the crop coefficients to relate pan evaporation to irrigation requirement. For this reason, the study of evaporation from the pan has always been of interest to researchers. Modeling this important parameter can be very effective and helpful in accurately estimating of missing data.

In this research, by using of the Gene Expression Programming model (GEP) and some time series models, including Exponential smoothing model, Holt’s model, ARIMA, Brown’s linear trend and Winters’ model, the daily evaporation from pans in Khuzestan province was evaluated. For this purpose, daily pan evaporation for 20 years (2000 to 2020) of three synoptic stations of Ahvaz, Abadan and Dezful were used. These stations have the longest and most complete data among the stations of this province. For modeling the pan evaporation data, 80% of the data was used for the training stage and the remaining 20% was used for the model testing stage. In this research, seven patterns were defined for data modeling. These patterns include the use of data from 20 months ago (M20), 16 months ago (M16), 14 months ago (M14), 10 months ago (M10), 6 months ago (M6), 4 months ago (M4) and 2 months ago (M2). Three evaluation statistics ware also used for evaluate the results of the models. This statistics are include the Root Mean Squared Error (RMSE), Nash- Sutcliffe coefficient (N.S) and Coefficient of Determination (R2). The model with the lowest root mean squared error value and the highest Nash- Sutcliffe coefficient and coefficient of determination was selected as the best model.

The evaluation of the results based on the 3 evaluation indices, showed that the patterns M14, M16 and M20 have the highest accuracy in modeling in both training and test stages. In other words, by increasing the memory of the model, the results show more accuracy and less error. Also, based on the evaluation statistics, the amount of simulation error in the cold months (October to March) was 28% lower than in the hot months (April to September). However, in all 12 months of the year, at least one suitable patterns with acceptable accuracy was obtained for simulating the daily evaporation data. The best results in the warm months were observed for Dezful and Abadan in August and for Ahvaz in May and in the M20. The error in these stations is 0.93 mm, 0.95 mm and 0.95 mm per day, respectively. The Nash- Sutcliffe coefficient (N.S) is more than 0.80 in all stations. In the cold months of the year, the lowest error (0.70 mm per day) was observed in December of Abadan, along with the Nash- Sutcliffe coefficient of 0.82, which indicates the high efficiency of the GEP model in data simulation. Comparing the results of the Gene Expression Programming model (GEP) with the studied time series models also showed that the GEP model has lower error and higher R2 and N.S coefficient in all months in Abadan. In Dezful, the Holt model provided better results than GEP in January and September. The error rate in these two months is 61% and 71% less than GEP model, respectively. In Ahvaz, the Exponential smoothing model in October and the Holt model in November estimated the daily pan evaporation with 48% and 68% less error, respectively.

Steel industry is one of the most important water consuming industries in the world and Iran. steel industry Water consumption is about 17% of country's industries total consumption in Iran. The steel industry wastewater quality is different and depends on the type of process. Chromium wastewater is one of the most dangerous wastewater produced in steel industry then if it releases into the environment causes will be dangers. Therefore, removal of Chromium from water is very important and can reuse if treat completely. Constructed wetlands (CW) are receiving special attention due to rising environmental issues and growing importance of natural and sustainable wastewater treatment techniques. CW are popular because of their low maintenance, less energy consumption.

In this research aim is the design of a horizontal subsurface flow constructed wetland on laboratory scale with slag bed and plant Typha latifolia for treat Chromium wastewater from water resources .The innovation concept used in this paper is addition of bioabsorbent from agricultural waste to slag in the wetland bed. In order to, ponds were built with length, width and height 150, 50 and 50 cm respectively. Two baffles be installed in the wetland to provide flow distribution and ensure that the pollutant passes through the entire bed. The input concentration of Chromium contaminated water was used 100(mg/L) which was similar to the output wastewater of galvanized sheet production. Experiments were designed in 3 different phases. In the first phase, Corn straw with particle diameter about 1-2 cm selected as preferred bioabsorbent for chromium removal. In the second phase, the wetland bed system was divided into two layers and was investigated optimum mix of Corn straw with slag. Finally, in the third phase, with the placement of the selected bedding (chosen from second phase) in the wetland system, experiments were carried out to study the effect residence time on the chromium removal efficiency. residence times of experiments selected were 3, 5 and 7 days.

The results showed that if the bed filled only with slag and the residence time was 7 days, after a week, removal efficiency obtained about 80%. But after 12 weeks, the removal efficiency reached less than 10% and the wetland failed. By adding bioabsorbent to the slag in the bed with the retention time of 7 days, the chromium removal efficiency after 12 weeks reached above 99.97% and the exiting chromium concentration was 0.02 (mg/L).Because wetland performance was good, the project was continued. The results showed that the wetland efficiency was still high and the chromium removal efficiency after 7 months was 99.7% and the exiting chromium concentration of the wetland was 0.35(mg/L). In the third phase, the results showed that the percentage of chromium removal for retention time of 5 days after 12 weeks was about 99% and the exiting chromium concentration of the wetland was 1(mg/L). Also for the retention time of 3 days, the percentage of chromium removal was about 87% and the concentration of chromium of the wetland was 13 (mg/L).

Heavy metal pollution is one of the most important environmental hazards found in all human societies. One of the most important of these pollutions is pollution by cadmium, which because of to its effects on the environment, it is necessary to purify it from soil and water. Among these risks, we can mention the increase in the concentration of heavy metals in the environment, the contamination of the human food chain, and the increase in cancer cases. There are various methods for purifying polluted water, among them using the ability of plants, i.e. phytoremediation is a suitable solution for purifying heavy metals from the environment due to its greater compatibility with the environment. Pollution by heavy metals such as lead, nickel, and especially cadmium has been reported in the industrial areas and towns of Golestan province, and even the use of these wastewaters is widespread without performing pollution reduction processes.

in this research, in order to evaluate, prevent and correct the damages of using cadmium-contaminated water, an experiment with 6 treatments and 3 repetitions was conducted in the form of a randomized block design with and without phytoremediation process with the aim of providing irrigation water to rapeseed plants. Reed and vetiver plants were used for herbal treatment. The drip irrigation system was selected. A retention time of 10 days was chosen for the treatment of water contaminated with cadmium, and the irrigation cycle was considered accordingly. During the experiment and after harvesting the rapeseed crop, the amount of changes in the concentration of cadmium in water samples, plant components and soil were measured and analyzed using SAS software.

The results showed that the amount of cadmium accumulated in the seeds of the rapeseed plant and in its aerial parts, in the treatments irrigated with contaminated water after the phytoremediation process by reed and vetiver grass, had a significant decrease of 1% compared to the treatments without phytoremediation. At the end of the growing season, the concentration of cadmium in the soil that was irrigated with water treated with reed and vetivergrass was 1% lower than the concentration of cadmium in the soil irrigated without treatment. Of course, the investigation of the mutual effects of plant treatment on the yield parameters characteristics of rapeseed including height, pod number, stalk diameter, root depth and weight of 1000 seeds indicated that water pollution with cadmium had no significant effect on the mentioned yield parameters.

Water and moisture in the soil is one of the main factors in determining area under cultivation and as a result production of agricultural products, which is limited in arid and semi-arid areas such as Iran, this limitation and lack of water resources affects the performance of plants and especially Medicinal plants. Using deficit irrigation methods and promoting the concept of water productivity in the production of agricultural products is a practical and common method in different parts of the world to maintain and optimally use water resources. Water productivity actually expresses the amount of product or income. It is obtained from the water consumption unit. During their growth period, plants may face many environmental stresses that have different effects on their growth and performance based on the sensitivity and growth stage of the plant. Drought stress is one of the most important factors limiting the physiological and nutritional growth of plants. It is always necessary and important to know the combination or combinations that lead to reducing the effects of drought stress in plants. Although the toxicity of selenium in high concentrations is evident on plants and it is considered a type of stress, nevertheless, the beneficial effects of its low concentrations in protecting plants against non-living stresses through almost complex mechanisms have been identified. Nowadays medicinal and aromatic plants have received a lot of attention in various fields, including agriculture and pharmaceutical industries. Peppermint plant is a herbaceous and perennial plant that is considered as a medicinal and aromatic plant and is widely used in the pharmaceutical industry. The main purpose of this research is to compare and investigate the effect of selenium in different situations of its application (Mixing with irrigation water and foliar spraying before and after applying moisture stress) on water productivity and some properties of peppermint plant )Mentha piperita L) was under Drought Stress.
For this purpose and in order to investigate the effects of drought stress and different forms of selenium application on water productivity and some characteristics of Mentha piperita L, an experiment was performed in factorial form and in a completely randomized design and in three replications on Mentha piperita L in the research greenhouse university of Torbat-e Jam. The effects of drought stress include two levels 100 (I1) and 50 (I2) percent of water requirement and the application of selenium includes four levels (no application (zero), I (Mixing with irrigation water at the rate of 5 milligrams per liter of sodium selenate (, Leafbefore (Foliar application of selenium at the rate of 5 milligrams per liter of sodium selenate before applying moisture stress) and Leafafter (Foliar application of selenium at the rate of 5 milligrams per liter of sodium selenate after applying moisture stress) was investigated. In order to properly establish the seedlings, plants were irrigated once every other day for two weeks after the transfer of rhizomes. Then the process of applying the treatments began. In this way, in the treatment of selenium mixing with irrigation water, sodium selenate at the rate of 5 milligrams per liter was mixed with irrigation water and given to the desired pots in each irrigation cycle, and moisture stress treatments were also applied at the same time. Finally, after 5 weeks of selenium treatments and moisture stress, the plant was harvested. Also, in the Leafbefore treatment, the desired pots were treated with sodium selenate (Na2SeO4) with a concentration of 5 milligrams per liter as a foliar spray solution. Foliar spraying was done three times every other day and 24 hours after the last foliar spraying, the desired pots were subjected to moisture stress for 30 days and then the plant was harvested. Also, in the Leafafter treatment, after proper establishment of seedlings, the pots were first subjected to moisture stress, and after 30 days of applying moisture stress, foliar spraying of selenium at the rate of 5 milligrams per liter of sodium selenate three times as It was done every other day and one week after spraying the plant, the plant was harvested. The results of this research showed that with the increase of drought stress level from 100% of water requirement to 50% of water requirement, fresh weight, dry weight, percentage of essential oil, plant height, number of leaves and root fresh weight Mentha piperita L decreased by 34/95%, 33/64%, 34/53%, 29/35%, 34/17% and 33/61% respectively, and water productivity increased by 30/69%. Also, in the selenium treatments including Leafbefore, Leafafter and I, compared to the absence of selenium, water productivity 66/87%, 41/79% and 29/25% respectively increased. Among the selenium treatments, the Leafbefore treatment had the highest increase in fresh weight, dry weight, water productivity, essential oil percentage, plant height and number of leaves, and treatment I had the highest increase in the root fresh weight Mentha piperita L. The results showed that selenium in the concentration used in this research increased some properties of Mentha piperita L and was effective in reducing the effects of drought stress in this plant.

Water distribution network analysis is traditionally done under the assumption that the demand requirements are met at all the nodes. In reality, a network could be met with various abnormal and uncertain conditions, resulting in variations at the demand nodes. Softwares such as EPANET 2 analyze a network using demand dependent analysis (DDA). Under pressure deficient conditions, DDA will not give satisfactory results. In such cases pressure-dependent or pressure driven analysis called as node flow analysis (NFA) is required, where outflows at the demand nodes are treated as functions of pressure using node head-flow relationships. Fuzzy analysis helps in understanding how the uncertainty in various independent parameters of water distribution network such as, nodal demands, pipe roughness values, reservoir heads, pipe diameters and so forth will affect the dependent parameters such as pipe velocities, discharges and nodal pressures. The membership functions of dependent parameters are obtained by considering membership functions of uncertain independent parameters. The Impact Table method from literature suggests a repetitive analysis by considering the monotonous relationship between dependent and independent parameters. The Impact Table method was also employed for carrying out fuzzy analysis under pressure deficient condition to obtain fuzzy membership function of nodal outflows. Optimization based methods of fuzzy analysis are more useful when relationship between dependent and independent parameters are non-monotonous.

Optimization based methods of fuzzy analysis are more useful when relationship between dependent and independent parameters are non-monotonous. Genetic algorithm is used in this study for performing fuzzy analysis on three networks by pressure dependent approach. The objective functions which are evaluated are (1) nodal pressures and (2) the actual demand at the nodes under the uncertain conditions. The membership function considered is triangular. The analysis is performed by setting up hydraulic model in the software EPANET and linking it with the MATLAB for performing optimization through an EPANET-MATLAB toolkit. Fuzzy NFA incorporates nodal outflows as additional dependent parameters. The outflows at pressure-deficient nodes are also observed to change monotonically as a result of changing the nodal demands and pipe roughness coefficients. Using this observation of monotonic change, the fuzzy analysis methodology of Gupta and Bhave (2007) is extended to obtain a membership function of available nodal flows under pressure-deficient conditions.The fuzzy NFA procedure has the following steps:Step 1. Carry out a NFA of the network considering normal values of uncertain parameters.Step 2. Change an uncertain parameter to its maximum value keeping other uncertain parameters at their normal value; and obtain the values of dependent parameter. Note the impact of changing an uncertain parameter on the dependent parameter, i.e. whether increasing, decreasing or none. Step 2 is to be repeated for all uncertain parameters.Step 3. To determine the maximum (or minimum) value of the dependent parameters, take an appropriate extreme value of an uncertain parameter based on its impact and carry out the analysis. Step 3 can be repeated for all dependent parameters and for different α-cuts.For validation, two networks were selected from previous researches, and the networks were analyzed with the developed model and WaterNetGen software, and finally the results were compared. Then paid to hydraulic analysis of the water distribution network of Jangal city under uncertain conditions and lack of pressure as a case study.

Fuzzy analysis is the approach adopted in this study to quantify thevagueness of a water distribution network. An optimization model is employed to find out theextremities in the responses of the system, as the relationship between independent and dependentvariable are not necessarily monotonous. The hydraulic system is analyzed by node flow analysis totake care of the head-demand relationships under pressure deficient conditions. As most of the hydraulic simulation software perform analysis considering that demands are met at all the nodes, the results will vary when there is a pressure deficiency in the network. This assessment of network can be incorporated into the better designing of a WDN. The obtained results showed that the proposed model can perform hydraulic simulation well in the condition of lack of pressure. This study has considered only the uncertainties in the nodal demands, but it can be further extended to any input parameter just by considering them as variables in the algorithm and extreme responses can be obtained.

The dams and reservoirs are usually designed with a certain capacity to meet agricultural, urban and industrial needs. Karst terrains are typically considered inappropriate for dam construction because of their complex geological and hydrogeological characteristics. The Tangab Dam with a reservoir volume of 140 million cubic meters was built to control river flood and supply part of downstream agriculture water. Geologically, the dam and reservoir are located at the entrance of a karst valley, on the northern limb of the Podeno Anticline, in the simply folded Zagros Zone. The Podeno Anticline is made mainly of Pabdeh marlstone, Asmari limestone, alternating layers of limestone and marlstone of a transitional zone, and Razak marlstone. By beginning of impoundment in 2009, the reservoir has faced with a leakage problem. In order to reduce water leakage, the additional grouting and treatment works were designed and executed at dam site. In this research, an attempt has been made to investigate the function of additional grouting and treatment works on reducing the hydraulic connection between the reservoir and downstream groundwater.

The geologic map of the study area was prepared based on a geological map provided by the Geological Survey and Mineral Exploration of Iran. Water level in the reservoir and boreholes were measured monthly during a five years period by the Fars Regional Water Authority. The grouting history at the dam site was determined based on the available reports. The dam site was divided into three sectors including the left abutment, riverbed and the right abutment. At each part, effect of the initial grouting and treatment works on the changes in the groundwater level was investigated. Pearson coefficient was used to determine correlation between the reservoir water level and water level in downstream boreholes.

The initial water tightness system of the Tangab Dam includes a cut-off wall implemented in the riverbed and a 180 m deep grout curtain with 256 and 216 m extension respectively into the left and right abutments. By starting of reservoir impoundment in 2009, discharge of the downstream springs was increased (from 1.4 to 3 m3/s) due to water losses from the reservoir. To reduce further leakage, two additional grout curtains with 300 and 570 m extensions were executed respectively in the left and right abutments. Moreover, additional grouting was done at different parts of the initial grout curtain. At the left abutment, similar fluctuations were observed in the reservoir water level and downstream groundwater. The calculated correlation coefficient between the reservoir water level and water level in boreholes located upstream and downstream of grout curtain varies between 0.80 to 0.96 and 0.70 to 0.89, respectively. About 50 m difference between the reservoir water level and water level in downstream boreholes shows an acceptable performance of grout curtain at the left abutment. At the riverbed, it seems that the cut-off wall and grout curtain works appropriate because the boreholes located in the dam foundation did not show considerable relation with the reservoir (correlation coefficient between 0.06 and 0.12). At the right abutment, the lowest correlation between the reservoir and the boreholes water levels was observed in the RG2, ARG2 and RG6 galleries. Remedial works in these sections have also cause several meters falling in downstream water level. It appears that the closest relation between reservoir water and downstream groundwater was observed along the 570 m long grout curtain constructed at the reservoir bank. Here, it was concluded that permeable sections were remained in the rocks located at the upper levels (especially more than 1420 meters) because a significant rising in groundwater was observed in response to the 25 m rising in the reservoir water level. Results of this research show that the initial grout curtain and the additional treatment have worked successfully in reducing the rock permeability and also increasing the length of leakage paths. However, reservoir water could be leaked by moving through, below or by passing the ends of the hanging grout curtain which is not connected into the impermeable rocks in depth and at the ends. To reduce leakage from the Tangab Reservoir, the additional treatment needs an extensive and expensive grouting works. Also, achieving a complete sealing of the reservoir is not guaranteed even with the execution of this grouting. Therefore, it is suggested that no other grouting operations be designed and implemented at this site, because the leaked water through the Asmari Aquifer is not unused. Deep percolation of karst water is limited by the Pabdeh marlstone at the bottom of the aquifer. If the reservoir water moves along the edge of the anticline towards the plunge area, it will recharge the karst aquifer and use in future. If the reservoir water moves to the southern limb of the anticline, it will discharge through the downstream spring and use for the local agricultural purpose.

The accurate estimation of the design Precipitation is one of the requirements for the construction of hydraulic structures, which is done by various methods of frequency analysis. Classical methods of fitting observational data use the assumption of constant parameters of distribution functions; while, many studies have been done on non-stationary data due to factors such as climate change. Therefore, this paper aims to use the functions of non-stationary parameters - if necessary - and compare them with the stationary assumption of the maximum daily precipitation data of the Atrak river basin. Mann-Kendall test and White test were used to check the non-stationary in the mean and variance of annual data. The Generalized extreme value distribution function was also fitted to the data time series. Among the 24 stations with long-term data, 5 stations with trends and 6 stations with variance non-stationary were detected. Evaluation criteria including Akaike (AIC), Bayesian (BIC), Root mean square error (RMSE), and Nash-Sutcliffe efficiency (NSE) coefficient was determined under stationary and non-stationary assumptions, for all stations. The results showed that in all stations with non-stationary, considering the mentioned conditions in the analytical calculations is a good choice. Also, the lower (5%), median (50%), and upper (95%) limit values with the return period of 100 years with both assumptions were determined and compared with the classical maximum likelihood method. The underestimation of the maximum likelihood method compared to the Bayesian method used by using Markov chain Monte Carlo (MCMC) in parameter estimation was observed. Also, Akaike criterion provided better results among the used evaluation criteria.

The use of drip irrigation systems for citrus orchards has become a standard method. Economically, drip irrigation is cost-effective for many fruit trees. But only using these systems cannot improve water productivity or net income, and the suitable irrigation water depth should be determined based on production-water and cost-water relationships. Deficit irrigation is one of the appropriate ways to optimize water use in water limitation conditions. However, its economic effects should be evaluated. The optimum applied water depths are used to enhance the product or the net income in water limiting conditions. Therefore, as the first step, the water-production and water-cost functions must be prepared. Production-water function is a quadratic function that relates production to the amount of applied water during the irrigation season. The cost-water function is a linear function that relates total production costs to total applied water. By optimizing these functions, the optimal depth of irrigation water is obtained. English method is an appropriate method to determine the optimal irrigation water depth, which is based on water-production and water-cost functions.

In order to determine water-production and water-cost functions, an experiment was conducted in an orange orchard in Sari. The trees were 25-year-old Thomson Navel oranges spaced in 6×6 meters, which were drip irrigated. The climate in the study area was mild with hot and humid summers and humid and mild winters. Four irrigation levels including 100, 80, 65 and 50% of irrigation water depth were applied in 5 replications. To determine the irrigation water depth, soil moisture was measured and the amount of irrigation water depth (D) and irrigation volume (V) were calculated. Applied water was considered in two cases. In the first case, irrigation water was considered as the applied water, and in the second case, irrigation water plus precipitation was considered as the applied water. Then, the optimal irrigation water depths were determined by mathematical optimization. Next, the economic evaluation of these optimal depths was carried out using 6 indices. It is worth mentioning that in deficit irrigation, the water use per unit of area (one hectare) is reduced compared to the full irrigation, and therefore the irrigated area will be more than one hectare. Thus, the amount of equivalent production and equivalent net income per unit of land increase.

This study showed that when water is not limited, applying full irrigation 〖"(W" 〗_"m" ) provides the highest amount of net income per unit of land. In water and land limiting conditions, if the water limitation is mild, using the optimum depth in water limiting condition 〖"(W" 〗_"w" ) leads to a 26 percent reduction in irrigation water use, which causes a 4 percent decrease in net income per unit of land. But it increases net income per unit of irrigation water by 16 percent. In addition, if the water limitation is severe, it is more useful to apply the equivalent optimum applied water depth 〖"(W" 〗_"ew" ). Although it causes a 17 percent decrease in net income per unit of land, it causes a 46 percent decrease in irrigation water use. Furthermore, when precipitation occurs, the sum of irrigation water and precipitation should be considered as applied water. However, in order to evaluate the effect of deficit irrigation, only irrigation water should be considered to determine the equivalent irrigated area. Therefore, in water limiting condition, if land is not limited, the use of 〖"(W" 〗_"ew" ) leads to the highest net income per unit of land. Because by using 〖"(W" 〗_"ew" ), more area can be irrigated. In addition, the highest water productivity is obtained from the optimal depth under water limiting conditions ("W" _"w" and W_ew). On the other hand, according to the current prices of fruit and water, the net income and optimal depth of applied water are not sensitive to the price of irrigation water. However, they are highly sensitive to the price of fruit. This is due to the large difference in the price of fruit compared to the price of water, which makes production play a more important role than water on the net income. Overall, the use of optimal depths in water limiting conditions can be a suitable solution to overcome the problems of water scarcity in Iran. Moreover, return on investment (ROI) is a key factor along with technical analysis that experts should consider in order to provide an acceptable irrigation schedule for farmers.

human intervention in nature and the land-use change of rivers and floodplains, and climate change, the risk of flood has increased in the world. Controlling and reducing the damages flood is done in two methods, structural and non-structural. Research conducted in different parts of the world shows that the use of non-structural methods such as flood forecasting and warning systems along with structural methods reduces flood damage. Flood forecasting and flood notification are logical tools to reduce flood risks in flood-prone areas. Precipitation forecasting is very important due to its use in flood and water resources studies. Numerical weather predictions have been extensively developed in recent years. Today, the world's leading meteorological centers have used these models in their meteorological forecasts. The ECMWF is one of the centers in global meteorological forecasts. The present study was conducted to evaluate the performance of the ECMWF center for precipitation forecasting in the Poldokhtar watershed. Numerical prediction models have systematic errors. Therefore, the purpose of this study was to investigate the effect of 7 bias correction methods (Delta, EQM, EZ, QM, LS, STB, TVSV) on the ECMWF rainfall forecasting model.

The studied area is the Poldokhtar watershed from the subbasins of the Karkheh basin. This watershed is located in Lorestan province. The information from 7 rain gauges station was used in this research. In this study, the comparison of ECMWF center forecasted rainfall with rain gauge station data was made point by point. 7 rain gauge stations in the Poldokhtar watershed were selected for point evaluation. The distance of these stations from the center of gravity of the network points was less than 10 km. The period used in this study is from 2016 to 2020. In the first step, the predicted rainfall was downloaded from the TIGGE database website. The data of this database is in GRIB2 format, which was extracted with QGIS software in Excel format. In the next step, predictions were evaluated before bias correction. Then due to the bias in the predictions, corrections were made with 7 bias correction methods. Finally, the bias correction forecast was evaluated. Bias correction methods that were used in this study include the Delta method, Elevation Zone (EZ), Quantile Mapping based on Empirical Distribution (EQM), Quantile Mapping (QM), Linear Scaling (LS), Spatio-Temporal Bias correction (STB), and the TVSV method. In this study, the daily precipitation forecast of the ECMWF center was used. In the used methods, 70% of the data were considered for the control period and 30% of the data for the prediction period. In the Delta method, the changes between the average observations and the simulation are added to the daily observed precipitation. In the LS method, the correction of daily values is based on the difference between the observed control period and the uncorrected data. The elevation zone (EZ) bias correction method, corrects the forecasted precipitation at the high altitude. The EQM method is a statistical-empirical base-quantile method, which is based on the experimental transformation and bias correction of the simulated precipitation by the regional climate model. The QM method removes biases by using cumulative distribution functions (CDF) for observed and predicted values at any time scale. In the STB method, the predicted daily precipitation is calculated for the relevant time window, and the values of the ground stations and the corrected prediction values are replaced and calculated bias. The TVSV method is based on the 7-day time window. In this study, two types of statistical indicators continuous and classified were used to evaluate the numerical model of precipitation forecasting. The continuous index includes RMSE, ME, and MAE and the classified indicators include POD, FAR, and BIAS.

The results showed that the ECMWF model had a low RMSE in most parts of the Poldakhtar watershed and had acceptable accuracy. Also, the corrected precipitation evaluation showed that the Delta method had a good performance in all the rain gauge stations under study. The STB method in two stations corrected 90% of the precipitation data. The EZ and QM methods in about 4 stations corrected about 85% of the predictions. These two methods had similar performance. LS and EQM methods had poor performance in all 7 points studied. In other words, they could not correct the bias of the predictions. The TVSV method also did not have acceptable performance. The Delta method improved the predicted precipitation in most parts of the RMSE and the STB method was able to correct the low estimate of the predicted precipitation. The results of this study showed that altitude is involved in the accuracy of predicted precipitation. If the low altitude forecast model had the lowest RMSE and at high altitudes, the highest value of this index. Biased correction methods improved the predicted precipitation values to an acceptable level, which increases the application of the predicted precipitation model in the flood warning system. According to the ME index, the underestimation is higher in the upper elevations of the basin. The main reason for this difference can be not correct the effect of altitude on the value of precipitation. At the ECMWF center, no significant change was observed in the POD index after bias correction. The small change in the POD index at the ECMWF center can be due to the good performance and structure of the numerical model at this center. The POD index at high altitudes performed better than this index at low altitudes. The bias correction methods improved the predicted precipitation values to an acceptable level, therefore increasing the effectiveness of the precipitation forecasting model in the flood warning system.

As a new product, nanoabsorbents play an important role in controlling and removing environmental pollution. Fe3O4 nanoparticles, due to their high absorption level, have a great ability to increase the efficiency of zeolite adsorbents in removing pollutants. Naeej et al. (2013) explained Zeolite modified with zero iron nanoparticles, due to having many absorption sites as a reducing agent, can have a great ability to remove nitrate from drinking water. Yaghmaian et al. (2015) investigated the removal of nitrate from aqueous solutions with zero-valent iron nanoparticles and stated that at a pH of 5.8 and a contact time of 55 minutes, more than 80% absorption is obtained. Qarlaqi et al. (2015) investigated the efficiency of iron oxide nanoparticles for urban sewage treatment. They stated that at pH equal to 3 and contact time of 15 minutes, the maximum amount of absorption is obtained. Therefore, in this study, clinoptilolite zeolite adsorbent and nano composite prepared from A Zeolite Fe3O4 nanoparticles were prepared in order to remove nitrate ions from real wastewater in industrial system. Also, zeolite treatment and zeolite- clay treatment were tested for comparison.

In this research, Fe3O4 nanoparticles were used to increase the efficiency of zeolite in removing nitrate from aqueous solutions and real wastewater. Laboratory columns made of PVC material with a height of one meter and a 100 mm diameter were used. The investigated columns were filled up to a height of 60 cm with the investigated materials and 20 cm of wastewater was continuously placed on the columns. The investigated treatments include three adsorbent materials: a) six kilograms of zeolite (clinoptilolite), b) three kilograms of zeolite and three kilograms of clay, and c) six kilograms of nanocomposite prepared from zeolite and nanomagnetic with an optimal ratio (Ratio of Zeolite: 0.5 Fe3O4) was laboratory. Synthetic wastewater with a concentration of 40 ppm was prepared and used. The temperature of the wastewater used was 20 degrees Celsius and the pH of the treated wastewater was measured as 7.2. The experiment was carried out factorially and in the form of a completely random basic design in three replications.

The results showed that the nano composite based on zeolite and Fe3O4 can absorb 70% of nitrate in a small laboratory scale and non-continuous flow. In continuous flow and on a large-scale laboratory that has industrial application, the absorption rate of nanocomposite will reach 27% after 8 hours of continuous flow. This absorption rate is 17% for zeolite-clay and 13.4% for zeolite. Decreasing the contact time and increasing the amount of wastewater in continuous flow will reduce the effect of absorbents. The results of the average comparison of the nitrate concentration in the wastewater from the columns with different absorbers show that the difference between the nitrate concentration in all measurement times between the nanocomposite absorber and the other two absorbers is statistically significant at the 1% level. Also, the results of one-way analysis of variance to compare the effect of wastewater removal on an industrial scale between the adsorbents used showed that the nanocomposite adsorbent used has more efficiency than zeolite and zeolite-clay adsorbents. Due to the fact that the composition of nanocomposite (zeolite modified with nano Fe3O4) has more surface area than zeolite and clay adsorbent due to having nano compounds, so the reactivity of this adsorbent is increased and nitrate absorption in this adsorbent is more than other adsorbents. In general, the results of this research show that the nanocomposite used in this study has a relative ability to remove nitrate from the water environment, and if the contact time is increased, it can be used on an industrial scale with a suitable absorption percentage. The current research was done with continuous flow and short contact time. This is despite the fact that in most of the investigated studies, the contact time was more than 50 minutes. Therefore, the amount of absorption is less than the laboratory scale and non-continuous flow. To solve this problem, the continuous flow system should be designed in such a way that the contact time reaches at least more than 50 minutes. In addition, with proper design, passing through the filter can be done in two stages so that maximum absorption takes place.