مجله مدیریت آب و آبیاری
سال دوازدهم شماره 4 (زمستان 1401)

Groundwater inflow is one of the most important problems in Constructing a conveyance tunnel. Increasing pressure on the tunnel wall and reducing its stability, the related issues of drainage and pumping, destructive impacts on the mechanical and geological condition of the tunnel surrounding environment, loss of life, increased costs, and advance delays are among the most important challenges that can be existed during excavation. Therefore, it is crucial to evaluate the amount of water inflow and predict the required measures previously. Conventional techniques for estimating the water inflow are analytical-experimental techniques whose efficiency in complex heterogeneous and anisotropic aquifers is always tainted. Accordingly, this study intends to investigate the effectiveness of the Meshfree (Mfree) numerical method for simulating the groundwater level in the environment surrounding the Safarood water transfer tunnel in Kerman. Also, considering the uncertainty analysis, uncertainty of parameters (hydraulic conductivity), input data, and structure of numerical modeling were addressed using DiffeRential Evolution Adaptive Metropolis (DREAM) algorithm. Hence, an open-source framework based on a Mfree numerical method and DREAM algorithm was proposed for the simulation-optimization process of groundwater level prediction in the environment surrounding the tunnel, and finally, the water inflow discharge was estimated. The results of uncertainty analysis indicated that hydraulic conductivity parameters may be ranged between 0.0002 to 0.2 m/day in different homogeneous zones. Also, the study of thin sections samples collected from field observation shows that hydrothermal conditions have influenced directly the alteration of rocks and minerals in some zones and likely it is the main factor in increasing permeability in these areas. The results showed that the recorded input data has a four percent underestimation. The uncertainty of the parameters involved with the structure of numerical modeling also proved that to obtain an adequate accuracy, the size of the local domain must be about 0.85, and the support domain should be considered at least three nodes to estimate the weight function. The simulation results of groundwater level fluctuations using the derived true values of parameters showed that there is a good accuracy between the observed and simulated values (the RMSE index was estimated to be about 2.531 meters). In addition, the assessment of numerical simulation of groundwater inflow into tunnel indicated that inflow rate in the north and south parts is respectively 72.43 and 09.45 l/s.

The largest area of rainfed fig orchards in the world, with more than 22000 hectares, is located in Estahban, Fars province. During the last two decades due to frequent droughts and lack of fresh water resources in this area, the saline groundwater has been applied for irrigating fig trees. In the past, no comprehensive research has been done on the effects of supplemental irrigation with saline water on rainfed fig orchards. This study investigated the effects of saline irrigation water (7.38-7.8 dS/m) and high soil electrical conductivity on the quality and quantity of rainfed fig during 2010-2011. Experiments were carried out in a private rainfed fig orchard located in the village of Khane-Ket by sampling soil and roots in different parts of the garden. The results showed high tolerance of fig trees to high EC values of water and soil. However, increasing soil salinity under uniform irrigation conditions reduced the yield. Based on the results, there is a negative linear correlation between salinity and yield, with the coefficient of determination (R2) equal to 0.5. A 36 percent reduction in EC values could increase the yield by 68 percent. Also, the regression equation between EC at different depths and the amount of production was obtained. Also, by determining the EC profile in the soil, its maximum value was found at a depth of 60-90 cm. In terms of fruit quality, soil salinity did not significantly affect fruit color and size; however, it increased the total soluble solids (TSS) of fruits.

Lack of water resources in Mazandaran province and the volume of effluent produced in different sectors, ‎has caused that in order to reduce the withdrawal of surface and groundwater resources in the province, the ‎use and management of unconventional water resources, much attention is paid. The purpose of the present ‎study is to evaluate the application of unconventional water use scenarios on the amount of runoff and ‎sediment in six stations (including Kordakhil, Garmroud, Varand, Vastan, Parvijabad and Aliabad stations) in ‎the Tejn watershed during the years 2000 to 2017 using the SWAT model. Recalibration and validation of the ‎model using data from 2003 to 2012 and 2013 to 2017 and then to evaluate the scenarios of allocating 30% of ‎the available wastewater for agriculture (scenario one), allocating 30% of unconventional water to feed ‎aquifers in the conditions of applying scenario one (scenario two) and a 20% reduction in the extraction of ‎underground water sources for irrigation and the use of unconventional water sources as alternative sources ‎to meet environmental needs (scenario three).‎‏ ‏Evaluating the efficiency of the model using R2 and NSE ‎coefficients shows the proper performance of the model in simulating these two parameters. The results ‎indicate that the application of scenario one did not affect the amount of runoff and sediment in the basin, but ‎with the application of scenario two, the amount of runoff and sediment decreased by 13.4% and 9.1%, ‎respectively. Applying Scenario three should be 10 to 20% of the annual discharge for the second six months ‎and 30 to 40% of the average annual discharge for the first six months of the year in order to meet the ‎environmental needs. The results obtained from the present research show that the use of non-conventional ‎water, in addition to solving the water shortage, also reduces the problems caused by the flow of runoff and ‎the settling of sediments.‎

The quality parameters of the river, including electrical conductivity, are highly dependent on changes in flow rate. Adding the flow rate parameter to the simulation of this parameter can increase the certainty of the simulation results. For this reason, in this study, random forest, CARMA and CARMA-GARCH models were used to model the electrical conductivity values in Gerdyaghoub, Kutar and Bitas stations in Mahabadchai basin, taking into account the flow rates. In this regard, the monthly values of electrical conductivity and flow discharge in the statistical period 1986-2018 were used. The results were analyzed using Nash-Sutcliffe statistics, root mean square error and violin plot. The results of evaluation the root mean square error and Nash-Sutcliffe statistics showed that the simulation results of CARMA-GARCH model compared to CARMA model in Bitas and Kuter stations as well as the training step in Gerdyaghoub station were improved. The results showed that the combination of nonlinear and linear models could improve the modeling error in three stations, Gerdyaghoub, Kotar and Bitas in the training step of 9.56, 9.70 and 21.68 percent. By examining the violin plots, the results showed acceptable accuracy and performance of CARMA and CARMA-GARCH models compared to the random forest model. In general, the results showed that time series models have higher accuracy in bivariate simulating of electrical conductivity values in the study area.

Evapotranspiration calculations by the FAO Penman-Monteith method require many parameters, the lack of some of which makes the calculations difficult. On the other hand, it is necessary to use methods that are easier to calculate and are easily understood by farmers. One of the indirect methods of estimating reference evapotranspiration is the pan evaporation method, which can be considered as a suitable index to estimate the evapotranspiration of the reference plant and finally the main plant. In this method, in order to calculate the potential evapotranspiration, the results of pan evaporation must be multiplied by the pan coefficient. Accurate calculations related to the estimation of the pan coefficient are very important because it can be used for irrigation planning when there is no lysimeter equipment. In this study, by using of daily, hourly meteorological data, and data from class pan A evaporation from meteorological stations of Kermanshah province in the long term, potential evapotranspiration values of the FAO Penman-Monteith and then pan coefficients were calculated. The index coefficients as a measure of estimation methods for Cuenca, Allan, Snyder, Modified Snyder, and Orang were used. The results showed that the, Orang and modified Snyder method had a higher level of accuracy compared to the other methods. The R2 with Orang method for different cities of Islamabad Gharb, Qasr-e Shirin, Kermanshah, Sararood, Sonqor, Gilan-e Gharb, Sarpol-e zahab, Kangavar were determined as: 0.84, 0.77, 0.72, 0.76, 0.85, 0.79, 0.77, and 0.73, respectively. Finally, the values of pan coefficients calculated by all methods in study stations in different months were calculated and presented. It is hoped that the results of this study will be used by managers and farmers in the region.

In this research, the simulation and phase transfer of heavy metal solution in the river has been done by developing a one-dimensional qualitative model. Environmental parameters (T), temperature, dissolved oxygen, (DO) (pH) and salinity (EC) are considered as influencing parameters on the change in the concentration of the solution phase of heavy metals lead, cadmium and zinc in springs and wells of the displacement-diffusion equation. Became to determine the above hydrodynamic and environmental parameters for use in the developed model, Hec-Ras hydrodynamic model and Qual2kw qualitative model have been used. In decoupling the spring and well terms of the displacement-diffusion equation of the qualitative model developed using the measured data from the Sarouk River, various relationships were considered to relate the kinetic coefficient of the first-order reaction of the dissolved phase of heavy metals to the above environmental parameters. And to find the constant coefficients of these relations, the method of minimization of simulation errors and Vba coding was used, and the linear relation including all the above parameters is considered as the final relation. The kinetic coefficient of the reaction is different in different parts of the river, and to simulate and determine the concentration of the solution phase of heavy metals at each point, the kinetic coefficient of the reaction corresponding to the same point should be used. Also, there is a significant increase in the accuracy of the developed model if the above environmental parameters are used in the spring and well term of displacement-diffusion equations and the effect of other qualitative parameters is insignificant, which indicates its proper efficiency in simulating the dissolved phase of heavy metals in the river.

Climate change is one of the most important factors affecting the world's climate. Due to the importance of estimating these effects, it is necessary to use appropriate tools and models to estimate the effects of climate change on climatic variables (especially temperature and precipitation). For this purpose, the use of Atmosphere-Ocean General Circulation Models (AOGCMs) as the most common of these tools, has found a lot of use in studies related to climate change. In this regard, the aim of this study was to evaluate the accuracy of the latest AOGCMs related to the sixth IPCC assessment report of IPCC in in different regions of Iran. For this purpose, the historical outputs of 10 AOGCMs in the period 1980 to 2014 were extracted from the IPCC database and compared with the ERA5 reanalysis data of the ECMWF center. This comparison was based on RMSE, Pearson correlation coefficient and Kling-Gupta combined index (KGE). The results showed that different models do not have the same accuracy in estimating the temperature and precipitation of Iran in different months of the year. The variability of the model errors in precipitation estimation were more than the variability of these errors in temperature estimation. On the annual scale, the results showed that the IPSL-CM6A-LR model had the best performance in estimating temperature and the HadGEM3-GC31-LL model had the best performance in estimating annual precipitation. Also, the results showed that the error rate of these models was lower in central and eastern regions of Iran than the other regions.

The present study was conducted to survey water use efficiency in onion production and field evaluation of its improvement strategies. In the first phase, 12 onion farms located in Zanjan plain were selected and studied. The factors related to productivity such as inflow discharge, water consumption, irrigation program, soil nutrition, crop yield, production costs and revenue were determined and then the physical and economic indicators of water productivity were calculated. In the second phase, irrigation management was implemented as a practical solution to improve water use efficiency in the control treatments and compared with the results from actual conditions. Based on the results of field monitoring, the average volume of water consumption in onion farms was obtained about 19626 m3/ha and the average water productivity indices CPD, BPD, and NBPD were calculated 3.14 kg/m3, 68 and 40 thousand Rials/m3, respectively. On average, implementation of proper irrigation program led to a reduction of 58 percent of water consumption and, consequently, an increase of 147 percent of the water use efficiency index in experimental farms. Using the wrong pattern in irrigation programming and lack of control and supervision over the exploitation of water resources were identified as the main reasons for excessive water consumption in onion farms. The results showed that only by correcting the irrigation time, the volume of water consumption can be reduced significantly and the water use efficiency can be improved.

The purpose of this research is to evaluate the effects of climate change on temperature, precipitation, and future droughts in Al-Shatar and Khorramabad stations, for this purpose, the output of the general circulation model MRI-ESM2 according to the latest IPCC report (sixth report) and the emission scenarios SSP 1.2.6, SSP 2.4 5, SSP 3.7.0 and SSP 5.8.5 were used in these study areas. Using the decision tree model (M5 Tree), the most dominant predictor variables of the MRI-ESM2 model were selected. Next, the predictor variables were included as input in the advanced artificial neural network (FFNN) statistical microscale model and with the firefly optimization algorithm (FFA), the process The exponential micro-scale of precipitation parameters, maximum temperature, and minimum temperature for the base period (1970-2014) was carried out with favorable results in the studied stations. After proving the capability of the neural network model, forecasting the average temperature and monthly precipitation changes during the near future periods (2062 2023-2023) and the distant future (2063-2100) were carried out under the scenarios of the joint socio-economic trajectories (SSP) related to the coupled model of the sixth phase (CMIP6). In general, the results showed that these variables in both future periods On a monthly scale will have several fluctuations, so that in the two stations of Aleshtar and Khorramabad, during the periods of the near future and the distant future, the maximum temperature, and the minimum temperature will have an increasing trend compared to the observation period in all SSP scenarios, and the minimum temperature changes compared to The maximum temperature will be higher in the near future The annual rainfall of Elshtar station will decrease between 0.3 Percent and 16 Percent and Khorramabad station between Seven percent and 12 Percent under SSP scenarios. In the distant future, the average annual precipitation of Aleshatar station will decrease between 10-20 Percent and Khorramabad station between 12-24% under SSP scenarios.

Water level control and regulators have a main role in water conveyance and distribution. Despite the simplicity of structure settings in a steady-state condition, applying an appropriate setting in unsteady flow is complicated. Hence, control logic is used to set these structures, usually developed in languages such as MATLAB, Python, and FORTRAN. To use these logics, they must be combined with hydraulic models. In HEC-RAS, there is an elevation controlled water level boundary condition that can be used to control structures. In this research, the evaluation of the performance of this boundary condition was considered to regulate the water level in the E1R1 canal of the Dez network. The results showed that the rate of opening and closing of the gate has a significant impact on the performance, and if they are chosen correctly, the depth changes will be small. The results showed that the IAE indicator is around 1 percent in all the examined options and except in a few cases where the maximum value of MAE exceeds 10 percent and reaches up to 15 percent, its value is also low. Therefore, it is suggested to use this boundary condition in the control of structures.

This study was done as a pot experiment to investigate the effect of biochar applying in drought stress ‎conditions on yield and water productivity of French lettuce. It was carried out from November 2019 to ‎February 2020 in the greenhouse of Zanjan University Research Farm as a factorial experiment based on ‎randomized complete blocks design with three replications. The experimental treatments included biochar ‎at three levels (zero (B0), one (B1) and two (B2) percent w/w) and irrigation at two levels (70 (I70) and ‎‎100 (I100) percent of crop water requirement). The water requirements of the control treatment crops were ‎determined by weight method. Based on the results, application of deficit irrigation significantly reduced ‎means of plant canopy diameter, shoot dimeter, plant hight, chlorophyll content, relative water content and ‎plant wet mass (yield) compared to the control treatment (8.0, 19.8, 26.1, 13.6, 6.20 and 21.1 percent, ‎respectively). Application of one and two percent biochar significantly increased means of plant canopy ‎diameter (13.1 and 7.8 percent, respectively), shoot dimeter (31.9 and 15.5 percent, respectively), plant ‎hight (26.1 and 12.5 percent, respectively), chlorophyll content (25.5 and 13.7 percent, respectively), ‎relative water content (11.61 and 5.30 percent, respectively), plant wet mass (yield) (23.6 and 12.1 ‎percent, respectively) and water productivily (24.6 and 12.3 percent, respectively) compared to the control ‎treatment (B0). Based on the results of the treatments interaction effects, maximum and minimum mean of ‎water productivity were in I70B2 and I70B0 (27.30 and 20.02 kg.m-3, respectively) as well as in the yield ‎they were in I100B2 and I70B0 (15.54 and 10.39 t.ha-1, respectively).‎

Water pollution is a major global problem that requires constant evaluation and revision of water resources policy at all levels. Dissolved oxygen (DO) is one of the most important indicators of water quality. In the present study, the water quality parameter of dissolved oxygen using intelligent Long Short-Term Memory (LSTM) method based on discrete wavelet transform (DWT) and Complementary Ensemble Empirical Mode Decomposition (CEEMD) pre-processor methods in both temporal and spatial modes. It was investigated in five consecutive stations on the Savannah River. The results of analysis of models showed the ability and high efficiency of the method used in estimating the amount of dissolved oxygen in water. On the other hand, pre-processor methods improved the results. It was also observed in the investigations that the results of analysis based on wavelet transformation in spatial modeling reduced the RMSE error by two percent and also the empirical mode decomposition in temporal modeling by 15 percent. The best evaluation for test data was obtained using the empirical mode decomposition in temporal modeling corresponding to the previous day with values ​​of DC=0.977, R=0.988 and RMSE=0.017. Also, in the spatial modeling to estimate dissolved oxygen in the third station, it was found that the results obtained from the inputs of the dissolved oxygen parameter one day before the second station and two days before the first station have the best results.

The metropolis of Tehran has seven drinking water treatment plants, which according to the water needs, ‎more than one billion cubic meters of water treated by the treatment plants are provided to the customers ‎annually. Five percent of the volume of water entering the treatment plants is converted into wastewater, ‎which is estimated at 50 million cubic meters per year. If managed in the recycling process, it will play an ‎important role in balancing water resources and preventing water loss. Therefore, this study seeks to evaluate ‎the recycling process of water treatment in the field of drinking water supply in Tehran to increase the ‎stability of water supply and demand cycle. For this purpose, in order to effectively regenerate this cycle, it ‎was evaluated in the treatment plant No. seven in Tehran with an incoming water volume of 155 million cubic ‎meters per year. In this regard, the results of evaluation of the recycling process change in the treatment plant ‎showed that by changing the wastewater treatment process and the use of polyelectrolyte, the amount of ‎effluent decreased by 95%. The results showed that the volume of effluent decreased from 7.7 million cubic ‎meters per year to 310,000 cubic meters per year, which in fact, Five percent efficiency of effluent production ‎to three tenthe of percent of effluent production in this process change. This change in the effluent system ‎produced in the drinking water treatment plant can greatly contribute to the sustainability of water resources, ‎especially groundwater, given the volume of water resources required by Tehran.‎

The global increase in water demand, along with its limited and declining supply, has caused the water crisis to threaten almost all parts of the globe, making it one of the greatest challenges in the present century. It is predicted that if the current trend of exploitation of these resources continues, more than 21 percent of the world's population will be exposed to severe water stress by 2050. Therefore, most countries have tended to adopt new policies related to water demand management instead of water supply management, as well as developing market-based mechanisms as a sustainable, flexible, and efficient method in managing of water resources and redistributing it between different uses. However, the effective role of water markets in strengthening the use of very limited water resources, increasing opportunities to improve productivity and efficiency of its consumption is well understood. However, the ability of the market to efficiently and optimally allocate water depends on the establishment of special conditions, and the use of this method in Iran requires knowledge of the necessary conditions for the formation of a water market as well as its economic consequences. The present article introduces a new approach to demand-based water management with a review-analytical approach, explains the theoretical foundations of the water market, its concepts, and features, and explains the requirements for its implementation in practice, examines past experiences of the water market in Iran and the world, and, depicts its advantages and challenges, then proposes solutions for reform with emphasis on the economic, social, and legal conditions governing the management of the country's water resources.