Journal of Water and Irrigation Management
Year:2020 | Volume:9 | Issue:2|Papers Count:12

The main purpose of this paper is to investigate the Shannon’ s Entropy in surface water quality evaluation. To achieve this aim, the Shannon’ s entropy and the World Health Organization methods have been used to assign weights of the water quality parameters. Monthly hydrometric data including; Ca, Mg, HCO3, Na, SO4, EC, pH, TDS were analyzed, form 1968-2015, which were measured and recorded at Ahwaz, Darkhovein, Gotvand and Molasani stations of Karun River and as well as; Quran-Talar and Koshtargah hydrometric statins of Babolrood River. The above mentioned rivers are flowing in south and north of IRAN, respectively. The result demonstrated the accuracy of the Shannon’ s Entropy performance. As the result showed, the Shannon’ s Entropy result gave an encouraging level of agreement with the WHO’ s result. However, there were small discrepancies between these two results. Shannon’ s entropy weights and the effective parameters of Karun River water quality at different hydrometric stations are Ahwaz pH=0. 15, Darkhovein TDS=0. 11, Gotvand EC=0. 13 and Molasani pH=0. 15, respectively, and in a same way for Babolrood River at stations; Quran-Talar pH=0. 15 and Koshtargah TDS=0. 14, respectively. According to the water quality index values of Karun River, its waters are classified in both excellent and good conditions. However, based on the mentioned values the Babolrood River is classified in excellent condition.

Some experiments were performed around the Agricultural and Natural Resources Research Station of Islamabad-Gharb city in order to determine the economic evaluation of corn crop behavior to deficit irrigation and surge irrigation strategy in Islamabad-Gharb Area under ferrow irrigation. The statistical design of the research was Factorial design (as compound analysis in two years) in a randomized complete block design Which has two factors at 3 and 4 levels. Factor A (irrigation water quantity) and factor B (surface irrigation method), so there was 12 treatments and 3 replications. The results showed that in different irrigation methods The highest net and net profit than the amount of water consumed at 2016 occurred of S1-2 treatment respectively 6. 46 and 2. 84 billion rials per cubic meter also at 2017 occurred of S1-2 treatment respectively 6. 49 and 2. 62 billion rials per cubic meter and in different irrigation regimes The highest net and net profit than the amount of water consumed at 2016 occurred of 75% water requirement treatment respectively 6. 98 and 3. 5 billion rials per cubic meter also at 2017 occurred of 75% water requirement treatment respectively 6. 91 and 3. 2 billion rials per cubic meter.

Monitoring network optimization is a decision making process for the best combination of available stations. Due to economic considerations and reduction of monitoring costs, the optimization approach in this study is to reduce monitoring stations without reducing the amount and accuracy of the information obtained. In this study, an optimal design of groundwater quality monitoring network was carried out with the help of an optimization model in the Neishabour plain aquifer. The optimization of the wells network was accomplished by a Multi Objective Particle Swarm Optimization (MOPSO) algorithm. Two objectives containing of minimizing the root mean square error (RMSE) and the number of wells was applied in current research. Kriging interpolation was used for calculating groundwater chlorine concentration values and compared with observation values. As a result of this research was presented a Pareto front exctracted from MOPSO showing the number of wells against their corresponding RMSE, which could be a guide for the design of a groundwater quality monitoring network. The outcome showed that the sampling wells can be reduced to 58 percent with a minimum error increase (all 50 wells in base network with zero error may be reduced to 21 with chlorine concentration error of 13. 57 mg/l) in the Neishabour aquifer. Also, the position of these wells was considered as the optimal position.

The meteorological data of 12 synoptic stations of Khuzestan province with a 20-year statistical period (1999-2018) were used to perform the present study. First, using CROPWAT software, the effective rainfall was estimated from three methods USDA, FAO and the developed experimental formula. Using AquaCrop software, real transpiration evaporation of rainfed wheat in the study area was calculated and effective rainfall amount was obtained. Then, using ArcGIS software, effective rainfall zoning at the stations studied was drawn in November, December, January, February and March. Relative error (RE) results showed that in the three most rainy months of November, December and January, the best estimation of rain was the experimental method with mean error of-8. 8 percent, FAO with-21. 7 percent and experimental with 12. 9 percent, respectively compared to the inverse solution method. In the low rainfall months of February and March, the USDA method had the best estimation of the effective rain of these three methods with the inverse solution method with-48. 6 percent and-51. 6 percent, respectively. The zoning map of the estimated effective rainfall also showed that in the rainy months and when the plant is in early growth, the amount of effective rainfall increases by moving from the north side of the province to the southern part. The overall results show that the percentage of confidence in the experimental methods is low and by calculating the effective rainfall and changing the date of cultivation at the country level can increase the productivity and production of rainfed crops.

Dams are effective in controlling the flood and reducing its damage. But, during the flood, the overtopping and the flow of water from the dam is always threatening it. Therefore, in order to maintain the dam safety against flood and also to maintain the efficiency of the dam, it should be balanced between the water level in reservoir of dam and its overtopping risk. Using the system dynamics, a set of complex, relevant, and effective overtopping factors could be simulated to examine the impact of different scenarios. The current research investigated the effect of different parameters on the overtopping risk on Hajilarchay dam (Northwestern Iran) using the system dynamics and Monte Carlo simulations, and estimated the human losses caused by the dam failure using of 441 and 118 persons for two cases of without warning and adequate warning, respectively. The overtopping risk of 2. 27×10-6 was calculated in accordance with the USACE method. Given this risk value, a reliable level for reservoir water is set to 1040. 70 meters above sea level, and the agriculture area at the downstream is set 1660 hectares for development. The results also show that the overtopping risk will increase by increasing the life of the dam, especially after 20 years, due to accumulation of sediment and settlement of the dam, and considering too much increase in overtopping risk caused by the change of dam’ s spillway in order to save the cost of its construction, then adaptation strategies are provided including reservoir water level control.

Agricultural and industrial development has led to a sharp increase in water use, a decrease in the quantity, quality and pollution of groundwater resources. Appropriate measures to prevent pollution of groundwater resources are the identification of vulnerable aquifers. In this study, combined method is the combination of DRASTIC and SINTACS methods, was used to evaluate the vulnerability of Khoy plain aquifer. Both methods use hydrological and hydrogeological parameters of this area to investigate the aquifer vulnerability and zoning of susceptible areas, but each of these methods has inherent characteristics and presents different results. Therefore, in this study due to the similarity of the results of these two. The method has been used simultaneously using combination of their advantages. Validation of each of methods were carried out with measured nitrate values from 26 wells in the study area. The Correlation Index (CI) and correlation coefficient (r) were calculated between vulnerability maps and nitrate values to validation and compare these methods. The results showed that the CI and r of combined method is high; therefore, this method is more suitable for assessing the vulnerability of this region. Based on the results of the combined method, 19, 42 and 39 percent of Khoy plain aquifer are located within low, medium and high vulnerable areas.

The goal of this study was to investigate the effect of conjunctive irrigation with seawater and fresh water on the growth properties of Spinach (Spinacia oleracea L. ) in greenhouse condition. In this study, four conjunctive use of seawater and fresh water (tap water, irrigation with 1/2 of seawater with tap water, alternate irrigation with seawater and tap water, the mixture of seawater and tap water) is evaluated on yield and yield components of Spinach. The research was done based on completely randomized design including 3 replications as pot planting in Gorgan University of agricultural sciences and natural resources during 2016. The results indicated that the effect of different moderation of irrigation regimes on the shoot and root dry weights, shoot fresh weight was highly significant (P<0. 01), but root fresh weights, leaf number, plant height, and chlorophyll were significant at 5 percent levels (P<0. 05). The result showed that the highest yield and yield components of Spinach in control treatment and afterward 1/2 seawater followed by 1/2 freshwater irrigation regime compared to other regimes (a mixture of 30: 70 seawater and freshwater, alternate regimes), was measured. half alternate of sea water and tap water has resulted in decreasing of shoot fresh and dry weights 1. 05 and 1. 1 percent, respectively.

Accurate prediction of river daily discharge is a suitable tool for water resources planning and management. In this paper, cross station discharge of the Arkansas River in U. S. A, were examined using Gaussian Process Regression (GPR), Extreme Learning Machine (ELM) and complete ensemble empirical mode decomposition combined models. For this Purpose, in the first step, the daily and monthly discharge was predicted via GPR and ELM models. Then, the discharge time series were broken up by CEEMD method into cages, and these subclasses were introduced into the Gaussian process regression end ELM modeling to simulate discharge. Furthermore, direct correlation (DC), Root Mean Square Error (RMSE), correlation coefficient (R) and Mean Absolute Percentage Error (MAPE) were used to evaluate the efficiency of the models. The results showed that the CEEMD approach improved the performance of the above mentioned models dramatically. For instance, the values of MAPE correspond to GPR hybrid model in forecasting discharge in the first, second and third station with CEEMD pre-processing were reduced by 34, 27and 32 percent, respectively, as compared to those in the GPR model without pre-processing. Also, the effect of each of the sub-series of ensemble empirical mode decomposition model (Residual and IMFs) was studied to improve predictive outcomes. It was observed that the most inefficient subseries in the complete ensemble empirical mode decomposition model is the residual subseries. The CEEMD-ELM model can be used in watershed management and flood control in Iran.

The process of infiltration is one of the most important components of the hydrological cycle and field water management. The direct measurement of infiltration process is difficult, time spending and expensive. Therefore, infiltration models are used. Kostiakov, Kostiakov-Lewis, Philip, Soil Conservation Service of America, Horton and Overton models infiltration based on double ring results carried out in two wheat and bean fields to the determination of best infiltration model in the Jahad Nasr Khuzestan province. The results showed that the mean infiltration rate in wheat field was 35. 47 cm hr-1 in 15. 83 percent moisture before first irrigation up to 6. 35 cm hr-1 in soil moisture content of 29. 20 percent after second irrigation. The average infiltration rate in the bean field with initial moisture was 16. 43 percent before the first irrigation from 61. 63 to 13. 70 cm hr-1 in the soil moisture content of 23. 10 percent after the second irrigation. The lowest and highest RMSE for coefficients of cumulative infiltration models in wheat field were obtained from Philip and Horton equations with 1. 21 and 3. 14 cm with R2 of 0. 93 and 0. 95 and the bean field was 1. 57 and 3. 42 cm with R2 of 0. 90 and 0. 92, respectively. The lowest and highest RMSE of the infiltration rate in the wheat field were obtained Philip and Horton equations with 0. 46 and 0. 63 cm min-1 and in the bean field were 0. 90 and 1. 40 cm min-1, respectively. The accuracy rating of the studied models in two fields showed that Kostiakov-Lewis and Horton models have the highest accuracy in the infiltration rate and Kostiakov-Lewis and Phillip models in cumulative infiltration.

One of the factors of the water resources crisis is the lack of attention to the social dimension of water governance. This paper investigates the social assessment of groundwater governance scenarios. For this purpose, in the first step, the modified scenarios of groundwater governance were defined by the participation of actors and with regard to the water, food, energy nexus. Then, the performance of groundwater governance scenarios from the social perspective was assessed using criteria-based appraisal. For this purpose, social acceptance, social justice and social participation were defined as social criteria and their values were calculated by using questionnaire and social network analysis. The groundwater governance scenarios were ranked socially applying a compromise-programming algorithm to combine the criteria. The results showed that developing cohesive region-specific cropping pattern and enforcing cropping pattern by chain value management scenario had the highest score (0. 485) and modifying regulation to seal all unauthorized wells scenario had the lowest score (0. 392) in terms of social impact in comparison with the other groundwater governance scenarios. Therefore, the social assessment of groundwater governance scenarios enables policymakers to assess the impact of scenario implementation on society to formulate a better policy.

By considering the lack of high-quality water resources, the use of refined sewage as cheaply available water resources can reduce the challenge for water demand in Iran. This research aimed to investigate the accumulation of lead and cadmium in soil and seed of wheat and barley crops that are irrigated by refined sewage and a mixture of unrefined sewage and well water, respectively, in Qods city. During two growth months (March and May 2017), every ten days, one sample of each treatment was investigated to evaluate the physical and chemical properties of incoming water (totally nine samples per treatment). Sixty samples (30 samples from each plant) were randomly harvested. For soil measurement, 30 samples were randomly sampled in each filed (May 2017). The results showed that the values of EC, biological and chemical oxygen demands, lead and cadmium concentrations were more in the mixture of well water and unrefined water than refined water. There was no significant difference between the cadmium concentrations in the seeds of the two plants; however, the lead concentration in the seeds of barely was significantly more than wheat. The differences in the mean of lead and cadmium concentrations in the soil of two plants were not significant. The results of the bioconcentration factor i showed that none of the plant’ s ability to extract lead and cadmium. Only the concentration of lead metal in barley is higher than the World Health Organization standard, which indicates that the grain produced in this field is harmful to human consumption.

Common genetic programming (CGP) with considering empirical data (observed) improves and evolves estimated data (calculated). However, CGP is not able to solve multi-conditional problems with satisfactory performance. In this study, capability of the CGP is improved through development and integration of mathematical functions and logical operators on it. Proposed algorithm is called logic genetic programming (LGP) that its performance improvement is investigated in comparison with CGP in field of water resources. Results show that LGP capability, is more effective and more efficient than CGP, so that LGP improves objective function by 39 percent compared to CGP, in extraction of standard operating policy (SOP) [with minimization of mean absolute error (MAE)]. Comparison of algorithms results using the evaluation criteria indicate that LGP algorithm in SOP reconstruction resulted in a 22% decrease in RMSE and a 1% increase in NSE compared to CGP.