IRAN-WATER RESOURCES RESEARCH
Year:2018 | Volume:13 | Issue:4 |Papers Count:22

Optimal allocation of water resources with flexibility to meet the water demands and priorities in allocations will require the integrated river basin management. To overcome the complexity of this approach, the use of water resources planning models has been very useful in the recent years. In this research the optimum water allocation in the Gorganroud River basin was investigated through coupling MODSIM model as the simulation engine and Cuckoo Optimization Algorithm (COA) as an optimization engine developing the COA- MODSIM model. The objective function in one case was to maximize the supply's volume for the demands and in another case to maximize the reliability of supply. Results indicated acceptable performance of the simulation- optimization model used to solve the problem of optimal allocation of water resources at the basin scale. It is also shown that the simulation-optimization model increased the amount of water supply in the basin considering the return flows by %36 and decreased the outflow from the basin by about %24 compared to the simulation of the status quo. These results indicated the significance of the optimal allocation policies to increase the water supply and reliability and to reduce the loss of water resources in the basin.

"Combining the technological and social-behavioral solutions" is one of the most important exit strategies in dealing with water crisis that can result in characteristic changes in the society towards water resources conversation. Accordingly, the purpose of this study was to analyze farmers' participatory- oriented water conservation behavior (FPOWCB) in the environmental psychological background. The study was a descriptive-correlational research. The research instrument was a questionnaire which was validated by a panel of agricultural extension and education specialists and water experts and its reliability was verified using Cronbach's alpha coefficients (0.75£a£.90). The statistical population was farmers in southern part of Lake Urmia's catchment area (N=23750) from which 378 farmers were selected as a sample using Krejcie and Morgan sample size Table and stratified random sampling method. Regression analysis revealed that farmers with individualistic values show fewer participatory-oriented behavior toward water resources conservation than whom with collectivist values. Moreover, these two variables could predict 32.5% of changing FPOWCB. The result of independent t test showed there is a significant difference in terms of FPOWCB between two groups of farmers who participated in training courses related to water issues and those who had not.

The analysis and assessment of climate model outputs for Atmosphere- Ocean General Circulation have become of great global interest. If the appropriate skill of the dynamic seasonal climate forecasts is approved over the long-term (hindcast period) in Iran, decision makers can be supported by real-time seasonal forecast systems for monthly and seasonal planning. In this research, the output of 8 models enrolling in the North American Multi-Model Ensemble (NMME) including NASA, National Centers for Environmental Prediction (NCEP), National Oceanic and Atmospheric Administration (NOAA), Environment Canada models, and Geophysical Fluid Dynamics Laboratory (GFDL) models are used for evaluating seasonal precipitation forecasts over Iran. Analyses are provided for the first 6 months of the water-year when the proportion of precipitation is the highest of total annual rainfall over many parts of the country. The bias and anomaly correlation of NMME precipitation outputs are calculated for three seasons (OND, DJF, JFM) in different lead times with respect to a reference data over the period of 1983-2013. The results showed that the skill of NMME seasonal precipitation forecasts is not similar over Iran's 30 main river basins. Moreover, the anomaly correlation of NMME individual models is significant for all seasons in lead 0 over many river basins and also for 1-month and 2-month lead time for OND. For the Southwest Iran the raw NMME outputs without any post-processing exhibited anomaly correlation coefficient of more than 0.6. The bias between -1 to+1 mm/day was identified over almost all grid points within the study area. The results of the research addressed the need to apply post- processing methods and develop multi- model ensembles to benefit from high skills in each individual model for forecasting seasonal amount of precipitation in Iran.

In most parts of Iran a considerable part of the drinking water is supplied by wells and groundwater resources. Water resources which are used to supply urban drinking water are always exposed to different pollutants. Accordingly the groundwater protection is one of the major concerns for decision-makers in supplying and distribution of drinking water. Precise calculation of wellhead protection areas is very important in this regard; since deciding on smaller area raises the risk of contamination of the well and considering larger areas causes capital losses. In this study, different methods were applied using WhAEM2000 to determine the wellhead protection area for Damaneh- Daran aquifer in Isfahan province. The results indicated that protection area with analytic element method is more conservative than calculated fixed radius method. Thus this method can be used to determine three zones of emergency, essential, and supportive protection with travel times of 2, 5, and 10 years, respectively. Accordingly, essential protection area for drinking wells in this region was varying from 15 hectares for well number 2 in Damaneh to 25 hectares for wells number 1 and 2 in Daran in the direction of groundwater flow.

Abbandans are man-made wetlands constructed by excavation and borders of soil dykes around it. These hydro-structures have significant contributions in farmland irrigation in Mazandaran province. However like other types of constructed wetlands there is a question about their ability to bioremediat the input contaminants. For a period of 9 months from Dec 2012 to Aug 2013 and on a monthly basis, 54 samples were collected from inlet and outlet water of three Abbandans; Nobbor and Lalle-Marz utilized for fish culture and Sar-Abbandan with agricultural function located in north of Sari city. The temperature and pH were measured in-situ and concentration of nitrate, nitrite, ammonia and total phosphorus were measured by Atomic Absorption Apparatus in the laboratory. Total nitrogen was calculated from the sum of the nitrogen data. Significant difference was observed on input-output concentrations of total phosphorus for Sar-Abbandan (0.083-0.016 ppm) and the fish farming had no bioremediating or polluting effect on outlet parameters (a=0.05).

Salinity of water resources is a common problem at many river basins all over the country. Helleh River Basin (HRB) with semi-arid climate located at south of Iran is one of such basins, where primary (natural) sources such as salt diapirs and salt formations are the main sources of salinity. This study deals with developing a basin-scale model for analysis of water resources salinity. The model consists of two modules of water balance and salt balance. SWAT model takes the role of water balance module and the salt balance module is developed in an external programming environment. It is worth mentioning that the original version of SWAT is not capable of modeling soil and water salinity. The model is applied to Shoor River, a highly saline river, located at upstream part of HRB and SUFI2 algorithm is utilized for model calibration and validation. Calibration is performed based on monthly records of discharge and TDS for the period of 1995-2000 at Shekastian hydrometric station on Shoor River. Calibration resultsshowed that for the best parameters' estimation, goodness-of-fit measures of R-squared (R2) and Nash-Sutcliff (NS) respectively were 0.76 and 0.73 for discharge and 0.63 and 0.56 for TDS. Also validation was based on the 2001-2003 observations where R2 and NS related to the best estimation were obtained respectively as 0.81 and 0.71 for discharge and 0.81 and 0.65 for TDS. Results demonstrated the reliable performance of the model for analyzing river basin’s water and salt regimes.

Climate Change and prediction of its impactson Earth’s system is an important issue in order to reduce the vulnerability and to have appropriate measures to deal with it. In this context, deep uncertainty is the key factor in Climate Change studies. In this study we used the regional risk assessment framework (RRA) to integrate assessment of river basin situation considering deep uncertainties. In this regard, the Zrebar Lake basin was selected as a case study for assessing the proposed methodology. The calibrated SWAT model was used for simulation of the Zrebar Lake basin in the base and climate change condition. The downscaled outputs of RCP2.6, RCP4.5 and RCP8.5 emission scenarios of nine GCM models in three projected periods (2011-2040 and 2041-2070 and 2071-2100) were entered into the model to simulate the effects of climate change. After assessing changes in vulnerable factors in Zarebar Lake basin in order to improve the condition of these factors, adaptation strategies were evaluated with regional risk assessment framework. The results showed that the mean annual temperature was increased by 0.3°C in the first projection period, by 0.6°C in the second projection period and by about 1°C by the end of the twenty-first century. Also the mean annual precipitation in the three projected periods was increased respectively by about 38.5, 66.0 and 87.1 mm. Assessment of the climate change impacts on risk receptors showed that the crop yield and the recharge of aquifers faced the greatest damage under climate change condition. Also, rainfed wheat dealt with more damage compared to other crops. The results indicated the need for appropriate infrastructure in order to cope with the effects of the climate change.

The main land use in Kordkandi-Duzduzan plain is agricultural activities and therefore the possibility of aquifer contamination by irrigation return flows contaminated by chemical fertilizers is very high. Thus, vulnerability assessment of the aquifer seems to be essential for the land use management and preventing groundwater contaminations in the area. The main aim of this study is mapping the region's vulnerability by DRASTIC method and then calibration of DRASTIC model with nitrate data to improve this method. Factors affecting the groundwater vulnerability such as depth of groundwater, net recharge, aquifer media, soil media, topography, impact of vadose zone, and hydraulic conductivity were prepared as raster format in GIS media. Two nitrate data sets were used for validation and calibration of DRASTIC model. The results showed that the determination coefficient between nitrate concentration and the corresponding vulnerability increased from 0.6783 to 0.7903 when modifying layer weights. Based on calibrated DRASTIC vulnerability map, vulnerability index for the study area was calculated between 66.56 and 148.89. The determination coefficient between nitrate concentration values and calibrated DRASTIC vulnerability map were increased compared to the original DRASTIC map which confirms the validity of the calibration process.

As a matter of fact, public funds are not considered to be sufficient and adequate for the construction of infrastructures, buildings and socio- economic facilities required by the country. By providing many public-private projects, the government uses the private organization's finance in order to develop and complete the required infrastructures. In this study, we evaluated and ranked the risk of public-private partnership in Iran’s water supply projects. At first, according to works and researchers performed nationally or internationally, 39 risk factors have been discovered. Then, using FMEA, risk priority number was obtained. After normalization process, 22 factors were considered as critical risks and have been classified into four subcategories appointed as experimental, legal, financial, and technical/ engineering. After analyzing and computing the overall level of risk in each subcategory using Fuzzy Synthetic Evaluation method, the experimental subcategory found to be the most critical one and financial, legal, and technical/ engineering ranked as the next priorities in respect. Finally, the overall risk level of public-private partnerships for water supply projects in Qom has been proved to be 6.19, which indicated a remarkable risk in these projects.

Comprehensive assessment of debris flow hazards is a challenging issue due to its complex and uncertain nature. In this paper, the effect of antecedent rainfall (AR) on the debris flow occurrence in Alborz Zone, Iran, was assessed using Bayesian networks (BN). In this model, the effect of factors such as average basin height, average basin slope, watershed area, the current rainfall, AR (three days preceding the event), and discharge for one-day ahead have been used as the model’s input. Six scenarios were considered including the amounts of AR three days preceding separately, AR two days preceding separately, AR one day preceding, cumulative rainfall of AR three days preceding, cumulative rainfall of AR two days preceding, and the effect of excluding AR. The results indicated that the performance of BN model in the first scenario is %13 better than in the second scenario. The highest accuracy of the model was obtained for the scenario of AR 3 days preceding separately, with a forecasting accuracy of %91. Furthermore, excluding the effect of any of the AR events from the model declined its performance. The proposed model is able to provide reliable results in warning systems for debris flow hazards in watersheds.

This study tries to introduce the flexibility to the yield model using fuzzy approach in order to insert the hydrologic uncertainties and improve the system performance. This purpose attained through artificial time series and applying fuzzy membership function which converts the rule curve into rule band in the yield model. To evaluate the improved rule curve, further artificial time series are generated and the results of reservoir’s simulating via new model and classic model are compared with each other for downstream demands. Performance criterions have been hired for model evaluation. The results for Karaj Dam reservoir in 50 models shows that the average reliability of the systems for firm yield are equal in both classic and new fuzzy model (approximately 98%). The second yield founds around 82% and 55% in the classic and fuzzy model, respectively. The reliability averages for the third yield were 48% for classic model and 31% for fuzzy model. Vulnerability for classic and fuzzy models achieved 28% and 22%, respectively for the firm yield. It found 98% and 45% for the second yield in classic and fuzzy models. For the third yield this criteria was equal to 100% for all series in the classic model, but 82% in average for the fuzzy model.

In south Khuzestan construction of drainage systems is vital for amending saline soils and protecting the lands against salinity stress. However, these systems have some potential environmental effects and have become a major challenge in the region in recent years. These environmental effects can be divided into two categories; short- term effects of primary leaching and long- term effects. According to the salinity distribution in the soil, short-term and long- term environmental effects are conflicting; so that, less salt is discharged to the environment in primary leaching and it will result in high salt discharge to the environment during drainage operation. Therefore, short and long term environmental effects are discussed in this study to determine the optimal parameters for drainage designs. For this purpose, multi-objective simulated annealing model was used. Also, fair benefit division model has been used to select final optimal points among the multi- objective outputs. As a case study to test the ability of presented model, the data of Salman Farsi agro- industrial enterprise was used. According to the multi-objective model results, the optimum installation depth for the output varied between 1.1 to 2.7 m. This optimum installation depth was reduced to 1.45 to 2 m using the fair benefits division model. Optimum installation depth using symmetric Nash method was approximately 1.5 meters.

The aim of this study was to review the effect of excessive withdrawals and recent droughts on groundwater reservoirs of Saveh Plain. The 7 stations in the plain were selected for the monthly rainfall data. In this research, the droughts were examined for CZI, ZSI, MCZI, and SPI indices using DIP software and for the time scales of 3, 6, 9 and 12 months. The groundwater level drawdown in Saveh aquifer was approximately 31.86 meters during the 22 years of 1992-2014. The data for the wells was taken into account during two 10-year periods (1991-2001 and 2001-2011). Considering 5-year periods, we concluded that in the period of 1991-1996 a good regression was obtained and the drawdown was very slow. However in the next 5-year period a steep slope was detected in the regression which was followed by the same or slightly steeper slope in the next period (2001 to 2011). This was assessed as the consequence of unauthorized and uncontrolled exploitation of groundwater through wells. In a review of groundwater quality using AqQa software the Piper diagram indicated calcic facies in the study area and the Durov diagram showed a sudden increase in total dissolved solids and a close to bicarbonate type. This can be due to the formations concerned, the leakage from an underlying semi-confined aquifer, or mixing with another source which requires further reviews.

Evaluation of water quality parameters is very important in knowledge of aquifer- quality conditions, pollution sources, and determination the most appropriate management strategies. With regard to the role of wastewater and agricultural activities in contamination of groundwater resources with compounds such as nitrate and nitrite, water samples were collected from 22 points from urban areas and agricultural lands near residential areas as well as areas with high density of agricultural activities in Asadabad plain. Sampling and analysis of water samples were conducted according to the latest guidelines from the Standard Methods for the Examination of Water and Wastewater. The results indicated that the mean concentrations of nitrate and nitrite in the study area are 19.78 mg/l and 0.035 mg/l, respectively. Taking 33 mg/l and 0.097 mg/l respectively as the maximum allowable concentrations for nitrate and nitrite, it can be said that pollution due to these compounds was less than the standard limits. However the concentrations of nitrate in urban areas and around residential areas reached 24.53 mg/ l which indicated the influence of the released urban wastewater in these areas. The prepared zoning maps of these two anions and combining them into one common layer actually determined the increasing trends in concentrations in the urban and dense agricultural areas.

Recent droughts together with the unsustainable and uncontrolled development, especially the sharp drop in aquifers have led to significant reductions in dams' inflow and accordingly many dams in Iran cannot perform as planned at the time of their studies. Karkheh Dam is amongst crucial dams facing severe hydro stress. Karkheh catchment is one of the most important watersheds in Iran in which there are many dams under construction or under study. Thus, accurate planning given the withdrawals in recent years and the drawdowns in groundwater levels is vital which is considered in this study.To determine the features of water resources development in Karkheh basin, the basin was simulated in MODSIM under various scenarios and the results were analyzed. Where the natural runoff was given as model input, the water demands were supplied in high levels except for a limited number of dams. However with the actual runoff as model input, none of the dams were able to meet their demands. In this case, the agricultural demands were reduced by removing second rotations of crops in all dams. This has led to a relative increase in the supply of agricultural need.

The lack of complete data should not hinder the study of the hydrological condition and the long-term forecasts for performing hydro-projects in one region. Various researchers have used different methods such as Ratio Analysis, Fragment, and Thomas- fiering for the reconstruction of incomplete flow data in hydrometric stations. So, in this study, the accuracy of these methods and computerized methods such as, artificial neural network, hybrid wavelet-neural network, and support vector machine have been investigated and compared. The results showed that the computerized methods have the higher accuracy than the other three methods. Comparison amongst the computerized methods showed that the artificial neural network method (R2=0.98, RMSE=6.18, SE=0.476), the support vector machine method (R2=0.902, RMSE=6.074, SE=0.486), and the hybrid wavelet-neural method (R2=0.889, RMSE=6.96, SE=0.54) ranked first to third, respectively. Although, these three methods have not significant differences in results, but the support vector machine constructed the data in the less time and with more ease and hence had an advantage in comparison with the other methods.

This study is carried out to estimate monthly rainfall data of Oroumieh station which are assumed to be lost from 2006 to 2007. This is performed using classic statistical methods and M5 model tree employing the software Weka based on data from Mahabad, Khoy, Salmas, Makoo, and Tekab stations. Among the studied stations, Mahabad station (R=0.90) had the highest correlation with Oroumieh station. From the 26 scenarios which were introduced to Weka software for 10 year data of the nearby stations, the one which included three stations of Mahabad, Makoo and Tekab with MAE=7.19, R=0.90, and RMSE=9.64 was defined as the simplest and most accurate scenario due to the less input parameters to the model. Among the classical methods, the single best estimator (SIB) method has been selected as the best method with the highest correlation coefficient and the lowest error (R=0.90, RMSE=10.51, and MAE=7.07). M5 model tree had the best performance in estimating data (R=0.91, RMSE=9.94, and MAE=7.29) and was considered as an alternative and applied method in the calculation of monthly precipitation data due to simple linear and comprehensible relationships.

Finding sustainable and cost-effective solutions in water resources management is one of the most prominent challenges which communities are confronting. Urmia Lake is one of largest hyper saline lakes with an strategic significance in the region. While the status of Urmia Lake is catastrophic, finding management practices to restore a sustainable ecological status for the Lake, is vital. In this paper, system dynamics approach was used in order to evaluate the effects of different restoration policies on Urmia Lake. Policies such as increasing irrigation efficiency, reduction in cultivated land, changing in crop patterns and water transfer from Aras and Zab Rivers were evaluated in this regard. The results showed that none of the individual projects was effective on Urmia Lake restoration and the simultaneous implementing of increasing irrigation efficiency, changing in crop patterns, and reducing cultivated area had the greatest effect on increasing water level in the Lake and in a period of about 8 years Urmia lake could be restored.

Hydraulic models are the primary tools used to plan and develop structural and non-structural flood mitigation and management solutions. Such tools are used to simulate probable inundation damage on a given area depending on several flood scenarios with different intensity, duration and return period. Raster-based models have recently gained credence in the modelling of floodplain inundation and flood hydraulics. In this paper the 2D hydraulic model, LISFLOOD-FP, was applied to a 7 km reach of the Chehlchay River in Golestan province to predict flood extents with different return periods. The model was calibrated for a flood event in 2011 using floodplain and channel friction parameters against observed inundation extent as determined from satellite (Google Earth) images. The friction parameters were found through a calibration procedure where a measure of fit between predicted and observed extent is maximized. Model validation was performed using a distinct flood event in 2016. The measure of fit (F) was obtained in the calibration and validation process as %71 and %78, respectively. Finally, the calibrated model was used to predict floods with different return periods.

The salinity of fresh water is one of the serious contamination threat of groundwater in many countries. Garu Spring in the East of Khuzestan province is one of the salty springs in the Zagros zone. Based on field investigations, possible sources of salinity in the region include dissolution of Gachsaran evaporative formation and oilfield brines. To identify the source of salinization in the study area, two sets of samples (20 and 17 samples) were taken from groundwater and surface water resources in February and September 2015 in order to determine respectively the main elements and Br. Combination diagrams of bicarbonate against calcium, magnesium, sodium, sulfate, and the ratio of Br/ Cl and TDI against chlorine were used as the best distinction between various origins of the salinity in the area. The results show that the main reason for salinity is influx of high volume of Temby river water in wet seasons and mixing with oil brines in dry seasons.