Research Article
Irrigation
N. Najafi Iman Abadi; M.A. Gholami Sefidkouhi; S. Shiukhy-Soqanloo
Abstract
Introduction
Today, the crisis of water resources is one of the biggest challenges of human societies. Population growth and industrialization have increased the demand for water consumption. The agricultural sector is facing many problems to supply the required water resources. Irrigation management ...
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Introduction
Today, the crisis of water resources is one of the biggest challenges of human societies. Population growth and industrialization have increased the demand for water consumption. The agricultural sector is facing many problems to supply the required water resources. Irrigation management and the use of plastic mulches play a crucial role in raised-bed cultivation of horticultural and medicinal plants, serving various purposes such as enhancing quality and increasing yield. Moreover, given the current water scarcity conditions, improving the quantitative and qualitative yield of medicinal plants relies heavily on effective irrigation management and efficient cultivation practices.
Material and Methods
In this research, a split-plot experiment was conducted using a randomized complete block design (RCBD). The experimental treatments included: the main factor of irrigation management (IM) with four levels (IM100, IM80, IM60 and IM40) and the sub-factor of plastic mulch (PM) with two levels (black plastic mulch (PM1) and no mulch (PM0)) with 3 replications during the growth season 2022-2023 and was conducted at Sari Agricultural Sciences and Natural Resources University (SANRU), Iran. The dimensions of the experimental plot was arranged as 1.80 × 1.20 meters (length and width). Lemon balm was planted in rows with a spacing of 30 cm between plants and 40 cm between rows. Soil moisture was measured by weight method and irrigation was done manually with a sprinkler. In the end, the data obtained from measuring water productivity (WP), relative water content (RWC), essential oil content, morphological and biochemical characteristics of lemon balm were analyzed using ANOVA of SAS software. The Duncan multiple range post hoc test was employed to compare treatment means.
Result
Based on the findings, the interaction effect of irrigation management and plastic mulch on water productivity was significant. So, the IM100 conditions and PM1, the highest water productivity was observed with 38.5 kg.m-3 and the lowest amount was related to IM40 and PM0 25 kg m-3. The results showed that the simple effect of IM on the RWC in IM100 was very noticeable and obvious compared to other IMs. The highest (74.3%) RWC was observed in IM100, while the lowest RWC was related to IM40 (40.1%). In PM1, the highest amount of RWC (62.1%) was observed and the lowest amount was related to the PM0 (51.8%). The results showed that vegetative wet and dry weight, leaf area index (LAI) and the number of lateral branches of lemon balm increased under the IMs and PM1 affect compared to the control (PM0). The comparison of averages indicated that the highest wet and dry root weights were 217 kg ha-1 and 140.8 kg ha-1, respectively, observed in the IM100 treatment. Additionally, the highest wet and dry root weights under the plastic mulch treatment (PM1) were 151.1 kg ha-1 and 108.5 kg ha-1, respectively. The results also showed that the highest vegetative wet and dry weights were recorded at 647.2 kg ha-1 and 231 kg ha-1, respectively, in the IM100 treatment. Furthermore, the interaction effect of irrigation management (IM) and plastic mulch (PM) on the leaf area index revealed that the highest LAI value (2.8) was observed in the IM100 and PM1 combination. This was while the lowest value of the LAI was related to IM40 and PM0. The interaction effect of IM and PM on the number of lateral branches indicated that IM100 and PM1, the highest number of lateral branches (12) was generated. Based on the obtained results, the highest amount of phenol and flavonoids content were related to IM40 and PM0 with 13.4 mg.GA g-1 and 14.6 mg.QU g-1, respectively. While their lowest amount was observed under IM100 and PM1 with 10.2 mg.GA g-1 and 11.8 mg.QU g-1, respectively. Also, the results showed that the highest essential oil content was related to IM100 and IM80 conditions with 1.14% and 1.13 %, respectively, and the lowest was observed in IM40 condition with 0.53%.
Conclusion
The evaluation of the irrigation management and plastic mulch effects on water productivity and quantitative and qualitative yield of lemon balm showed that the use of plastic mulch by maintaining soil moisture and improving cultivation conditions, increased the vegetative growth and some qualitative characteristics. In general, due to the crisis of lack of water resources and the challenge of water scarcity, irrigation under IM80 conditions and the use of black plastic mulch in the rise-bed of lemon balm are suggested.
Research Article
Irrigation
P. Tahmasbi; F. Dalvand; S.A. Hosseini; B. Karimi; H. Ghadrshnas
Abstract
IntroductionAgriculture plays a dual role in the energy sector meaning that it acts both as a source of raw material for bioenergy production and as a major consumer of energy, particularly in the processes of planting, cultivation and harvesting, transportation, processing, and storage of agricultural ...
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IntroductionAgriculture plays a dual role in the energy sector meaning that it acts both as a source of raw material for bioenergy production and as a major consumer of energy, particularly in the processes of planting, cultivation and harvesting, transportation, processing, and storage of agricultural products. Among the numerous challenges facing the agricultural sector, optimizing energy or input consumption is of paramount importance. These key inputs play a crucial role in ensuring food security and economic stability for the country. One of the most important agricultural development programs in the country should be to increase efficiency of energy consumption in the agricultural sector. In Iran, approximately 9.2 million hectares have been equipped with modern irrigation systems (pressure system) which has increased the water productivity index from 0.87 kg m-3 in 2014 to 0.32 kg m-3 in 2014. Accordingly, it is predicted to reach 0.60 kg m-3 hectares until 2025. The Dehgolan Plain, located in the east of Sanandaj city, has an area of 84,982 square kilometers. Groundwater is the only source of water for agriculture in the region. Due to the annual decrease in the groundwater level, energy consumption for water extraction has increased. Common irrigation systems in the region's farms include fixed-mobile sprinkler classic rain irrigation systems, center pivot, and lateral roll. Thus, it seems necessary to evaluate the energy productivity and efficiency indexes in the mentioned plain. The main objective of this study is to evaluate the energy consumption indexes of wheat in farms under fixed-mobile sprinkler classic and Willet rain irrigation systems. Materials and MethodsThis study was conducted in the farms of Dehgolan plains where the energy consumption trend of input factors in two irrigation systems was investigated. All information related to input factors and working hours of machinery, agricultural equipment, and manpower was recorded at the end of the cropping season 1400-1401 through filling out questionnaires. The studied farms in this research were all under dry wheat cultivation and equipped with two rain irrigation systems, system 1 (fixed-mobile sprinkler classic) and system 2 (Wheel move irrigation). The required input factors for wheat production in each hectare were determined. The amount of different input factors for conversion to energy standard was calculated using energy coefficients and equivalents. As a result, energy productivity, energy use efficiency, specific energy, and net energy indexes were used to investigate the energy consumption trend of wheat in the two mentioned irrigation systems. Results and DiscussionThe results of this study showed that the total input energy for wheat production in systems (1) and (2) was 85943.97 and 69189.04 MJ ha-1, respectively and energy consumption in the Willet rain irrigation system was higher than in the fixed-mobile sprinkler classic rain irrigation system due to the high consumption of electricity and irrigation water. The electricity consumption in both systems accounted for the highest energy consumption. Moreover, the energy productivity and efficiency of the two systems were almost equal as well as the net energy of irrigation system (1) and irrigation system (2) was 41510.96 and 64156.03 MJ ha-1, respectively. ConclusionIn conclusion, this study focuses on evaluating the energy trends in rain irrigation systems used in dry wheat farms in the Dehgolan plains, Kurdistan province, Iran. In this study, the energy indexes of wheat in smallholder farmers' farms in Dehgolan plain, Kurdistan province, were evaluated. The studied farms were categorized into two groups, system (1) (fixed-mobile sprinkler classic rain irrigation system) and irrigation system (2) (Willet rain irrigation system), the energy source of which was electricity for both systems. At the end of the cropping season, the total amount of input and output factors were collected by filling out questionnaires in person, and to validate the amount of electricity consumption, its amount was obtained from the Dehgolan Electricity Company. The results of the research showed that the energy consumption per unit of wheat production in the Willet irrigation system was higher than in the fixed-mobile sprinkler classic irrigation system. This difference was due to the higher consumption of electricity and irrigation water in the Willet irrigation system. The energy productivity and efficiency indexes were almost equal in both systems. Eventually, the net energy of the fixed-mobile sprinkler classic irrigation system was higher than that of the Willet irrigation system.
Research Article
Soil science
N. Lotfi; Sh. Kiani; H.R. Motaghian
Abstract
Introduction
Selenium (Se) is one of the beneficial elements for plants, which is usually not supplied in the nutrient solutions used in soilless cultures. It is an essential element for both humans and animals. Application of Se at low concentrations has a positive effect on the growth and quality ...
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Introduction
Selenium (Se) is one of the beneficial elements for plants, which is usually not supplied in the nutrient solutions used in soilless cultures. It is an essential element for both humans and animals. Application of Se at low concentrations has a positive effect on the growth and quality indices of plants. Nitrate accumulation in leafy vegetables poses threaten to human health. Leafy vegetables such as lettuce (Lactuca sativa L.) contain high levels of nitrate. According to the results of some researches, application of Se in the nutrient solutions can decrease nitrate accumulation in vegetables. However, the optimum concentration of Se in the nutrient solution for lettuce production in hydroponic culture is still not clear. This experiment was conducted to elucidate the effect of different levels of Se in the nutrient solution on the growth indices, yield, and nitrate accumulation of red French lettuce (cv. Lolla Rossa) in soilless culture.
Materials and Methods
A perlite culture experiment, using completely randomized design, was carried out with seven levels of Se in the nutrient solution (0, 0.1, 0.5, 1, 5, 10 and 20 µmol L-1) with four replications in the research greenhouse of Shahrekord University. Lettuce seedlings were grown in 1.7 L plastic pots (one plant per pot) containing perlite with size of 0.5-5 mm and were manually fertigated with the nutrient solutions on a daily basis. Different concentrations of Se were applied as sodium selenate (Na2SeO4.2H2O) in the nutrient solution (Domingues et al., pH= 5.4±0.1, EC=1.36-1.41dS m–1). After four weeks, lettuce plants were harvested and the fresh weights of shoots and roots were measured. Plant growth indices consisting of leaf number, leaf length, leaf width, plant height, plant diameter, leaf chlorophyll index, and leaf total soluble solids were determined. In one bush in each treatment, the leaves were separated as 1st to 10th outer leaves and other inner leaves. The leaves were dried in an oven at 70 °C and were ground. Nitrate concentrations in outer and inner leaves were measured calorimetrically using a spectrophotometer at a wavelength of 410 nm. Shoots Se concentration was determined with ICP-MS after wet digestion of samples with HNO3 and H2O2. Analysis of variance was done using SAS software and means comparison was conducted using the least significant difference test at 0.05 probability level.
Results and Discussion
The results indicated that application of Se in the nutrient solution had not significant effect on the lettuce growth indices including of leaf length, leaf width and leaf number. Application of 10 µmol L-1 of Se in the nutrient solution led to significant decrease of plant height in comparison with control, but plant diameter increased with application of Se in the nutrient solution. The highest plant diameter was observed in 10 μmol L–1 of Se treatment. The highest and the lowest shoot fresh weight were obtained under 0 and 1 μmol L–1 of Se in the nutrient solution, respectively. Application of 1 μmol L–1 Se increased shoots fresh weight by 22% comparing to the control. Shoot Se concentration was increased with application of Se in the nutrient solution. The highest concentration of Se in shoots (15 mg kg-1 dry matter) was observed at the rate of 20 μmol L–1 of Se in the nutrient solution. The amount of Se accumulated in the plant tissue is important in biofortification programs. The results showed that application of Se in the nutrient solution (with the exception of 1 µmol L-1 of Se) led to significant decrease in the nitrate concentration of roots, outer leaves, inner leaves and all leaves of lettuce. The lowest nitrate concentration in all leaves of lettuce (2095 mg kg-1 fresh weight) was obtained in plants nourished with 0.5 μmol L–1 of Se in the nutrient solution. Compared with control (0 μmol L–1 of Se), nitrate concentration in all leaves for 0.5 μmol L–1 of Se treatment was decreased 28%. Selenium has a positive function on decreasing nitrate accumulation in plants via regulating the transport of nitrate and enhancing activities of nitrogen metabolism enzymes.
Conclusion
According to our results, application of Se decreased nitrate concentration in lettuce plants. Therefore, application of Se in the nutrient solution at the rate of 0.5 μmol L–1 is suggested for red French lettuce production in hydroponic culture under the conditions of the present study.
Research Article
Soil science
S. Hosseinzadeh; E. Fateh; A. Aynehband; M. Farzaneh; J. Habibi Asl
Abstract
Introduction
Tillage is an important component of soil management that affects the production of crops. Maintaining and improving the quality of the soil is a basic requirement to ensure the sustainability of the ecosystem. This experiment was conducted in order to investigate the effect of different ...
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Introduction
Tillage is an important component of soil management that affects the production of crops. Maintaining and improving the quality of the soil is a basic requirement to ensure the sustainability of the ecosystem. This experiment was conducted in order to investigate the effect of different tillage methods and the use of plant residues on the yield, protein and nitrogen percentage of triticale plant and physical and chemical indicators of the soil.
Materials and Methods
The experiment was carried out as split plots based on a randomized complete block design with three replications at Shahid Chamran University of Ahvaz during 2023-2024. The main factor including different methods of tillage at three levels (conventional tillage, reduced tillage and no tillage) and the sub factor also including 5 levels of plant residue application (without residues (control), wheat residues, mung bean, sesame and half of wheat residues + half of residues Mung bean) were considered. The amount of residues used for each plot was approximately 30% of the biological yield of the product, which was considered to be 3, 1.5 and 1 ton.ha-1 for wheat, sesame and mung bean, respectively. At the end of the experiment yield and yield components, seed nitrogen and protein of triticale plant and physical characteristics (bulk density, percentage of porosity) and chemical (pH, EC, organic carbon content, nitrogen) soil properties were measured. All statistical calculations were made using SAS 9.3 statistical software and for the LSD test was used to compare the means at a probability level of 5%.
Results and Discussion
The interaction of tillage treatments and the use of plant residues showed that the highest grain yield was equal to 8.6 ton.ha-1 from the treatment of reduced tillage and the use of Mung bean residues, and the lowest value obtained was related to the effect of the treatment conventional tillage and no residues (control) with 3.5 ton.ha-1. The grain yield in the reduced tillage method was 12.5% and 7.6% higher than the conventional tillage and no tillage methods. The reduced tillage method resulted in a 32.2% increase in seed protein and a 32% increase in seed nitrogen compared to conventional tillage. The results also indicated a significant interaction effect between tillage treatments and residue application on grain yield (p < 0.01). Additionally, the interaction between tillage and residue application had a significant effect on soil bulk density (p < 0.01). The lowest bulk density (1.3 g.cm-3) was observed in the conventional tillage treatment combined with wheat and mung bean residues, with this combination falling within the same statistical group. The highest bulk density (1.75 g.cm-3) was obtained from the no-tillage treatment and the use of NO residues (Control). Based on the obtained results, the interaction effect of tillage treatments and the use of residues on soil organic matter, soil organic carbon and nitrogen soil (p<0.05). The interaction between the effects of tillage and the use of residues showed that the highest soil organic matter (1.53%) was from the treatment of reduced and the use of wheat residues.
Conclusion
The results showed that tillage methods and the use of plant residues, in addition to affecting the percentage of nitrogen and protein of triticale seeds, also affected the physical and chemical indicators of the soil. The changes related to the physical and chemical indicators of the soil in the method No tillage are more than the two methods of reduced tillage and conventional tillage, and the improvement of these characteristics has been limited even at this time. Overall, from the point of view of soil protection, the results of this experiment clearly show the superiority of conservation tillage methods compared to conventional tillage methods. Sustainable agriculture aims to achieve optimal yields while preserving environmental structure and minimizing the adverse impacts of agricultural activities. One of the key challenges in sustainable agriculture is the lack of organic matter and its associated consequences. Implementing conservation tillage and managing plant residues-critical elements of agricultural production-can help address this issue. By improving soil quality, these practices contribute to increased productivity in farming.
Acknowledgement
We would like to thank the Research and Technology Vice-Chancellor of Shahid Chamran University of Ahvaz for funding this research, which is part of the research contract SCU.AA1400.309.
Research Article
Soil science
A. Neisi; M. Chorom; H. Ghafari; J. Alkasir
Abstract
IntroductionSugarcane (Saccharum officinarum L.) is a perennial plant belonging to the cereal family. Sugarcane is a major agricultural crop cultivated extensively in tropical and subtropical regions worldwide. Its phenological growth cycles lead to changes in the plant's nutritional requirements. Understanding ...
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IntroductionSugarcane (Saccharum officinarum L.) is a perennial plant belonging to the cereal family. Sugarcane is a major agricultural crop cultivated extensively in tropical and subtropical regions worldwide. Its phenological growth cycles lead to changes in the plant's nutritional requirements. Understanding these changes requires comprehensive knowledge of the plant's growth stages, as well as the decomposition processes of soil and plant leaves throughout these stages. The availability of nutrients required by the plant during the growth stages of the plant is one of the key points of normal plant growth, therefore, plant nutrition management plays a significant role in achieving optimal performance. Considering these changes, the leaf analysis and diagnosis method can prevent the limitations caused by plant nutritional disorders and the optimal use of fertilizers required in sugarcane cultivation. The combined nutrient detection (CND) method is one of the appropriate methods in interpreting the results of plant nutrient analysis, nutrient requirements and nutritional balance status in plants. Performing leaf sample analysis is an effective approach to monitor and assess the nutritional status of sugarcane. Given that sugarcane may have a multi-year cycle, this method provides a reliable indicator for assessing the nutritional needs of the crop during its cultivation period. One of the effective methods for assessing nutritional limitations in sugarcane is through the CND method. This method provides the advantage of quickly delivering up-to-date standards while identifying specific nutrients responsible for nutritional imbalances that may reduce productivity. Additionally, it enables the detection of limitations caused by deficiencies and excesses, indicated by negative and positive indices, respectively. The aim of this study was to determine the order of limitation for nitrogen, phosphorus, potassium, calcium, magnesium, copper, iron, manganese, and zinc using the CND in the commercial sugarcane variety CP69-1062 grown in ratoon farms. In the northern Khuzestan farms, which have the potential for higher sugarcane production, nutritional limitations may still restrict productivity. Materials and MethodsThe present study was conducted in ratoon sugarcane fields in the Shuaibih area of Imam Khomeini sugarcane cultivation and industry. The objective of this study was to examine the impact of fertilization management and assess nutrient balance in the commercial sugarcane variety CP69-1062 grown in ratoon farms. To achieve this, 25 farms were selected during the 2023-2024 crop year. The concentrations of nitrogen, phosphorus, potassium, calcium, magnesium, iron, manganese, zinc, and copper were analyzed in the leaves of the sugarcane plants. After the harvest season, the yield of each field was measured and recorded. The intermediate yield, obtained using the Khayari method, allowed the farms to be divided into two groups based on whether the yield was favorable or unfavorable. Subsequently, CND reference numbers, CND nutrient index and nutrient balance index (r²) were calculated. This index was calculated using the Keith-Nielson method, based on the Chi-square statistical distribution function (K²) in Excel software. Results and DiscussionThe results of the cumulative distribution function of the variance of nutrients, with an intermediate yield of 99 tons per hectare, indicate that 52% of the studied ratoon sugarcane farms were in the high yield group and 48% were in the low yield group. After solving the equations of the cumulative function of the third order of the studied nutrients, the nutrient balance index values were found to fall within the range of (2.62 to 20.58) in the optimal performance group, with an average value of 109.28 tons per hectare. The highest value of this index (r2 = 199.95) was observed in the Raton sugarcane field, with a yield of 73.08 tons per hectare. The CND reference numbers of the evaluated nutrients and remaining compounds were as follows: V*N= 2.87, V*P= 1.04, V*K= 2.64, V*Ca =1.95, V*Mg =1.29, V*Fe = -1.75, V*Mn = -3.35, V*Zn = -4.72, V*Cu = -3. 92, and V*Rd = 4.13. The index of CND nutrients showed that copper and iron had the highest negative index among micronutrients in the group of low-yielding ratoon sugarcane fields. The presence of calcareous conditions in the soil of the studied fields can be one of the reasons for this observation. ConclusionThe CND nutrient balance index (r2) was positive, especially in low-yielding ratoon sugarcane fields, and much higher than its value in high-yielding fields, which indicates nutritional imbalance in these fields. Proper management and balanced use of fertilizers should be considered. It can improve yield and growth cycle of sugarcane.
Research Article
Soil science
Sh. Asghari; K. Heidari; M. Hasanpour Kashani; H. Shahab Arkhazloo
Abstract
Introduction
The study of soil mean weight diameter (MWD) of wet aggregates that is important for sustainable soil management, has recently received much attention. As the prediction of MWD is challenging, laborious, and time-consuming, there is a crucial need to develop a predictive estimation ...
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Introduction
The study of soil mean weight diameter (MWD) of wet aggregates that is important for sustainable soil management, has recently received much attention. As the prediction of MWD is challenging, laborious, and time-consuming, there is a crucial need to develop a predictive estimation method to generate helpful information required for the soil health assessment to save time and cost involved in soil analysis. Therefore, it is useful to use different models such as multiple linear regression (MLR) and intelligent models including artificial neural network (ANN) and gene expression programming (GEP) to estimate MWD of wet aggregates through easily accessible and low-cost soil properties. The objectives of this study were (1) to creating MLR, ANN and GEP models for predicting MWD from the easily measurable soil variables in forest, range and cultivated lands of the Fandoghloo region of Ardabil province, (2) to compare the precision of the mentioned models in the prediction of MWD of wet aggregates using the coefficient of determination (R2), root mean square error (RMSE), mean error (ME) and Nash-Sutcliffe coefficient (NS) criteria.
Materials and Methods
Disturbed and undisturbed soil samples (n= 80) were nearly systematically taken from 0-10 cm depth with nearly 50 m distance in forest (n= 20), range (n= 23) and cultivated (n= 37) lands of the Fandoghloo region of Ardabil province, Iran (lat. 38° 24' 10" to 38° 24' 25" N, long. 48° 32' 45" to 48° 33' 5" E) in summer 2023. The contents of sand, silt, clay, CaCO3, pH, EC, bulk (BD) and particle (PD) density, organic carbon (OC), geometric mean diameter (GMD) of dry aggregates were determined in the laboratory using standard methods. Total porosity (n) was calculated using BD and PD data (n= 1-BD/PD). The mean geometric diameter (dg) and geometric standard deviation (σg) of soil particles were computed by sand, silt and clay percentages. The mean weight diameter (MWD) of wet aggregates was measured in the aggregates smaller than 4.75 mm by wet sieving equipment using sieves with 2, 1, 0.5, 0.25 and 0.106 mm pore diameter. All data were randomly divided into two series as 60 data for training and 20 data for testing of models. The SPSS 22 software with the stepwise method, MATLAB and Gene Xpro Tools 4.0 software were used to derive multiple linear regression (MLR), artificial neural network (ANN) and gene expression programming (GEP) models, respectively. A feed forward three-layer (9, 8, 6 and 6 neurons in the hidden layer) perceptron network and the tangent sigmoid transfer function were used for the ANN modeling. A set of optimal parameters were chosen before developing the best GEP model. The number of chromosomes and genes, head size and linking function were selected by the trial and error method, and they are 30, 3, 8, and +, respectively. The rates of genetic operators were chosen according to literature studies. The precision of MLR, ANN and GEP models in predicting MWD of wet aggregates were evaluated by the coefficient of determination (R2), root mean square error (RMSE), mean error (ME) and Nash-Sutcliffe coefficient (NS) statistics.
Results and Discussion
The values of sand (13.14 to 64.79 %), silt (21.11 to 74.96 %), clay (3 to 42.18 %), OC (1.01 to 7.17 %), PD (2.00 to 2.67 g cm-3), n (0.39 to 0.87 cm3 cm-3), GMD of dry aggregates (0.8 to 1.33 mm) and MWD of wet aggregates (0.35 to 2.65 mm) showed good variations in the soils of the studied region. The studied soils had clay loam (n= 11), sandy clay loam (n= 6), sandy loam (n= 12), loam (n= 13), silty clay loam (n= 14), silty clay (n= 1) and silt loam (n= 23) textural classes. There were found significant correlations between MWD with OC (r= 0.67**), sand (r= 0.70**), GMD (r= 0.30**) and PD (r= -0.46**). Also, significant and positive correlation was found between OC and sand (r= 0.59**). Due to the multicollinearity of sand with dg (r= 0.87**), we did not use the dg as an input variable to estimate MWD of wet aggregates. Generally, four MLR, ANN and GEP models were constructed to predict MWD of wet aggregates from measured readily available soil variables. The results of MLR, ANN and GEP models indicated that the most suitable variables to estimate MWD of wet aggregates were sand, OC and GMD of dry aggregates. The values of R2, RMSE, ME and NS criteria were obtained equal 0.52, 0.48 mm, 0.13 mm and 0.48, and 0.85, 0.30 mm, 0.03 mm and 0.78, 0.79, 0.35 mm, -0.10 mm, 0.95 for the best MLR, ANN and GEP models in the testing data set, respectively. Many researchers also reported that there is a positive and significant correlation between MWD of wet aggregates and OC.
Conclusion
The results showed that sand, OC and GMD of dry aggregates were the most important and readily available soil variables to predict the mean weight diameter (MWD) of wet aggregates in the Fandoghloo region of Ardabil province. According to the lowest values of RMSE and the highest values of R2 and NS, the precision of ANN models to predict MWD of wet aggregates was more than MLR and GEP models in this study. Because ANN is more flexible and effectively captures non-linear relationships, it performed better than the other models in predicting MWD.
Research Article
Agricultural Meteorology
S. Mirshekari; F. Yaghoubi; S.A. Hashemi
Abstract
Introduction
The 21st century is witnessing the increase of climate change as an important challenge due to its destructive environmental and socio-economic effects. Extreme climatic conditions have become frequent and more intense in recent decades as a result of human activities. Iran, as one of the ...
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Introduction
The 21st century is witnessing the increase of climate change as an important challenge due to its destructive environmental and socio-economic effects. Extreme climatic conditions have become frequent and more intense in recent decades as a result of human activities. Iran, as one of the countries in the Middle East with a different climate in each region of the country, has suffered significant adverse effects of climate change. Considering the importance of the climate change, it is important to investigate the changes in climate variables to know the future conditions and make management decisions. In the field of climate research, global climate models are useful tools that are often used to investigate the global climate system, including historical and projected periods. Since the use of the CMIP6 dataset provides improved clarity and accuracy for predicting future climate forecasts, the main objective of the present study is to predict the temperature and precipitation changes in the near, mid, and far future in Sistan-va-Baluchestan province.
Materials and Methods
The minimum temperature, maximum temperature, and precipitation data of 10 general circulation models (GCMs) of the 6th IPCC report for the baseline (1990-2014) were downloaded from the Global Climate Research Program database (https://esgf-node.llnl.gov). Then GCMs were including ACCESS-CM2, CMCC-ESM2, CNRM-CM6-1-HR, CNRM-ESM2-1, EC-Earth3-CC, EC-Earth3-Veg-LR, INM-CM4-8, INM-CM5-0, MIROC6, and NorESM2-MM. Four statistical indicators including correlation coefficient (R2), RMSE, Nash-Sutcliffe efficiency (NSE), and mean absolute error (MAE) were used to evaluate the performance of 10 GCMs. Based on the results obtained from the these indicators, the models that had higher performance in predicting the temperature and precipitation data were selected as the best models for forecasting in the future. The ensemble of these models under two SSP2-4.5 and SSP5-8.5 scenarios for the near, middle, and far future (2026-2050, 2051-2075, and 2076-2100) were extracted from the World Climate Research Program database.
CMhyd (Climate Model data for hydrologic modeling) tool was used to bias correction climate data of the selected models. In order to choose the best bias correction method, the R2, RMSE, NSE, and MAE were estimated.
After bias correction, the climate data of selected models were ensembled and then the changes in precipitation and maximum and minimum temperature in three future periods compared to the baseline was estimated.
Results and Discussion
The results showed that out of 10 GCMs, seven models had good performance (R2 > 0.40, 4.23 < RMSE < 12.02°C, 0.12 < NSE < 0.74, and 3.36 < MAE < 9.59°C) in simulating daily minimum and maximum temperature. However, the performance of all models in simulated daily precipitation was poor (R2 > 0.19, 1.24 < RMSE < 3.70 mm, -7.41 < NSE < -0.57, and 0.23 < MAE < 0.85 mm).
Among the different bias correction methods of temperature and precipitation available in CMhyd, the distribution mapping method had the best performance.
In all three regions, compared to the baseline, the average annual minimum and maximum temperature under two scenarios will increase in the future periods and precipitation will decrease in most periods and scenarios. These changes will be mainly in the SSP5-8.5 scenario compared to SSP2-4.5 and also in the far future period compared to the middle and near future. Averaged across all locations, annual maximum temperature showed increases in near, middle, and far projected periods of 1.3, 2.1, and 2.8°C under SSP2-4.5 and 1.6, 3.1, and 5.1°C under SSP5-8.5, respectively (Fig. 2), while for minimum temperature, the increases will be of 1.6, 2.6, and 3.4°C for SSP2-4.5 and 1.9, 3.9, and 6.3°C for SSP5-8.5. The range of annual precipitation among all sites was from –58.22 to 49.33% under SSP5-8.5 in the near and far future periods in Zabol and Iranshahr, respectively.
The annual increase in the average maximum and minimum temperature will be mainly due to the increase in air temperature in the months of January, February, August, September, October, November and December. The annual decrease in precipitation will mainly result from the decrease in precipitation in January, February, March, November, and December, and the annual increase in precipitation will result from the significant increase in precipitation in May and October compared to the baseline.
Conclusion
The results showed that under different scenarios of climate change, the maximum and minimum temperatures in the near, middle, and far future periods will face an increase compared to the baseline. However, the precipitation changes in the future time periods are not the same as compared to the baseline, and in some periods the precipitation will decrease and in others it will increase. But in general, the decrease in precipitation will be more than its increase. Therefore, it is very important to formulate and implement appropriate management programs for the needs of each region, in order to properly manage water resources and adapt to extreme temperatures and their consequences.
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