مجله مهندسی آبیاری و آب ایران
پیاپی 44 (تابستان 1400)

Bottom intakes are one of the most efficient water diversion structures in rivers that have the task of transferring the flow to the collecting canal. The orifice bottom intake is used in the surface water collection and diversion network to the turbine. In the present study, the effect of different parameters of square orifice bottom intake including perforated plate longitudinal slope (S), opening area ratio (A) and number of orifices (N) on the discharge coefficient and percentage of flow passing through the perforated plate under different subcritical flow conditions in laboratory and numerical condition investigated. The results showed that parameter A and S had the highest effect on P and Cd. By increasing A from 0.01 to 0.07, the percentage of flow passing through the perforated plate has increased 7.58 times. Also, by decreasing the longitudinal slope by 10 degrees, the percentage of flow passing through the perforated plate increased by 45.57%. Also the simulation results of this structure in Flow-3D software showed that the value of P was inversely related to turbulence and pressure.

The purpose of this paper is to investigate the energy dissipation in stepped spillways using numerical method with ANSYS CFX software. In this study, finite volume method based on element was applied for modeling and the SIMPLE iterative algorithm was applied to couple the velocity and pressure terms. Field of flow solution was continued until reaching to remaining with amount of 10-5. The RNG k-ε model was used to evaluate the turbulence using CFX software to model the mixing of two-phase water-air and free-surface flow called Free Surface. This research has been continuously analyzed. To perform the validation and capability of software, at first a broad-crested weir mode were modeled and the results of model were compared with the laboratory model. Then the laboratory model of stepped spillway was selected and analyzed for various discharge. Consider to results of the energy dissipation in stepped spillway and broad-crested weir and comparing with experimental results, it can be concluded that numerical method as well as laboratory method has the ability to provide acceptable results in field analysis of flow in different types of stepped spillways and their results can be used to predict flow behavior for different conditions. The results of the presented numerical model showed the appropriate efficiency of stepped overflows in energy dissipation. For the model with the ogee crest, the dissipation rate for the selected flow discharge obtained from 80 to 90% and for the model with the broad cast weir, the energy dissipation obtained from 55 to 80%.

The emphasis of this study was to study the effects of waves, prediction and estimation of sediment transport rate at different coastal forest cover densities. Experiments were performed on the effectiveness of a mangrove tree to reduce tsunami energy, by a simulated polyethylene artificial shrub structure. The cover has a rigid structure (including 2 cm trunk system and 25 cm height and 1 cm root) and structure (including branch

The master recession curve (MRC) provids an average characterization of baseflow amount and can be a sign of ground water contribution to the surface flow amount. The purpose of this research is to estimate the regression equations of MRC in 28 hydrometric stations of Ardabil Province. Toward this, the Visual Basic programming was used to obtain regression equations of the principal subtraction curve. After obtaining the MRC of all study river gauge stations, the slope values, the recession constant and the explanatory factor were determined. The logarithmic regression formula with the value of 0.83 was considered as the best fitness criterion. The slope coefficient of MRC in Boran, Firoozabad, and Moshiran stations were 2.70, 2.43 and 2.20, respectively, which are the perennial rivers with highest discharge value, the amount of average yearly discharge were 17.97, 2.95, and 13.79 m3s-1. While the slope of the Hajahmadkandi, Kouzehtopraghi and Nir hydrometric stations respectively were 0.09, 0.051 and 0.05, which have the smallest amount of slope and the amount of discharge respectively, equal to 0.16, 0.93 and 1.22 m3s-1. Regarding the constant values, the Polealmas, Barogh and Firoozabad stations had the highest constant values ​​of 896, 572, and 15.89. Also, the Hajahmadkandi (0.35), Akbrdavood (1.416), Dostbeiglo (4.359) stations had the lowest constant coefficients. The results can be used to compare the studied watersheds in terms of hydrological response and baseline flow contribution in the river flow

Hydropower energy is the third largest source of electricity generation and also the most important renewable energy producer in the world. For this reason, the optimal use of this huge and expensive source is essential. In this study, Moth Swarm Metaheuristic Algorithm (MSA) was used for optimization of the hydropower operation of Karun-4 reservoir located in Karun basin for a period of 106 months (from October 2010 to July 2019). After verifying the reliability of the MSA algorithm using several standard benchmark functions, a model was developed for optimal hydropower operation of the Karun-4 reservoir. Also, the results of the algorithm were compared with the results of known metaheuristic algorithms of the Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). The MSA, GA and PSO algorithms were capable to generate energy 105853, 105697.4, and 105841.6 MW, respectively, compared with the actual value 64987.54 MW, during the statistical period. Also, the objective function value for MSA, GA and PSO algorithms, was obtained 0.147, 0.3026, and 0.1584, respectively. The results revealed that the MSA algorithm was the superior algorithm in optimal hydropower operation.

In addition to wasting water and energy, leaks in water distribution networks also cause social and environmental problems. So it is important to try to save as much as possible. In leaks made by meta-heuristic methods, the decision variables are leak node number and flow leakage. In this study, a method is presented with the combination of inverse solution of flow equations and meta-heuristic algorithm. In the proposed method, only the leakage node number is considered as the decision variable in the Harmony search method, and the leakage amount is calculated using the inverse solution of continuity and energy equations. In addition to a number of measurements for the objective function of the meta-heuristic algorithm, it is necessary to measure pressure nodes and discharge pipes as many as leakage nodes for the hydraulic model. The results in the two hypothetical networks show that this method determines and calculates the position and amount of leaks with high accuracy, even if the leakage amount is small. If there is an error in measuring the node pressure, the position and amount of leaks are calculated accurately by increasing the nodes of the objective function.

Consumption of water as the main request is unavoidable in human life. Many areas of Iran, including Mazandaran, faced problems with access to water in necessity seasons. In wet areas with good annual rainfall, proper management of available water resources and rainwater harvesting is a worthy solution. The aim of this study is to analyze the long-term rainfall in Babolsar based on synoptic data in order to select areas prone to rainwater harvesting in the city. In this study, the time series of daily rainfall data in a period of 68 years including the years 1952-2012 has been used and the climatic parameter of precipitation in three periods of monthly, seasonal and annual has been analyzed. Analysis indicated the implementation of rainwater harvesting systems and areas prone to this in the city of Babolsar is approved. The results of this study showed that the Gamma operator with a coefficient of 0.7 is the best option for the study area. According to the calculations, the amount of runoff in the city was estimated at 696,570 cubic meters, which is very suitable for rainwater harvesting.

Due to the increasing environmental and economic costs associated with nitrogen (N) consumption, improving N use efficiency in rice cultivation systems is of great importance. In this regard, the combined effect of different surface and subsurface drainage systems and water management on the nitrogen harvest index (NHI) of rice was investigated. During three rice growing seasons (2014 to 2016), two rice varieties of Tarom Hashemi and Tarom Daylmani were cultivated under alternate wetting and drying in paddy fields with surface and subsurface drainage systems. At harvest, grain yield and biomass and plant and seed nitrogen were measured. The NHI was determined as the ratio of grain nitrogen to nitrogen absorbed by aboveground part of plant. The amount of NHI was directly related to the amount of urea fertilizer used, varying between 58.31 and 68.45 in different seasons. The average nitrogen absorbed by the Hashemi and Daylmani plants in the subsurface drainage systems was 161.7 and 155.7 kg ha-1, respectively, and in the control was 144.7 and 193.7 kg ha-1, respectively. Also, the average grain yield, grain nitrogen, harvest index and NHI in the subsurface drainage systems were 5329.3 kg ha-1, 105.9 kg ha-1, 37.8% and 67.2%, respectively, and in the control treatment was 4667.7 kg ha-1, 88.6 kg ha-1, 32.4% and 56.3%, respectively. Based on the results, drainage through subsurface drainage systems under intermittent irrigation and drainage management can improve the N use efficiency in rice cropping system

Jiroft Plain with arid and semi-arid climate is one of the plains that experienced a significant increase in groundwater depletion in recent years. In the present study, to investigate the effects of precipitation and climatic conditions on the fluctuations of groundwater level, precipitation data of 6 rain-gage and evaporation stations during 1992-2014 were used and the average amount of precipitation of plain was calculated by Thiessen polygon method using Chirps satellite data. The results of the Pearson correlation between precipitation and level of groundwater showed a correlation of 0.23. However, the Standardized Precipitation Index was used to find the effects of drought and wet periods on the groundwater level. The results of consecutive time series analysis showed that SPI7 with 7 months long term scale has more correlation (0.35) with the groundwater level of plain. Evaluation of the hydrographic data of Jiroft plain in the statistical period of 2003-2014 showed that during this period, the groundwater level dropped by 8.65 meters and the average annual decrease is 0.61 meters. Also, the results of zoning maps using the Kriging method over 5-year intervals showed that the groundwater level decrease in the south and central parts of the plain had more drop. Then, using Ward analysis, Jiroft plain was divided into four clusters, which for cluster 1 Kalroud piezometer, for cluster 2 Saghari piezometer, for cluster 3, Konarsandal piezometer and Finally for cluster 4, Chehre Abad piezometer were selected. The correlation of average precipitation in each cluster with groundwater level fluctuations with the selected piezometers of that cluster were 0.51, 0.37, 0.38 and 0.55 for Kalroud, Saghari, Konarsandal and Chehre Abad respectively. Due to the sharp annual decline and over-depletion of the plain, if serious and effective action is not taken in this regard, this plain will not only by exacerbate environmental consequences but also will face economic and social problems in the future.

Nitrate is one of the most common contaminants that originates from fertilizers, pesticides or domestic and industrial wastewater. This non-point source contaminant exposes the Salmas plain aquifer to groundwater pollution due to extensive agricultural activity. Therefore, it is necessary to assess the contamination risk of aquifer to high nitrate concentration and identify the high-risk areas in this aquifer. In this research, the contamination risk of Salmas plain aquifer was investigated using DRASTIC-L framework and groundwater velocity. For this purpose, after constructing of DRASTIC-L framework, the weights of eight layers of the framework optimized by genetic algorithm to obtain the aquifer vulnerability map to nitrate contaminant. Finally, the contamination risk map to nitrate was achieved from multiplying the aquifer vulnerability and groundwater velocity. The results showed that against to the eastern and central parts of the aquifer, the contamination risk of the aquifer is high in the western part of the aquifer.

In recent years, groundwater overexploitation has led groundwater depletion Jiroft plain and considering the strategic role of this plain in supplying water required for agricultural products, planning to improve the water resources of this plain is essential. Therefore, the purpose of this study was to investigate the effects of groundwater resources management in Jiroft plain in the past (2005-2019) and the near future (2019-2031) using GMS10.4 software based on hydrological, hydrogeological and Topographic data. Also, to investigate the impact of water resources changes on crops cultivation pattern, changes in cultivation pattern of major horticultural crops in terms of their water requirement in Jiroft plain were studied using information and statistics of major horticultural crops in Jiroft plain during the last three decades. The results showed that aquifer has yearly faced with a decline about 0.86 m during the baseline period (2005-2019), which indicates overexploitation of groundwater resources in this plain. The aquifer status was predicted in the future under different scenarios using the GMS 10.4 model. Also, studying the development trend of major horticultural products in Jiroft plain showed that despite the declining trend of groundwater resources over the past three decades, the share of horticultural products with high water requirement has been increased in the crop cultivation pattern of this plain and the behavior of farmers to develop the pattern of agricultural products cultivation has been influenced by factors except groundwater resources limitations. Therefore, it is suggested that scenarios of reducing groundwater resources exploitation in Jiroft plain and also paying attention to cultivation pattern appropriate to water resources in different parts of the plain should be a priority for agricultural planners.

In regional and local climate studies usually coarse- resolution global climate models’ outputs are downscaled to produce necessary fine scale data. Regional climate modeling is a dynamical downscaling method. In this study HadGEM2 general circulation model outputs have been downscaled by RegCM4 Regional Climate Model coupled with CLM4.5 land surface model. The model was run over Toyserkan plain for a reference period (1999-2005) and up coming period (2015-2025). For reference period, daily, monthly and yearly modeled precipitation, temperature and runoff were compared with observed values at monitoring stations in the region. Modeling efficiency, correlation coefficient, bias, mean absolute error and root mean squared error statistical indices were used to evaluate model’s simulations. Model shows its best performance for monthly temperature, runoff and precipitation respectively. Predictions are based on RCP4.5 scenario of the Fifth Assessment Report of Intergovernmental panel on climate change. For this period spatiotemporal variations of surface water budget components including precipitation, evapotranspiration and runoff have been studied and water balance equation in the catchment has been evaluated.  Finally considering small area of the catchment and short time of prediction period that does not allow to detect impacts of climate change, model performance in estimating water balance for the catchment is acceptable.

For estimating evapotranspiration of landscape, in addition to vegetation coefficient, coefficients related to microclimate, plant density adjustment and specific plant species adjustment must also be calculated. In this study, using Landsat 7 satellite images and Mashhad Synoptic Station data, the actual evapotranspiration of landscape was calculated then, using climatic and environmental parameters obtained from satellite images and Seabl model, a relationship between microclimate coefficient and air temperature as well as relationship between density coefficient and normalized difference index of vegetation was established. Finally, the obtained relationships were evaluated by field monitoring of soil moisture in Ghadir Park of Mashhad. By determining the locations of field locations on the satellite image the relationship between NDVI index and the landscape density coefficient was investigated. The results showed that the best model presented using linear regression as Kd = 0.9941 * NDVI + 0.5058 with a correlation coefficient of 0.98 that the maximum percentage of error between calculated evapotranspiration for landscape using extracted relationships and measured values from moisture weight monitoring is less than 24%. due to severe water deficit in the forest landscape and insufficient water availability of the plant, evapotranspiration calculation using the Sabal model is inappropriate and has many errors. Therefore, instead of using the Sebal model, the extracted relationships can be used to determine the vegetation coefficients and the water requirement of urban landscape.

Investigation of the potential impacts of climate change on hydropower generation and reservoir operation at the basin is a necessary issue. In this research, the effect of climate change on the generation of hydroelectric energy in the Karun 4 dam was investigated. For this purpose, after collecting the required data, temperature and precipitation variables were generated using general circulation models (GCM) under RCP4.5 and RCP8.5 climate scenarios for the upcoming period (2029-2050). Then, the temperature and precipitation values were downscaled for the future period using the changes factor method. The generated time series were used as inputs for the IHACRES rainfall-runoff model and the runoff were simulated under different scenarios. Then the effect of runoff variation under considered scenarios in the amount of generating hydroelectric energy was investigated. Climate predictions indicate an increase of 1.72 and 2.4° C in the long-term average annual temperature, and a reduction in the annual precipitation of 5% and 14% under the RCP 4.5 and RCP 8.5 scenarios, respectively, in the period of 2029-2050. The results of rainfall-runoff modeling indicate that the average annual inflow into the dam reservoir will be decreased 21% and 34% under the scenarios RCP 4.5 and RCP 8.5, respectively. In order to investigate the effect of runoff reduction on reservoir status and hydroelectric generation, the reservoir of Karun 4 Dam was simulated with WEAP software. The results showed that the generated hydroelectric energy by the Karun 4 Dam in the upcoming period (2029-2050) will be decreased by 17% and 31% under RCP 4.5 and RCP 8.5 scenarios, respectively.

Use the output of atmospheric general circulation models to understand the weather conditions and to prevent the spread and consequences of climate change on groundwater resources in all ecosystems, especially in arid and semi-arid regions is necessary. The present study was conducted to investigate the impacts of climate change on groundwater level fluctuations in Kerman plain, Iran. In order to investigate the impact of climate change in future periods, the CanESM2 climate model and SDSM4.2 software were used under RCP2.6, RCP4.5 and RCP8.5 emission scenarios. Then, GMS10.0.5 was used for quantitative modeling of groundwater in Kerman plain. The mathematical model prepared for the steady state in 2002-2003 was calibrated over 2002-2012 in 120 steps for the unsteady state condition and the 2012-2015 period for the calibration. The results of climate scenarios in the upcoming period (2006-2030) showed that temperature will increase by 1.12, 1.23 and 1.37 degrees Celsius while rainfall will increase by 14.69, 19 and 26.29 percent in RCP2.6, RCP4.5 and RCP8.5 scenarios, respectively. The results of climate scenarios showed that in spite of increased rainfall and the assumption of constant utilization of groundwater, the average groundwater level in RCP2.6, RCP4.5 and RCP8.5 scenarios in the upcoming period would be lower than the water level compared with the base year (2002-2003), by 7.19 and 7.26, and 7.33 meter in the whole region, respectively. It is recommended that measures to deal with global warming resulting from climate change and over-exploitation of groundwater resources by reforming cropping patterns, irrigation new methods.

In this research by combining individual models outputs, the strengths of each single model are used to make a new model that has better performance than each single model. In this study the efficiency of nonparametric K nearest neighbor and BMA model were compared with BGA , GRA,  AICA, BICA, equal weights averaging and lasso methods. For this purpose, the evaporation rate from the water level was simulated at three stations of Marwa Tappeh, Gonbad and Gorgan, using the individual models of the US Land Development Organization, Tchymyorov, Ivanov, Hanfer, Shahten, Marciano and Meyer. Then each combination of models was implemented to combine the outputs of each single model. The results showed that during the calibration and validation period, the best performance was related to the experimental model of the US Land Development Organization. The best performance of the combination models for the calibration period and validation period at the Marah-e-Tappeh station in GRA in Gonbad and Gorgan stations. Regarding the error indices, the best performance of calibration period of GRA method and validation data is related to the GRA, BICA and AICA methods and the worst the function is related to the EWA method. For the validation period, the nearest KNN neighbor method has a better performance than other combination methods.  Bayesian average results showed that in all three stations, in the case of gamma distribution, different modes of its variance modeling were similar and in all stations of normal distribution modes, they had better performance than gamma distribution modes, as well as the range of uncertainty in normal distribution mode, it was smaller than gamma distribution. On the other hand, in the estimation of the point, Bayesian average modification with normal distribution after gra method performed better than other combination models.

Drought is one of the most important problems which affects agriculture section and water resources. Nowadays, the use of the remote sensing technique has been considered as useful tool for drought monitoring. This study aimed to predict the temporal drought using ground station and TRMM3B43 satellite data between the years of 1998-2017. Therefore, precipitation data were first converted to the SPI index, and then, using the intelligent Gaussian Process Regression (GPR) method based on Complementary Ensemble Empirical Mode Decomposition (CEEMD), Tabriz drought was investigated. Different models were defined and the impact of different input parameters were assessed. It was observed that the rainfall amounts from the TRMM satellite in the monthly scale had a good correlation with the Tabriz station precipitation and the results of drought analysis using satellite data were almost similar with ground station data. The obtained results proved the high capability and efficiency of the applied method in predicting the SPI drought index and it was observed that time series decomposition based on the complementary ensemble empirical mode decomposition led to more accurate outcomes. The input data decomposition increased the predictive accuracy by approximately 30 to 40 percent. It was observed that in prediction of drought the climatic elements including mean monthly temperature and relative humidity, as well as SPI indexes related to the previous months, were effective and by climatic parameters eliminating, the modeling error increased up to 15-20%. Also, the results of sensitivity analysis showed that SPIt-1 is the most effective parameter in modeling.

Due to the water scarcity in areas with hot climates, an accurate estimation of evapotranspiration has a significant impact on water resources management and planning. In this paper, the gene expression programming (GEP) approach was used to estimate the daily evapotranspiration in Yazd (hot and dry climate) and Jiroft (warm and humid climate) synoptic stations. The results of this method along with the results of empirical relation of Hargreaves-Samani were validated with those of the empirical relation of Penman Mantis FAO-56. Statistical indices of coefficient of determination (R2), root-mean-square error (RMSE) and mean absolute error (MAE) were employed to evaluate the efficiency of the utilized methods. The results indicated that GEP model (with R2 = 0.951 and RMSE = 0.66 mm/day for Yazd and R2 = 0.958 and RMSE = 0.65 mm/day for Jiroft) had higher performance compared to Hargreaves-Samani relation. Therefore, the use of GEP as a model with high capabilities is recommended for estimation of evapotranspiration in areas with hot-dry and warm-humid climates

The rate of evapotranspiration in the plants is the basis of irrigation planning for water consumption in the agricultural sector. The most accurate method to assess the water requirement in plants is the water balance assessment in weighing lysimeters. The use of conventional weighing lysimeters has different problems such as require to continuous expert presence at the installation site of lysimeter. Therefore, the aim of this study is to design and manufacture of fully automatic portable weighting micro-lysimeter with high accuracy and low cost that in specific time periods (without time limit from a few minutes to a few days) without the need for the presence of an expert, able to measure the required factors in relation to the water balance in the micro-lysimeter, able to automatically add the required water shortage of the plant to the system, able to send the report of measures to the user, able to save the data on the memory card automatically and provide accurate measurement of plant water requirement and automatic irrigation based on the predetermined pattern. In this system, the calculation and sending of the required irrigation information are done by the microcontroller based on the predetermined algorithm. The results of the correlation between the collected data series from the designed Micro-lysimeter and the measured data by the expert person within 10 days (including 6-hour, 12-hour and 24-hour time periods) indicated that the correlations coefficients in all three periods were not different with the perfect reliable line at 99% significant level.

Aji-Chay is one of the greatest permanent rivers in Tabriz study area that finally flows into the Uremia Lake. The river quality is degraded by different pollution sources along its way especially in the Tabriz Plain. In this research for assessing quality of the Aji-Chay River using water quality indices for specific uses, water samples were collected from 16 sampling points along the river in wet (May 2016) and dry (September 2016) seasons. Physicochemical parameters including pH, temperature (T), turbidity (Turb), electrical conductivity (EC), total solids (TS), total dissolved solid (TDS), inorganic constituents including major (sodium, potassium, Calcium, Magnesium, Chloride, Sulfate, Bicarbonate) and minor (nitrate and phosphate) ions, inorganic parameters comprising dissolved oxygen (DO), chemical oxygen demand (COD), biological oxygen demand (BOD), and biological parameters such as total coliform (T.C) and fecal coliforms (F.C) were measured. Based on the results, values of some parameters are above the pertaining standards of Iranian drinking water. Assessing quality of the Aji-Chay river using river pollution index (RPI), Oregon water quality index (OWQI), Said index, Dinius index and weighted arithmetic water quality index (WQI) confirmed very bad qualitative statue of the river in most stations especially in the middle parts of the Tabriz plain due to the entry of the pollutant sources. Based on the results quality indices of Said, Dinius and WQI are suitable ones for assessing quality of the river for particular purposes and then its qualitative management as

This study aim was to evaluate the relationship between the drinking water quality in Arak city regions and the drinking water sources to identify areas with inappropriate quality drinking water and its zoning with the geographic information system (GIS) and planning to address drinking water quality problems. In this research, drinking water from 18 areas in the city was sampled to measure physical and chemical parameters during 2016. Parameter analysis was carried out by the standard water and wastewater. To extract the contamination maps, IDW method was used in GIS environment. The drinking water quality parameters average  for pH, TDS, EC, TH, F, Cl, NO3 and SO4 was 7.4, 50.67(mg/l), 28.840(µS/cm), 28.38(mg/lCaCO3), 17.0(mg/l), 15.95(mg/l), 19.66(mg/l) and 27.49 (mg/l) respectively. The results showed that the highest concentration of pH, TDS, and EC was in the east.  TH is located in the south. The highest amount of F is in the west of the city and F is highest in the south, the highest NO3 and SO4 are located in the south. In general, the comparison of measured values ​​with the set value indicates that the average value of all elements was lower than national standards, but the mean of TDS, TH, and NO3 is higher than global standards.

This paper tries to forecast and determine the desertification warning threshold using groundwater resources quantitative and qualitative parameters modeling. The data from 62 piezometric wells and 55 quantitative wells were selected from Iranian Water Resources Management Company and Khorasan Razavi Regional Water Authority. Handling missing data, and statistical analyzes such as the Mann-Kendall test and Pearson correlation were performed. The desertification intensity and early waring maps was provided based on the Iranian Model of Desertification Potential Assessment (IMDPA) Model. The maps of quantitative and qualitative indices of groundwater were classified according to the desertification severity and threshold of each index for a 20-years period (1996-2016). Desertification intensity and warning threshold maps of each groundwater quantitative and qualitative index were classified according to the IMDPA Model. The ground water parameters were predicted by MATLAB 2015 software and artificial intelligence fore 2022. The results showed that among the quantitative and qualitative indices the highest decertification warning area was related to drop index. The electrical conductivity index was in second-order warning. Sodium sorption index is located in low desertification class and only southern part of Mashhad aquifer will be in warning condition in 2020. In terms of chlorine content, the aquifer of Mashhad plain has not been under warning condition. But considering the trend of changes in the index in the future may be on the verge of warning.