مجله آبیاری و زهکشی ایران
سال هفدهم شماره 4 (مهر و آبان 1402)

This research was conducted with the aim of investigating the effects of salinity and biochar on quinoa plant in deficit irrigation conditions. The experiment was carried out in a factorial and completely randomized design with three replications in greenhouse conditions. The treatments include three irrigation water treatments (60, 80 and 100% of the water requirement, ), three biochar treatments (0, 2 and 4% by weight of potting soil, ) and three the water quality treatment was (1, 4, and 7 dS/m, ). From the time of planting until the establishment of seedlings, all the pots were fully irrigated with fresh water and up to the agricultural capacity. Then the pots were weighed every other day and at each level of biochar and salinity, the deficit irrigation to the level of humidity was calculated based on the changes in the pot's weight. At the end of the growing season, the seeds were harvested from the spike. The index parameters of leaf area, spike weight, seed yield, water consumption efficiency and seed protein percentage were measured carefully in each pot. . With the reduction of irrigation water, the amount of quantitative parameters and plant yield decreased. The use of biochar up to the level of 2 percent by weight of the soil increased the parameters. The use of biochar at the level of 2 and 4% by weight increased the seed protein by 23.5 and % 12.08 respectively, compared to the control treatment. there was no significant difference in yield between 2 and 4 dS/m salinity treatment and the percentage of seed protein in 4 dS/m salinity was higher than 2 dS/m, it is possible to use water with 4 dS/m salinity for quinoa irrigation.

In order to study the effect of deficit irrigation (DI) and partial Root-Zone Drying (PRD) on water productivity and photosynthetic characteristics of mungbean, a field experiment was conducted as a split-plot experiment in a randomized complete block design with three replications and nine treatments at the research farm, Ilam University during the growing season in 2021. Treatments included three levels of deficit irrigation (50, 70 and 100% of water requirement) as main plots and three irrigation methods including; usual irrigation, fixed partial root-zone drying, and alternative partial root-zone drying as subplots. The results showed that the effect of drought stress on water productivity, carboxylation efficiency, and photosynthetic water use efficiency was significant. Also, the Interactive effect of drought stress and irrigation method on water productivity and carboxylation efficiency was significant. The highest amount of water productivity, in all irrigation methods, was found in 75% water requirement treatment. The highest water productivity (0.49 kg/m3) was recorded with the alternative PRD method in 75 % of the water requirement level. There was no significant difference between alternative PRD and DI methods at 75 and 100 % of water requirement levels on water productivity. In severe drought stress, water productivity in the alternative PRD method was significantly higher than the other two methods. Therefore, in drought stress conditions, using the PRD method was effective in reducing the effects of drought stress.

Underpass gates are structures in which water moves through the gate. The purpose of this research is to investigate the effect of the sill on the hydraulic characteristics of flow in sluice and radial gates numerically using FLOW-3D software. For this aim, sills with different geometric characteristics in width, thickness, and height were investigated. The results showed that the statistical indicators in the RNG turbulence model have high accuracy compared to the k-ε, k-ω, and LES models in comparison with the experimental results. The RMSE in the RNG turbulence model for the upstream water depth and the discharge coefficient are 0.0079 m and 0.0117 m, respectively, and the average percentage relative error for these parameters is 2.94% and 1.60%, respectively. The Kling Gupta Efficiency (KGE) for the optimal mesh and mentioned turbulence model is in the very good range. In the same opening in the case without and with a suppressed, the discharge coefficient with the sill is higher than without the sill. Among the investigated sills, the discharge coefficient in the semi-circular sill is higher than in the rectangular sill. Also, the discharge coefficient of the radial gate in the without and with a sill is higher than the sluice gate in the corresponding state. The results showed that the increase in the thickness of the sill leads to an increase in the shear stress of the flow and consequently the discharge coefficient decreases. The discharge coefficient of the gate with different heights of the sill is always higher than the one without the sill, but due to the constant ratio of the depth parameter above the sill to the opening, the discharge coefficient increases with the increase of the height of the sill up to a certain level and then decreases.

The vortex settling basin, which includes a cylindrical chamber and a central orifice in its bottom, the inlet and outlet channel, is used with the purpose of separating particles from water flow, the present research is done by image processing technique. The study of particle movement in the field of vortex flow in a laboratory model of settling basin was done. The particle velocity distribution, particle detention time, and settling length were calculated using the particle tracking technique by an automatic code. Also, the abstraction ratio, particle flow path and water surface profile were measured, identified and drawn, and also to determine the tangential, radial and axial velocities flow inside basin by Nortek 21 MHz Micro-ADV three-dimensional magnetic speedometer. The results showed that similar to the velocity distribution obtained by the semi-automatic code, the velocity distribution of the automatic code in the vortex basin is in the form of a sinusoidal function and there is a good match between the water surface profile obtained from direct measurement and the profile obtained from image processing, so that the average relative error is 1.36%. The values of particle and flow velocity (ADV device data) are close to each other, which proves the hypothesis of equality of particle velocity and flow velocity.

Pressure distribution is of utmost importance in both 1D and 2D analysis of steady flow in coarse-grained porous media. In the present study, the pressure distribution in length and height of the gravel media has been investigated in a experimental for three gradations of small, medium, and large in three lengths of 0.5, 1, and 1.5 meters. A piezometer is used to measure the pressure on the floor and walls of the laboratory flume. Experimental data show that; in the initial parts of the gravel media, the real pressure distribution (recorded in the laboratory) has relatively a good agreement with the hydrostatic pressure, and as the end of the gravel media is approached and the increase of water level curve, the pressure difference increases. The average Mean Relative Error (MRE) between the real pressure and the hydrostatic pressure for the two endpoints of the gravel media for the three gradations mentioned in the 0.5 meter media are respectively equal to 36.34%, 32.36%, and 33.64%, for 1 meter length is equal to 33.63%, 28.17%, and 29.34% respectively and for 1.5 meter length, it is equal to 39.46%, 25.66%, and 27.62% respectively. In other words, to check the steady flow in the coarse-grained porous media, the use of real pressure will increase the accuracy of the calculation process.

Water is a vital factor in agricultural production and its optimal use is very important. Considering that the agricultural sector is recognized as the major consumer of groundwater in Iran, therefore, it is necessary to implement strategies to optimize the use of groundwater in this sector. Controlled delivery of water and installation of smart water meters are considered as one of the tools for management of groundwater extraction. Despite this, the implementation of this plan in Iran has faced challenges that can overshadow its sustainability and effectiveness. Therefore, the current research has evaluated the installation of smart water meters on agricultural water wells, based on a socio-hydrological approach, using the grounded theory strategy. The sample of the research is made up of 46 owners of agricultural smart wells in Darab County. The results show that issues such as one-sided and top-down modification of the farmers' exploitation licenses and reduction of the water they can withdraw after installing the meter, weakened livelihood of the farmers and the perceived high cost of purchasing the meter, have cuased dissatisfaction of the farmers. So, the Ministry of Energy insists on compulsory and top-down methods to implement the plan of installing smart meters on agricultural wells. The result of such an environment is the formation of the phenomenon of lack of desirability and satisfaction with the plan and doubts about its effectiveness and sustainability among the farmers. Therefore, it is suggested that the Ministry of Energy make a serious revisions in the implementation of the smart meter installation plan, in accordance with the related jurisprudential and legal rules and based on systematic and participatory approaches.

Estimating the inflow to the reservoir of dams is of particular importance in planning and optimal management of water resources, water supply needed by different sectors and flood management. Therefore, in the current research, it was tried to evaluate the performance of random forest (RF) and Gaussian process regression (GPR), machine learning models by using the preprocessing method of complete ensemble experimental mode decomposition (CEEMD) for estimating the monthly inflow to Dez Dam in the period of 1971 to 2017. For this purpose, the input patterns in four different scenarios, including the use of flow data with time delays, the combination of flow and precipitation data with time delays, and adding periodic term to the previous two modes, were prepared and introduced to standalone models. The results showed that each model achieves its maximum accuracy with different scenarios, and in the meantime, the performance of the GPR model was the best with an RMSE value of 97.49 (m3/s). After determining the best input patterns in each scenario, the relevant data were analyzed by CEEMD method and the modeling process was performed with RF and GPR methods. Based on the evaluation criteria, the error reduction and accuracy increase in the developed integrated models were significantly evident. So that the CEEMD-GPR model was able to reduce the value of the RMSE index by about 47 (m3/s). The same behavior was observed for the CEEMD-RF model. In general, the performance of CEEMD-GPR is more suitable compared to all the developed models (single or integrated) and it is recommended for predicting the inflow to Dez Dam.

Iran is faced with a dry and semi-dry climate with destructive floods, droughts, and water shortages. Droughts and floods can affect the environment, economic, and social activities. Therefore, examining and predicting river discharge and planning management to control it, especially for future water consumption, is very valuable. In this study, changes in river discharge were modeled using statistical data from 2001 to 2020.Statistical data from synoptic and hydrometric stations in a semi-arid region in Urmia city of West Azerbaijan province and a humid region in Amol city of Mazandaran province were used. Out of twelve time-series models defined for the Long Short-Term Memory (LSTM) network, the best model was identified. Then, LSTM modeling was performed based on pre-processing methods of Discrete Wavelet Transform (DWT) and Complementary Ensemble Empirical Mode Decomposition (CEEMD). The results showed that the selected model has high ability and efficiency in estimating the amount of river discharge. On the other hand, pre-processing methods improved the results such that the DC evaluation criterion in the wavelet transform increased from 0.93 to 0.95 in the Nazloo River and from 0.83 to 0.90 in the Chalous River. The best evaluation results for test data using wavelet transform for the Nazloo River in the semi-arid climate with evaluation criteria of R=0.977, DC=0.954, and RMSE=0.018 were obtained. Furthermore, the results of the sensitivity analysis indicated that the discharge parameter of one day before is the most effective in daily discharge estimation.

In this study, the groundwater resources of Urmia Plain were evaluated for agricultural uses using a combined method that includes vulnerability, potential, and groundwater quality models. The vulnerability was evaluated by the DRASTIC method and the final map was classified into five classes with very high to very low vulnerability. The layers of NDVI, digital elevation model, drainage density, precipitation, and well density were considered as inputs of the potential model, and Analytical Hierarchy Process (AHP) was used to determine the weight of each layer. The potential map was also classified into five classes with very high to very low potential. The groundwater quality map was produced with three input layers including electrical conductivity (EC), sodium absorption ratio (SAR), and residual sodium carbonate (RSC) and weighting method. The combined map was produced by the maximum likelihood classification (MLC) method with five classes. The first and second zones with 40.31% of the area are suitable for agricultural uses, which include the northern, northwestern, and central semi-northern regions. The third zone with 22.90% of the area is in moderate condition and includes the central areas of the northern half and the southern half. The fourth and fifth zones with 36.79% of the area are in unsuitable conditions for agricultural use.

Currently, according to the recent droughts, the fresh water that can be used for the cultivation of plants is decreasing, therefore, there is a need to conduct sufficient studies regarding the threshold of tolerance to salinity of plants. Purslane plant is one of the valuable and nutritious plants, which in recent years, many measures have been taken in the development of its cultivation. In order to evaluate the salinity tolerance and some quantitative characteristics of Purslane, an experiment was conducted in a completely randomized design with 3 replications in a pot in the greenhouse of the National Salinity Research Center. Experimental treatment includes 5 levels 0.4 (control), 3, 6, 9 and 12 dSm-1. In this study, some growth traits such as plant height, fresh and dry weight of shoots and roots, leaf area, relative water content, ion leakage, potassium and sodium of shoots were measured. The results showed that the increase in salinity from the control treatment to a salinity of 18 dSm-1 caused a 49% decrease in plant height, 78% leaf fresh weight, 71% shoot dry weight and 16% relative water content, also, an increase of 56 and 6% was observed in the amount of ion leakage and sodium content of purslane plant, respectively. The results of salinity tolerance threshold indicated that the salinity level of irrigation water which caused a 50% and 100% yield reduction was calculated as 12.97 dSm-1 and 26.24 dSm-1, respectively. Based on the obtained results, purslane was classified as a salinity tolerant plant.

The knowledge of crops response to salinity stress application methods in growth stages, can lead to better management of stresses. This research was done on the S.C 704 maize, in the mini-lysimeter space and in Qazvin region. The experiment was performed factorial and in a completely randomized design. The salinity treatments of soil saturated extract (the main factor) were applied at four levels of 1.7(S1), 3(S2), 5(S3) and 7(S4) dS.m-1. The crop growth stage treatments (sub-factor) were defined as one-stage of 6 leaves (C1), flowering (C2), seeds milking (C3) and two-stages of C1C2, C1C3 and C2C3. The research target was to simulate the maize yield by AquaCrop model, in conditions of pulsed salinity stress application in crop growth stages. The stress application data in one and two growth stages, were used for calibration and evaluation the AquaCrop model, respectively. From S1 to S4 treatment, the crop dry matter was decreased from 157.2 g. plant-1 to 115.9, 53.2, 77.7, 86.1, 97 and 46.5 g. plant-1 in the C1, C2, C3, C1C2, C1C3 and C2C3 treatments, respectively. The sudden application of salinity stress in a sensitive growth stage (C2 and C3 treatments), was caused the more damage relative to C1C2, C1C3 treatments. Because once application of salinity stress in the 6-leaf stage (C1) has caused the crop adaptation to future stresses (increasing the tolerance threshold). In AquaCrop model evaluation, the statistical parameters of CRM, EF, R2, RMSE, NRMSE and ME were equal to -0.084, 0.833, 0.91, 12.05, 11.34% and 18.32, respectively. Those showed good accuracy of AquaCrop model in simulation the maize yield. As a result, by management the salinity stress in crop growth stages, will be reduced the negative effects on the maize yield. With simulation the crop yield by AquaCrop model, different stress application states can be evaluated.

The arid and semi-arid climates of Iran are characterized by a hot and dry season in summer and a mild annual temperature and precipitation in winter. Under these conditions, agricultural crops are often submitted to water stress, and the estimation of water losses requires more accuracy due to evapotranspiration. In such regions, the local advection is considered the main source of error in the estimation of reference evapotranspiration (ETo) by most empirical and combined methods. Therefore, according to the local conditions, the necessary corrections for some parameters, such as the wind function, should be made. In this study, two years of historical observed data were used on an hourly time scale. These data were obtained and analyzed from the meteorological-lysimeter station located on the research farm of the Shahid Bahonar University of Kerman. The effect of advection on ETo values was investigated and finally, the wind functions were suggested for the semi-arid climate of Kerman for nighttime and daytime, separately. The results showed that the model tends to overestimate ETo by about 50% with the increase of the advection index. The proposed wind function for Kerman region has an exponential form during the daytime and a power form at nighttime. On average, these functions have added 26 and 8 percent to the accuracy of ETo estimation for these two-time scales, respectively.

The issue of water delivery and distribution in the irrigation network is one of the important issues to realize the goals of the network and achieve the desired efficiency, and by affecting the size of the delivery structures, the capacity of the channels and the cost of construction, it causes the efficient design of the network. In addition, the poor performance of irrigation canals on the one hand and its effect on the reduction of agricultural water productivity on the other hand has necessitated the provision of effective planning for the optimal exploitation of canals. This type of issue is a multi-objective, multi-variable and multi-constraint optimization problem, and its solution requires powerful optimization methods such as evolutionary algorithms. In this research, two optimization models based on the HSA (Harmony Search Algorithm) and WOA (Whale Optimization Algorithm) algorithms are developed to provide the order and sequence of branches in irrigation canals in order to decreasing in main channel capacity and decreasing in irrigation time. For this purpose, first the number of branches, the maximum capacity of each channel, the area covered by each branch, the gross irrigation requirement, the irrigation cycle, and the number of blocks were introduced as inputs to the model. After implementing the model of the best turn of branches in each block, the minimum capacity of the distributor channel and the minimum irrigation time in optimal conditions were presented as outputs. In order to control and check the developed program, the optimal water delivery program in the irrigation sub-network of Jazmurian lands (Dasht Jiroft) was extracted using the above two models, and while matching with standard functions to check the accuracy of the algorithms, the HSA model was determined in each two-factor discharge and time has a better performance than the WOA model.

While having economic advantages, non-linear weirs have more passing flow capacity than linear weirs. These weirs have higher discharge efficiency with less free height upstream compared to linear weirs by increasing the length of the crown at a certain width. Intelligent algorithms have found a valuable place among researchers due to their great ability to discover complex and hidden relationships between effective independent parameters and dependent parameters, as well as saving money and time. In this research, the performance of support vector machine (SVM), gene expression programming (GEP), software (QNET) and artificial intelligence network (ANN) in predicting the discharge coefficient of non-linear Weirs of 318 data series for the first scenario And the second scenario includes the number of 363 data series and the third scenario includes data integration (the sum of the first and second scenario) which includes 681 data series. The difference between the first and second scenarios is in the shape of the quarter-circle and semi-circle weir crown. The geome tric and hydraulic lines used in this research include total water load ratio (H_T/p), magnification) L_C/W), cycle wall angle (α) and discharge coefficient (Cd). The results of artificial intelligence showed that the combinations (Cd, H_T/p, α, L_C/W) in QNET, ANN, GEP, SVM algorithms in the training stage related to the superior scenario are equal to the evaluation indicators respectively (R2=0.9960), (RMSE=0.0080), (DC=0.9961), (R2=0.9980), (RMSE=0.0057), (DC=0.9980), (R2=0.9837), (RMSE=0.0207), (DC=0.9838) and (R2=0.9902), (RMSE=0.0186), (DC=0.9830). Which has led to the most optimal output compared to other combinations, which indicates a very favorable accuracy in all four methods, namely ANN, QNET, SVM and GEP in predicting the weir discharge coefficient is non-linear. The results of the sensitivity analysis showed that the effective parameter in determining the nonlinear weir discharge coefficient in all methods is the total water load ratio parameter (H_T/p).

One of the important factors that reduce plant growth is the short-term water stress applied to the plant in the period of two irrigations. This research aims to investigate the relationship between crop water stress index (CWSI) of sugarcane and soil moisture under two systems of closed-end furrow irrigation (CI) and subsurface drip irrigation (SDI) at research station number one of sugarcane development research and training institute was done from July to September 2022. For this purpose, a field including ratoon 3, of the variety CP69-1062, with four replications for both irrigation systems was selected. First, the upper and lower baselines were determined for CI. Then, using these baselines, the average CWSI for SDI and CI systems was estimated for each month, separately. The highest value of CWSI for CI in September was 0.54 and for SDI in August was 0.49. Results showed that there is a high correlation between CSWI and soil moisture only in CI method for the depths of 0-30, 30-60 and 60-90 cm. The correlation between CWSI and soil moisture for CI was determined in the range of 0.60-0.70, and for SDI, in the range of 0.46-0.12. It seems that in addition to water stress, other stresses such as salinity stress caused by irrigation water and farm soil are also applied to the plant.