Irrigation
M.S. Fakhar; A. Kaviani
Abstract
Introduction
Achieving food security in the future with sustainable use of water resources will be a big challenge for the current and future generations. Population increase, economic growth and climate change intensifythe pressure on existing resources. Agriculture is a key consumer of water, and ...
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Introduction
Achieving food security in the future with sustainable use of water resources will be a big challenge for the current and future generations. Population increase, economic growth and climate change intensifythe pressure on existing resources. Agriculture is a key consumer of water, and it is necessary to closely monitor water productivity for it and explore opportunities to increase its productivity. Systematic monitoring of water productivity through the use of remote sensing techniques can help identifying the gaps in water productivity and evaluate appropriate solutions to address these gaps.
Materials and Methods
Qazvin plain is known as a hub of modern agriculture by providing about 5% of the country's agricultural products. Therefore, estimating water demand and water productivity in agricultural management in the region is considered important and necessary. In order to monitor water productivity through access to various data across Africa and the Middle East, the WaPOR database provides the possibility to examine the rate of evapotranspiration, biomass and gross and net biomass volume productivity based on the land use map in the period of years 2009 to 2021. In this database, it is possible to check the mentioned items at three levels with different spatial resolution, which according to the scope of the study, it is possible to check values with a spatial resolution of 250(m). In order to determine the efficiency and accuracy of the land cover classification map of the WaPOR database, the results obtained are examined and compared with the Dynamic World model, which represents a global model with high accuracy. For this purpose, the latest land use map related to 2021 Using the WaPOR database and Dynamic World in the GEE system, it was prepared and based on the classification of the region in order to check the accuracy of the user map of the WaPOR database and to determine the percentage of each class compared to each other. Finally, all estimable indicators were calculated and checked by the WaPOR database during the years 2009 to 2022.
Results and Discussion
The amount of evapotranspiration of the plants covered by the irrigation network in the period of 2009 to 2016 has been associated with a relatively stable trend, but this trend has decreased in 2017 onwards, which is one of the reasons for the decrease in the amount of evapotranspiration in this the period of time and can refer to the lack of water available to the plant due to the limited water resources in recent years. The investigation of the total amount of biomass in different lands shows that during the years 2009 to 2022, this index has been accompanied by a gradual increase in all uses, so that the amount of TBP index in 2020 was 17% more than in 2009. It shows the amount of biomass in different lands. The amount of biomass in the lands covered by the water network is 5 to 6 times higher than that of the rainfed lands. Among the influential parameters in estimating the TBP index, we can mention the amount of evaporation, transpiration, and transpiration, the increase or decrease of each of these parameters will have a significant impact on the estimated amount of biomass. The results showed that the amount of biomass production in the areas covered by the irrigation network largely depends on the high transpiration rate in these areas. From the beginning of 2009 to 2016, the gross amount of biomass water in the lands covered by the irrigation network has been accompanied by an increase, but in 2017, drastic changes in the process of underground changes will decrease the area of the lands covered by the network and many of these lands. It has been turned into fallow and rainfed lands. The analysis of NBWP index also showed that the amount of net productivity in rainfed lands is strongly dependent on the annual increase rate, and much of the crop yield in rainfed lands is dependent on the amount received. Among the influential parameters in estimating the total amount of biomass, we can mention the amount of evaporation, transpiration and transpiration, the increase or decrease of each of these parameters will have a significant impact on the amount of estimated biomass.
Conclusion
WaPOR database data can play an important role in estimating the rate of delayed transpiration and parameters related to water productivity in the region due to its ten-day spatial resolution and the absence of data gaps. In general, the WaPOR database can be used as a guide in the reliable determination of evapotranspiration values and planning related to water resources in the agricultural sector.
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.
Aida Mehrazar; Jaber Soltani; omid Rahmati
Abstract
Introduction: Limited water resources and its salinity uptrend has caused reducing water and soil quality and consequently reducing the crop production. Thus, use of saline water is the management strategies to decrease drought and water crisis. Furthermore, simulation models are valuable tools for improving ...
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Introduction: Limited water resources and its salinity uptrend has caused reducing water and soil quality and consequently reducing the crop production. Thus, use of saline water is the management strategies to decrease drought and water crisis. Furthermore, simulation models are valuable tools for improving on-farm water management and study about the effects of water quality and quantity on crop yield.. The AquaCrop model has recently been developed by the FAO which has the ability to check the production process under different propositions. The initial version of the model was introduced for simulation of crop yield and soil water movement in 2007, that the effect of salinity on crop yield was not considered. Version 4 of the model was released in 2012 in which also considered the effects of salinity on crop yield and simulation of solute Transmission in soil profile.
Material and methods: In this project, evaluation of the AquaCrop model and its accuracy was studied in the simulating yield of maize under salt stress. This experiment was conducted in Karaj, on maize hybrid (Zea ma ys L) in a sandy soil for investigation of salinity stress on maize yield in 2011-2012. This experiment was conducted in form of randomized complete block design in four replications and five levels of salinity treatments including 0, 4.53, 9.06, 13.59 and 18.13 dS/m at the two times sampling. To evaluate the effect of different levels of salinity on the yield of maize was used Version 4 AquaCrop model and SAS ver 9.1 software .The model calibration was performed by comparing the results of the field studies and the results of simulations in the model. In calculating the yield under different scenarios of salt stress by using AquaCrop, the model needs climate data, soil data, vegetation data and information related to farm management. The effects of salinity on yield and some agronomic and physiological traits of hybrid maize (Shoot length, root length, dry weight and crop yield) under different levels of NaCl solution osmotic potential were also investigated by SAS ver 9.1 software. Data's mean comparisons were performed by Duncan's multiple range test. To assess the accuracy of AquaCrop Model for Simulation of the Maize Performance under Salt Stress used from Indicators RMSE, MAE, CRM, NSE, d and Er.
Results Discussion: The results of RMSE and MAE indices showed that AquaCrop model can simulate maize yield under the salinity stress. Accuracy decreased and crop yield prediction underestimated with increasing salinity from treatment 0 to 18.13 ds/m in the first and second harvest. The highest yield related to salinity treatment of 0 dS/m and the lowest yield related to salinity treatment 18.13 dS/m. yeild simulation error increased by increasing salinity, the highest and lowest error of yield simulation in model respectively related to salinity treatments 18.13 and 0 dS/m. The highest and lowest error was in the first harvest respectively 0.56 and 13.1 percent and in the second harvest respectively 0.42 and 21.79 percent, that in the comparison with the results of studies conducted by Steduto and colleagues on maize is not much different. The results comparison in the first and second harvest showed that soil salinity was increased by increasing irrigation number in second harvest, so the error in second harvest is greater than first harvest and the maximum error is related to treatment 18.13 ds/m in the second harvest 21.79 percent.The coefficient of determination R2 for the first and second harvest is respectively 0.850 and 0.834, that indicates a high correlation between yeild values of measured and predicted by the AquaCrop model. CRM index was negative and near zero in both harvest under Salinity different scenarios. According to CRM value, AquaCrop model was overestimated and the model was simulated maize yield under the salinity stress a little more than measured yield. The d statistic index value is close to unity, indicates that yield values in model is compatible with actual values. NSE index was calculated for the first and second harvest respectively 0.81 and 0.84, that is close to one and showed that the model has suitable performance in the yield simulation. Comparison of means by Duncan's multiple range test and analysis of variance in the software SAS ver 9.1 indicated Salinity has a very significant effect on all traits including shoot length, root length, dry weight and crop yield that all traits were decreased significantly by increasing salinity.
Conclusion: Comparison of the results of AquaCrop model and statistical analysis in software SAS ver 9.1 showed that maize yield was reduced with increasing salinity. According to index CRM, AquaCrop model was simulated maize yield under the salinity stress more than measured yield in farm. The results showed that the AquaCrop model simulated well maize yield in moderate and low stress, but accurately simulation slightly decreased in high stress. The results of this study was compared with other research and indicated that the error values of AquaCrop model in Karaj is not much different with the error values of other research.
