مجله مهندسی آبیاری و آب ایران
پیاپی 22 (زمستان 1394)

Traditional water distribution system models, which are referred to as demand-driven analysis are normally analyzed under the assumption that water demands at nodes are known and always satisfied, i.e., they are equal to nodal outflows, regardless of the pressure at nodes. Such analysis is valid under normal design conditions. However, in many critical situations such as pipe burst or breakage and fire-fighting demand on demand nodes, the nodal outflows affected by low pressure will decrease. Therefore, network simulation under deficient pressure conditions using conventional demand-driven analysis can cause large deviation from actual situations. In this study, the combination of three pressure-dependent demand (PDD) methods with WaterGems hydraulic model has been used to simulate deficient-network performance. Assessing the performance of three methods proposed was done using two base network and part of the Ilam water distribution network. The results showed that the results of PDD and Abdy Sayyed et al. (2014) methods are close and preferred to very long and Time-consuming relations proposed by researchers, and they yield results just by one-step simulation. These methods respectively provide 82.83 and 82.07 percent of total network demand at the time of breakage in one of the pipes in Ilam water distribution network considering desired pressure equal to 15meters.

Chemical fertilizers used in agriculture are sources of environmental pollution. Factors affecting the movement of salt and water in the soil profile help effective management and reduce nitrate leaching from the root zone. In the present study¡ NO3- dispersivity in sandy soil and simulation by hydrus2D has been investigated. In order to perform it¡ 5 different height of soil column 20¡ 40¡ 60¡ 80 and 100 cm (H1-H5) selected. Brigham model was used for calculation of dispersivity and HYDRUS software was used for simulation of NO3 movement. Results of the HYDRUS simulation indicated that the dispersivity of sandy porous media was not dependent on the height. The result of HYDRUS showed that with increase of aquifer length¡ dispersivity increased but it was not significant.

Treated municipal wastewater (TMW) as a non-conventional water resource¡ is well recognized as one of the most important factors of water resources management in arid and semi- arid religion. The main goal of this research is evaluating the effect of irrigation with TMW on nitrate distribution in the soil profile under greenhouse conditions. This experiment was carried out in randomized complete block design based on a factorial experiment with three replications. Three irrigation levels were considered consisting of TMW¡ alternative TMW- water and tap water. Soil samples extracted from four different depths (0¡ 7.5¡ 15 and 22.5 cm) and three horizontal distances into plant location (0¡ 5 and 10 cm). The results showed that nitrate of TMW had significantly greater amount in comparison with water (27.1 mg/lit for TMW¡ 19.6 mg/lit one among irrigation TMW- water and 4.5 mg/lit for water). Nitrate concentrations have largely been observed in the closest point of the plant. Also¡ diagrams¡ which have been drawn in order to compare the irrigation treatment on the cultivated plants¡ showed that amount of nitrate in the soil profile of tomato root’s region was significantly higher in comparison to corn. This could be due to plants unequal required nitrate. Based on the results obtained¡ using of TMW can reduce require nitrogen fertilizer for plants and it can also do to help reduce pollution of soil and water by nitrogen fertilizer.

World population growth¡ quick process of industrialization and wide utilization of fertilizers cause the intensive and extensive intrance of pollutants specially nitrogen compounds in rivers and other aquatic environments increasingly. Un-ionized ammonia is one of the mineral nitrogen components that is very harmful for the aquatic organisms specially fish. In this study the trend of un-ionized ammonia pollution was investigated in Kor river during 9 months of the years 1384 and 1385 (2005 and 2006). The results showed that concentration of un-ionized ammonia vigorously increase (16-230 time of the background concentration) immediately downstream of the petrochemical plant and then decrease gently downstream of the Kor river during the course of the study. The results of the study also showed that the amount of un-ionized ammonia after the petrochemical plant increased to 0.2 to 1.4 mg/L is harmful for aquatic life due to concentrations higher than the standard values of short periods (0.05-0.35 mg/L) and long periods (0.01-0.02 mg/L).Therefore after petrochemical plant¡ we could not trace any aquatic life. The results of our research showed that the main point source of excreation of un-ionized ammonia is the petrochemical factory of Shiraz and other pollutants are additive. Among parameters that affecting the concentration of Un-ionized ammonia¡ the water pH was the most influence and the chlorine concentration was less effective.

Forecasting of inflow to reservoirs is essential in efficient planning and operation of water resources. In this research¡ the application of two different intelligent models including Artificial Neural Networks (ANNs) and Adaptive Neuro-fuzzy Inference System (ANFIS) technique based on subtractive clustering method are investigated for forecasting inflow to Kamal Saleh reservoir in Markazi province¡ Iran. For this purpose precipitation and discharge data in a 31-year statistic period (1981-2011) were used and forecasting of inflow was done in the daily and monthly time steps. The amount of discharge and precipitation in previous time steps were used as input patterns for models.Both ANNs and ANFIS models had very acceptable performances at daily and monthly forecasts of inflow based on the error measures; R¡ RMSE and MAE¡ however ANFIS model performance was better than ANNs (less than 3%). Using seasonality coefficient (α) improved the performance of models in monthly forecasts. In the following¡ the effect of large scale climate variables including North Atlantic Oscillation (NAO) index and Southern Oscillation Index (SOI) examined on monthly forecast that was resulted from the best input pattern in optimized model of the previous section. The results showed that using climatic indices in input combination can improve the performance of model to forecast the inflow. Although SOI had greater impact on improving the monthly inflow forecast. So that the statistical indices to evaluate the error of ANFIS model including R¡ RMSE and MAE obtained as 0.91¡ 3.56 and 3.73 respectively¡ this shows the potential of this way to increase the precision by improving the evaluation criteria about 11%¡ 9% and 11%¡ respectively.

One of the effective ways to deal with the water crisis and control runoff is constructing of water storage ponds that named Ab-Bandan in the Northern provinces. Water seepage from Ab-
Bandans, in addition to reducing the volume of water stored in them, will cause saturation and slide of banks soil; As a result, to reduce seepage from Ab-Bandan different materials such as nanoclay should be added to improve soil impermeability. In this study with permeability tests in lab, the effects of different percentages of nanoclay (0.5, 1, 1.5 and 2%) were evaluated on soil hydraulic conductivity. A physical model of the Ab-Bandan was built. nanoclay performance in reducing water leakage was evaluated. Ab-Bandan was simulated with the seep/w software and the effect of nanoclay on the amount of seepage and phreatic surface was analyzed .The results showed that the permeability reduced from 1.58* 10-4 to 2.88*10-5 with the addition of %0.5 nanoclay and then the permeability was less affected by the amount of nanoclay, so 0.5% nanoclay was chosen as the optimum percentage. Water seepage losses from Ab-Bandan with physical and numerical models, reduced %58 and %22 respectively. Phreatic surface after combining soil with nanoclay, on average, respectively, 2.73 and 4.53 cm have been reduced in physical and numerical model. So with the help of nanoclay can reduce water seepage losses from Ab-Bandan.

Estimation of sediment concentration in rivers is very important for water resource projects planning and managements. Various models have been developed so far to identify the relation between discharge and sediment load. One of the most common methods for estimating sediment of rivers is sediment rating curve. For better estimation of the amount of sediment based on the sediment curve rating equation¡ it is possible to optimize its coefficients. One of the methods used for optimizing the coefficients of the sediment curve rating equation is taking advantage of meta-heuristic algorithms. Nowadays¡ optimization algorithms are used regularly for solving complex and non-linear problem. The main objective of this research is the use of genetic algorithms and particle swarm to optimize the relationship between discharge and sediment discharge in Kohak station on the Sistan River and comparison the results of these models with sediment rating curve. For the calculation of sediment discharge by the models initially necessary statistics and information including flow discharge and sediment concentrations have been measured since 1981-2011 in the stations are collected. Genetic Algorithm(GA) and Particle Swarm Algorithm(PSO) models were coded in MATLAB. After the models were trained with 70% to 30% of the data at both stations were tested. Evaluation parameters efficiency such as coefficient of determination (R2)¡ root mean square error (RMSE) and Nash-Sutcliffe coefficients (CE) are used in evaluating the models. The results showed that the genetic algorithm with 33484.47 values at Kohak station has lowest root mean square error in all models. After genetic algorithm¡ Particle swarm algorithm with 34754.31 values has lowest values of the objective function.

Reservoirs as traditional structures in water resources management system in MAZANDARAN province play a major role in supplying irrigation water for paddy fields. Dredging and improvement of such structures can result in getting more benefits from the surface runoff. In current research¡ using satellite images and ArcGIS software¡ land use over the case study area of GATAB¡ BABOL¡ Iran¡ was determined. Then the potential of the surface runoff in the area was estimated by SCS method. Also¡ irrigation costs for paddies¡ irrigated by groundwater well (four groundwater wells) and reservoir water (four Reservoirs)¡ were estimated. The effect of dredging and improvement of reservoirs on the reduction of groundwater withdrawal and irrigation costs were evaluated. The potential of runoff in the area was estimated to be 31 MCM (million cubic meters). Dredging of all Reservoirs by 1 to 2 meters would result in the exploitation of 1.68 to 3.37 MCM from the surface runoff. A fall in irrigation cost¡ estimated to be 991 to 1982 million Rials per Hectare¡ is a consequent of more proper utilization of surface runoff. According to the results¡ the increase in the storage capacity of reservoirs will result in saving part of groundwater storage in the case study area.

To study the effect of irrigation water salinity on soil chemical characteristics¡ a randomized complete block design experiment was conducted with four treatments of irrigation water salinities of 2¡ 6¡ 9 and 12 dS/m with three replications for each treatment in a corn field under drip irrigation system (T-Tape). The study was carried out in an arid region with high initial soil salinity and soil texture of loam. Results of soil chemical analysis from different soil depths of 0-30¡ 30-60 and 60-90 cm showed that in each layer of soil with increase in irrigation water salinity the salinity of soil saturated extract increases and the salinity of soil saturated extract in deeper layers was higher than upper layers. During the growing season¡ for each of three soil layer profiles¡ with uniform irrigation with water salinity of 1dS/m the value of the ECe¡ SAR¡ HCO3¡ Cl and ESP were decreased. However¡ irrigating with different irrigation water salinities caused that the above values increase after the crop stage of four leaf corn and the maximum increase occurred at the end of growing season. In regions with lack of fresh water¡ irrigating with saline water under drip irrigation will result in uniform distribution of water and soil salinity in soil profile.

In recent years¡ Khtam as a city of yazd province has been taken in to consideration due to excessive exploitation of ground water for agriculture production. The present study was carried out with two aims¡ 1- estimation of excess water for strategic crops of city such as wheat¡ barley¡ corn and watermelon¡ 2- comparison of sustainability index of water used among three separated groups based on the amount and kind of excess water. The first groups are quite efficient farmers without applying any excess water. The second group includes farmers who use extra water due to being inefficient in using of water and the third groups are those farmers who use extra water due to both inefficiency of water used and excess input for production. The average amount of excess water used for each group is zero¡ 3914.319 and 5166.669 m respectively and sustainability index obtained for each group was 458.49¡ 395.72 and 367.64 it show the inverse relationship between extra water used and sustainability index.Estimation of excess water and calculation of sustainability index was implemented by Deap2 and WinQSB.

Potential evapotranspiration has an important role in agricultural studies¡ the project of water resources management¡ design of drainage and irrigation network and water structure. According to the importance of this parameters¡ in this study it has been tried to Classify the potential evapotranspiration using Self Organizing Map (SOM) of neural network in south of Fars province. Parameters that used in this study to classify with SOM method include: minimum temperature¡ maximum temperature¡ mean temperature¡ Sunshine hour¡ maximum of Sunshine hour¡ wind speed and relative humidity. Result of this paper shows that minimum temperature¡ maximum temperature and mean temperature have significant relative in study area. Also the minimum temperature¡ maximum temperature and mean temperature have invers relation by relative humidity in study area. According to Self Organizing Map (SOM) of neural network method and input parameters of this model¡ potential evapotranspiration in study area classified in 3 classes. So that class 3 has the highest evapotranspiration and class 1 has the lowest evapotranspiration.

Continual drought affected on the earth surface and has changed appearance of it. Therefore accurate assessment of changes in the climate parameters and effect of them on the environmental factors and water resources is very important and necessary. In this paper¡ precipitation and temperature changes in Shiraz synoptic station since 1983 to 2013 were evaluated. In this study various drought indexes such as SPI¡ RAI¡ PNPI¡ DI and SIAP evaluated in the annual scale and based of them¡ the different rainfall regimes in Shiraz were categorized. According to the monitoring of drought and wet years condition¡ maximum similarity is between SIAP index and DI¡ RAI indexes¡ SPI and RAI indexes have minimum similarity. According to the Results of this paper in the recent decade changes trend of annual precipitation¡ maximum intensity of rainfall and minimum absolute of temperature have been decreased. So that annual precipitation decreased about 50 millimeters in the last decade¡ maximum intensity of daily precipitation decreased 20 percent and average of minimum annual temperature decreased 2 degrees centigrade. Also the trend changes of maximum absolute temperature and number of frost days have been increased. According to results difference between maximum and minimum annual temperature have been increased¡ average of maximum absolute temperature in the ten years periods have been increased about 0.6 degrees centigrade.