IRAN-WATER RESOURCES RESEARCH
Year:2015 | Volume:11 | Issue:2 (33)|Papers Count:13

Study on spatial variation of any groundwater quality parameter is not possible without taking the spatial relationship amongst the parameter values into account. Geostatistical methods are useful tools for conducting such studies. In this study, due to significant spatial and temporal variation of salinity (EC) in Feyz Abad-Mahvelat plain, EC data collected between the years 1386 and 1391 from operational wells in the plain, were analyzed to identify the best Geostatistical method applicable to the EC data in the plain. Although EC values change over time and space, for the spatial analysis an average annual data was considered. Based on the preprocessing of the data, capabilities and properties of different Geostatistical methods, and literature review on the subject, six different Geostatistical methods were selected for the analysis including appropriate types of Ordinary and Universal Kriging and Empirical Bayesian Kriging (EBK). Since there are numerous internal parameters in different methods of Kriging, a systematic multi-step procedure was used to optimize the parameters and to find the best model. To achieve this, 390 combinations of methods and parameters were generated and used in the comparative analysis. First the best models were selected using cross validation and a defined lumped statistical measure that combines two conventional error measures in a single one. Then, sensitivity analysis was performed on the selected best models and also they were evaluated in terms of compliance with the field conditions. The procedure was applied to the first and last year of the available data, separately (year 1386 and year 1391). The results indicated the superiority of the EBK method in terms of both accuracy and performance compared to the other methods. In addition, the generated maps showed the high level of salinity in the northern, southern, and western plain borders and significant salt water intrusion from the western border over time.

Public participation has been given a momentum in the recent decades. Stakeholders’ participation in the process of decision making can result in a variety of ideas and experiences which can come up with alternative solutions. Stakeholder analysis will help to recognize the power and the benefits of all players involved in a managerial process or a policy. Water resources systems should be assessed from different aspects in a systemic way. Although very vital, assessment of the social structure in water resources development plans is indeed a forgotten stage in the process of water resources management. The present study aims at investigating the social structure to enhance the process of water resources management relying on the local water governance. That purpose is illustrated in terms of stakeholder analysis in the Rafsanjan plain study area. Thus, adopting the UNDP methodology based on field and questionnaire surveys, the paper adopts the stakeholder assessment in three steps. The data were statistically analyzed using the Exploratory Factor Analysis (EFA) method in the SPSS software. As the results, the stakeholders’ power and benefits were found out and they were prioritized regarding their levels of importance. The key stakeholders were identified and four levels of participation were suggested for the groups of stakeholders. Close interaction and decision making in the first level of stakeholders was identified as the ideal scenario to motivate stakeholders' participation in achieving a consensus on a road map to conquer the local water problems. The outputs can be considered as the starting point to encourage the local public participation.

Optimal operation of multi-reservoir systems is amongst the important problems in the field of water engineering which cannot be easily solved. Nowadays, water engineering experts are using Meta-heuristic algorithms to solve this problem due to the computational capabilities of these algorithms. Ant Colony Optimization algorithm is one of the algorithms which is based on foraging behavior of real ants. In this research, the capability of four different ant colony optimization algorithms, Ant System, Elitist Ant System, Ranked Ant system, and Max-Min Ant System has been tested to solve the four- and ten-reservoir benchmark systems. For each algorithm two different formulations are proposed; in the first formulation reservoir releases and in the second formulation reservoir storages are considered as decision variables of the problem. The results showed that the Ant Colony Optimization algorithm is a competent algorithm to solve Multi-reservoir system operation optimization problem. The Max-Min Ant System is also assessed as superior to other algorithms for such problems.

Many models (e.g. hydrologic, meteorologic, crop yield) need for stochastic daily rainfall generation. Most of the stochastic models are single-station and rather few deal with rainfall correlation structure (occurrence and amount). A plausible shortcoming of the later, however, is due to not considering the possible time-non-stationarity. A total of 36 rain gage stations with 30 years of record were considered in North-, Razavi-, and South-Khorasan Provinces for this study. One stochastic rainfall generation consisting of first order Markov model for rainfall occurrence and Gamma probability density function for rainfall amount for 6 rainy months of November to May was adopted. Results showed that the model parameters (rainfall probability conditioned to previous day rainy or dry state, and two parameters of Gamma distribution) were depended on the month of the year and on the geographical location. Yet significant relations were not found to describe them. It was shown that all parameters were non-stationary in time. Non-stationarity was modeled through regime shift concept. Results showed that nearly all parameters of rainfall amount model (Gamma probability density function) were independent of regime shift. This may be a clue for a plausible regional probability density function. However, the regime shifts for all parameter were not consistent which poses difficulty in modeling the stochastic generation of daily rainfall in the region.

The right water pipe selection would save the cost and minimize the wasted water in the water conveyance and distribution systems. The aim of this study is to determine the proper pipe for water networks in less populated areas. Villages of East Azerbaijan, Iran is studied in detail as the case study to this research. To evaluate different types of the pipes, 22 effective criteria are initially proposed through questioning nineteen experts. The degrees of consensus of decision-makers on the weights of these criteria are calculated by a rigid consensus way; standard deviation method. With the help of a rigid consensus degree, 8 of the criteria with higher consensus were then selected. The final choice for pipe type among the four types of Polyethylene, Steel, Ductile Cast Iron, and PVC is then made based on the rigid method using TOPSIS. Again, to check the consensus on criteria using soft methods, a questionnaire is designed. Seven experts, who worked on the previous part, evaluated the criteria in a pairwise approach. The weights for the eight criteria have been calculated with the Orderd Weighted Averaging method (OWA) and finally the alternatives are ranked with TOPSIS method. Using GFDM software a more detailed sensitivity analysis has been also performed. Finally the polyethylene pipe is recommended as a most robust and effective option.

In this paper, the climate change impacts on snowmelt-runoff processes in upstream of Zayanderoud river basin, the sub-basin upstream of Ghaleh Shahrokh hydrometry station, has been studied. For this purpose daily and eight days MODIS snow cover products have been used to monitor snow cover changes as effective variables in SRM runoff-rainfall model. As a preprocessing step, the accuracy of MODIS products in snow cover assessment are evaluated by the observed land data. The results indicated that the accuracy of the daily snow product in overall, clear sky conditions, and eight day product is 73.4, 92.1 and 84.2 percent, respectively. The snowmelt runoff is modeled in the sub-basin utilizing extracted snow cover, temperature, and precipitation variables and SRM model parameters. The modeling results indicated acceptable performance of SRM in calibration and validation procedures. In this research, the HadCM3 model data under A2 and B2 emission scenarios is utilized. SDSM model have been used to downscale GCM data. The results showed a decreasing trend in precipitation over the case study area for the upcoming decades. Finally using GCM downscaled outputs and the developed snowmelt model, the future runoff in two periods of 2011-2040 as a near future and 2071-2099 as a far future are evaluated under climate change condition. Results showed that annual runoff will decrease and seasonal winter runoff will increase. Also the seasonal runoff in spring will significantly decrease.

Salinity and water deficiency are the major constraints of crop production in arid and semi arid areas. Plants in these areas may simultaneously be affected by salt stress and drought based on the water quality and quantity. Considering the limitations of water resources in such areas, optimization of product depth of irrigation is very important. The main goal of this study is to provide a water resource allocation optimization method according to the qualitative and quantitative restrictions in order to manage water allocation in droughts. Also to enhance the modelling efficiency, water allocations in irrigation networks, crop productions and their growing stages and irrigation periods are considered in the optimization procedure. Finally, the developed model is able to estimate crop yields as well as the optimal amounts of water allocation from reservoir to plant growth stages due to salinity and water resources constraints. Evaluation of proposed model in Zayandehroud irrigation network showed that the modeling system used in this study is able to cover required calculations for allocation and distribution of water between sub-networks, crops, and agricultural irrigation planning according to the qualitative and quantitative restrictions in water resources.

In recent years, due to the increasing rate of water demand and severe droughts, groundwater resources are considered as the most important sources of fresh water. Accordingly, a comprehensive strategy along with a long term plan is needed for preventing groundwater destruction. Variations in aquifer water level, are amongst the main factors which provide correct judgment about groundwater status and govern the watershed management projects. In the present study, monthly data (1999 to 2009) from 33 observational wells in Shahrekord Plain have been used for simulating the groundwater level. The relationship among the Shahrekord Plain coordinates and the groundwater level variations, for 1, 3, 5 and 10 year period, were investigated using Linear Discriminant Analysis (LDA), Quadratic Discriminant Analysis (QDA), and Support Vector Machine (SVM). The results showed that the SVM is superior to the other two models due to its lowest average relative error in 1 and 3 year periods, and its acceptable precision in 5 and 10 year periods.

Climate change causes the change in temperature, rate of evapotranspiration, soil moisture, wind speed, and temporal and spatial variation in precipitation. These factors will lead to changes in hydrological parameters, such as groundwater level. According to the important role of climate parameters in water resources management, in this study HADCM3 model and A2, A1B and B1 scenarios are used to predict the climate parameters. For the statistical downscaling of atmospheric general circulation model data, LARS-WG model is used as one of the most famous random weather generator models. Also prediction of groundwater levels changes in Tasuj basin was done by time series models in R software for the period of 2013-2022. The results revealed a decrease in rainfall as well as higher temperatures in the A2 scenario compared to the other scenarios. Changes in temperature and precipitation are similar in A1B and B1 scenarios. In all three scenarios, maximum rising temperatures and the highest percentage of precipitation decrease will occur in the months of June, July, August and September which coincides with the peak of groundwater use for drinking, agricultural and environmental purposes. Also the cross-correlation showed that the impact of rainfall on groundwater levels has a 2 months lag. Due to the climate change and assuming the persistence of the existing conditions of exploitation from groundwater in Tasuj basin, the cumulative decline of groundwater level in a 10-year period is predicted as 7.85 meter below the baseline in 2002. These forecasts should be taken as a serious warning for water management in this region so that to prevent human and environmental disasters.

Waste load allocation (WLA), which refers to determination of the optimum treatment level of waste load discharged into a river by every pollution source, has attracted the researchers and policy makers during the last decades. In most proposed WLA models, objectives and constraints such as minimizing the treatment costs, equity considerations in distributing costs, minimizing the amount of river water quality violations, and minimizing the duration of violation intervals are taken into account. In spite of the importance of the researches on WLA in rivers, there is only one paper by de Melo and Câmara (1994) in the literature which present an integrated review on the main objectives and constraints in river water quality management models. Recently, modeling important uncertainties and dischargers’ utilities have become the major focus of many WLA researches. In this paper, more than 60 major papers in the field of WLA in rivers are reviewed and their main aspects, virtues, and limitations are discussed. Also, some prospects and ideas for improving the current models in future are presented.

Pressurized irrigation is one of the proposed plans to resolve the Urmia lake crisis. The effects of such plan can be assessed using the hydrological simulation. But different agricultural management approaches and uncertainty in the model inputs lead to complexity in the basin modeling which in turn increases the uncertainty of model outputs. The main purpose of this study is to determine the effect of the pressurized irrigation on Zarinehrud basin as the largest sub-basin of the Urmia Lake basin. For this purpose, by determining the probable scenarios of water demand, the impact of these scenarios on the basin hydrological components were simulated with SWAT model. Then by combining the results of the scenarios, the uncertainty bounds of the hydrological components were estimated using Bayesian model averaging (BMA). The results showed that the annual average of upper and lower bound of the basin outflow will be 1391 and 1316 MCM. Also irrigation efficiency in the field scale and in the basin scale varied between 40-47 and 78-81 percent, respectively. In case the pressurized irrigation is applied, the annual average of upper and lower bound of the basin outflow will be 1322 and 1364 MCM which did not show a significant change compared to the current conditions.

Rainfall-Runoff is considered one of the most important processes in water resources studies. In this study, to simulate the daily rainfall-runoff process of Balikhluchay Basin, four hybrid models of Support Vector Machine, Artificial Neural Networks, Wavelet-Support Vector Machine, and Wavelet-Neural Networks have been applied and compared. Daily Rainfall-runoff data for the period of 2000 to 2008, have been used for training and testing the models. In general, the results indicated acceptable accuracy of all the models. In terms of priority, the hybrid model of Wavelet-Neural Network with the highest accuracy and lowest errors was in the first rank and the Hybrid models of Wavelet-Support Vector Machines, Artificial Neural Networks and Support Vector Machines, were in next priorities.

Any change in the pattern of precipitation can have a significant impact on the water resources availability, agriculture, and ecosystem. Therefore, knowledge on rainfall trends is an important aspect of water resources management. In this study time series of moving summation with ranks of 1 to 48 months were studied in the 32 national synoptic stations using nonparametric Mann-Kendall method (after removing the correlation value of the first series) and Sen’s slop stimulator. The Results indicated abundance of trends in the long series compared to the short-term series (in total 60% of the obtained trends have significant downward trend, 32% showed a significant upward trend, and 8% were in non-significant trend). Spatial distribution of significant downward trends in most parts of the country is considerable. The present condition can be a serious threat to groundwater resources in most parts of the country since the significant portion of water resources in Iran is dependent on the groundwater resources and these resources are in direct contact with long series of precipitation.