نشریه علوم آب و خاک (علوم و فنون کشاورزی و منابع طبیعی)
سال بیست و هفتم شماره 2 (پیاپی 104، تابستان 1402)

The objective of the present study was to conduct field studies for direct measurement of canola under farmers' management in one crop season (2019-2020) in 27 farms in Behbahan, Khuzestan province. Water requirement was calculated based on the FAO Penman-Monteith model using the daily statistics of the Behbahan synoptic meteorological station. A T-test was used to statistically compare the results such as the depth of irrigation and applied water productivity in the field in different irrigation systems. Linear multivariate regression analysis was used to investigate the effects of the independent variable on the dependent parameter of water productivity. The volume of applied water in the fields ranged from 4085.5 to 7865.3 m3/ha. The results of comparing the average yield of two irrigation systems in the t-test showed that the two sprinkler and surface irrigation systems with yields of 2614 and 2330 kg/ha, respectively, were not significantly different. Applied water productivity in traditional and modern irrigation systems was calculated to be 0.386 and 0.486 kg/m3, respectively, which had significant differences. The results of the analysis of variance in the regression model showed that among the independent variables, yield with t-statistic (23.997) and equivalent beta coefficient (0.880) had the most significant positive effect at a 1% level on applied water productivity. After that, the volume of applied water (irrigation water + effective rainfall) with a t-statistic of (-11.702) and a beta coefficient of equivalent (-0.793) had the most negative and significant effect at the level of 1% on the applied water productivity. The results of the Pearson correlation coefficient showed that irrigation events had a positive and significant correlation at a 5% level with applied water and yield. These correlations were 0.455 and 0.380, respectively. By increasing irrigation events, the volume of applied water has practically decreased and has become as close as the plant needs, and has increased water productivity.

Awareness of water resources status is essential for the proper management of resources and planning for the future due to the occurrence of climate change in most parts of the world and its impact on different parts of the water cycle. Hence, many studies have been carried out in different regions to analyze the effects of climate change on the hydrological process in the coming periods. The present study examined the effects of climate change on surface runoff using the Atmosphere-Ocean General Circulation Model (AOGCM) in Khomeini Shahr City. The maximum and minimum temperatures and precipitation of the upcoming period (2020-2049) were simulated using a weighted average of three models for each of the minimum and maximum temperatures and precipitation parameters based on the scenario A2 and B1 (pessimistic and optimistic states, respectively) of the AOGCM-AR4 models. The LARS-WG model was also used to measure the downscaling. The HEC-HMS was used to predict runoff. The effects of climate change in the coming period (2020-2049) compared with the observation period (1971-2000), in the A2 scenario, the minimum and maximum temperatures would increase by 1.1 and 1.6 Degrees Celsius, respectively, and the precipitation would decrease 17.8 percent. In the B1 scenario, the minimum and maximum temperatures would increase by 1.1 and 1.4 degrees Celsius, respectively, and the precipitation would decrease by 13 percent. The results of runoff were different in the six scenarios in the way the most runoff reduction is related to the scenario of fixed land use and scenario A2 (22.2% reduction), and the most increase is related to the scenario of 45% urban growth and scenario B1 (5.8% increase). So, according to increase urban texture in the future and consequently enhance the volume of runoff, this volume of runoff can be used to feed groundwater, irrigate gardens, and green space in the city.

The objective of the current study was to zone flood probability in the Marzdaran watershed. Since the allocated budget for management work is limited and it is not possible to carry out operations in the whole area, having a map that has prioritized different areas in terms of the probability of flood occurrence will be very useful and necessary. A well-known data mining model namely MaxEnt (ME) is applied due to its robust computational algorithm. Flood inventories are gathered through several field surveys using local information and available organizational resources, and the corresponding map is created in the geographic information system. The twelve predisposing variables are selected and the corresponding maps are generated in the geographic information system by reviewing several studies. The area under the curve (ROC) is used to evaluate the modeling results. Then, the most prone areas of flood occurrence which are prioritized for management operations are identified based on the prepared map. Based on the results, about 100 km2 of the study area is identified as the most prone area for management operations. The results showed that the accuracy of the maximum entropy model is 98% in the training phase and 95% in the validation phase. The distance from the river, drainage density, and topographic wetness index are identified as the most effective factors in the occurrence of floods, respectively.

Due to the climatic conditions of Iran, increasing water scarcity, and the effect of drought stress on the efficiency of irrigation water consumption and chemical fertilizers application, an experiment was conducted to investigate the effect of irrigation intervals (6, 9, and 12-day intervals), different levels of nitrogen fertilizer (200, 300, and 400 kg urea per hectare) and cultivation methods (on-ridge or heeling up and in-furrow) on yield and productivity of sugarcane as a factorial design based on randomized complete block design in 3 replications at Hakim Farabi Agro-Industry Company in Khuzestan province. The results showed that the maximum (106.73 tons/ha) and minimum (59.10 tons/ha) sugarcane yields were observed in 9-day and 12-day irrigation intervals, respectively. Also, the highest sugarcane yield (99.89 tons per hectare) was obtained in the treatment of 400 kg urea per hectare and the in-furrow planting method resulted in a higher yield compared to the on-ridge planting method. The highest water productivity in sugarcane stem yield and sugar production with 3.55 and 0.34 kg per cubic meter of applied water, respectively, was obtained in a 9-day irrigation interval. A significant increase in water use efficiency in sugarcane stem yield was observed in 400 kg urea/ha compared to the other two fertilizer levels. However, there was no significant difference in water productivity of sugar yield between different fertilizer treatments. The results showed that 6 and 9-day irrigation intervals in most of the studied traits were not significantly different. Therefore, using a 9-day irrigation interval is suggested in the studied area when the sugarcane cultivation area is high and the amount of available water is limited. In-furrow planting method can also be effective in reducing water consumption. Therefore, deficit irrigation and proper nitrogen fertilizer consumption can be very effective in sugarcane cultivation.

One of the basic steps in water resources management and planning according to population increase and lack of water resources in Iran is to optimize the use of dam reservoirs. In this research, the effect of meteorological droughts on the optimization of the Aydoghmoush dam reservoir in the northwest of Iran was evaluated by applying metaheuristic algorithms under the impact of future climate change. Three models and two scenarios of SSP2-4.5 and SSP2-8.5 of the sixth IPCC report, and the LARS-WG downscaling model were used for Aydoghmoush dam weather station for the base period (1978-2014) and future periods of 2022-2040 and 2070-2100. The inflow and outflow of the dam, as well as the optimal utilization of the dam reservoir, were evaluated using standalone, and hybrid mode of genetic, slime mold, and ant colony algorithms. Results of the best release scenario (SSP2-8.5) showed that the annual rainfall in the future periods will decrease by 8.9 mm, and 14.5 mm, respectively, compared to the base period. The objective function of optimizing the use of the dam reservoir was defined as minimizing the sum of squared relative deficiencies in each month and maximizing the reliability in the statistical period of 2011-2021. The results showed that in terms of time reliability, vulnerability, and stability, the hybrid slime mold-genetic algorithm was better than other algorithms with values of 0.73, 0.32, and 28.78. Prediction of the dam's inflow and outflow using the hybrid slime mold-genetic algorithm indicated high accuracy compared to other models by 13% and 19% errors, respectively.

According to the effects of climate change on evapotranspiration and using of water resources, climate change prediction is vital due to water resources management improvement and decreasing damages of drought. The first rank of mango production in Iran belonged to Hormozgan province and the most amount of mango produced in Minab plain. In the present study, the amount of evapotranspiration of mango plants was calculated with FAO Penman-Monteith from 1985 to 2020 using meteorological data at Minab station. The evapotranspiration values of the plant were estimated from 2021 to 2100 with two optimistic and pessimistic scenarios using the last version of CMIP (CMIP6), atmospheric-ocean general circulation models, and performing statistical deviation corrections by the Python software. The results showed that the values of annual evapotranspiration will increase by 0.31 and 1.23 mm on average in the optimistic and pessimistic scenario, respectively in the future due to the increase in annual temperature.

The ability of remote sensing (RS) in irrigation scheduling has been accepted in the world due to the collection of data on a large scale and the determination of water stress indicators with greater speed and less cost. Crop Water Stress Index (CWSI) and Water Deficit Index (WDI) are components of the most recognized water stress indices. Despite the accuracy and precision of the CWSI index that has been proven in plant irrigation scheduling, the lack of complete density of vegetation, especially in the early stages of growth, is one of the most important defects of using this method in crop irrigation scheduling. While estimating the water deficit index using remote sensing technology does not have these limitations. An experiment was performed in the crop year 98-99 in the city of Karaj to check the accuracy of this index. The amount of WDI and CWSI in a wheat field with optimized irrigation management was determined and compared and evaluated using statistical parameters. The results showed that the coefficient of explanation between these two indicators in the months of April, May, and June is 0.77, 0.85, and 0.71, respectively.

The selection of precision value for Roughness coefficient (RC) is necessary to design and utilize earth canals due to the vast distribution of Echinocola crus-galli in earth canals. Therefore, the current study was conducted to evaluate roughness coefficients in earth canals with Echinocola crus-galli at the Moghan plain (in the North-west of Iran). In the network of Moghan, 42 canal sections were selected to measure vegetation density and wet weight, water flow velocity (with a flow meter), and canal cross sections (with profilimetery devices). The hydraulic characteristics were estimated after water depth measurements. The Manning roughness coefficient (n) was applied to estimate the roughness coefficient. Path analysis was applied to identify the factors affecting the roughness coefficient. Multivariate cluster analysis using Ward's method and squared Euclidean distance was applied to cluster factors affecting the roughness coefficient in canals. The results revealed that RC averaged 0.015. The path analysis showed that the wetted perimeter, crop biomass, flow cross-sectional area, flow velocity, and hydraulic radius had the highest total effect on the roughness coefficient, respectively. The factors clustering showed that two clusters were obtained in the Euclidean distance of 11. The first cluster included flow velocity, crop biomass, flow rate, and bed slope; and the second cluster included flow cross-sectional area, wetted perimeter, and hydraulic radius. The findings could be helpful for designing and operating canals in the studied or similar regions.

Using transfer functions to predict soil moisture parameters has been considered strictly a scientific and economical method among researchers. In this research, field capacity (FC) and permanent wilting point (PWP) of soil were predicted using classic regression (linear and non-linear), support vector machine (SVM) algorithm, and gene programming expression (GEP) algorithm based on three performance assessment criteria as determination of coefficient (R2), root mean square error (RMSE), and standardized developed discrepancy Ratio (DDR) in the Arasbaran plain in the northwest of Iran. Independent parameters were determined as clay percent (Cl), silt percent (Si), gravel percent (Sa), organic carbon (OC), bulk density (ρb), and actual density (ρs) which (S, ρb, ρs) and (ρb, ρs) were opted to predict FC and PWP using Gamma test, respectively. The results showed that each three transfer functions are capable to simulate FC and PWP parameters but the SVM algorithm is the superior predictor among the three functions so the values of (R2, RMSE, and DDRmax) of training and testing phases for FC were obtained (0.9908, 0.5517, 17.50), (0.9785, 0.7004, 11.62) and those of PWP were calculated (0.9782, 0.5764, 2.85) and (0.8389, 1.187, 3.09), respectively.

Due to water scarcity, it is impossible to utilize all irrigated cropland in arid and semi-arid areas. Therefore, dense cultivation with a drip irrigation system that delivers water directly to the plant's root zone is an appropriate choice to enhance water productivity. The objectives of the present study were to compare wheat yield and water productivity under two different water distribution patterns in the drip-tape irrigation system and surface irrigation in full irrigation and deficit irrigation levels. The experimental treatments consist of two irrigation systems (drip-tape (DT), and surface irrigation (SU)), and three different irrigation levels (a full irrigation level (W1), two deficit irrigation levels, the irrigation interval twice, and the same irrigation depth of W1 level (W2), applied half of the irrigation depth of W1 level at the same time (W3)). The SU was implemented in place with 100% efficiency to avoid runoff. The yield in full irrigation level in DT was 5338.4 kg/ha and in SU was 5772.8 kg/ha. Applying deficit irrigation in two irrigation systems has different effects due to various water distribution patterns. In the DT, the most yield reduction was in W2, and in SU was in W3. The highest water productivity in DT was observed in W3 with a 1.44 kg/m3 value. The highest water productivity in SU was observed in W2 with a 1.46 kg/m3 value. For each irrigation system, some type of deficit irrigation management is optimal.

In the present paper, crop pattern criteria have been evaluated relying on sustainable development to increase agricultural water productivity. Seven criteria were selected as the main environmental and economic criteria and were prioritized and reviewed for important and strategic products in the Tajan catchment of Mazandaran province. Criteria prioritization was done using optimization through a genetic algorithm with an objective function based on sustainable development. Then, physical and economic productivity indices were calculated to determine the productivity value. Based on the results, in the selection of the crop pattern, firstly, the category of economic criteria and finally the category of environmental criteria have been given attention to the farmers in the current situation. But in the genetic optimization algorithm, all priorities have a similar order from the environmental point of view and then from the economic point of view although each product has its order of criteria. By this prioritization, the parameters of the cultivated area, the volume of water consumed, and the amount of chemical fertilizers have decreased on average by 26%, 34%, and 21%, respectively, and the parameters of product performance and profitability have increased by 43% and 61%, respectively. In addition to providing environmental standards and increasing sustainable development, this prioritization causes an average increase in physical productivity by 84% and an increase in economic productivity by 72%.

Shifting of surface irrigation to drip system is key tool to reduce water saving. Due to the soil moisture profile variation of the drip irrigation; water distributed of the root zone is not uniform. Moreover, moisture deficit and inefficient fertilizing in drip system due to unavailability in deeper layers of soils is one of the disadvantages of drip system in pistachio orchards with depth root systems. An experiment was carried out by adjusted subsurface drip irrigation (SSDIadj) system in pistachio of Damghan region (Semnan province) in a randomized complete block design with split plot arrangement in three replications for three years. The potassium fertilizer amounts (Fertigation) at three levels (50, 70, and 100% of requirement) were considered as the main plot and the design of conductor tubes of the SSDIadj system in seven levels as sub plots. The irrigation guide tubes were arranged for sand tube irrigation in (control), 40-40-40-40, 40-40- 50-50, 40-40-60-60, 40-40-50-60, 40-40-50-70, and 40-40-50-80. Meteorological data from the nearest meteorological station was collected and analyzed. Yield, water consumption, irrigation water productivity index and growth conditions of ShahPasand pistachio cultivar were determined in different treatments. Data were analyzed using Genstat-12 software and based on the analysis of surplus costs and aerial data, the best treatment including combination of potassium fertilizer and arranged tubes of SSDIadj system was determined. The recommended treatments are including of full irrigation, full potassium fertilizer and guide tubes 40-40-50-70 and or 40-40-50-80. The treatments with stratified conductive tubes in the optimal distribution of water, improving productivity and reducing inefficient consumption water. In addition, there are no restrictions on subsurface irrigation such as root accumulation, root penetration into pores of drippers and as well as accumulation of salts.

The geomorphic characteristics of the watersheds are interrelated and the temporal and spatial scale in the form of season and sub-basins affect the concentration of suspended sediment. One of the objectives of this study was to investigate the relationship between suspended sediment concentration and watershed characteristics of Kan River using principal components regression and to recognize the effect of seasons and sub-basins on sediment concentration. The concentration of suspended sediment during four rainfall-runoff events in three seasons and in sub-basins was measured and calculated. The sixteen physiographic and land use characteristics were determined in the sub-basins and the main factors were identified and the scores of each factor for each feature were calculated using principal component analysis (PCA). The results of variance analysis showed that the concentration of suspended sediment was significant in terms of time scale and spring had the highest rate of sedimentation. Redundancy analysis and canonical analysis on the properties that participate in the first factor (PC1) showed the characteristics of the percentage of erodible formation, relatively erodible formation, and percentage of free construction activity, respectively. Road (slope leveling) and stream length are the most essential attributes of sub-basins in the production and concentration of suspended sediment in the study area.

Identifying the behavior of precipitation is one of the most important planning principles related to water resources. In this research, an attempt was made to analyze the trend of time changes in extreme rainfall profiles of the country by using the daily rainfall data of 3423 synoptic, climatology, and rain gauge stations for the period from 1970 to 2016 and by performing interpolation using the kriging method. Then, using percentile profiles (percentile less than 10, less than 25, 25 to 75, 75 to 90, and above 90) and regression analysis, changes in the frequency of member days of each of the percentile methods over time were calculated and mapped. The results showed that during the studied period, 86.6% of cells associated with days with the tenth percentile or less in the country had an increasing trend. On the other hand, the pixels associated with days with the 90th percentile and more have shown an increasing trend. Considering that the pixels with the 25th, 25th-75th percentiles (normal), and 75th percentile have shown a decreasing trend in terms of the number of days in their group, it can be concluded that the country's rainfall conditions and the days with rainfall are towards the limit values has moved and the possibility of drought or destructive floods has increased in the country.

The present study investigated the related parameters to decrease the seepage through homogenous and heterogeneous earth dams by employing experimental models and solutions. Two heterogeneous earth dam models with vertical clay cores were considered to illustrate the effect of the electrokinetic application on the time failure factor. The seepage lines were measured along the longitudinal section from the heel to the toe using the observation wells by adjusting the electrodes of the electrokinetic application through the vertical clay core. The initial comparison expounds that adjusting the electrokinetic approach can decrease the level of the seepage line due to depleting water by considering horizontal drainage. Furthermore, the failure time was increased by 18 percent due to inputting the voltage in the clay content. The results indicated that the models with an electrokinetic approach were stabilized more than the ones. The hydrographs of the flow discharge were measured along the experimental tests to investigate the effect of electrokinetics with and without electrodes in 10 and 20 clay percent of the dam soil content. Results indicated that employing the electrokinetic application due to increasing clay content caused the effect of the electrokinetic was significantly increased and it caused the discharge flow reduced of 32 percent.

The use of biotechnology-based methods in the field of geotechnical engineering has led to the birth of new knowledge of biogeotechnology and several studies have been conducted using this new knowledge in various geotechnical issues including reducing permeability and increasing shear strength, especially in sandy soils and the desired results have been obtained. Nevertheless, little research has been done using biogeotechnology in the field of improving the mechanical properties of clay soils, especially in reducing the swelling of expansive soils, which is considered one of the types of problematic soils. The main cause of swelling of expansive soils is the presence of montmorillonite clays in these types of soils. Using chemical additives to stabilize expansive soils such as lime and cement is a common practice. However, environmental concerns related to greenhouse gas production caused by the production of chemical substances and the destructive effects of these substances on the environment and soils have encouraged researchers to use other sustainable stabilization alternatives. Microbial Induced Carbonate Precipitation (MICP) is a technique that can be a promising solution to solve this problem. The objective of the present study was to investigate the effect of the MICP method on the swelling of expansive clay soils and its effect on the mechanical strength of this type of soil. One-dimensional swelling tests, uniaxial compressive strength tests, and Atterberg limits tests were performed on clay soil with a liquid limit of 53 using Sporosarcina pasteurii bacteria, calcium chloride, and urea as nutrients. Taguchi's method was used for the design of the experiments and the statistical analysis of the results. This method designs experiments through partial factorial and reduces their number without a significant effect on the results. Bacterial concentration, nutrient molarity ratio, treatment time, and soil moisture were selected as four factors with Four levels of variation. The results showed that the (MICP) method was effective in reducing the swelling potential of expansive soils and also caused a significant increase in the unconfined compressive strength of the soil and its undrained shear strength.

Maintaining soil structure and stability is essential, especially in arid and semi-arid regions with poor soil structural stability. Destruction of soil and its crust can cause wind erosion and desertification. The objective of this study was to investigate the effect of using hydrogel nanocomposite mulch on the stabilization of sand surfaces. A wind tunnel test was used to evaluate the erodibility of samples treated with different amounts of hydrogel nanocomposite. The compressive strength of the samples was measured by a manual penetrometer. The prepared nanocomposites were examined using scanning electron microscopy (FE-SEM), infrared spectroscopy (FTIR), and X-ray diffraction (XRD) images. The results of the wind tunnel showed that the addition of hydrogel nanocomposite to the samples improved the soil erosion rate by 100% at a speed of 15 m/s compared to the control sample. Bonding between sand particles by spraying hydrogel nanocomposites improves the erodibility of sand. Measurement of mechanical strength of treated samples after 30 days showed that the resistance of the crust increased with increasing the amount of nanocellulose in the composite, which can be expressed due to the increased surface area of the nanoparticle and the possibility of further bonding of the nanocomposite polymer bed with sand particles. While the crust diameter showed no significant difference with increasing concentration and the sample treated with nanocomposites containing 3% nanoparticles was thicker compared to other samples.

To monitor and compare the changes of salts in the soil profile around the roots of the corn plant, the plant yield, and the productivity of corn water, an Experimental was conducted in a completely randomized block of three repetitions in two crop years 2017-2018 and 2018-2019 at Ahvaz Agricultural Research Station. Experimental treatments included two subsurface drip irrigation systems with a working depth of 30 cm from the soil surface and tape irrigation and two irrigation intervals of 2 and 4 days. The results of monitoring soil solutes obtained from sampling depths (0-25, 25-50, and 75-50 cm) showed that soil salinity in the second year in both systems as a result of improving the quality of irrigation water from 3.61 dS/m to 2.01 dS/m, it was reduced by two times. The results of soil salinity monitoring showed the highest ratio of salinity reduction with a 2-day irrigation interval in both irrigation systems. The most leaching was done at the irrigation depth of 25-50 cm in the subsurface drip irrigation system and at the depth of 0-25 cm in the tape system. The highest yield of corn dry fodder was 9.13 and 7.13 tons per hectare, respectively, and the best water efficiency based on dry corn fodder at the rate of 13.74 kg/m was obtained in the strip drip irrigation system (tape) with a two-day irrigation interval and in the second crop year. Also, the results of the soil salinity measurement showed that the implementation and exploitation of the drip irrigation system can be the basis for improving the quality of the soil as the most important non-renewable resource of agriculture.

Parent material and topography are among the soil-forming factors that affect soil evolution by influencing different parameters. This study was conducted to compare the effect of marl and calcareous parent materials in different slope positions, including the summit, shoulder, foot-, and toe-slopes on soil clay mineralogy in the Karoon 3 Basin, east of Khuzestan Province. Four soil profiles in each of the two topo-sequences were dug. They were sampled based on their genetic horizons and some physical, chemical properties, and clay mineralogy were measured. The results showed that the type and abundance of clay minerals identified for both parent materials were more affected by topo-sequence position. The composition of minerals identified in the topo-sequence with marl parent materials included kaolinite, palygorskite, smectite, chlorite, mica, and quartz, and in the topo-sequence with calcareous parent materials, palygorskite, smectite, chlorite, mica minerals, and quartz, and most of the identified minerals were also observed in all positions in the C horizon. However, in marl parent materials kaolinite, and calcareous parent materials, smectite seems to have been formed pedogenically. The result of the association between Weaver and Beck indicated that most of the clay minerals are in the equilibrium of Palygorskite.

Soil erosion followed by sediment production is the most important phenomenon that causes soil and environment degradation in many areas and is increasing. Sediment fingerprinting is a method to identify sediment sources and determine the contribution of each source to sediment production. The present research was carried out to evaluate the relative erosion sensitivity of lithological units and to determine the contribution of each unit in bed sediment production using geochemical properties in the Vaz River located in Mazandaran province. The 33 soil samples were taken from the whole watershed and one sediment sample at the outlet of the watershed. Then, five tracers of B, Al, Sc, Mo, and Sn were selected as the optimal combination using three statistical tests range tests, Kruskal-Wallis, and discriminant function analysis. Finally, using optimal tracers and a combined multivariate model, the contribution of lithological units with very high (A), high (B), medium to high (C), and medium (D) sensitivity in bed sediment production were obtained using FingerPro statistical package and R software. The results showed that the contribution of lithological units with very high (A), high (B), medium to high (C), and medium (D) sensitivity in bed sediment production were 24.23, 50.77, 15.62, and 9.36%, respectively. Then, the specific contribution of each sensitivity class was also calculated to remove the effect of area on the results. The Qal lithological unit including the Quaternary sediments in the river bed and banks with very high sensitivity to erosion (A) and a specific contribution of 0.0807 % per hectare had the maximum contribution in bed sediment production in Vaz River.