S. Hamzeh; AbdAli Naseri; H.A. Kashkuli
Abstract
Two issues of the drainage systems which are less studied in the literature are drainage in layered soils and bi-level derange systems. Hence, it is necessary to do more research in these topics. Therefore the present study was carried out under above conditions in the Imam Khomeini Farming and Industrial ...
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Two issues of the drainage systems which are less studied in the literature are drainage in layered soils and bi-level derange systems. Hence, it is necessary to do more research in these topics. Therefore the present study was carried out under above conditions in the Imam Khomeini Farming and Industrial Lands, located in the north of the Khuzestan province, Iran. In this area based on primary studies, lateral spacing was estimated about 70 m and they were installed at the depth of 2.1m. But after two years of establish these drainage systems, it was observed that due to existence a soil layer with a very low infiltration rate (less than 10 time in compare with its above and below layers) at the depth of 110 to 160 cm, drainage systems in 500ha of these fields had low performance. Then, in order to overcome with this problem, the implementation of bi-level drainage system was proposed. Hence, a new drain line was installed at the depth of 1.2m between the old drain lines. After establishment of these new drains one field was selected to evaluation the performance of this new system. In the selected field three rows of observation wells were installed (in total 20 observation wells). After equipment of these observation wells, water table fluctuation, inflow and outflow water values from the field were measured in 3 irrigation periods. Then the results of field observations were compared with the obtained results from analytical solution in the literature. Results show with establish new drain lines the problem of these fields are solved and the water table profile will drop-off to the below of root zone in less than 36hr. Also it was concluded that the rate of water table decline by moving from the end of field to the open collector of field will be increased and the discharge of deep drains are more than low-deep rains. Results show that analytical solution is not able to predict the water table profile with well accuracy and predicted values by this equation only in a small area of water table profile were consistent with the observed values in the field. The main reason of this difference was the specific situation of layers of the soil.
sabah mohamadi; Rasool Ghobadian; mahmood kashefipoor
Abstract
Introduction: It is so important for engineers to be able to predict the places in which deposition and scouring occurs. In recent two decades using the numerical models arecommon for simulating flow and sediment transport. Numerical models are valuable tools for estimating flow conditions and sediment ...
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Introduction: It is so important for engineers to be able to predict the places in which deposition and scouring occurs. In recent two decades using the numerical models arecommon for simulating flow and sediment transport. Numerical models are valuable tools for estimating flow conditions and sediment transport, and are widely applied in water resources management. For this reason, many researches focus on modeling and simulation of flow on a mobile bed in natural and alluvial rivers. Analyzer of sediment transport is one of the most complicated topics in sediment and river hydraulic.
Material and Methods: In this research a one dimensional, unsteady, hydrodynamic model is developed which can be used for simulating flow and sediment transport as semi-coupled model in river systems. In this research, the Saint- Venant’s first order partial differential hyperbolic equations are numerically solved using the Visual Basic program for river systems. In this research study a semi implicit finite difference scheme is developed to solve the Saint- Venant equations for unsteady flow. The linear equations are produced based on the partial differential equations and the staggered technique, so it is possible to employ the tri-angular matrix algorithm (TDMA) to solve them, with this algorithm the time of running model being minimum due to the least mathematical computations. The matrix form of the linearized momentum and continuity equations for a channel with upstream and downstream boundary conditions is provided. Another technique used to solve the matrix of the linear equations is Influence Line Technique (ILT). Base flow discharge and depth in each branch are introduced into the model as the initial conditions. To avoid divergence in numerical calculations, the downstream end discharge of each branch is calculated using initial flow depth and stage-discharge or Manning’s relationship. At the junctions, the upstream discharge is calculated using the algebraic sum of the discharges of the downstream branches and vice-versa; this process is continued up to the last branches at the upstream of the river system. After solving the above equations, the computed hydraulic parameters in this part are sent to the sediment transport segment. In the sediment subroutine the bed and suspended dynamic equations are discretized by finite volume method, and solved with flow equations as semi-coupled scheme. In this study the bed and suspended load rates are individually solved. The dynamic advection- dispersion equation and the bed load differential equation were applied to calculate the suspended sediment concentration and bed load transport, respectively. The Exner equation is then used to predict the changes in the river bed elevations innon-equilibrium conditions. Because ofthe nature, the sediment transport is often in non-equilibrium form, in this study, the non-equilibrium Exner equation is used to compute the bed elevations, unlike many of the known models. The use of non-equilibrium method due to the complexity of the solution and the presence of non-equilibrium parameters such as coefficients of the adaptation length and recovery is very difficult.
Results and Discussion: In non-equilibrium conditions, the numerical models have high sensitivity to two parameters including, the adaptation length coefficient for bed load and recovery coefficient for suspended load, with the sensitivity analysis for these coefficients being carried out in this research. In this study, a sensitivity analysis was performed on these parameters using developed numerical model. The developed model has this ability to simulate flow and sediment transport in complex and loop river systems. Finally, the model was simulated for the Chaudhry loop river systems. Thisriver system has 9 branches that form the loop. All channels have rectangular sections and their flows are sub-critical. The upstream boundary condition is an unsteady hydrograph with peak discharge of 250 cubic meters per seconds and base time of 8 hours. The calculated stage and discharge by the model (using Manning’s equation) was supplied to the model as a downstream boundary condition at last node. The model outputs are discharged hydrographs on different sections of each channel. The developed model has good ability to simulate the flow and sediment transport in river systems. The result showed that by selecting the adaptation length coefficient, equivalent to a multiple of 1 to 3 times the distance between cross sections, the results of the numerical model can be more realistic. Also it was concluded that empirical equation of Lin(1984) used for the recovery factor of the suspended load.
Saeid ghavam seeidi noghabi; Abbas Khashei-siuki; Hossein Hammami
Abstract
Introduction: Water is one of the most important factors limiting agricultural developments in arid and semi-arid regions in the world. One of the important issues of water management is assessment and determination of water requirement of plants. One of the main water management strategies in agriculture ...
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Introduction: Water is one of the most important factors limiting agricultural developments in arid and semi-arid regions in the world. One of the important issues of water management is assessment and determination of water requirement of plants. One of the main water management strategies in agriculture is to assess and determine the plants water requirement. Due to dry and semi-arid weather conditions in Iran the optimal use of water resources is crucial. Plants water requirements are the important parts of the hydrological cycle, and its precise estimation is essential for water budget studies, facilities, management, design of new irrigation systems and water resources management. The determination of behavior and characteristics non-reference vegetation compared to reference vegetation (grass) is the first step in estimating the evapotranspiration of crops. It is important to determine the crop factor in order to measure the water requirement of the crop at different stages of growth. The crop coefficient expresses the effects of crop and soil moisture on a non-reference plant species relative to the reference plant. Among the medicinal herbs, Hibiscus sabdariffa L. is an annual tropical and sub-tropical herbaceous plant belongs to Malvaceae family. Red calyces of Roselle are a source of anthocyanins (about 1.5 g/100 g dry weight), vitamin C and other antioxidants, such as flavonoids (gossypetin, hibiscetine, and sadderetine). Roselle is a medicinal plant that cultivated in Iran especially in Sistan and Baluchestan province. Regarding the long history of cultivation, and high consumption in Iran and the world so far, there has not been a scientific report about Roselle water requirement at different stages of growth. Therefore, this research was carried out with the aim of obtaining Roselle water coefficients and studying the pattern of its changes during the growing season in dry and semi-arid climates of Birjand using the lysimetric method.
Materials and Methods: To determine the Roselle crop coefficient, as a valuable medicinal herb, a lysimetric experiment was conducted in faculty of agriculture, Birjand University during the growing season in 2017. The lysimeters used for this experiment have 20 cm diameter and 16 cm in height. Three lysimeters used for sowing Roselle and three lysimeters used for reference plant. There are six orifices as a water drain in the bottom of each lysimeter. Floor of lysimeter covered by 5 cm granule layer, then filled with soil and cow decayed fertilizer mixture. In each lysimeter, 25 seeds of Roselle were sown. To determine potential evapotranspiration, 12 centimeters height grass was used as the reference plant. Water requirement of Roselle was determined by water balance method. The Roselle growth period was divided into four stages included initial (10% plant growth after emergence), development (between 10% plant growth and before flowering), middle (between early flowering and end flowering), and end (between end flowering and seed ripening). Weed control was achieved by hand hoeing during the growth season. Drainage water was measured by weighting and soil moisture hold at field capacity during the growth season.
Results and Discussion: Results of this study showed that Roselle plant in the initial stage due to slow growth and low transpiration have low Kc compared to middle and development stage. The average coefficient of Roselle was 1.26, 1.55, 1.81, and 0.96 in the initial, development, middle, and end stages respectively. Duration of growth stages for Roselle in Birjand region is 35, 75, 100, and 30 days after emergence. This results revealed an increasing trend from initial to development and middle stages. However, in the end stage of Roselle, Kc decreased. The result of this study showed that evapotranspiration of Roselle was 3819.57 mm whereas the reference plant evapotranspiration was 2420.3 mm. Due to water shortage in the arid and semi-arid region, this plant is not proper for sowing in this area.
Conclusions: According to the results of this study, the annual average evapotranspiration rate of the Roselle was 3819.57 mm whereas the reference plant evapotranspiration was 2420.3 mm. Therefore, the water requirement of Roselle is very high during growth period. Finally, according to the high water requirement and water deficient in Birjand, Iran; it seems that Roselle is not a proper plant for sowing in this area.
S. Jamali; H. Ansari; S.M. Zeynodin
Abstract
Introduction: Since the agriculture is the main water consumer, it is necessary to increase water use efficiency. As a management practice, deficit irrigation strategy is applied to cope with water shortages, especially during drought periods. A greenhouse experiment was conducted to investigate the ...
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Introduction: Since the agriculture is the main water consumer, it is necessary to increase water use efficiency. As a management practice, deficit irrigation strategy is applied to cope with water shortages, especially during drought periods. A greenhouse experiment was conducted to investigate the impact of water and salt stress on Quinoa plants (Chenopodium quinoa Willd.), Aly et al (2) showed that quinoa plants can tolerate water stress (50% FC) when irrigated with moderately saline water (T1 and T2, respectively). The results of some studies showed that Amaranth was the most responsive plant to water. Quinoa showed the best performance in the treatment with the upper-middle water level among the other evaluated species. Millet showed thermal sensitivity for cultivation in the winter, making grain production unfeasible; however, it showed exceptional ability to produce biomass even in the treatment with higher water deficit. Water stress can affect plants by reducing the plant height, relative growth rate, cell growth, photosynthetic rate, and the respiration activation. Cultivated plants have several mechanisms of adaptation to water deficit, but the responses are complex and adaptation is attributed to the ability of plants to control water losses by transpiration, which depends on the stomatal sensitivity and greater capacity of water absorption by the root system, among other factors. In PRD method, half of the root zone is watered and the other half is kept dry intermittently. The objective of this research was to study yield and yield components of Quinoa (Chenopodium quinoa Willd.) Titicaca cultivar, using PRD irrigation method in three growing bed, under greenhouse conditions.
Materials and Methods: This research was conducted to study the effects of water stress on yield and its components of Quinoa under the different growing beds in the experimental research greenhouse of Ferdowsi University of Mashhad during 2018. Titicaca cultivar of Quinoa was planted and experimental design was factorial, based on complete randomized design and three replications, included two irrigation managements (FI, full irrigation and PRD, partial root-zone drying method) and three levels of growing bed (S1, silty clay, S2 clay loam and, S3 sandy loam). Research station is located in north-east Iran at 36° 16' N latitude and 59° 36' E longitude and its height from sea level is 985 meters. The seeds of Quinoa were planted at a depth of 1.5 centimeters in the soil of each pot and were irrigated with tap water. Plants were harvested after 4 months and plant height, branches number, panicle number, thousand kernel weights, grain yield, biomass; steam, leaf, and panicle dry weight panicles were measured. Physical and chemical properties of irrigation water and soil were determined before the beginning of the experiment. The obtained data analyzed using the statistical software of SAS (Ver. 9.4) and the means were compared using LSD test at 5 % percent levels.
Results and Discussion: Results showed that the highest plant height (84.4 cm) was in FI treatment and the shortest plant height (82.5 cm) was in PRD treatment. The highest and the lowest 1000 kernel weights and grain yield were measured in FI (4.0 and 19.7 g per plant) and PRD (3.6 and 17.7 g per plant) treatments, respectively. With a 50 % reduction of water in PRD compared to FI treatment, 1000 kernel weights were decreased by 9.1%. Grain yield was decreased by 10.2% (changing from FI to PRD). The highest and the least grain yield (20.2 and 18.4 g per plant) were obtained in S1 and S2,3 soils, respectively. Silty clay soil with 1000 kernel yield of 4.12 g had higher than clay loam and sandy loam soil, which produced 3.78 g and 3.78 g, respectively.
Conclusion: In general, the effect of the PRD irrigation method on reducing water use in the greenhouse production of Quinoa was positive and recommendable. Silty clay soil with 1000 kernel yield of 4.12 g had higher than clay loam and sandy loam soil, which produced 3.78 g and 3.78 g, respectively.
L. Qasemi far; A. Golchin; F. Rakhsh
Abstract
Introduction: The accumulation of heavy metals in water, sediments, and soils has led to serious environmental problems. In recent years, several processes have been developed with the aim of reducing or recovering heavy metals from contaminated environments. Physical and chemical approaches are capable ...
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Introduction: The accumulation of heavy metals in water, sediments, and soils has led to serious environmental problems. In recent years, several processes have been developed with the aim of reducing or recovering heavy metals from contaminated environments. Physical and chemical approaches are capable of removing a broad spectrum of contaminants, but the main disadvantages of these methods lie in the increased energy consumption and the need for additional chemicals. In recent years, the processes such as bioleaching, biosorption, bioremediation, phytoremediation, and bio precipitation are all based on the use of microorganisms that have the ability to solubilize, adsorb, or precipitate heavy metals. Therefore, it is necessary to find some solutions to reduce the negative effects of heavy metals in soil. Materials and Methods: A factorial experiment was conducted in the greenhouse of the Faculty of Agriculture, the University of Zanjan, using a completely randomized design with three replications. In this experiment, the effects of different levels of soil cadmium (0, 5, 10, 25, and 50 mg/Kg) and soil inoculation (without inoculation and inoculation with Glomus mosseae, Glomus intraradices, Glomus mosseae + Rhizobium trifolii, Glomus intraradices + Rhizobium trifolii bacterium, Rhizobium trifolii, Glomus mosseae + Glomus intraradices and Glomus mosseae + Glomus intraradices + Rhizobium trifolii) on growth of berseem clover were assessed. Results and Discussion: The results of this study showed that the soil cadmium levels has a significant effect (p < 0.05 and p < 0.01) on fresh weights of aerial parts and roots, height, number of the plant in the pot, Fe, Zn and Cd concentrations in aerial parts and roots of berseem clover. The fresh weights of aerial parts and roots, height, number of the plant in the pot, Fe and Zn concentrations in aerial parts and roots of berseem clover decreased as the levels of soil cadmium increased. The lowest concentrations of iron and zinc were measured in treatment with 100 mg Cd/Kg. Also, Cd concentration in aerial parts and roots increased as the level of soil cadmium increased. The results of this experiment showed that soil inoculation with mycorrhizal fungi and Rihzobium trifolii had a significant effect (p < 0.05 and p < 0.01) on fresh weights of aerial parts and roots, height, number of plant per pot, Fe, Zn and Cd concentrations in aerial parts and roots of berseem clover. The inoculation of soil with mycorrhizal fungi and Rhizobium trifolii increased the fresh weights of aerial parts and roots, height and No. of plant per pot. The highest fresh weights of aerial parts and roots of berseem clover, height, and number of plant per pot were obtained in treatments co-inoculated with Glomus mosseae and Rhizobium trifolii. The highest and lowest concentrations of iron and zinc in aerial parts and roots of berseem clover were measured, respectively, for the treatment co-inoculated by Glomus mosseae and Rhizobium trifolii and control treatment (without inoculation). However, the opposite trends were found in Cd concentrations in the plant. The highest and lowest Cd concentrations in aerial parts and roots were measured in control treatment (without inoculation) and treatment co-inoculated by Glomus mosseae and Rhizobium trifolii (MT), respectively. Conclusion: Bioremediation and phytoremediation are considered as two very safe and necessary technologies which naturally occur in the soil by microbes and plants and pose no hazard to the environment and the people life. The procedure of bioremediation and phytoremediation can be simply carried out on site without initiating a major disruption of normal actions and threating the human life and the environment during transportation. Bioremediation and phytoremediation are used less than other technologies for cleaning-up the wastes and contaminated soils. Microorganisms and plants possess inherent biological mechanisms that enable them to survive under heavy metal stress and remove the metals from the environment. These microbes use various processes such as precipitation, biosorption, enzymatic transformation of metals, complexation and phytoremediation techniques of which phytoextraction and phytostabilization have been very effective. However, environmental conditions need to be adequate for effective bioremediation. The use of hyperaccumulator plants to remediate contaminated sites depends on the quantity of metal at that site and the type of soil. The results of this experiment showed that the Rhizobium trifolii and Glomus mosseae could be used to reduce the soil cadmium contamination. Also, the berseem clover is a hyperaccumulator plant for phytoremediation of cadmium in soils. According to the results of this study, co-inoculation of mycorrhizal fungus Glomus mosseae and Rhizobium trifolii can be recommended to improve the yield and uptake of micronutrients such as iron and zinc in cadmium contaminated soils.
Irrigation
Z. Sojoodi; H. Shokati; Y. Sojoodi; M. Mashal
Abstract
IntroductionThe constructive effects of green spaces on the quality and livability of the urban environment have been reported in many studies. Therefore, using methods that can accurately estimate the evaporation of transpiration in green space can help to reduce water loss. The purpose of estimating ...
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IntroductionThe constructive effects of green spaces on the quality and livability of the urban environment have been reported in many studies. Therefore, using methods that can accurately estimate the evaporation of transpiration in green space can help to reduce water loss. The purpose of estimating water demand for urban green space is also different from the purpose of determining water demand for an agricultural farm. In urban green space, the goal is to maintain good growth, appearance and acceptable plant health, while biomass production is the main goal on agricultural farms. Therefore, urban green space can typically be managed using an irrigation area that is less than the amount of water needed to produce agricultural products. Due to the limited water resources in arid areas, the use of less irrigation in urban green space can be desirable to save water consumption.Materials and MethodsThe Wucols method for estimating Water requirements in green space was developed by Castello et al. (4). They developed the Wucols water taxonomy guidelines for planting green space in California. The Wucols method estimates evapotranspiration in green space using reference evapotranspiration and a set of coefficients (Species factor, density factor and microclimate factor). PF method is the minimum acceptable irrigation for green space plants that emphasizes maintaining the beauty of the plant. In this method, the water required by green space plants is considered as a percentage of ET0 so as not to reduce their appearance and performance. In this approach, PF is a regulatory factor that is actually considered instead of Kc and multiplied by ET0, except that the emphasis is on the appearance of the plant and not on its optimal growth and yield. The IPOS method has been developed by the Government of South Australia for planning and managing water needs in public open spaces, especially sports lawns and amusement parks. In this method, the water requirement of grass in urban open space is calculated. In this method, plant transpiration evaporation (ETL) is calculated by multiplying reference transpiration evaporation factors (ET0) by grass vegetation coefficient (Kc) by plant stress factor (Kst).Results and DiscussionThe results showed that the highest rate of evapotranspiration obtained by Wucols method was 83.38 mm during 21 Jun-21 Jul. Also, the rate of transpiration evaporation during one year of the experimental period was estimated to be 556.5 mm. The results of estimation of transpiration evaporation by PF method also show the maximum amount of transpiration evaporation during 21 Jun-21 Jul and is 75.55 mm. The evapotranspiration rate during one year was estimated to be 505.9 mm. For the Ipos method, the highest rate of transpiration evaporation was estimated to be 36.38 mm during 21 Jun-21 Jul and 242.9 mm during the experimental period. Gross irrigation requirement is estimated by considering 70% irrigation efficiency for each month using all three methods. For the Wucols method, the gross irrigation need during one year was estimated to be 794.8 mm. For the PF method was 722.7 mm and for the IPOS method was 346.9 mm. According to the reported irrigation records for the study area, which is 900 mm per year, the Wucols method has the closest result to the irrigation records.ConclusionThe results showed that the Wucols method has the best and closest estimate according to the irrigation records of the study area. The gross irrigation requirement calculated by the Wucols method during a year is 794.8 mm, which is 12% less than the gross annual irrigation requirement of the studied green space. While PF and IPOS methods determined the amount of gross demand 20 and 62% less than the annual irrigation rate in the region, respectively. The results of this study show that the Wucols method for estimating the water requirement of plants in urban green space where there is a combination of different plant species is more reliable than the PF and IPOS methods due to the diversity of species, vegetation density and different climates.
Irrigation
H. Ramezani Etedali; F. Safari
Abstract
IntroductionEvaluation of plant models in agriculture has been done by many researchers. The purpose of this work is to determine the appropriate plant model for planning and predicting the response of crops in different regions. This action is made it possible to study the effect of various factors ...
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IntroductionEvaluation of plant models in agriculture has been done by many researchers. The purpose of this work is to determine the appropriate plant model for planning and predicting the response of crops in different regions. This action is made it possible to study the effect of various factors on the performance and efficiency of plant water consumption by spending less time and money. Since the most important agricultural product in Iran is wheat, so proper management of wheat fields has an important role in food security and sustainable agriculture in the country. The main source of food for the people in Iran is wheat and its products, and any action to increase the yield of wheat is necessary due to limited water and soil resources. Evapotranspiration is a complex and non-linear process and depends on various climatic factors such as temperature, humidity, wind speed, radiation, type and stage of plant growth. Therefore, in the present study, by using daily meteorological data of Urmia, Rasht, Qazvin, Mashhad and Yazd stations, the average daily evapotranspiration values based on the results of the FAO-Penman-Monteith method are modeled and the accuracy of the two methods temperature method (Hargreaves-Samani and Blaney-Criddle) and three radiation methods (Priestley-Taylor, Turc and Makkink) were compared with FAO-56 for wheat.Materials and MethodsThe present study was conducted to evaluate the accuracy and efficiency of the AquaCrop model in simulation of evapotranspiration and biomass, using different methods for estimation reference evapotranspiration in five stations (Urmia, Qazvin, Rasht, Yazd and Mashhad). Four different climates (arid, semi-arid, humid and semi-humid) were considered in Iran for wheat production. The equations used to estimate the reference evapotranspiration in this study are: Hargreaves-Samani (H.S), Blaney-Criddle (B.C), Priestley-Taylor (P.T), Turc (T) and Makkink (Mak). Then, the results were compared with the data of the mentioned stations for wheat by error statistical criteria including: explanation coefficient (R2), normal root mean square error (NRMSE) and Nash-Sutcliffe index (N.S).Results and DiscussionThe value of the explanation coefficient (R2) of simulation ET and biomass in the Blaney-Criddle method is close to one, which shows a good correlation between the data. The NRMSE and Nash-Sutcliffe values for both parameters and the five stations are in the range of 0-20 and close to one, respectively, which indicates the AquaCrop model's ability to simulate ET and biomass. On the other hand, the value of R2 in the Hargreaves-Samani method for biomass close to one, NRMSE in the range of 0-10 and Nash-Sutcliffe index is more than 0.5, which indicates a good simulation. The NRMSE index in the evaluation of ET and biomass wheat is excellent for the Blaney-Criddle method and about Hargreaves-Samani for ET is poor and for the biomass is excellent.The Turc method with NRMSE in the range of 0-30, explanation coefficient close to or equal to one and a Nash-Sutcliffe index of one or close to one can be used to simulate ET and biomass at all five stations. Also, for biomass simulation, Priestley-Taylor and Makkink methods have acceptable statistical values in all five stations.Based on the value of explanation coefficient (R2) of estimation ET and biomass wheat for radiation methods, the correlation between the data in all three radiation methods is high. Percentage of NRMSE index of Makkink method for wheat in ET evaluation in Qazvin station is poor category and in Urmia and Rasht is good and in Mashhad and Yazd is moderate and about biomass in all five stations (Qazvin, Rasht, Mashhad, Urmia and Yazd) is excellent category, the error percentage of Priestley-Taylor method for wheat in ET evaluation in Yazd station is good and the rest of the stations is poor, about biomass is excellent in all five stations (Qazvin, Rasht, Mashhad, Urmia and Yazd). The error rate of Turc method for wheat in ET evaluation in Urmia, Rasht and Mashhad stations is good and in Qazvin and Yazd is poor and about biomass is excellent in all five stations (Qazvin, Rasht, Mashhad, Urmia and Yazd).ConclusionAccording to the results obtained using Blaney-Criddle method with R2 value close to one, NRMSE in the range of 0-20% (excellent to good) and Nash-Sutcliffe index close to one and Turc method with R2 value close to one, NRMSE in the range of 0-10% (excellent) and Nash-Sutcliffe index close to one was showed a good accuracy of AquaCrop model in simulation of evapotranspiration and biomass with these methods of estimation of evapotranspiration compared to other methods.
Irrigation
F. Borzoo; H. Ramezani Etedali; A. Kaviani
Abstract
IntroductionClimate change is one of the most important issues in the world in the 21st century which affects various sectors of agriculture, forestry, water and financial markets, and has serious economic consequences (Reidsma et al., 2009). In recent years, the management of agricultural water consumption ...
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IntroductionClimate change is one of the most important issues in the world in the 21st century which affects various sectors of agriculture, forestry, water and financial markets, and has serious economic consequences (Reidsma et al., 2009). In recent years, the management of agricultural water consumption has always been considered as one of the important issues in water resources management. Koochaki and colleagues (Koochaki and Kamali, 2006) by evaluating the climatic indicators of Iran's agriculture showed that during the next 20 years, the average monthly temperature will increase in almost all regions of the country, and the increase in evaporation and transpiration is one of the most important consequences of this warming. Simulated climate parameters can be obtained through different general GCM atmospheric models. Due to the low spatial resolution of these models, its output should be downscaled using dynamic or statistical methods. Materials and MethodsThe LARS-WG model predicts meteorological variables for a period of time in the future by using a series of basic and fine-scale meteorological data, output of one of the GCM models. Research has shown that the LARS-WG model has the necessary accuracy for this task. Calculating the amount of evapotranspiration and yield of very complex plants are time-consuming and dependent on spending a lot of money and limited to the tests performed, the shortness of the test time and also the limitation in the number of scenarios that are checked by the test. Therefore, plant models are considered and evaluated by researchers. The AquaCrop model has demonstrated commendable accuracy in various regions of Iran and globally for forecasting plant growth, water consumption efficiency, and evapotranspiration requirements. These predictions hold significant potential for optimizing irrigation strategies across different agricultural settings. AquaCrop is one of the applied agricultural models that was obtained from the modification and revision of FAO publication No. 33 by prominent experts from all over the world. In this study, the values of green water footprint of winter wheat plant (Pishgam) were estimated in climatic conditions obtained from LARS-WG model and DKRZ database under scenarios 4.5 and 8.5 and at different planting dates (15 October, 1 November, 15 November, 30 November and 15 December), in the next 4 periods (2021-2040, 2041-2060, 2061-2080 and 2081-2100) and by Aquacrop model. Results and DiscussionThe results showed that if planting date is on October 15, in the climatic conditions obtained from the LARS-WG model and under scenarios 4.5 and 8.5, in all future periods, the footprint of green water will increase compared to its value in the base period, and if planting is the rest of the dates, in each of the next 4 periods, the average green water footprint will decrease compared to its value in the base period. The results obtained for the DKRZ database show that the green water footprint attained for the dates of cultivation and periods investigated in scenarios 4.5 and 8.5 does not have a particular trend. On the planting dates of October 15 and November 1 for the periods of 2061-2080 and 2081-2100, the green water footprint will decrease and on the other three dates (15 November, 30 November, and 1 November) for these periods, there will be an increasing trend. On 15 December, for the DKRZ database, in both scenarios defined for all periods, an increase in green water footprint compared to the base period is reported. However, in the period of 2081-2100 in scenario 8.5, a decrease compared to the base period will be observed. The highest amount of green water footprint in all these periods and models for the period 2041-2060 under the climatic conditions of the DKRZ database in scenario 4.5, if the planting date is 15 October, it is estimated that the amount of water consumed is equal to 4272 cubic meters per ton with a standard deviation of 5018 cubic meters per ton is predicted. The lowest footprint of green water for the period 2081-2100 under the climatic conditions obtained from the LARS-WG model in scenario 8.5, if the planting date is on 15 December, is reported to be 232 tons per hectare with a standard deviation of 52.3 tons per hectare.
Hojjat Ahmadi; Mohammad Hemmati; Mehdi Motallebian
Abstract
Introduction: Coastal aquifers are major source of freshwater in many parts of the world. Saltwater intrusion is a serious environmental issue since 80% of the world’s population live along the coast and utilize local aquifers for their water supply.Under natural conditions, these coastal aquifers ...
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Introduction: Coastal aquifers are major source of freshwater in many parts of the world. Saltwater intrusion is a serious environmental issue since 80% of the world’s population live along the coast and utilize local aquifers for their water supply.Under natural conditions, these coastal aquifers are recharged by rainfall events, and the recharged water flowing towards the ocean would prevent saltwater from encroaching into the freshwater region. However, over exploitation of coastal aquifers has resulted in reducing groundwater levels (hence reduced natural flow) and this has led to severe saltwater intrusion. Saltwater intrusion from the sea into below the freshwater of aquifer impairs the quality of these resources. Cause ofthe complexity of saltwater intrusion issues and generally they cannot be solved analytically, so numerical methods can be useful tools for simulation and prediction of salt water intrusion.
Materials and Methods: CTRAN/W is a finite element software product that can be used to model the movement of contaminants through porous materials such as soil and rock. The comprehensive formulation of CTRAN/W makes it possible to analyze problems varying from simple particle tracking in response to the movement of water, to complex processes involving diffusion, dispersion, adsorption, radioactive decay and density dependencies. SEAWAT is a three-dimensional variable density groundwater flow and transport model developed by the USGS based on MODFLOW and MT3DMS. SEAWAT is based on MODFLOW and MT3DMS. SEAWAT includes two additional packages: Variable-Density Flow (VDF) and Viscosity (VSC).In this study, the precision of CTRAN / W and SEAWAT models to simulation and prediction of saltwater wedge were investigated in three states: a) steady state salt-wedge data observed underdifferenthydraulic gradient conditions; b) transient salt-wedge data observed underintruding-wedge conditions; and c) transient salt-wedge data observed under receding-wedge conditions. Both models were initially calibrated and then the models were performed for the above conditions. The simulation results of the two models with the experimental results of Goswami and Clement (2007) have been compared. For comparing the measured data and simulated data, statistical indicators were used: root-mean-square error (RMSE), a measure of Nash-Sutcliffe (CE), the Correlation Coefficient (R^2), the ratio of difference (r) and the General Standard Deviation (GSD).
Results and Discussion: In this study, the precision of CTRAN / W and SEAWAT models to predict saltwater wedge wasinvestigated. At first step, both models were calibrated and the best values for longitudinal and transverse dispersion were obtained 0.5 and 0.05, respectively.Then simulation was performed with both models for all three modes(a- steady state salt-wedge data observed underdifferenthydraulic gradient conditions; b- transient salt-wedge data observed underintruding-wedge conditions; and c- transient salt-wedge data observed under receding-wedge conditions). The results showed thatCTRAN/W and SEAWAT models have high precision for simulation of position and movement of saltwater wedge in steady state with average of root mean square error (RMSE) equal to 1.05 and 1 cm, respectively and Both models have a higher estimate than the actual value for a steady state. As well as for transient state under the underintruding-wedge conditionsCTRAN/W and SEAWAT models have high precisionwith average of root mean square error (RMSE) equal to 0.65 and 0.44 cm, respectively and other statistical indicators were acceptable. The results of prediction of position and movement of saltwater wedgeunder receding-wedge conditionswith average of root mean square error (RMSE) equal to 0.54 and 0.56 cm, respectively provided acceptable estimates of both models. Finally, in order to determine the accuracy of the models in estimating the flow rate from the source of fresh water to the source of salt water, a comparison was made between the results of the models and the laboratory data, which showed that The CTRAN/W revealed appropriate estimation of amount of transferring discharge from freshwater reservoir to saltwater reservoir in compared with SEAWAT model. In general, according to statistical indicators, the results of both models were acceptable
Conclusion: The results showed thatCTRAN/W and SEAWAT models have high precision for simulation and prediction of position and movement of saltwater wedge with average of root mean square error equal to 0.67 and 0.58 cm (less than 10% of the average of measured data), respectively. The CTRAN/W revealed appropriate estimation of amount of transferring discharge from freshwater reservoir to saltwater reservoir in compared with SEAWAT model. In general, according to statistical indicators, the results of both models were acceptable.
F. Ahmadi
Abstract
Introduction: Surface water has always been one of the most essential pillars of water projects and, with modeling and predicting the river flow, in addition to the management and utilization of water resources, it is possible to inhibit the natural disasters such as drought and floods. Therefore, researchers ...
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Introduction: Surface water has always been one of the most essential pillars of water projects and, with modeling and predicting the river flow, in addition to the management and utilization of water resources, it is possible to inhibit the natural disasters such as drought and floods. Therefore, researchers have always tried to improve the accuracy of hydrological parameters estimation by using new tools and combining them. In this study, the effect of seasonal coefficients and mathematical methods of signal analysis and signal processing on wavelet transform to improve the performance of the Gene Expression Programming (GEP) model were discussed.
Materials and Methods: In the present study, for the prediction of the monthly flow of Ab Zal River, the information of Pol Zal hydrometric station in period 1972 to 2017 was used. In the next step, different input patterns need to be ready. To this purpose, the data are presented in three different modes: (a) the use of flow data and considering the role of memory up to four delays; (b) the involvement of the periodic term in both linear (?-GEP) and nonlinear (PT-GEP) states, and (c): data analysis using the Haar wavelet, Daubechies 4 (db4), Symlet (sym), Meyer (mey), and Coiflet (coif), was done in two subscales, prepared, and introduced to the GEP model. To better analyze the effect of mathematical functions used in the GEP method, two linear modes (using Boolean functions including addition, multiplication, division, and minus) and nonlinear (including quadratic functions, etc.) were considered. The wavelet transform is a powerful tool in decomposing and reconstructing the original time series. Wavelet function is a type of function that has an oscillating property and can be quickly attenuated to zero. Modeling was done based on 80% of recorded data (432 months) and the validation was done based on the remaining 20% (108 months). To evaluate the performance of each of models, statistical indices such as mean square error (RMSE), mean absolute error (MAE), and correlation coefficient (R) were used.
Results and Dissection: The results of linear and nonlinear GEP models showed that in both cases, the four-delay model achieved the most accuracy in river flow prediction. Still the performance of nonlinear GEP model according to RMSE (4.093 (m3/s)), MAE (2.782 (m3/s)) and R (0.660) were better than another, respectively. In the next step, the periodic term was added to the model inputs. Based on the results, the PT-GEP model with M4 pattern had the lowest error, the highest accuracy and was able to reduce the RMSE index by 8%. Then, in the third step, the river flow data were divided into approximate subdivisions and details using five wavelet functions. The most appropriate level of analysis based on the number of data was considered as number three. The results of the W-GEP modes showed an excellent performance of this method so that the model was able to reduce the RMSE statistics with 48.6%, 41.2%, and 31.1% compared to the L-GEP, NL-GEP and PT-GEP methods, respectively. Also, the best performance of the W-GEP model with the Symlet wavelet and the decomposition level of one had the highest accuracy (R=0.847) and the lowest error (RMSE =2.898 (m3/s) and MAE =1.745 (m3/s) among all models (35 models) such as linear and nonlinear, seasonal and non-seasonal and wavelet hybrid models.
Conclusion: Based on the results, it can be concluded that the overall use of data preprocessing methods (including seasonal coefficients and wavelet functions) has improved the performance of the GEP model. However, the combination of wavelet functions with the GEP model has significantly increased the accuracy of the modeling. Therefore, it is recommended as the most suitable tool for river flow forecasting.
Irrigation
H. Ojaghlou; F. Ojaghlou; Mohammad Mahdi Jafari; Farhad Misaghi; Bijan Nazari; Esmaeil Karami Dehkordi
Abstract
Introduction
Over the last years, long-term average rainfall has experienced a meaningful decrease (from 250 to 206 mm per year) leading to continuous drought in Iran. In addition, population growth and increasing demand for food put more pressure on the limited available water resources. Thus, the ...
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Introduction
Over the last years, long-term average rainfall has experienced a meaningful decrease (from 250 to 206 mm per year) leading to continuous drought in Iran. In addition, population growth and increasing demand for food put more pressure on the limited available water resources. Thus, the quantitative and qualitative improvement of agricultural products become a necessity. There is 640,000 hectares of alfalfa cultivated land, standing for 5.4% of the total cultivated area. One of the most basic obstacles in these farms is the unsuitable model of water consumption management. Previous studies were conducted with the aim of evaluating the mutual effects of different treatments in controlled plots. Nonetheless, there is a need for large-scale investigations to monitor and improve water productivity in agricultural systems. In this research, the focus was on irrigation management and optimizing irrigation timing as a potential solution to enhance water productivity, considering the fixed irrigation cycles and traditional use of available water resources. The study began by assessing the current water productivity in 11 alfalfa farms located across four regions in Zanjan province, ensuring a suitable spatial distribution. Subsequently, the impact of irrigation management, particularly the adjustment of irrigation timing, was evaluated to determine its effectiveness in improving water productivity in these farms.
Materials and Methods
Eleven alfalfa farms, covering a total area of 28 hectares, were initially selected in the agricultural lands of Zanjan province. The majority of these farms were equipped with sprinkler irrigation systems. From these 11 farms, two specific farms were chosen to implement the proposed methods aimed at improving water productivity. These selected farms served as experimental sites where the irrigation management techniques were applied and evaluated. Improvement solutions were mainly focused on irrigation management. Each farm was divided into two parts; one part with real conditions (farmers' management) and the second one with controlled conditions. In the controlled treatments, irrigation management was implemented through optimization of irrigation time. A nutritional program was also prepared according to the soil quality of the fields and applied in the controlled treatments. In each farm, basic information such as area, physical and chemical properties of soil and water quality were determined. Irrigation information (such as inflow discharge and irrigation schedule) was measured and determined at least three times during the cropping season. Soil moisture were measured before and after irrigation in order to calculate the water application efficiency. The amount of harvested product and production costs were obtained at the end of the cropping season through measurements and interviews with farmers. In this research, the indicators including the volume of irrigation water, the water use efficiency, and the physical and economic efficiency of water have been calculated to analyze the water productivity.
Results and Discussion
The volume of irrigation water in alfalfa farms was measured as 14250 m3/ha on average (with the lowest and highest consumption values of 9849 and 20576 m3/ha, respectively). The average of irrigation water in farms with surface irrigation systems equals to 17,806 and in farms equipped with sprinkle irrigation systems is about 13,460 m3/ha. While the net water requirement of alfalfa in study area was 7160 to 7290 m3/ha. The minimum and maximum values of water application efficiency were 38.3 and 82%, respectively, with average of 64%. The average of application efficiency in surface and sprinkle irrigation systems were obtained 50 and 67%, respectively. The measured alfalfa yield ranged from a minimum of 6.5 ton/ha to a maximum of 14.1 ton/ha, with an average yield of 10.4 ton/ha. After implementing the revised irrigation program in the controlled plots, the harvested water decreased by an average of 49.5%. It was observed that the irrigation schedule in most farms followed a traditional and estimated pattern, with the depth of irrigation water in the middle of the growing season exceeding the net irrigation requirement. The water use efficiency (WUE) values varied between 0.42 and 1.28 kg/m3, with a minimum value of 0.42 kg/m3 and a maximum value of 1.28 kg/m3. The average WUE was calculated as 0.79 kg/m3. Analyzing the correlation between water consumption and the water use efficiency index revealed a decreasing trend. As the volume of irrigation water increased, the water use efficiency index experienced a decline. Specifically, an increase of 1000 m3 in irrigation water resulted in a decrease of 0.04 kg/m3 in the water use efficiency index. The implementation of the corrected irrigation program and appropriate to the water demand led to an increase of the mentioned index by 72%.
Conclusion
The lack of proper irrigation programs that consider climatic conditions and the actual needs of the alfalfa plant was identified as a key factor contributing to high water consumption in the farms. Additionally, the inefficient selection and design of the irrigation system led to lower irrigation efficiency than expected. Despite the majority of farms being equipped with sprinkle irrigation systems, the harvested water did not decrease significantly due to inadequate water management practices. These factors ultimately resulted in a decline in both physical and economic productivity indicators in the alfalfa farms. However, the results of the study highlighted that implementing corrected irrigation management, particularly through modifications to the irrigation timing, can lead to a significant decrease in volume of irrigation water and an improvement in both physical and economic productivity.
Irrigation
Sh. Nourinezhad; M.M. Rajabi; T. Fathi
Abstract
Introduction Simulation of quantity and quality of surface runoff in mountainous watersheds is one of the most challenging topics in modeling due to its unique features, such as unusual topography and complex hydrological processes. One of the lesser-known aspects of modeling such catchments is ...
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Introduction Simulation of quantity and quality of surface runoff in mountainous watersheds is one of the most challenging topics in modeling due to its unique features, such as unusual topography and complex hydrological processes. One of the lesser-known aspects of modeling such catchments is the uncertainty analysis of water quality predictions, especially about the vital phosphorus parameter. Phosphorus is one of the important quality variables in water, and its increase in water resources can cause eutrophication phenomena in streams and reservoirs of dams. Due to the importance of the phosphorus parameter and the fact that water quality modeling has not been employed in the Karaj catchment area so far, in this research, total phosphorus has been modeled as a water quality parameter along with the flow and sediment discharge. This study aims to identify the most sensitive parameters of the model to flow, sediment, and total phosphorus discharge and calibrate, validate and analyze the parametric uncertainty of the SWAT model in predicting these three variables in a mountainous catchment. The case study was the catchment area of the Karaj River upstream of Bileqan pond, which is one of the mountainous watersheds in Iran. There are two critical water structures along the Karaj River, namely Amirkabir dam and Bilqan pond. Amirkabir dam (Karaj) is a multi-purpose project that is constructed to supply drinking water to Tehran and regulate water for irrigation and agriculture in the suburbs of Karaj. The Bileqan pond is also the essential point of supply and transfer of drinking water in Tehran. Given the importance of this region in supplying water for different uses, providing a calibrated model for quantitative and qualitative variables of water can be the basis for decisions to apply future management scenarios in this basin.Materials and Methods The case study was the Karaj River catchment area upstream of Bilqan Basin, which with an average height of 2880 meters, is one of the mountainous areas located in the Alborz Mountains. This basin with an area of 1076 square kilometers in the north, includes parts of Mazandaran province. In the east and south of the catchment area includes parts of Tehran province and most of it is located in Alborz province. The average annual temperature and rainfall in this basin are 12.1 °C and 480 mm, respectively, and the average of 117 glacial days during the year is observed in this area. The long-term daily data of synoptic stations adjacent to the study area from the beginning of 1998 to the end of 2018 (21 years in total) was introduced to the model. Also, daily data of relative humidity, rainfall, minimum and maximum temperature, solar radiation hours, and wind speed as meteorological parameters measured at stations in the study area were introduced to the model. It should be noted that there was a lot of missing data in meteorological information, especially for daily temperature data. In addition to the above information, daily flow data discharged from Amirkabir dam and technical specifications of the dam were introduced to the model. In addition, orchard management information, including irrigation periods and information related to phosphate fertilizers used in regional orchards, were presented to the model. The global sensitivity analysis method was used to determine the sensitive parameters of the model. Furthermore, the SUFI2 algorithm was used in SWAT_CUP software to calibrate and analyze the parametric uncertainty of the SWAT model. This algorithm quantifies the output uncertainty by 95% prediction uncertainty boundaries.Results and Discussion According to the results of sensitivity analysis, the parameters Baseflow alpha-factor (ALPHA_BF), Manning’s “n” value for overland flow (OV_N), and Precipitation Laps rate (PLAPS) were the most sensitive parameters to flow, sediment, and total phosphorus, respectively. The best Nash-Sutcliffe (NS) coefficients for runoff, sediment, and total phosphorus simulation obtained in all stations and after full calibration and validation periods were equal to 0.76, 0.56, and 0.92, respectively. Simulation of the peak points of the diagram of all three quantities was also associated with increased uncertainty and decreased model prediction accuracy, but due to the placement of more than 70% of the measured runoff and sediment values and nearly 60% of the measured total phosphorus values in the prediction uncertainty boundaries generated by SUFI2 algorithm the final value of the parameters used in the calibration process can be appropriate for simulating future scenarios in similar mountain catchments. The main weakness of the model is simulating the peak points of flow and sediment discharge. In the case of flow and sediment discharge, the liability of modeling can be generalized due to the lack of accurate prediction of the snowmelt inflow to the river in spring, which begins to increase in February and reaches the peak point in May. A considerable number of missing data in meteorological stations can effectively reflect the lack of accurate model prediction at the peak points. In this region, missing daily temperature data compared to other meteorological parameters has been significant. The dependency of the SWAT model on many experimental and quasi-experimental models such as SCS-CN and MUSLE can be another factor affecting the weakness in predicting the peak points of the sediment discharge, as well.Conclusion According to the uncertainty analysis results, most of observed flow, sediment and total phosphorus discharge values were within the uncertainty prediction boundaries generated by the SUFI2 algorithm. The NS coefficient for all three variables has met the satisfactory modeling threshold. Therefore, it seems that the sensitive parameters identified and used in the calibration process in this study and their final values can be appropriate for modeling future scenarios for this study area and similar mountain catchments. One of the limitations of the present study was a large number of missing data in meteorological stations, especially for the temperature variable. Thus, providing required measured meteorological data to the model may emhance the simulation, especially at peak points.
Irrigation
R. Saeidi
Abstract
IntroductionSalinity stress causes reduction of crop evapotranspiration (ETc) and yield. An unsuitable seed planting date can result in negative atmospheric effects, such as temperature stress, during the crop growth period. Consequently, salinity stress and unfavorable climatic conditions during this ...
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IntroductionSalinity stress causes reduction of crop evapotranspiration (ETc) and yield. An unsuitable seed planting date can result in negative atmospheric effects, such as temperature stress, during the crop growth period. Consequently, salinity stress and unfavorable climatic conditions during this period interact to reduce crop water uptake. The mentioned conditions effect, should be investigated on crop transpiration amount (actual water requirement) and soil surface evaporation losses. This research results will have a determinative effect on the optimal use of water resources. Materials and MethodsThe studied crop in this research was S.C 704 maize. The crop planting was conducted in mini-lysimeters with a diameter of 40 cm and a height of 70 cm. The experiment factors included soil salinity stress and seed planting date. Soil salinity treatments were selected at four levels of 1.7 (S1), 2.5 (S2), 3.8 (S3), 5.9 (S4) dS.m-1. Seed planting date included of 5 May (P1), 25 May (P2) 14 June (P3) and 4 July (P4). Crop growth period for all planting date treatments, was 140 days (FAO-56). Experiment was conducted as factorial based on completely randomized design with 16 treatments and three repetitions. Variance analysis and average comparison of data was done by SPSS software and with Duncan's multi-range test (at 5% probability level). Daily soil moisture amount was measured by a moisture meter. Irrigation time was determined for without water stress conditions. Readily available water limit was determined 0.4. Irrigation volume was calculated according to soil moisture deficit (up to FC limit), soil density, root depth, leaching fraction and soil surface area. To separate the evapotranspiration components, all treatments were performed in two series of mini-lysimeters. In the first series, soil moisture reduction was related to crop evapotranspiration amount. But in the second series, the plastic mulch was placed on soil surface. Soil moisture reduction in the second series, was only related to crop transpiration amount. Difference of data in the first and second series was equal to the evaporation amount. Linear function of Mass and Hoffman (1977) was used as the function of evapotranspiration-salinity, transpiration-salinity, and evaporation-salinity. Results and DiscussionAs salinity increased from S1 to S4 levels, evapotranspiration, transpiration, and evaporation amounts were measured on the planting dates P1, P2, P3, and P4. The measurements were as follows:Evapotranspiration (mm): 619-548 (P1), 621-549 (P2), 624-547 (P3), and 625-544 (P4)Transpiration (mm): 429-309 (P1), 421-295 (P2), 418-281 (P3), and 412-265 (P4)Evaporation (mm): 190-239 (P1), 200-254 (P2), 206-266 (P3), and 213-279 (P4)These ranges reflect the measured amounts for each variable under increasing salinity levels across the different planting dates. Under the influence of salinity stress, soil water potential decreases, leading to a reduction in water uptake by the crop and subsequently decreased crop transpiration. As a result of this reduction in crop water uptake, the remaining water in the soil is utilized for evaporation. In S4 level and on dates of: P1, P2, P3 and P4, crop transpiration portion decreased to 12.9%, 14.1%, 15.6% and 17.2%, respectively, and evaporation portion increased to the same amount. By adjusting the seed planting date to optimize the utilization of favorable atmospheric conditions during crop growth stages, the increase in the portion of evaporation is prevented. In initial stage of growth period, only 0 to 10% of soil surface is covered by crops (FAO-56) causing the evaporation component to have a dominant portion in the crop evapotranspiration parameter. As a result, placing of initial growth stage in warm days of year caused an increase in evaporation losses. It seems that S1P1 treatment was the optimal condition for transpiration increase and evaporation decrease. The estimated functions showed that (in salinity stress conditions) crop transpiration decreased more than ETc. Therefore, the transpiration rate should be considered as the crop's net water requirement instead of ETc (crop evapotranspiration). According to the Mass-Hoffman function, under stress conditions, the decreasing slope of transpiration and evapotranspiration and the increasing slope of evaporation become more pronounced. For instance, in planting dates of P1, P2, P3, and P4, for each unit (dS.m-1) of increase in soil salinity, the evapotranspiration rates decreased by 2.51%, 2.82%, 3.3%, and 3.65%, respectively. Similarly, the transpiration rates decreased by 6.1%, 7.34%, 8.42%, and 9.2%, respectively, while the evaporation rates increased by 5.5%, 6.7%, 7%, and 7.82%. ConclusionSalinity and atmospheric temperature stresses had interaction effects on evapotranspiration and components rates. Postponing the seed planting date and not utilizing optimal weather conditions, especially during spring, can lead to damage to transpiration, which is a favorable aspect; however it is unfavorable in evaporation,. Therefore, in irrigated crops, it is advisable not to plant seeds during the warm months of the year, especially in July and August. Consequently, by controlling soil salinity and selecting the appropriate planting date, water can be optimally utilized.
majid arabfard; ali shahnazari; Mirkhaleg Ziatabar Ahmadi
Abstract
Introduction: The use of commonly known irrigation methods (especially surface irrigation or even irrigation under pressure) is limited due to the specific physical characteristics of keeping moisture and lowering the water holding capacity. In sandy beaches or desert plains (called sandstones) with ...
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Introduction: The use of commonly known irrigation methods (especially surface irrigation or even irrigation under pressure) is limited due to the specific physical characteristics of keeping moisture and lowering the water holding capacity. In sandy beaches or desert plains (called sandstones) with mentioned physical characteristics. lack of nutrients necessary for plant growth restrict the commonly known irrigation application. Gravity Drip Irrigation (GDI) is a new method that avoids the use of extra energy (pumping station). The total amount of pressure head required by the GDI for fields with a maximum area of 100 hectares is between 1 and 3 meters height. The main purpose of GDI is to reduce the required pressure by the drippers. The utilization of drip tape irrigation as one of the GDI methods has been considered in Iran in recent years. Several studies have been carried out in this regard, each of which pursues specific goals. The GDI benefits includes: reducing water consumption per unit area while increasing the moisture content of the plant root zone, increasing water use productivity, the possibility of irrigation in uneven terrain, reducing weed, pests and diseases damage, ease of distribution of fertilizer, requires lower pressure which consequences to lower cost and energy in the production process. Pot irrigation method is one of the most effective methods for irrigating in these conditions with rough terrain, coarse texture and light soils with high water penetration and saline water which surface irrigation methods normally cannot be used. The application of methods that can provide optimal irrigation conditions for such soils with their specific characteristics, such as delay in water infiltration and low outflow, can lead to improved physical conditions and optimal management of these soils.
Materials and Methods: This research was carried out in the first four months of 2016 in a sandy field located in a part of the agricultural land of Jihad-e-Tavan Co. in Kashan city. In this research, according to the custom of the region, the local watermelon of Sunbek district in Aran and Bidgol city, were chosen as a study plant. A factorial design in a completely randomized block including three main treatments of localized irrigation and three irrigation treatments (total of nine treatments) with three replications, as well as furrow irrigation treatment as control were applied. In each row, 12 plants were planted with a distance of one meter on a row and three meters between rows, on an area of 1080 (36×30) square meters.
Results and Discussion: The role of pulsed irrigation cycle in providing favorable growth conditions and consequently increasing yield can be achieved by comparing the performance of localized treatments and control treatment. The Duncan's test results for number of fruits and yield comparison using selected irrigation methods showed that there was no significant difference in the number of watermelons and their weight at the probability level of 1% and 5%. For different irrigation methods, there was a significant difference between yield and number of watermelons at same probability level. By the end of the 110 days after planting, the yield in furrow irrigation, pot irrigation, drip tape and GDI were 11426, 1224, 7527 and 11457 kg/ha, respectively. The improvement percentage of yield in comparison with the control treatment, were 85%, 1034% and 1626% in pot irrigation, drip tape and GDI, respectively. This research results revealed that the ratio of water used to yield in furrow treatments, pot, drip tape and GDI were 1.18, 5.55, 0.9 and 0.09 m3/kg. Also, considering the amount of water used for each treatment, 49.7 and 23.4 percent decrement in applied water in drip tape and GDI and 371.2 percent increment in applied water in pot irrigation observed per kilograms of watermelon produced compared to the conventional irrigation method (furrow irrigation). Highest water productivity index achieved in GDI among the four methods studied, as much as 1.7 kg of watermelon produced per cubic meter of water.
Conclusion: In this study, the efficiency of more than 80% achieved in furrow irrigation in sandy soil. Improvement in irrigation efficiency in these soils can be achieved by managing parameters involved like furrow length, time and irrigation discharge. The results showed that with the amount of water consumed equal to 6790 cm3/ha in each of the gravity localized irrigation methods and 13452 cm3/ha in the control treatment, the watermelon yield in pot irrigation, gravity drip, drip tape and furrow irrigation methods were 1224, 11457, 7527 and 11426 kg/ha, respectively, and the water productivity index was equal to 0.2, 1.7, 1.1 and 0.8 kg/ha.m3, respectively. In comparison with the one-day irrigation interval, using pulses irrigation in localized irrigation, irrigation efficiency increased from 87% to 98%. In general, by using localized irrigation in comparison with furrow irrigation in sandy soils, in addition to increasing water productivity, high yield could be achieved in plants like watermelon.
R. Ghobadian; H. Shekari
Abstract
Introduction: The concentration changes of suspended load along the river reach and the contributing factors are of importance for hydraulic and environmental engineers. The first step to calculate the concentration of suspended sediment load is determining the flow hydraulic characteristics along a ...
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Introduction: The concentration changes of suspended load along the river reach and the contributing factors are of importance for hydraulic and environmental engineers. The first step to calculate the concentration of suspended sediment load is determining the flow hydraulic characteristics along a river reach. Although most of flow in nature are unsteady, the quasi-steady flow condition was considered to be simple in this study and the water surface profile along the river reach with irregular cross sections was calculated by standard step-by-step method. In order to calculate suspended sediment load under non-equilibrium condition, the advection-diffusion equation with source term was numerically solved. In the present sediment model, ten discretization methods, five relations for calculating capacity of suspended sediment load, eight relations for diffusion coefficients and eight relations to calculate particle fall velocity were used and their effects on suspended sediment distribution along 18480 m of Gharasoo river were investigated.
Results and Discussion: The HEC-RAS model output was used to calibrate the present hydraulic model. The models were run with the conditions as same as Manning roughness coefficient and river geometry conditions. The results showed that the calculated water surface profile along the river reach by two models are completely overlapped each other. In other words, the present model has a very good accuracy to predict the water surface profile in the river reach. As most commercial 1-D models (same as HEC-RAS) only consider the equilibrium condition for sediment transport and the bed or total load sediment, comparing the results of present sediment model with them seems not to be reasonable. Therefore, to validate the present suspended sediment model and finding the best method of discretization, an especial shape concentration hydrograph was introduced to the present model as input hydrograph and the model was run when the source term has been deleted deliberately. The volume below the input concentration hydrograph and calculated hydrographs in different cross sections was compared to each other. Comparing the hydrographs showed that the maximum error in calculating the volume of concentration hydrograph with the input hydrograph was 0.029% implying that the model satisfies the conservation laws as well as reliable programing. Among ten discretization methods, the best method for discretization of the advection-diffusion equation was Van Leer's method with the least error compared to other methods. After validating the model, effect of five relations for calculating capacity of suspended sediment load was investigated. The results showed that using the Wife equation estimated the amount of suspended sediment higher than other equations. The Toffaletti equation also estimated suspended sediment load lower than other equation. Among eight particle fall velocity formulas, Stokes relationship estimated the fall velocity larger than other equations. Hence, the Stokes equation application decreases the possibility of suspending the sediment particles. However, employing Van Rijn and Zanke relationships resulted in a greater suspended sediment load distribution along the river reach. Among eight relationships for diffusion coefficients, Elder and the Kashifipour - Falconer equations exhibited the lowest and the highest amount of diffusion in the concentration hydrograph, respectively. Furthermore, the calculated suspended sediment concentration under non-equilibrium conditions was 11.7 % higher than that under equilibrium conditions along the river reach.
Conclusion: Most 1-D numerical models only simulate the bed and total loads sediment transport under equilibrium condition while sediments are transported under non-equilibrium conditions in nature. Sediment transport under non- equilibrium conditions may be greater or lower than the equilibrium condition known as the capacity of sediment transport. In this research, a numerical model was developed to simulate the suspended sediment transport in a river reach under non-equilibrium conditions. The amount of suspended sediment concentration was calculated for each sediment grain size. The results showed that the distribution of suspended load along the river reach is not significantly sensitive to the fall velocity relations while the type of sediment transport equation affected the suspended sediment transport concentration. The concentration of suspended sediments for non-equilibrium conditions was also 11.7% higher than the concentration of sediments in equilibrium condition.
H. Sadeghi; ali mohammad akhondali; meisam haddad; M. Golabi
Abstract
Introduction: Accurate water demand modeling for the city is very important for forecasting and policies adoption related to water resources management. Thus, for future requirements of water estimation, forecasting and modeling, it is important to utilize models with little errors. Water has a special ...
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Introduction: Accurate water demand modeling for the city is very important for forecasting and policies adoption related to water resources management. Thus, for future requirements of water estimation, forecasting and modeling, it is important to utilize models with little errors. Water has a special place among the basic human needs, because it not hampers human life. The importance of the issue of water management in the extraction and consumption, it is necessary as a basic need. Municipal water applications is include a variety of water demand for domestic, public, industrial and commercial. Predicting the impact of urban water demand in better planning of water resources in arid and semiarid regions are faced with water restrictions.
Materials and Methods: One of the most important factors affecting the changing technological advances in production and demand functions, we must pay special attention to the layout pattern. Technology development is concerned not only technically, but also other aspects such as personal, non-economic factors (population, geographical and social factors) can be analyzed. Model examined in this study, a regression model is composed of a series of structural components over time allows changed invisible accidentally. Explanatory variables technology (both crystalline and amorphous) in a model according to which the material is said to be better, but because of the lack of measured variables over time can not be entered in the template. Model examined in this study, a regression model is composed of a series of structural component invisible accidentally changed over time allows. In this study, structural time series (STSM) and ARMA time series models have been used to model and estimate the water demand in Isfahan. Moreover, in order to find the efficient procedure, both models have been compared to each other. The desired data in this research include water consumption in Isfahan, water price and the monthly pay costs of water subscribers between 1388 and 1390. In structural time series model, the model was generated by entering the invisibility part of the process and development of a state-space model, as well as using maximum likelihood method and the Kalman-Filter algorithm.
Results and Discussion: Given the value of the test statistic ADF, with the exception of changing water use variables with a time difference of the steady rest. Superpopulation different modes of behavior were assessed based on the demand for water. Due to the likelihood ratio statistic is most suitable for the parameters, was diagnosed the steady-state level of randomness and the slope. Price and income elasticities of demand for water, respectively -0.81 and 0.85 shows that water demand is inelastic with respect to price and income and a lot of water is essential. Identify the nature of the request of one of the most important results in estimated water demand in the urban part of the state space time series structure and patterning methods, as an Alternative for variable is Technology preferences use. The model is estimated for the city's water demand time series model, respectively ARMA (3,1). Model performance metrics to compare the structural time series and time series ARMA, the result represents a structural time series model based on the fact that all the performance criteria in this study outperformed the ARMA model to forecast water city demand in the Isfahan.
Conclusion: Of a time series model structure to model ARMA in this research is to estimate the model and predict the number the less time is required, and also can be used for modeling of other variables (such as income and price) to this is helping to improve the models. Also, in ARMA time series the best model for data was selected according to the Schwarz Bayesian and Akaike criterion. Results indicate that the estimation of water demand using structural time series method is more efficient than when ARMA time series model is applied. Therefore, structural time series model can be used as an efficient tool for managers and planners in the Management Departmentsin order to forecast water demand. Used was for compare the performance of these two models of standard root mean square error (RMSE), mean absolute error (MAE) and mean absolute percentage error (MAPE).
shahrzad gharcheh; M. Delbari; F. Ganji
Abstract
Introduction: An appropriate water resources management and planning is necessary due to the scarcity of water resources and rapidly growing world population. In this regard, selecting appropriate methods for irrigation is one of the most important issues. Drip irrigation is a recent advanced irrigation ...
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Introduction: An appropriate water resources management and planning is necessary due to the scarcity of water resources and rapidly growing world population. In this regard, selecting appropriate methods for irrigation is one of the most important issues. Drip irrigation is a recent advanced irrigation method in which fertilizers can be efficiently applied along with irrigation water. Drip fertigation, however, can potentially cause clogging of emitters. Various factors such as clogging increase manufactures’ coefficient of variation and water temperature and pressure changes could alter emitter discharge and water distribution uniformity. The aim of this study is to evaluate the effect of fertigation on clogging of emitters and the performance of drip irrigation systems.
Materials and Methods: This study was performed as a laboratory experiment at the University of Zabol. The experiment was done in the form of factorial in a completely randomized design with three replications in the hydraulics laboratory, the University of Zabol. The first factor was fertilizer type including: F0 (control), F1 (ammonium nitrate) and F2 (urea) and the second factor was the emitter types including one-nozzle on line (A), six-nozzles in line (B) and eight-nozzles on line (C). The tap water was used for irrigation. The system included 9 laterals, 3 m each with 18 emitters on each lateral. Fertilizer solution with known concentrations of 0.08 grams per liter was entered into the system from a plastic tank. Fertilizer tank was covered to avoid water evaporation even in a small amount. The experiment lasted for 60 days with 12 operating hours per day. The emitter discharge was measured every three days at the end of day. In order to evaluate the degree of emitter clogging, the percentages of discharge reduction (Qt), Christiansen’s coefficient of uniformity (CU), distribution uniformity (DU) and discharge coefficient of variations (Vm) were calculated as follows:
(1)
(2)
(3)
(4)
where qa, qm and qt are the average, primary and secondary emitter discharges (L/hrs), respectively, qi is the individual emitter discharge (L/hrs), Sm is the standard deviation of discharge (L/hrs) and n is the number of measurements.
Results and Discussion: The results indicated that both fertilizer and emitter type have significant effect on reduction of emitter discharge and distribution uniformity as well as on increase of emitter coefficient of variation. The Duncan test for comparing means showed that the A type emitters had the highest clogging while the B type emitters had the lowest clogging. The percentages of discharge reduction for emitters A, B and C were about 18, 24 and 22, respectively, for treatment F0 (control); 24, 39 and 30 for treatment F1; and 34, 44 and 32 for treatment F2. The results indicated that the emitter clogging increases with altering fertilizer from F0 to F2. F2 (urea fertilizer) had the worse effect on emitter clogging than F1 (ammonium nitrate fertilizer) which could be due to more nitrate produced by urea fertilizer. Also, the results showed that the emitter clogging and discharge coefficient of variation are increased by increasing the elapsed time. Urea and ammonium nitrate fertilizers are hydrolyzed in water and partly converted to nitrate, which is consumed by algae and other microorganisms causing slime accumulation. Bacterial slimes can be a direct cause of clogging for emitters.
Conclusion: According to the results, both fertilizer and emitter types may significantly change the hydraulic properties of emitters. The smallest clogging belonged to emitter of type A when fertilizer F0 was applied as it results in discharge reduction of 18.44%. The largest clogging belonged to emitter of type B when fertilizer F2 was applied (discharge reduction was about 44%). In general, it could be said that fertigation may influence emitter discharge depending on fertilizer treatments (e.g. fertilizer type and concentration), water properties and emitter type. The clogging problems must be attended more specifically as it may reduce farmers’ willingness for drip irrigation implementation and makes them do surface irrigation which may result in more water losses. This study showed that the quality of water used in drip fertigation increases the clogging made by fertilizer application. So, the quality of irrigation water should be investigated every few days. The use of nitrogen fertilizer may cause biological clogging of emitters, so when such fertilizer are used, the type of emitter should be considered.
Farzaneh Nazarieh; H. Ansari
Abstract
Introduction: Rainfall is affected by changes in the global sea level change, especially changes in sea surface temperature SST Sea Surface Temperature and sea level pressure SLP Sea level Pressure. Climate anomalies being related to each other at large distance is called teleconnection. As physical ...
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Introduction: Rainfall is affected by changes in the global sea level change, especially changes in sea surface temperature SST Sea Surface Temperature and sea level pressure SLP Sea level Pressure. Climate anomalies being related to each other at large distance is called teleconnection. As physical relationships between rainfall and teleconnection patterns are not defined clearly, we used intelligent models for forecasting rainfall. The intelligent models used in this study included Fuzzy Inference Systems, neural network and Neuro-fuzzy. In this study, first the teleconnection indices that could affect rainfall in the study area were identified. Then intelligent models were trained for rainfall forecasting. Finally, the most capable model for forecasting rainfall was presented. The study area for this research is the Khorasan Razavi Province. In order to present a model for rainfall forecasting, rainfall data of seven synoptic stations including Mashhad, Golmakan, Nishapur, Sabzevar, Kashmar, Torbate and Sharks since 1991 to 2010 were used.
Materials and Methods: Based on previous studies about Teleconnection Patterns in the study area, effective Teleconnection indexes were identified. After calculating the correlation between the identified teleconnection indices and rainfall in one, two and three months ahead for all stations, fourteen teleconnection indices were chosen as inputs for intelligent models. These indices include, SLP Adriatic , SLP northern Red Sea, SLP Mediterranean Sea, SLP Aral sea, SST Sea surface temperature Labrador sea, SST Oman Sea, SST Caspian Sea, SST Persian Gulf, North Pacific pattern, SST Tropical Pacific in NINO12 and NINO3 regions, North Pacific Oscillation, Trans-Nino Index, Multivariable Enso Index. Inputs of the intelligent models include fourteen teleconnection indices, latitude and altitude of each station and their outputs are the prediction of rainfall for one, two and three months ahead. For calibration of the models, eighty percent of the data belonged to six stations. Mashhad, Golmakan, Sabzevar, Kashmar, Torbate and Sarakhs were used. Verification of the model was carried out in two parts. The first part of verification was done with twenty percent of the remaining data which belonged to the mentioned six stations. The second part of verification was done with data from the Nishapur station. Nishapur geographically is located between other stations and did not participate in the calibration. So, it provides a ondition for assessing models in location except for the calibration stations. To assess and compare the accuracy of the models, the following statistical criteria have been used: correlation coefficient (R), normal root mean square error (NRMSE), mean bias error (MBE), Jacovides criteria (t), and ratio (R2/t). To evaluate models in different rainfall depths, rainfall data based on standard precipitation index (SPI) was divided into seven classes, and the accuracy of each class was calculated separately.
Results and Discussion: By comparing the models' ability to predict rainfall according to the R2 /t criteria it can be concluded that the ranking of the models is Neuro-fuzzy model, Fuzzy Inference Systems, and Neural network, respectively. R2 /to criteria for prediction of rainfall one, two, and three month earlier in the Neuro-fuzzy model are 0.91, 0.4, 0.36, in Fuzzy Inference Systems are 0.76, 0.38, 0.31 and in the neural network model are 0.43,0.27, 0.2. The statistical criteria of Neuro-fuzzy model (R, MBE, NRMSE, t, R2/ t) for rainfall forecasting one month earlier are 0.8, -0.55,0.43, 0.7 , 0.91; two months earlier are 0.79, -1.32, 0.48, 1.56, 0.4; and three months earlier are 0.73,-1.37, 0.54, 1.47, 0.36 . Calculation of MBE criteria for Neuro-fuzzy models in all classes of SPI indicated that this model has a lower estimate in extremely wet and very wet classes. This is because of lack of data belonging to these classes for model training.
Conclusion: The results of this research showed that teleconnection indices are suitable inputs for intelligent models for rainfall prediction. Computing the best structure of fuzzy, neural network and Neuro-fuzzy models showed that Neuro-fuzzy can predict rainfall the most accurately. But, the results of these models in very wet and extremely wet condition are not reliable .So, these models should be used with more caution in these conditions.
tahereh mansouri; Ahmad Golchin; Zahra Rezaei
Abstract
Introduction: Selecting the right source of nutrient in a particular cropping situation requires a consideration of economic, environmental, and social objectives. One of the objectives is to keep all nutrient losses to a minimum. Since the use of nitrogen chemical fertilizers began more than 100 years ...
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Introduction: Selecting the right source of nutrient in a particular cropping situation requires a consideration of economic, environmental, and social objectives. One of the objectives is to keep all nutrient losses to a minimum. Since the use of nitrogen chemical fertilizers began more than 100 years ago, it has been recognized that it can be lost as gaseous ammonia when an ammonical fertilizer is applied to calcareous soil. A process by which nitrogen exit from the soil in form of ammonia and enter to the atmosphere is called volatilization. Agricultural practices (use of chemical and animal fertilizers) are known as major sources of ammonia volatilization into the atmosphere. Nitrogen losses not only economically but also in terms of environment pollution is important. Ammonia volatilization is one way of the nitrogen losses from agricultural and non-agricultural ecosystems. A variety of soil chemical properties interact with environmental conditions at the site of the fertilizer application to determine the extent of NH3 loss. This article study some of the major factors that contribute to NH3 loss from N fertilizer. The aims of this study were to evaluate the impacts of concentrations of soil calcium carbonate (experiment 1), plant residue application (experiment 2), nitrogen fertilizer rate and source on volatilization of ammonia from soil.
Materials and Methods: Two factorial experiment with 36 treatments, three replications and 108 experimental unit for 25 days at a constant temperature of 30 ° C were conducted using a completely randomized design. The experimental treatments were three concentrations of soil calcium carbonate (20, 27 and 35% in experiment 1), three alfalfa plant residue application rates (0, 2.5 and 5% w/w in experiment 2), three rates of nitrogen (0, 200 and 400 kg/ha), four sources of nitrogen (urea, ammonium nitrate, ammonium sulfate and urea- sulfuric acid). Fertilizers were added to soil samples in form of solution and the moisture of soils was brought to field capacity. Samples were placed into special jars and amount of nitrogen volatilization were measured.
Results and Discussion: The results showed that ammonia volatilization from soil increased as the concentration of soil calcium carbonate, rates of nitrogen and alfalfa plant residues application increased. In first experiment the highest amount of nitrogen volatilization rate, as ammonia (33.21 µgr N/gr soil) was measured from 400kgN/ha soil for urea fertilizer and 35 percent calcium carbonate. Also the lowest amount (11.99 µgrN/gr soil) was obtained from 20 percent calcium carbonate without application of any nitrogen fertilizer. In this experiment, with an increase in the amount of soil calcium carbonate by 15%, the amount of volatilized nitrogen in the form of ammonia were six times. By increasing the amount of soil calcium carbonate of from 20 to 27% the amount of nitrogen losses as ammonia slightly increased but with a further increase of calcium carbonate (from 27 to 35%) the amount of nitrogen losses increased a lot and this increase was higher than the initial increase. The presence of calcium carbonate in the soil increase soil pH and ammonia volatilization. In second experiment the highest amount of nitrogen volatilization rate, as ammonia (32.28 µgr N/gr soil) was measured from 400kgN/ha soil for urea- acid sulfuric fertilizer and 5 percent of plant residues. Also the lowest amount (0.33 µgrN/gr soil) was obtained from soil without application of any nitrogen fertilizer and plant residues. The most of nitrogen losses in the form of ammonia in the amount of 15.34 micrograms per gram of soil was obtained from level of 5% of alfalfa residue. With the 2.5 percent increase in the alfalfa residue rate, ammonia volatilization from soil increased in rate of 3.24 micrograms per gram of soil and by increasing it from 2.5 to 5%, nitrogen volatilization increased in the amount of 8.88 micrograms per gram of soil.
Conclusion: The loss of nitrogen as ammonia with application of nitrogen fertilizers and without application of residues was as urea> ammonium sulfate> ammonium nitrate > urea-sulfuric acid and with application of crop residues was as urea-sulfuric acid
Irrigation
E. Farrokhi; M. Nassiri Mahallati; A. Koocheki; alireza beheshti
Abstract
Introduction: The modeling approach for the simulation of the growth and development of tomatoes in Iran has been overlooked. Calibrated crop simulation models, therefore, are increasingly being used as an alternative means for the rapid assessment of water-limited crop yield over a wide range of environmental ...
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Introduction: The modeling approach for the simulation of the growth and development of tomatoes in Iran has been overlooked. Calibrated crop simulation models, therefore, are increasingly being used as an alternative means for the rapid assessment of water-limited crop yield over a wide range of environmental and management conditions. AquaCrop is a multi-crop model that simulates the water-limited yield of herbaceous crop types under different biophysical and management conditions. It requires a relatively small number of explicit and mostly intuitive parameters to be defined compared to other crop models and has been validated and applied successfully for multiple crop types across a wide range of environmental and agronomic settings. This study was conducted as a two-year field experiment with the aim of the simulation of soil water content, evapotranspiration, and green canopy cover of tomato using AquaCrop model under different irrigation regimes at two growth stages in Mashhad climate conditions. Materials and Methods: A field experiment was conducted over two consecutive seasons (2016-2017) in the experimental field of Ferdowsi University of Mashhad, located in Khorasan Razavi province, North East of Iran. The experiment was laid out in a split-plot design with different irrigation regimes at the vegetative and at the reproductive stage as the main and subplot factors, replicated thrice. In total, 27 plots of 4.5×3 m (13.5 m2) were used at a planting density of 2.7 plants per m2. Seedlings were planted in a zigzag pattern into twin rows, with a distance of 1.5 m between them, so there were four twin rows of three meters in each plot. The distance between tomato plants within each twin-row was 0.5 meters. A buffer zone spacing of 3 and 1.5 m was provided between the main plots and subplots, respectively. The following experimental factors were studied: three irrigation regimes (100= 100% of water requirement, 75= 75% of water requirement, 50= 50% of water requirement) and two crop growth stages (V= vegetative stage and R= Reproductive stage). The drip irrigation method was used for irrigation. The tomato water requirement was calculated using CROPWAT 8.0 software. The irrigation water was supplied based on total gross irrigation and obtained irrigation schedule of CROPWAT. Model accuracy was evaluated using statistical measures, e.g., R2, normalized root means square error (NRMSE), model efficiency (E.F.), and d-Willmott. The 2016 and 2017 measured soil and canopy data sets were used for calibration and validation of the AquaCrop model, respectively. Results and Discussion: For a water-driven model, such as AquaCrop, it is important to evaluate its effectiveness in simulating soil water content. During calibration (2016), the model simulated the soil water content with good accuracy. The simulated soil water content values were close to the observed values during calibration (2016) for all treatments with R2 ranging from 0.90 to 0.97, NRMSE in range of 8.47 to 17.96%, d varying from 0.76 to 0.99, and M.E. ranging from 0.87 to 0.96. Validation results indicated the good performance of the model in simulating soil water content for most of the treatments (0.79<R2<0.99, 10.04%<NRMSE<18.65%, 0.77<ME<0.92). Appropriate parameterization of canopy cover curve is critical for the model to provide accurate estimates of soil evaporation, crop transpiration, biomass, and yield. In general, the calibration results showed good agreement between simulated and observed data for canopy cover development in all treatments with high R2 values (>0.87), good E.F. (>0.61), low estimation errors (RMSE, ranging from only 4.5 to 9.2) and high d values (>0.92). Conclusion: The AquaCrop model (version 6.1) was calibrated and validated for modeling soil water content, evapotranspiration, and green canopy cover for tomatoes under drought stress conditions. In general, soil water content, evapotranspiration, and green canopy cover of tomato were simulated by AquaCrop model with acceptable accuracy in both calibration and validation stages. However, the model performance was more accurate in no and/or moderate stress conditions than in severe water stress environments. In conclusion, the AquaCrop model could be calibrated to simulate the growth and soil water content of tomatoes under temperate conditions reasonably well and become a very useful tool to support the decision on when and how much irrigate. For R2, values > 0.90 were considered very well, while values between 0.70 and 0.90 were considered good. Values between 0.50 and 0.70 were considered moderately well, while values less than 0.50 were considered poor. Root mean square error ranges from 0 to positive infinity and expresses in the units of the studied variable. An RMSE approaching 0 indicates good model performance.
H. Taefi; Reza Erfanzadeh; M. Abedi
Abstract
Introduction: Amongst different habitats, fire is an ecological factor and determinant that affects many physico-chemical soil factors. In addition, among natural disturbances, fire plays an important role in plant diversity conservation and in some areas around the world, the presence of some plant ...
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Introduction: Amongst different habitats, fire is an ecological factor and determinant that affects many physico-chemical soil factors. In addition, among natural disturbances, fire plays an important role in plant diversity conservation and in some areas around the world, the presence of some plant species depends on natural fire. The extension of fire influences on soil is related to the fire severity. In fact, fire severity encompasses of two characteristics: extension and time of burning. On the other hand, fire extension and burning time are affected by humidity, air temperature, wind speed, topographical characteristics. Despite high frequency of fire in natural habitats and high level of fire effectiveness on soil parameters, study of fire impacts on soil characteristics were rarely reported in Iran. In addition, most previous studies were conducted in forest habitats, ignoring the severity of fire on soil.
Materials and Methods: In order to investigate the effect of fire severity on some soil physico-chemical characteristics, Yeylagh Dasht area (rangeland habitats) was selected in southern-east of national Golestan Park with three different plant covers, viz. grass, shrub and cushion. Many fires occurring have been reported in this park in each year. For the current study, we tried to select the habitats in which the fire was occurred at least one year before. A control area without burning with similar ecological parameters was also selected adjacent to the burnt area. in fact unburnt area was isolated by a road from burnt area, unable to extend the fire into unburnt area due to the road. Fire had been occurred in the burnt area in September, 2014. Soil samples with 15 replications in burnt area and 15 replications in unburnt were collected within a depth of 0-5 cm and then transported to the soil laboratory to measure some qualitative soil characteristics i.e. soil organic matter (SOM), particulate organic matter (POM), total nitrogen (TN) and aggregate stability (AS). All statistical analyses were done by R software. Before ANOVAs (one and two-ways) and unpaired t-test, we tested data for normal distribution by Shapiro-Wilk test and homogeneity of variance by Flinger Test.
Results and Discussion: The results of two-way ANOVA showed that the main effect of fire on soil was not significant while the main effect of fire severity and the interaction of fire and fire severity on SOM and POM were significant (Table 1). The results of one-way ANOVA showed that the content of SOM was significantly different between three different treatments in unburnt area (control area) while there were no significant differences between the three treatments (three fire severities) in burning areas. Therefore it can be discussed that the kind of vegetation (grassland, shrub or cushion) could affect SOM while the fire increased the spatial homogeneity of SOM. The same pattern of SOM was occurred for POM in burnt and unburnt areas. However, the results of unpaired t-test showed that POM was drastically decreased after high and intermediate fire severities. Aggregate stability and POM were significantly decreased in the intermediate and high severities of fire (cushion and shrub plant cover). Fire in the intermediate and high severities increased TN (Figure 1). We concluded that fire occurring by plants might be decreased POM and AS significantly. In addition, mineralization probable increased TN after burning. We also compared soil characteristics among three fire severities in burnt area and in unburnt area separately.
Conclusion: This study showed that the variation of soil characteristic was mainly affected by different fire severities. Therefore, we emphasized that fire severity should be considered in the studies of the impact of fire on soil in different habitats. Fire can decrease the spatial heterogeneity of soil parameters among different sites. We showed that soil POM is a characteristic more sensitive than total SOM in confronting with fire.
nafise seyednezhad; mahboobeh farzandi; H. Rezaee-Pazhand
Abstract
Introduction: The analysis of extreme events such as first frost dates are detrimental phenomena which influence in various branches of engineering, such as agriculture. The analysis and probability predicting of these events can decrease damage of agriculture, horticulture and the others. Furthermore, ...
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Introduction: The analysis of extreme events such as first frost dates are detrimental phenomena which influence in various branches of engineering, such as agriculture. The analysis and probability predicting of these events can decrease damage of agriculture, horticulture and the others. Furthermore, this phenomenon can have a relation with other thermal indexes. The analyzing of first frost dates of all synoptic stations of Khorasan Razavi province is subject of this article. The frequency analysis applied to eight distributions. Then the relationship between first frost dates and thermal index were studied. Best relation was between minimum temperature and return periods of first frost dates.
Materials and Methods: The analyzing of first frost dates (origin is March 21) of all synoptic stations of Khorasan Razavi province is subject of this article. At first data of each station were screening. The basic properties such as homogeneity, randomness, stationary, independence and outliers must be tested. The eight distribution Normal, Gumbel type 1, Gamma 2-parameter, Log normal 2 or 3 parameters, Generalized Pareto, Generalized extreme values and Pearson Type 3 fitted to data and the parameters estimated with 7 methods by the name of the several types of Moments (5 methods), maximum likelihood and the maximum Entropy. The Kolmogorov – Smirnov goodness of fit test can be used to compare the best distribution. The return periods of first frost dates are major application in frequency analysis. There is maybe a relationship between periods and thermal index such as min, max and mean temperature. This relationship can be adapted by regression methods.
Results and Discussion: The statistical analysis for prediction probabilities and return periods of the first frost dates for all synoptic stations in Khorasan Razavi province and the relationship between annual temperature indicators and this phenomenon is the aim of this article. The origin date of this phenomenon is March 21. First, data were screened. Then basic hypothesis test were applied which including the Runtest (randomness), the Mann-Whitney test (homogeneity and jump), the Wald-Wolfowitz test (independence and stationary), the Grubbs and Beck test (detection Outliers) and the three sigma methods (Outlier). The results were: 1-The Sabzevar, Mashhad and Gonabad had lower Outliers that will not cause any problem in data analysis by their skewness. The first frost data of all station were without upper outlier. 2- The independence of all stations was accepted at the 10% level. 3-All stations were Randomness, Independence and homogeneous and lack of jump. Eight probability distributions (Normal, Gumbel type 1, 2-parameter gamma, 2 and 3 parameters log-normal, the generalized Pareto, the generalized extreme values and the Pearson type 3) were applied. The skewness coefficients for all stations were more than 0.1 so Normal distribution was rejected. Also the7 methods of estimation (five different methods of moments, maximum likelihood and maximum entropy methods) were used. The ks fit test was applied. The ks for some stations were closed together at several estimations methods. The results are as follows: GPA (4 times), PT3 (4 times), LN2 (4 times), GA2 (3 times). Generalized Pareto distribution had the best fitted to data (60% of cases compared to the other functions). The results significantly indicated that the occurrence of first frost on the first day of process is in place. The first frost in the period of 2 years at all stations, not occur earlier than Aban(October 28). The 100-year return period event does not occur earlier than first of Mehr(September 22). There is no significant relationship between first frost in the period of 2 years with other factors such as altitude, latitude, longitude, temperature and precipitation as well.
Conclusion: Date of the first fall frost is one of the unfavorite climate influences that cause reduction in crop products. The purpose of this paper is to analysis the frequency occurrence of first frost day in several Khorasan’s synoptic stations as study area. Screening and initial basic tests such as randomness homogenity, independence, etc. were done. Eight distribution function, namely Normal, Gumbel type 1, Gamma 2 parameters, Log normal 2 and 3 parameters, Generalized Pareto and Pearson type III were fitted to data with five probability distributions methods (Ordinary Moments, Maximum Likelihood method, Modified Moments, Probability Weighted Moment and Maximum Entropy). Goodness of fit test was Kolmogorove-Smirnov test. PWM and ModM methods revealed relatively superior results compared to the rest of methods. Generalized Pareto distribution had the best fitted to data (60% of cases compared to the other functions). The results significantly indicated that the occurrence of first frost on the first day of process is in place. The first frost in the period of 2 years at all stations, not occur earlier than Aban. The 100-year return period event does not occur earlier than first of Mehr. There is no significant relationship between first frost in the period of 2 years with other factors such as altitude, latitude, longitude, temperature and precipitation as well.
Irrigation
M.R. Emdad; A. Tafteh; N.A. Ebrahimipak
Abstract
Introduction
Quinoa (Chenopodium quinoa) is native plant in Bolivia, Chile and Peru, which is widely adapted to different climatic conditions and can grow in all soils. This plant has shown adequate adaptation to arid and semi-arid areas conditions and is planted from areas with low elevation ...
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Introduction
Quinoa (Chenopodium quinoa) is native plant in Bolivia, Chile and Peru, which is widely adapted to different climatic conditions and can grow in all soils. This plant has shown adequate adaptation to arid and semi-arid areas conditions and is planted from areas with low elevation (sea level) to areas with an altitude of 4000 meters above sea level. Quinoa is often cultivated in areas with limited water resources, and it is rare to find quinoa cultivation under full irrigation conditions. Some studies have shown that quinoa yields slightly better under full irrigation (without water restriction) than quinoa under deficit irrigation. Crop growth models are very important tools in the study of agricultural systems and they can be used to simulate the yield of crop in different conditions. Given that the study of performance limiting factors requires numerous and costly research and experiments in different areas, so finding a way to reduce the number, time and cost of these experiments is worthwhile. Aquacrop model is one of the applied models that are used to simulate yield variations in different water and soil management.
Materials and Methods
This investigation was carried out in two growing seasons of 2019 and 2020 to determine the efficiency of Aquacrop model for simulating Quinoa grain yield and biomass under imposing three stress treatments of 30, 50 and 70% of water consumption in development and mid-growth stages. Plant spacing was 40 cm between rows and 7 cm between plants within rows. Seeds of quinoa (Titicaca cultivar) were cultivated in the first decade of August 2019 and in the third decade of July 2020. The experiment was a randomized complete block design with three replications. Three deficit irrigation treatments including 30, 50 and 70% of available water were considered in two growth stages (development and mid-growth) in 18 experimental plots (3 × 4 m). Soil moisture in rooting depth (about 40 cm) was measured by TDR and after the soil moisture of the treatments reached the desired values, plots were irrigated until the soil moisture reached the field capacity. The results of grain and biomass yield in the first year were used to calibrate the Aquacrop model and the results of the second year were used to validate the model. Root mean square error (RMSE), normalized root mean square error (NRMSE), Willmott index (D), model efficiency (EF) and mean error deviation (MBE) were used to compare the simulated and observed values.
Results and Discussion
The results of the first and second year were used to calibrate and validate the model, respectively. The results of the first year showed that irrigation with 50 and 70% of available water in the development stage reduced quinoa grain yield by 17 and 33%, respectively, compared to the control treatment. The application of these two deficit irrigation treatments in the middle stage reduced the yield by about 12 and 28%, respectively. The results of comparing the statistical indices of grain yield, biomass and water use efficiency showed that the NRMSE for grain, biomass and water use efficiency were 9, 8 and 14% in the first year and 9, 6 and 9% in the second years. Furthermore, the EF for these traits were 0.81, 0.77 and 0.64 in the first year and 0.68, 0.71 and 0.62, in the second year, respectively.
Conclusion
The results of calibration and validation of the model showed the accuracy and efficiency of the Aquacrop model in simulating grain yield, biomass and water use efficiency of quinoa. This model can be used to provide the most appropriate scenario and irrigation management for different levels of deficit irrigation managements.
Irrigation
S. JafarNodeh; A. Soltani; E. Soltani; A. Dadrasi; S. Rahban
Abstract
IntroductionAccurate knowledge of water balance components is necessary to optimize water consumption in agriculture. On the other hand, measuring water balance components is expensive and difficult. Therefore, the use of models that can simulate water balance values is important for water management ...
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IntroductionAccurate knowledge of water balance components is necessary to optimize water consumption in agriculture. On the other hand, measuring water balance components is expensive and difficult. Therefore, the use of models that can simulate water balance values is important for water management in agriculture and water used by plants. Crop simulation models have been turned into essential tools for studying plant production systems. In the SSM-iCrop2 models, it is presumed that diseases and weeds are optimally managed and will not affect growth and yield. Additionally, except in cases where the model accounts for specific nutrients such as nitrogen, it is generally assumed that nutrient deficiencies are eliminated through fertilization. Therefore, parameterized and evaluated models are designed to fit these conditions. These factors are present in the field and affect crop growth and yield as well as water use. However, in several cases it is required to estimate yield and water balance components and irrigation water volume under grower conditions. Naturally, models parameterized using experiments are unable to simulate these conditions. Therefore, a model must be prepared so that it can simulate the real conditions of farmers. In this study, the SSM-iCrop2 model has been calibrated for the real conditions of farmers, and the purpose of this study is to use the SSM-iCrop2 model in simulating water performance and water balance for farmers. Materials and MethodsIn this study, the SSM-iCrop2 model was calibrated for farmers conditions using variables such as yield and harvest index, which are available for farmers’fields or are cheap to measure. The effect of factors such as pests and diseases, weeds and unsuitable nutrients, density and sowing date entered the model along with the calibration of three parameters of radiation use efficiency, maximum leaf area and maximum harvest index for farmers’ fields. Calibration was done by comparing the performance of farmers against the performance simulated by the model and by changing the parameters of radiation use efficiency (IRUE), maximum leaf area (LAIMX) and maximum harvest index (HIMAX). This calibration was done at Hashem Abad station in Gorgan for irrigated rice (paddy) and wheat. The simulated actual yield was calibrated with the actual yield. Due to the acceptable simulation of actual yields after calibration, it was presumed that other estimates made by the model are also reliable. Results and DiscussionMeasurement of water balance and other estimates of the model from growth and yield formation in the grower fields is expensive, but a calibrated model can estimate them at a low cost. In this study, it was shown that with the model calibrated for farmers' conditions, not other easily measured information (such as the irrigation water volume) can be obtained, with the assumption that the model accurately captures this information as well as performance. To evaluate the simulated real performance model, it was compared with the actual performance of farmers (Agricultural Jihad Report) after calibration. In addition to phenology, the SSM model simulates traits related to growth and yield, evapotranspiration values, irrigation water volume, runoff, available soil water during planting and harvesting, cumulative drainage, etc. The output of the model shows the amount of irrigation water is needed for a certain amount of performance in a given place (with specified rainfall and transpiration). The irrigation water volume calculated by the model was compared with the results of field tests from previous studies conducted by researchers at agricultural research centers. It was found that the model's output and the observed values were in good agreement. The root mean square error for rice and wheat was 216.6 and 157.6 kg per hectare, respectively, and the coefficient of variation and correlation coefficient were 4 and 85% for rice and 3 and 94% for wheat, respectively. Then, the irrigation water volume estimated by the model was evaluated and validated with the measured irrigation water volume in different crops (in Golestan province for different years). Based on the results of the evaluation, the coefficient of variation and the correlation coefficient for the simulated irrigation water volume were 8.9 and 98%, respectively, compared with the observed value. This calibration was done for rice (paddy) and irrigated wheat in the fields of Gorgan town, and the simulation and running were done using the meteorological statistics recorded in Hashem Abad weather station, Gorgan. Noting the fact that the actual yield has been simulated with good accuracy after the calibration, it was assumed that the other estimates of the model are also reliable. Thus, the calibrated model estimates them with low cost and appropriate accuracy and can complement field experiments. ConclusionThis study discovered that the SSM_iCrop2 model, when calibrated for the conditions of farmers' fields, can accurately simulate both growth and yield traits as well as water balance characteristics. Notably, the model provides reliable estimates of irrigation water volume in farming scenarios, a crucial factor for agricultural planning and drought adaptation.
Hamid Reza Fooladmand; Farzaneh Karimi
Abstract
Introduction: Solar radiation on the earth surface has a wide range of applications in hydrology, agriculture and meteorology. Solar radiation is an important parameter of estimated models of reference crop potential evapotranspiration such as the Penman–Monteith equation. Also, total sunshine hours ...
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Introduction: Solar radiation on the earth surface has a wide range of applications in hydrology, agriculture and meteorology. Solar radiation is an important parameter of estimated models of reference crop potential evapotranspiration such as the Penman–Monteith equation. Also, total sunshine hours are one of the most important factors affecting climate and environment, and its long-term variation is of much concern in climate studies. Reference crop potential evapotranspiration is one of the most important parts of water cycle in the nature but, direct measurement of this crop parameter is so difficult and not practical. Therefore, equations that can estimate the value of evapotranspiration only by using meteorological data are necessary. As mentioned before, the Penman–Monteith equation can be used for estimating reference crop potential evapotranspiration, however this equation needs solar radiation data, and the measurement of solar radiation is done in a limited numbers of weather stations in Iran, and also in Fars province, south of Iran. Since, the measurement of solar radiation is expensive, therefore many models have been derived for its estimation in different climates of the world., Many investigators also have been tried to estimate solar radiation for different locations of the world based on more simple measured weather data such as air temperature (minimum, maximum or mean) and sunshine hours. Hence, the derived equations for estimating solar radiation based on other weather data can be used for estimating reference crop potential evapotranspiration with the Penman–Monteith equation.
Materials and Methods: In this study, solar radiation was estimated in Shiraz, central part of the Fars province in south of Iran. For this purpose, the daily measured of solar radiation data in Shiraz synoptic station were used. Also, other needed weather data were used. All available data was for the years 2006 to 2010. Measured data of years 2006 to 2008 were used for calibrating fourteen estimated models of solar radiation in seasonally and annual time steps and the measured data of years 2009 and 2010 were used for evaluating the obtained results. The equations were used in this study divided into three groups contains: 1) The equations based on only sunshine hours. 2) The equations based on only air temperature. 3) The equations based on sunshine hours and air temperature together. On the other hand, statistical comparison must be done to select the best equation for estimating solar radiation in seasonally and annual time steps. For this purpose, in validation stage the combination of statistical equations and linear correlation was used, and then the value of mean square deviation (MSD) was calculated to evaluate the different models for estimating solar radiation in mentioned time steps.
Results and Discussion: The mean values of mean square deviation (MSD) of fourteen models for estimating solar radiation were equal to 24.16, 20.42, 4.08 and 16.19 for spring to winter respectively, and 15.40 in annual time step. Therefore, the results showed that using the equations for autumn enjoyed high accuracy, however for other seasons had low accuracy. So, using the equations for annual time step were appropriate more than the equations for seasonally time steps. Also, the mean values of mean square deviation (MSD) of the equations based on only sunshine hours, the equations based on only air temperature, and the equations based on the combination of sunshine hours and air temperature for estimating solar radiation were equal to 14.82, 17.40 and 14.88, respectively. Therefore, the results indicated that the models based on only air temperature were the worst conditions for estimating solar radiation in Shiraz region, and therefore, using the sunshine hours for estimating solar radiation is necessary.
Conclusions: In this study for estimating solar radiation in seasonally and annual time steps in Shiraz region, three groups of equations were used (1: based on only sunshine hours. 2: based on only air temperature, and 3: based on sunshine hours and air temperature). Final results of this study for estimating solar radiation in Shiraz region were: 1) For autumn season the best equation was based on the extraterrestrial radiation, the ratio of daily actual sunshine hours to daily maximum sunshine hours, and minimum and maximum air temperatures. 2) For annual time step the best equation was based on the extraterrestrial radiation and the ratio of daily actual sunshine hours to daily maximum sunshine hours.
