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 ...
Read More
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.
R. Saeidi; H. Ramezani Etedali; A. Sotoodehnia; .B Nazari; A. Kaviani
Abstract
Introduction: Supplying human and animal nutritional needs requires suitable use of water resources. Due to the decrease of fresh water resources for agriculture, saline water resources cannot be ignored. Increasing water salinity reduces the water absorption by plant, due to decreasing the water potential. ...
Read More
Introduction: Supplying human and animal nutritional needs requires suitable use of water resources. Due to the decrease of fresh water resources for agriculture, saline water resources cannot be ignored. Increasing water salinity reduces the water absorption by plant, due to decreasing the water potential. On the other hand, soil infertility (such as nitrogen deficiency) decreases the evapotranspiration and crop yield. The present study was to increase the water and nitrogen fertilizer use efficiency of maize, under salinity stress condition. This was done by managing the consumption of saline water and nitrogen fertilizer. In this research, irrigation requirement was determined proportional to the plant evapotranspiration to avoid excessive saline water use. Materials and Methods: In this research, two treatments of water salinity and nitrogen deficiency in four levels and three replications were implemented as a factorial experiment in a randomized complete block design. The studied plant was maize (S. C. 704 cultivar) sown in plots with dimensions of 3 × 3 meters and 1.5 meters distance. In this research, fertility stress was in the form of nitrogen fertilizer consumption and at four levels. Treatments of ، ، and consisted of consumption of 100, 75, 50 and 25% of nitrogen fertilizer, respectively. Salinity stress has been applied by irrigation of the plant with saline water. Water salinity treatments were selected based on the yield potential of maize, at four levels of 100, 90, 75 and 50%. According to the above four performance levels, treatments of ، ، and included irrigation water with electric conductivity of 0.5, 1.2, 3.5 and 7.5 (dS/m), respectively. The soil moisture content was measured at the depth of root development during the interval between two irrigations. Daily maize evapotranspiration was measured by the volumetric balance of water at the depth of root development. The stomata resistance of maize leaf was measured by the AP4 porometer device between two irrigations interval. Variance analysis and mean comparison of data were done by SPSS software and Duncan's multiple range test, respectively. Results and Discussion: Water use efficiency In this research, the evapotranspiration and dry matter yield of maize decreased under salinity stress and nitrogen deficiency treatments. This seems to be caused by the water potential decrease (due to salinity stress) and the nitrogen deficit in the soil. Under these conditions, optimum use of water and fertilizer increased water use efficiency. At first without water and fertilizer management, water use efficiency in different treatments ( to ), ranged from 2.74 to 4.4 kg/ (in 2017) and from 2.57 to 4.35 kg/ (in 2018). With suitable management of irrigation, water use efficiency, however, increased in stress treatments and approached to optimum treatment. The range of water use efficiency was from 4.2 to 4.4 kg/ (in 2017) and from 4.15 to 4.32 kg/ (in 2018). The reason for this was the management of irrigation volume based on actual evapotranspiration in stress treatments. On the other hand, increasing soil nitrogen was an appropriate strategy to increase water use efficiency. But in high salinity stress, despite the optimum use of water and fertilizer, it was not possible to achieve optimal water use efficiency. This is explainable by the harmful effect of salinity on the reduction of nutrient uptake (especially nitrogen) by the plant. Nitrogen use efficiency Soil nitrogen deficiency and increasing water salinity reduced nitrogen use efficiency. In different stress treatments, nitrogen use efficiency ranged from 3.34 to 5.11 kg/kg (in 2017) and from 3.06 to 5 kg/kg (in 2018). The results showed the destructive effect of salinity on nitrogen uptake by the plant. Under these conditions, the ions in the soil (especially the sodium and calcium) caused the plant to be unable to absorb nitrogen from the soil. Therefore, the production of plant matter was reduced. The results showed that proper management of nitrogen can increase nitrogen use efficiency under salinity stress. At high salinity levels, the nitrogen fertilizer was not, however, absorbed by the plant and accumulated in the soil. Conclusion: The results showed that water use management could increase the water use efficiency under stress treatments, by controlling evapotranspiration. On the other hand, soil fertility increased nitrogen fertilizer use efficiency under salinity stress. Among all treatments, had optimum water and nitrogen use efficiency. Overall, the volume of water used in the field should be adjusted to the actual requirement of the plant to prevent excessive consumption under salinity stress. In addition, increasing soil nitrogen, rather than more irrigation water, appears to be a suitable strategy to increase crop yield.
B. Bahmanabadi; A. Kaviani
Abstract
Introduction: The exact estimation of evapotranspiration has significant importance in the programming of irrigation development and other distribution systems and water usage. Since the main user of water in the country is the agriculture sector, therefore, the exact estimation of plants’ water demand ...
Read More
Introduction: The exact estimation of evapotranspiration has significant importance in the programming of irrigation development and other distribution systems and water usage. Since the main user of water in the country is the agriculture sector, therefore, the exact estimation of plants’ water demand has been adverted extensively. The assessment methods of reference evapotranspiration are classified in two types of direct and indirect. The calculation of reference evapotranspiration in scientific and in vitro form and with high accuracy is possible by using lysimeter but in comparison to the indirect methods that are based on the climatic data of weather stations, the use of lysimeter is unfortunately inefficient. This is not just for the time consuming and high cost of lysimeter but it is for the limitation of weather stations and spottiness of the estimated values; in this way it is not possible to expand the obtained results to the large scale. Remote sensing is an authentic technique for the assessment of evapotranspiration in large scale which do not consume much time and money. The existence of different satellites by having different spatial and temporal resolution, redouble the importance and usability of this technique
Material and Methods: Actual evapotranspiration assessment in the region were done based on SEBAL, SSEB and TSEB algorithms on 46 imageries of MODIS, seven imageries of Landsat7 (ETM+) and seven imageries of Landsat5 (TM) in years of 2001-2003. Multiplicity of imageries of MODIS show the proper time resolution of this sensor and is a reason for less errors in the assessment of reference evapotranspiration. In the evaluation of the three algorithms of SEBAL, SSEB and TSEB in the three satellites.
Result and Discussion: In the evaluation of the three algorithms of SEBAL, SSEB and TSEB in the three satellites, MODIS shows the least errors (respectively, RMSE=0.856, 1.385 and 2.7 mm/day), then Landsat7 is placed in the second class by having higher spatial resolution (respectively, RMSE=1.042, 1.56 and 2.76 mm/day) and Landsat5 has the highest errors (respectively, RMSE = 1.14, 1.97 and 3.06 mm/day). NDVI was found at the lowest amount in the beginning of cultivation period because of germination and sparseness of vegetation, and increase respectively by increasing temperature and crop canopy. L factor has a significant importance in the assessment of SAVI which is related to the area crop coverage percentage. Amount of L has been estimated as L=0.6 that has the least errors in comparison to the others.
Conclusion: In this study, the proper amount for L factor in estimation of the SAVI amount was about 0.6 which was based on the investigations on soil correction factor, the results of statistical indexes and the type and dispersal of vegetation in the region. The accuracy estimation of evapotranspiration of two single-source algorithms of SEBAL and SSEB and one two-source algorithm of TSEB in Bushehr province were evaluated. SEBAL algorithm presented more exact results based on statistical indexes among two single-source algorithms and the obtained results in 95% level of this algorithm showed significant differences with lysimetric measurements. This algorithm was chosen as the premier algorithm in the region. Two-source algorithm of TSEB showed the highest amount of errors. Satellite imageries by having higher spatial resolution estimated evapotranspiration with higher accuracy, the reason of which is proper choosing of cold and hot pixels. Although, because of having proper time resolution and variation of image numbers and also presenting of more time series in comparison to ETM+ and TM, MODIS was more adverted. ETM+ which is located on Landsat satellite was lied in the second place because of its resolution and having higher spatial resolution.
reza saeidi; abbas Sotoodehnia; Hadi Ramezani Etedali; Bizhan Nazari; Abbas Kaviani
Abstract
Introduction: Estimating the actual evapotranspiration of the crops, is so important for determining the irrigation needs. Typically, the climatic, vegetative and management parameters are effective on actual evapotranspiration. If the crops are exposed to salinity, fertility and other stresses, reduce ...
Read More
Introduction: Estimating the actual evapotranspiration of the crops, is so important for determining the irrigation needs. Typically, the climatic, vegetative and management parameters are effective on actual evapotranspiration. If the crops are exposed to salinity, fertility and other stresses, reduce actual evapotranspiration and yield. The correct estimation of the actual evapotranspiration of crop will allow agricultural planners to the better agricultural water management. Previous researches show water stress and soil nitrogen deficiency (as management stresses), effect on increasing of stomatal resistance and reducing of crops evapotranspiration. Thus, goal of this study was to investigate the effect of salinity and soil nitrogen deficiency on the amount of Ks coefficient and readily available water of maize.
Materials and Methods: This study was conducted in research farm at University of Imam Khomeini International, Qazvin, Iran during June to November 2017. In this research, the effects of saline water and soil nitrogen deficiency on Maize (SC 704) evapotranspiration, were investigated. The applied treatments included irrigation with saline water (in four levels: 0.5 (S_0), 1.2 (S_1), 3.5 (S_2) and 5.7 (S_3) dS/m) and soil fertility (in four levels: nitrogen fertilizer consumption at 100 (N_0), 75 (N_1), 50 (N_2) and 25% (N_3)). The experimental design used in this research was a completely randomized block design with three replications. In this experiment, maize seeds were cultivated in the plots with Length and width of 3×3 meters. The prometer device (Model: AP4) was also used to measure stomatal resistance of maize leaf. Determining the irrigation schedule, was based on the soil moisture reached to the limit of RAW (Readily Available Water). At the same time, with increasing stomatal resistance, RAW was calculated and irrigation was done. Evapotranspiration of the under stress plants were ET_(c-adj) and evapotranspiration of S_0 N_0 treatment was ET_c. The stress factor (K_s ) is calculated by ET_(c-adj)/ET_c. The values of RAW and K_s were analyzed by SPSS software. K_s coefficient was modeled with amounts of salinity stresses and soil nitrogen deficiency.
Results and Discussion: The results of this study showed that the interaction between two factors of salinity stress and nitrogen deficiency on the K_s and RAW parameters (in level: 1%) are significant. K_s coefficient at the levels of S_1, S_2 and S_3, were 0.95, 088 and 0.77, respectively. In saline water of 0.5 (dS/m), the K_s coefficient of N_1, N_2 and N_3 were 0.98, 0.96 and 0.95, respectively. With increasing the 1(dS/m) salinity of water and 25% reduction in nitrogen consumption, decreased the K_s amount about 4.5% and 1.7%, respectively. The reason of results is that with increasing of water salinity, decreases the osmotic potential of water in the soil and the crop needs to consume more energy to obtain water. Thus, amount of crop transpiration is reduced and soil water content is remained. The linear, exponential, logarithmic, polynomial and power functions were fitted between N_i/N_0 and S_i/S_0 data. The ability of the above functions to estimate the K_s coefficient value was evaluated. The polynomial function has a good function for estimating the K_s coefficient. In the S_0، S_1، S_2 and S_3 treatments, by changing the fertility value from N_0 to N_3, amounts of RAW were 63.7, 58.7, 55.4 and 42% , respectively. Also in N_0، N_1، N_2 and N_3 treatments, with changing the salinity of water from S_0 to S_3, RAW values were 51.7, 46.3, 42.7 and 42%, respectively. Therefore, stresses that reduce crop evapotranspiration are effective on reducing the amount of RAW. In this situation, the actual water requirement of the crop is less than the potential evapotranspiration of the area.
Conclusions: Increasing water salinity and nitrogen deficiency decrease evapotranspiration of maize and increase soil water content. By calculating the stress coefficient (K_s ), it is possible to estimate the actual evapotranspiration of maize, in Qazvin. Thus, the amount of irrigation water is adjusted according to the actual water requirement of maize. Under salt stress conditions with increasing the soil nitrogen, Can be increased the K_s coefficient and evapotranspiration of maize. Therefore, calculating the crop's water requirement based on the existence of strtesse, it will help to saving water.
H. Ramezani Etedali; Maryam Pashazadeh; B. Nazari; abbas sotoodehnia; A. Kaviani
Abstract
Introduction: Regarding population growth rate and drought challenges, one of the effective strategies for sustainable development in agricultural sector is irrigation. In this regard, in recent years, the use of tape irrigation method has been considered in crop plants, but the use of this system will ...
Read More
Introduction: Regarding population growth rate and drought challenges, one of the effective strategies for sustainable development in agricultural sector is irrigation. In this regard, in recent years, the use of tape irrigation method has been considered in crop plants, but the use of this system will be successful if it is to evaluate the system performance in terms of soil sustainability before it is implemented and its problems are solved. Problems in the field of sustainable agriculture are saltinification of soil resources that the tape irrigation over time and due to the continuity of its use in cultivated land, especially in warm and dry areas due to global warming, climate change and decline of the atmospheric precipitation leads to salinity accumulation in the soil.
Materials and Methods: In order to investigate the distribution and changes of salinity of soil profile in the root development zone of wheat, maize, barley and tomatoes grown in Qazvin Plain with initial salinity of 1/5 dS/m and salinity of irrigation water 1 dS/m In hot and dry climate, a type of irrigation was used (strip drip) and during the 20 years of cultivation, the AquaCrop version 5 was used. The results of simulation output were analyzed by Minitab 17 and Excel 2007 softwares.
Results and Discussion: The results showed that in all previous stuides, the amount of salinity accumulated through the tape irrigation in the soil surface is greater, but in this study, due to the time effect on salt accumulation in the soil profile in the root development area, The maximum salt accumulation below the soil surface and at depths (0/5, 1/5, 0/5 and 0/16) meter of the total root development depth of each plant, respectively, for tomato, maize, barley and Wheat has occurred. It can be said that over time, accumulated salt on the surface of the soil evaporated, re-moved with irrigation and redistributed under the soil profile. Simulation results were obtained after statistical analysis with Minitab 17 and Excel 2007 software showed that in tomato and corn products, tape irrigation with irrigation water salinity of 1 dS/m resulted in significant increase in average salinity of The root development zone from 1/5 is 4 and 4/4 dS/m over the course of 20 years (correlation significance at 5% level) and sustainable utilization of soil resources is questioned, While the increase in average salinity of root development zone in wheat and barley products due to tape irrigation over the course of 20 years has risen from 1.5 to 2/03 and 2/02 dS/m, which is not noticeable and at the level of 5% is not significance. This can be attributed to rainfall during the growing season of wheat and barley, which led to salt salting from the root zone. The correctness of this theory was tested by the significance of the correlation between rainfall and salinity in the 5% level and proved to be. Therefore, it is recommended to wheat and barley with the ability to tolerate high soil salinity are placed in the top priority for local irrigation in hot and dry areas with limited atmospheric rainfall and limited water resources.
Conclusions: From the above results, it was observed that, in products such as maize and tomatoes, tape irrigation resulted in a significant increase in the mean salinity of the root development zone over time. However, the increase in average salinity of root development in wheat and barley products due to the tape irrigation is negligible and canceled over time. In other words, the cultivation of crops such as barley and wheat in areas with scarcity of water resources and soil salinity ensures sustainable land management. These results, while using water with salinity of about 1 dS/m, and soil cultivation with an average salinity of 1/5 dS/m, have been taken. Since comprehensive and practical research has not been done on long-term salinity changes and the use of tape irrigation, after the cultivation of important crops such as wheat, barley, corn, tomato, the results of this research can be used in conducting managerial guidelines, The selection and prioritization of the appropriate cropping pattern in the warm and dry areas will be beneficial with few atmospheric precipitations.
Farshid Ramezani; Abbass Kaviani; Hadi Ramezani Etedali
Abstract
Introduction: AquaCrop model was developed to simulate crop response to water consumption and irrigation management. The model is easy to use, works with limited input, and has acceptable accuracy. In this study, the data of an alfalfa field (as a perennial fodder plant) in the Iranian city of Ardestan ...
Read More
Introduction: AquaCrop model was developed to simulate crop response to water consumption and irrigation management. The model is easy to use, works with limited input, and has acceptable accuracy. In this study, the data of an alfalfa field (as a perennial fodder plant) in the Iranian city of Ardestan was used to calibarate and validate the performance of AquaCrop model to simulate the crop productivity in relation to water supply and irrigation management.
Materials and Methods: The data of Fajr-e Esfahan Company farms of Ardestan County were used for calibration and validation of the AquaCrop model, simulating the alfalfa performance in different harvests and over different years. The farms are 1004 m above sea level and located in 33°2' to 33°30' North and 55°20' to 55°22' East. The farm under investigation included ten plots of alfalfa field, with an area of 280 hectares. The data of two plots were used for calibration and, two others used for validation.
Considering that alfalfa is a perennial plant, the data regarding the first harvest was defined as sowing, and transplanting was used to refer to the next harvests. Considering the physiological changes of plants over a year and during different harvests, the numerical value of different parameters, including primary vegetation, maximum vegetation, the depth of primary root development, the maximum depth of primary root development, crop coefficient, germination date, flowering, vegetation senescence, and physiological maturity, were defined for the model. The CRM, NRMSE, R2, and EF indices were used for verification of the calibration results. The CRM index determines the overestimation or underestimation of the model. The EF index is variable between 1 and 0, where 1 indicates optimal performance of the model. If all estimated and measured values were equal, the value of CRM and NRMSE would be zero, and EF would be one.
Results and Discussion:After calibration, validation was performed to examine the performance of the model. Hence, the actual performance rate for different harvests and the results of simulations were compared. Lower NRMSE value is indicative of high accuracy of the model in estimation of the performance. The value of CRM was mostly positive, showing the underestimation of the model in most of the simulations. The maximum performance happened during the first harvest year. The annual harvest decreased with an average rate of 1.2, compared to former years. The evaporation and transpiration rate was calculated by the model and the results were compared with potential evapotranspiration (FAO Penman-Monteith) and National Document of Irrigation (NET WAT). The reference crop evapotranspiration (ET0) had the highest value, and was calculated through FAO Penman-Monteith equation. The numerical value of potential crop evapotranspiration (ETc), which is the result of multiplication of crop coefficient by reference crop evapotranspiration (ET0), was greater than the results of the model, i.e. the estimated actual evapotranspiration. The discrepancy between them is the result of stress coefficient (ET0×Kc×Ks), which the model takes into account in estimation of actual plant water requirement. Evapotranspiration refers to two factors, namely the water lost by transpiration from plants and by evaporation from the soil. The plant transpiration and green cover are considered to be the generating part; AquaCrop is able to examine and improve transpiration efficiency through managerial statements. The values of transpiration from plants and evaporation from the soil for alfalfa were differentiated from the values estimated by the model. The productivity of evaporation, transpiration, and evapotranspiration were calculated by the model. The difference in the productivity values of the plots during different years was the result of difference in chemical composition, harvest index, and transpiration rate.
Conclusion:The AquaCrop model performed well in simulation of crop performance compared to actual annual, and even monthly, performance, and its results were very close to the actual performance. The model is sensitive to temperature changes, and it is suggested to use the Growing Degree Days (GDD) instead of Calendar Days section. . The Version 5 of AquaCrop model can, in addition to moisture stress, include salinity stress in calculations; this is evident in the variation of actual evaporation and transpiration values estimated by the model. In this study, the annual evaporation and transpiration rate was predicted by the model. The higher rate of evaporation can lead to a 27 to 44 percent decrease in the efficiency of evapotranspiration (Y ET-1), compared to transpiration efficiency (Y T-1).
