Irrigation
Mohammad Reza Alashti; Mojtaba Khoshravesh; Fardin Sadegh-Zadeh; Hazi Mohammad Azamathulla
Abstract
Introduction
The rapid growth and development of urban communities, coupled with the increased industrial and economic activities in recent years, have led to the production and release of various pollutants into the environment. These pollutants have adverse effects on human health, living organisms, ...
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Introduction
The rapid growth and development of urban communities, coupled with the increased industrial and economic activities in recent years, have led to the production and release of various pollutants into the environment. These pollutants have adverse effects on human health, living organisms, and the overall environment. With limitations in water resources, insufficient rainfall, the looming risk of water crises in many countries, and the escalating pollution of surface and underground water, there is a pressing need for environmental solutions to mitigate these issues. It is important to acknowledge that wastewater often contains pollutants that may render it unsuitable for certain applications. The utilization of biochar derived from cost-effective materials and innovative technologies such as ultrasonics is one avenue that warrants exploration for enhancing water quality. In this approach, a nitrate solution is exposed to both an adsorbent and ultrasonic waves. This dual treatment induces changes in the physical and chemical properties of water, thereby offering potential improvements in water quality.
Materials and Methods
This study aimed to explore the impact of utilizing biochar derived from rice straw, which was coated with iron (III) and zinc cations, and subjected to ultrasonication, on the nitrate adsorption process from aqueous solutions. In order to produce biochar, cheap materials of rice straw were used. The chopped straw was placed in the electric furnace and heated for one hour to reach the desired temperature. Then it was kept at that temperature for 2 hours. After that, the obtained biochar was washed three times with distilled water at a ratio of 1:20 and dried in an oven at 70°C for 24 hours. In this research, two different temperatures of 350°C and 650°C were used for the production of biochar, which according to the results obtained in the pre-tests of the research that nitrate removal efficiency is higher in biochars made at 650°C. These biochars were used for the continuation of the experiments. In this research, after conducting pre-tests to optimize the adsorbent dose in the proportions of 0.1, 0.3, 0.5, 0.8 and 1 gram of the adsorbent and 40 ml of nitrate solution, concentrations of 20, 45, 80, 100, 150 and 200 ppm of nitrate solution was investigated. The research involved conducting experiments to determine the optimal parameters for each treatment, with three repetitions conducted in the water quality laboratory of Sari agricultural sciences and natural resources university during the years 2021 and 2022. The treatments comprised biochar (B), biochar and ultrasonic (BU), biochar with iron (III) coating (BF), biochar with iron (III) coating and ultrasonic (BFU), biochar with zinc coating (BZ), and biochar with zinc coating and ultrasonic (BZU). In this investigation, Langmuir and Freundlich adsorption isotherms were examined.
Results and Discussion
The results indicated that the BF and BFU treatments exhibited a higher maximum adsorption capacity. The Freundlich isotherm demonstrated higher correlation coefficients for BF, BFU, BZ, and B, suggesting a superior fit of the Freundlich model in these treatments. The better fit of the Freundlich adsorption isotherm indicates the heterogeneity of biochar surface adsorption sites, which means that the adsorption process is not confined to a single constituent layer. Nitrate adsorption on biochar surface is probably influenced by electrostatic adsorption and ion exchange. Conversely, the BZU and BU treatments showed a better fit with the Langmuir model. In the analysis of the Freundlich isotherm, nf values revealed that BF, BFU, and BZ treatments exhibited a favorable adsorption state with a desirable curve shape. The B treatment displayed a normal adsorption state with a linear curve shape, while BU and BZU treatments showed a weak adsorption state with an unfavorable curve shape. The elevated values of adsorption capacity (KF) obtained for BF, BFU, and BZ, namely 1909.414, 1484.22, and 386.63 ((mg/g)(L/mg)1/n), respectively, underscore the high nitrate adsorption capacity of these treatments. Also, biochars coated with iron (III) and with iron solution concentration of 10000 mg/L had a very good performance in removing nitrate from aqueous solutions. The new ultrasonic technology was able to improve the performance of the tested adsorbents in a period of 5 minutes without the need to stir the mixture of biochar and nitrate solution in the obtained equilibrium times, which were between 60 and 120 minutes. The use of this technology can be effective and useful in increasing the economic benefits of using limited water resources and increasing the efficiency of water consumption.
Conclusions
The utilization of cost-effective biochars derived from rice straw, along with the application of ultrasonic technology, can substantially decrease nitrate levels in aqueous solutions. In the case of biochar with iron (III) coating, biochar with iron (III) coating combined with ultrasonic treatment, and biochar combined with ultrasonic treatment, there is a notable affinity for nitrate to be adsorbed onto the surface of the adsorbent.
Irrigation
Abdolreza Zahiri; Khalil Ghorbani; Hamed Feiz Abady; Hossein Sharifan
Abstract
Introduction: The reservoirs are considered as vital sources of water supply for human societies, hence the correct and planned management of their reserves is an essential issue. Dams are used for purposes such as urban water supply, irrigation of agricultural lands, floods control and hydroelectric ...
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Introduction: The reservoirs are considered as vital sources of water supply for human societies, hence the correct and planned management of their reserves is an essential issue. Dams are used for purposes such as urban water supply, irrigation of agricultural lands, floods control and hydroelectric power generation. In order to properly manage and monitor the consumption of these important reserves, it is inevitable to know their capacities. Using water stage and the reservoir's initial volume-area-elevation curve, which is prepared with the hydrographic operations, is a common method for estimating the storage capacity of reservoirs at different water levels. Over time and the occurrence of numerous sedimentations that can occur due to factors such as floods, the initial volume-area-elevation curve of the reservoir changes, hence it needs to be modified.The hydrographic operation of reservoirs using tools like Eco-sounders is a conventional method for correction of this curve, which is not only expensive but also time-consuming. In recent years, various studies based on remote sensing with the aim of estimating the volume of water stored in reservoirs have calculated water levels to establish the surface area-elevation curve. The basis of these studies are the separation of water-lands masks with the help of spectral indices, the calculation of water levels, and the developing of reservoir surface area-elevation curves using linear or polynomials relationships. The main limitation of these methods is the inaccuracy of linear or polynomial relationships in fitting the surface area-elevation curves of the reservoir for the beginning and end points of the water stage change interval, which corresponds to the empty or fullness of the reservoir. and these happen due to the occurrence of factors such as drought or floods.In this research, with the help of to eliminating the limitation of linear and polynomial relationships for accurately predicting the points of the reservoir surface area-elevation curves where the observational data are not available due to non-occurrence, by drawing the hypsometric curve using the Modified Strahler method has been used. By using the hypsometric curve, it is possible to calculate the storage capacity of the reservoir between successive water levels and obtain the final volume of water stored in it. In this study, by comparing the volumes of water stored at the present and initial reservoir capacities, the sedimentation rate and the useful life of the reservoir of Negarestan dam have been estimated.
Material and Methods: Negarestan Dam (Kabudval) is located on the Qara Su (Zarin Gol) river, and 45 km east of the city of Gorgan in the Golestan province. This dam is used for purposes such as supplying urban water to Aliabad city and supplying water needed for the agricultural irrigation network of Qarasu. In this srudy, landsat8 satellite images were used to estimate the useful life of the Negarestan reservoir. The required images of the ROI were downloaded through the USGS database and pre-processed in Envi5.3 software. Using visible and infrared spectral bands, water indices NDWIMCFeeters, NDWIGao, MNDWI, AWEISh and TCWet were calculated to separate land-water masks. After evaluating the accuracy of the obtained water level results by comparing it with the initial volume-area-elevation curve of Negarestan reservoir, the MNDWI index was used as the most accurate index to calculate water levels.In this study, the modified Strahler method was used to obtain the hypsometric curve of the surface area-elevation of the reservoir, which has high accuracy in extrapolating the beginning and end points of the curve. By using the hypsometric curve, water level levels were extracted for arbitrary water levels and with the help of the prismoidal method relation of the volume between consecutive water levels, the sum of these volumes is equal to the current storage capacity of the reservoir. To estimate the sedimentation rate of the Negarestan dam reservoir, the current storage capacity of the reservoir was compared with the initial storage capacity in 2015, and based on this, the useful life of the reservoir was accurately predicted.
Results and Discussion: Validation results for calculating water surface areas using NDWIMCFeeters, NDWIGao, MNDWI, AWEISh and TCWet water indices showed that the MNDWI index with an average water surface areas calculation error equal to 5% is more accurate than other indices. Therefore, MNDWI index was used in this study. Also, the comparison of the volume of water stored in the Negarestan reservoir with its initial storage capacity at the time of operation showed that in a period of 9 years, the storage capacity of the reservoir (at the water level equal to about 189.5 meters), which is equivalent to the approximate level of the overflow crest. It has decreased from about 24 to 20 million cubic meters, based on which the average annual sedimentation rate of the reservoir was estimated to be about 1.6%. The results showed that in a period of 9 years, the average level of the bathymetry of Negarestan reservoir has increased by 10 meters due to the accumulation of sediments, and the minimum level of the batymetry has reached from 160 to about 170 meters.According to the statistics of the International Commission on Large Reservoirs (ICOLD), the average annual sedimentation rate of the world's reservoirs is reported to be about 0.95%, and the results show that this amount in the Nagaristan Dam reservoir is almost 2 times the average rate. It is universal. According to the results obtained from this research and assuming constant climatic conditions, the useful life of the Nagarestan dam reservoir was estimated to be about 53 years from the beginning of 2024.
Conclusion: Considering the increasing importance of water resources management, including dam reservoirs, in this study, a fast and inexpensive method based on remote sensing is used to calculate the volume of water stored in dam reservoirs and estimate the useful life. They were presented. In addition to the appropriate accuracy, this method was able to overcome the limitations of the previous methods in estimating the volume of accumulated sediment in the deep parts of the reservoir and can be used for the correct management of water resources.
Irrigation
Nadia Bahremand; Hossein Aroiee; Ahmad Aien
Abstract
Introduction: the watermelon (Citrullus lanatus) is a known product with high demand and nutritional value and the capability to export all over the world, and considering that the ultimate goal of all agricultural production systems is to achieve the maximum yield of the plant, and providing the water ...
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Introduction: the watermelon (Citrullus lanatus) is a known product with high demand and nutritional value and the capability to export all over the world, and considering that the ultimate goal of all agricultural production systems is to achieve the maximum yield of the plant, and providing the water required for the plant is most effective factor on yield, as a result, investigating of t water limitation effec seems to be an undeniable necessity. On the other hand, dificit irrigation has been introduced as a tool to increase water productivity, thus it is necessary to take into account the effects of this method of saving water consumption on plant production, which doubles the need for research and shows it more clearly, and in addition, Deficit irrigation is applied by providing a part of the plant's water needs, while regulated deficient irrigation is a type of deficient irrigation that can be implemented in several ways, including irrigation based on growth stages or, in other words, allocating of the water to stages that are more sensitive to drought. we should know that the response of plants to lack of the irrigation depends on several factors, including climatic conditions, type of plant, intensity and method of application of deficit irrigation, soil condition and management.
Materials and methods: In order to determine the effect of deficit irrigation and regulated deficit irrigation on yield and water productivity of the watermelon, an experiment in the form of randomized complete blocks with 8 treatments including three irrigation levels of 100, 70 and 50 % of the plant's water requirement (evapotranspiration estimated by the FAO-Penman-Monteith method) and 5 regulated deficit irrigation levels including 50% of the water requirement in the stages of seedling, vine, flowering, fruit expansion and fruit maturity was carried out with three repetitions under black plastic mulch, during 2020-2022, in the Research and Education Center of Agriculture and Natural Resources in the south of Kerman province. Irrigation as the main plot at three levels of 100, 70 and 50% of water requirement and mulching at three levels of crushed date palm leaf, black plastic and no mulch, as the sub-plot, were considered. Crimson B 34 watermelon seeds produced by Seminis company, were planted on January 2021, in plots with the size of 13.5 × 7 m, on furrows and ridges planting system (the width of furrows and ridges were 0.5 and 4 meters, respectively). After planting, bow-shaped wires were put on the planting rows and a transparent plastic was placed as a tunnel on them. In the first year, the total depth of the irrigation in aforesaid treatments was respectively 444, 321, 237, 413, 389, 435, 345 and 425, and in the second year 427, 303, 223, 395, 373, 416, 331 and 405 mm.
Results and Discussion: The results showed that the highest and lowest yield were observed in full irrigation and irrigation 50 % (60.1 and 16.3 t ha-1 respectively). Among the regulated deficit irrigation treatments, irrigation 50% at the seedling stage was the closest to full irrigation, and the irrigation 50 % at the fruit expansion stage had the lowest yield. the highest water productivity belonged to the irrigation 50 % in the seedling and vine stages (15.9 and 1.15 kg m-3 respectively). Irrigation 50% in fruit maturity stage despite irrigation 50% improved Qualitative characteristics such as soluble solids, vitamin C, dry matter, lycopene and fruit taste.
Conclusion: By applying of deficit irrigation with intensities used in this study, compared to full irrigation (control), a significant decrease in watermelon yield was observed. water productivity remained almost constant, there was no significant increase in the quality of the edible part, but treatments of regulated deficit irrigation including seedling stage in terms of yield without significant difference with full irrigation and irrigation 50 % of vine stage in terms of water productivity and irrigation 50% of fruit maturity stage were superior in terms of quality compared to the control. generally regulated deficit irrigation had better results than deficit irrigation due to less yield reduction, increased water productivity and fruit quality in the watermelon, which it can be noticeable in the conditions of water restriction. Finally, it is recommended that milder intensities of deficit irrigation that seem to have more favorable results in this plant should be investigated in the next studies.
Acknowledgement:
Irrigation
Helaleh Fahimi; Abd0llah Faraji; bohlul alijani
Abstract
Arabia Antyciclone (AA), is a component of atmospheric circulation affecting the cold-period precipitation in Iran. This study aimed to investigate the role of AA on the cold-period extreme precipitation in Iran. To this end, 7 patterns with the highest extreme precipitation and the highest spatial homogeneity ...
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Arabia Antyciclone (AA), is a component of atmospheric circulation affecting the cold-period precipitation in Iran. This study aimed to investigate the role of AA on the cold-period extreme precipitation in Iran. To this end, 7 patterns with the highest extreme precipitation and the highest spatial homogeneity during a 31-year period (1989-2020) were investigated. Using the ERA5 data, geopotential altitude and specific humidity maps were plotted. The results showed that the location and expansion of the AA changed under the influence of the tropical penetration of Western systems at different levels. By ascending to higher levels, due to the greater influence of Western systems, the AA finds a more southern position, and its effects on Iran are diminished. The AA in interaction with the mid-latitude cut off low and the southern branch of the westerlies leads to the formation of an atmospheric river (AR) with a tropical origin. Moreover, with its anticyclonic current, it leads to the humidity feeding of the atmospheric river along its way to enter Iran. Meanwhile, it is an important factor in the transfer of humidity to East Central Africa, where the atmospheric river is formed. At the ground level, the AA diverts humidity from the Arabian Sea and the Persian Gulf to the western and northwestern regions, preventing widespread entry of the Turkey low into the western and southwestern regions of Iran. It also prevents Sudan low from entering the Middle East by entering the southern Red Sea. Arabia Antyciclone (AA), is a component of atmospheric circulation affecting the cold-period precipitation in Iran. This study aimed to investigate the role of AA on the cold-period extreme precipitation in Iran. To this end, 7 patterns with the highest extreme precipitation and the highest spatial homogeneity during a 31-year period (1989-2020) were investigated. Using the ERA5 data, geopotential altitude and specific humidity maps were plotted. The results showed that the location and expansion of the AA changed under the influence of the tropical penetration of Western systems at different levels. By ascending to higher levels, due to the greater influence of Western systems, the AA finds a more southern position, and its effects on Iran are diminished. The AA in interaction with the mid-latitude cut off low and the southern branch of the westerlies leads to the formation of an atmospheric river (AR) with a tropical origin. Moreover, with its anticyclonic current, it leads to the humidity feeding of the atmospheric river along its way to enter Iran. Meanwhile, it is an important factor in the transfer of humidity to East Central Africa, where the atmospheric river is formed. At the ground level, the AA diverts humidity from the Arabian Sea and the Persian Gulf to the western and northwestern regions, preventing widespread entry of the Turkey low into the western and southwestern regions of Iran. It also prevents Sudan low from entering the Middle East by entering the southern Red Sea. Arabia Antyciclone (AA), is a component of atmospheric circulation affecting the cold-period precipitation in Iran. This study aimed to investigate the role of AA on the cold-period extreme precipitation in Iran. To this end, 7 patterns with the highest extreme precipitation and the highest spatial homogeneity during a 31-year period (1989-2020) were investigated. Using the ERA5 data, geopotential altitude and specific humidity maps were plotted. The results showed that the location and expansion of the AA changed under the influence of the tropical penetration of Western systems at different levels. By ascending to higher levels, due to the greater influence of Western systems, the AA finds a more southern position, and its effects on Iran are diminished. The AA in interaction with the mid-latitude cut off low and the southern branch of the westerlies leads to the formation of an atmospheric river (AR) with a tropical origin. Moreover, with its anticyclonic current, it leads to the humidity feeding of the atmospheric river along its way to enter Iran. Meanwhile, it is an important factor in the transfer of humidity to East Central Africa, where the atmospheric river is formed. At the ground level, the AA diverts humidity from the Arabian Sea and the Persian Gulf to the western and northwestern regions, preventing widespread entry of the Turkey low into the western and southwestern regions of Iran. It also prevents Sudan low from entering the Middle East by entering the southern Red Sea.
Irrigation
Seyed Abolghasem Haghayeghi Moghaddam; Fariborz Abbasi; Abolfazl Nasseri; Peyman Varjavand; Sayed Ebrahim Dehghanian; Mohammad Mehdi Ghasemi; Saloome Sepehri; Hassan Khosravi; Mohammad Karimi; Farzin Parchami-Araghi; Mustafa Goodarzi; Mokhtar Miranzadeh; Masoud Farzamnia; Afshin Uossef Gomrokchi; Moinedin Rezvani; Ramin Nikanfar; Seyed Hassan Mousavi fazl; Ali Ghadami Firouzabadi
Abstract
Introduction
The basic strategy to mitigate water crisis is to save agricultural water consumption by increasing productivity, which will result in more income for farmers and sustainable production. Due to the economic importance of barley production in the country, it is necessary to study the volume ...
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Introduction
The basic strategy to mitigate water crisis is to save agricultural water consumption by increasing productivity, which will result in more income for farmers and sustainable production. Due to the economic importance of barley production in the country, it is necessary to study the volume of irrigation water and water productivity to produce this strategic product. Based on extensive field research on irrigation water management and application of different irrigation methods in barley farms, the innovations of this research were: a) measuring water consumed and determining water use efficiency in barley production, b) the up-to-date of the measurements and research findings, c) findings applicability for application in agricultural planning at the national and regional levels, d) the ability to development the findings in barley farms at the national level to improve water use efficiency. The hypotheses of this research are: a) barley irrigation water is various in different regions, b) water applied in barley farms is more than the required one, c) the water use efficiency of barley is different in the main production areas, and d) The applied water of barley is not the same in different irrigation methods. Therefore, the main objective of this study is to determine the water consumed and water use efficiency in barley production; to measure the water applied to barley farms in the main production areas; to compare the water measured in the production areas with the net irrigation requirement; and finally to determine water use efficiency of the barley in the main production areas in the Iran.
Materials and Methods
For this purpose, the volume of irrigation water and barley yield in 296 selected farms in 12 provinces (about 75% of the area under cultivation and production of barley in Iran) including Khuzestan, East Azerbaijan, Ardabil, North Khorasan, Fars, Khorasan Razavi, Tehran, Semnan, Markazi, Isfahan, Hamedan and Qazvin were measured directly. Farms in the mentioned provinces were selected to cover various factors such as irrigation method, level of ownership, proper distribution and quality of irrigation water. By carefully monitoring the irrigation program of selected farms during the growing season, the amount of irrigation water for barley during one year was measured. At the end of the season and after determining the average yield of barley during the 2020-2021 year, the values of irrigation water productivity and total water productivity (irrigation+effective rainfall) were determined in selected barley farms in each region. The volume of water supplied was compared with the gross irrigation requirements estimated by the Penman-Monteith method using meteorological data from the last ten years, and compared with the values of the National Water Document. Analysis of variance was used to investigate the possible differences in yield, irrigation water and water productivity in barley production.
Results and Discussion
To assess the reliability of statistical analysis, we evaluated the sufficiency of the number of measurements needed for both the quantity of irrigation water and the ley yield on the farms. Subsequently, we computed statistical indices, such as the mean and standard deviation. The results showed that the number of measurements of irrigation water and barley yield was to be 296 and 283, respectively, which was more than the number of measurements required for irrigation water (41 dataset) and yield (50 dataset). Therefore, the sufficiency of the data for the statistical analysis was reliable. The results showed that the difference in yield, volume of irrigation water and water productivity indices were significant in the mentioned provinces. The volume of barley irrigation water in the studied areas varied from 1900 to 9300 cubic meters per hectare and its average weight was 4875 cubic meters per hectare. The average barley yield in selected farms varied from 1630 to 7050 kg ha-1 and the average was 3985 kg ha-1. Irrigation water productivity in selected provinces ranged from 0.22 to 1.53 and its weight average was 0.90 kg m-3. Average gross irrigation water requirement in the study areas by the Penman-Monteith method using meteorological data of the last ten years and the national water document were 4710 and 4950 cubic meters per hectare, respectively. Irrigation efficiency of barley fields in the country is estimated at 62-65% without deficit irrigation.
Conclusion
In order to reduce water consumption and improve water productivity, it is suggested to manage water delivery to farms during the season and deliver water rights to them according to crops water requirements. To reduce water losses and enhance productivity in the barley farms, it is suggested the application of modern irrigation systems according to the farms conditions with the suitable operation; and modification and improvement of surface and traditional irrigation methods. Note that, water is only one of several necessary and effective inputs in the optimal and economic production of barley. On the other hand, attention should be paid to the optimal application of other inputs including: seeds, fertilizers, equipment and tools etc.
Irrigation
Hajar Norozzadeh; Mahsa Hasanpour Kashani; Ali Rasoulzadeh
Abstract
Climatic changes and human activities are among the important factors that affect the flow of rivers and it is very important to determine the contribution of these factors in order to better manage water resources. In recent years, there have been major changes in the watersheds, and the amount of runoff ...
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Climatic changes and human activities are among the important factors that affect the flow of rivers and it is very important to determine the contribution of these factors in order to better manage water resources. In recent years, there have been major changes in the watersheds, and the amount of runoff and river flow has decreased, or in some cases, the flow has increased due to the occurrence of floods. The issue of reducing the amount of runoff, especially in the arid and semi-arid regions of Iran, is one of the basic challenges related to the management of water resources. Hydrological changes primarily result from a combination of natural or climatic factors, including precipitation levels, air temperature, and overall warming of the Earth. Additionally, human activities, such as the construction of dams, creation of reservoirs, urbanization expansion, and indiscriminate harvesting, play a significant role. It is important to note that these factors are interconnected, and alterations in one can impact the others. The increase of greenhouse gases and climate change has caused a change in the hydrological cycle and the amount of runoff in the watersheds and has increased the number of climatic extreme events. The main purpose of this study is to determine the contribution of each of these factors on the discharge changes of the Gharehsoo River, one of the most important rivers of Ardabil province, using elasticity-based methods (non-parametric and Bodiko-based methods).
Materials and Methods
In this research, firstly, in order to determine the point of change in the amount of river runoff and to divide the base and change period, Petit's test was used during the statistical period of 1984-2019. This test was done using Xlstat software. According to the results of this test, there was a change in the annual flow time series in 1997, which was considered as the base period from 1984 to 1997 and from 1998 to 2019 as the period of changes. Then, the contribution of each of these factors was determined using elasticity-based methods.
Results and Discussion
In the elasticity-oriented method, the non-parametric method and the methods based on Bodiko's assumptions were used to calculate the elasticity coefficient.The results showed that in Samyan station, in the non-parametric method, the contribution of human activities is 88.26% and the contribution of climate change is 11.74%. The contribution of human activities and the contribution of climate change for the methods of Schreiber, Aldekap, Bodiko, Peek and Zhang, respectively 91.98 and 8.02, 90.02 and 9.97, 91.98 and 8.02, 90.80 and 9.20, 92.37 and 7.62 are estimated. In general, in the elasticity method, the contribution of human activities is 88.26 to 92.37 percent and the contribution of climate change is from 7.63 to 11.74 percent, depending on the non-parametric and Bodiko method. At the Dost-Beiglo station, employing the non-parametric method reveals that human activities account for 96.13% of the observed changes, while the remaining 3.87% is attributed to climate change. The contribution of human activities and the contribution of climate change for the methods of Schreiber, Eldekap, Bodiko, Pick and Zhang are 97.71 and 2.29, 97.42 and 2.58, 97.56 and 2.44, 97.48 and 2.52, 97.71 and 2.29 are estimated. In general, in the elasticity-oriented method, the contribution of human activities between 96.13 and 97.71 percent and the contribution of climate change from 2.29 to 3.87 percent, depending on the non-parametric and Boudico-oriented method, have been met.
Conclusion
In this research, different hydrometeorological data such as precipitation, evaporation and transpiration and monthly discharge from the Samyan and Dost Beiglo stations were used for the statistical period of 1982-2019. First, by using Pettitt's test, it was determined that the river flow rate has changed abruptly since 2016. Therefore, the entire statistical period was divided into two natural and change periods, and then, using elasticity-based methods, the contribution of human activities and the contribution of climate change were determined. According to the results obtained in both stations, the impact of human activities (more than 88%) on the basin's runoff is far more than climate change (less than 11%). Therefore, it seems necessary to prevent the effective human activities on reducing the river flow in solving and managing water problems in the basin.
Irrigation
M. Fallahi khoshhi; A.R. Karbalaee Doree; Z. Hedjazizadeh; P. Hamezadeh
Abstract
Introduction
The large temporal and spatial changes of precipitation, especially in mountainous areas, have turned it into a controversial variable in climate models. Measuring precipitation (rain and snow) along with its distribution and changes is very important to improve our understanding of global ...
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Introduction
The large temporal and spatial changes of precipitation, especially in mountainous areas, have turned it into a controversial variable in climate models. Measuring precipitation (rain and snow) along with its distribution and changes is very important to improve our understanding of global water cycle and energy, water resources monitoring, hydrological modeling. Lack of reliable data is one of the most important challenges in rainfall analysis. Due to the significant temporal and spatial variability of precipitation in mountainous areas, accurate spatially distributed data is crucial for effective water resource assessment and management. However, many mountainous regions have limited rain gauge stations. Today, satellite products are commonly used to measure precipitation in these areas, but the variability among these products raises concerns about their accuracy in mountainous regions. Additionally, the quality of satellite products differs between various products and across different climatic regions, making it essential to thoroughly evaluate them before use. The purpose of this research was to evaluate the precipitation data of two satellite products (GPM, PERSIAN) and reanalysis data (ECMWF) in the estimation of precipitation in mountainous areas without stations in Lorestan province.
Method
This study utilized rainfall data from 24 synoptic and rain gauge stations across Lorestan province. Emphasis was placed on stations situated in or near mountainous regions. The selected stations were chosen based on their suitable spatial distribution and record length. The rainfall data spanned the period from 2015 to 2021 and included daily, monthly, and annual measurements. To evaluate satellite rainfall algorithms and estimate rainfall in regions with limited data, data from the GPM and PERSIAN satellites were employed, along with ECMWF reanalysis data. The PERSIAN rainfall algorithm is a remote sensing-based method that utilizes artificial neural networks. It calibrates infrared data with passive microwave estimates and converts longwave infrared images into rainfall estimates using a three-step process. The spatial resolution of this product is 0.25° x 0.25°, and it offers hourly, daily, and monthly temporal resolution. The PERSIAN rainfall algorithm data can be accessed from https://chrsdata.eng.uci.edu. The GPM mission aims to provide continuous observations of Earth's precipitation. It employs the GPM Microwave Imager (GMI) and Dual-frequency Precipitation Radar (DPR) to observe both snow and rain. The final product, called IMERG, is generated through multiple runs of the algorithm for each observation time. Initial estimates are quickly provided, and subsequent estimates improve as more information becomes available. The spatial resolution of the GPM product is 1° x 1°, and it offers hourly, daily, and monthly temporal resolution. IMERG data can be obtained from https://gpm.nasa.gov/data. CMWF reanalysis data is derived from the combination of short-term simulations of numerical weather prediction models with ground-based observational data. These simulations are controlled with observational data, and the resulting reanalysis database provides global coverage from 1979 with a spatial resolution ranging from 0.125° x 0.125° to 3°. The temporal resolution of ECMWF reanalysis data is hourly, daily, and monthly. More information about ECMWF data can be found at https://www.ecmwf.int/ (Azizi, 2019). To evaluate the accuracy of the products, R-squared correlation (R2), root mean square error (RMSE), standard deviation (MAD), correlation coefficient (R), error deviation (MBE) and Nash-Sutcliffe coefficient (NS) were used. Also, the probability of detection (POD), false alarm ratio (FAR), and critical success index (CSI) indices were used to validate the data.
Results
The results showed that none of the three products are suitable for estimating daily precipitation in mountainous areas. However, on a monthly scale, these products provide reasonable estimates. Among the three, the GPM satellite product demonstrated better accuracy on a monthly scale, based on error levels and the spatial distribution of estimated precipitation. On an annual scale, GPM also performed best, as indicated by both statistical errors and the spatial patterns of average annual precipitation. According to the MBE index, on daily and monthly scales, the ECMWF product tended to overestimate precipitation, while the PERSIANN and GPM products underestimated it. On an annual scale, GPM and ECMWF products overestimated precipitation, whereas PERSIANN underestimated it.
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.
Irrigation
A. Vaezihir; M. Khalkhali; M. Tabarmayeh
Abstract
Introduction Groundwater is an important resource for domestic, agricultural, and industrial purposes (Andualem and Demeke, 2019). However, the growing population and advanced irrigation technologies have significantly led to increased groundwater exploitation resulting in aquifer depletion. Exploitation ...
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Introduction Groundwater is an important resource for domestic, agricultural, and industrial purposes (Andualem and Demeke, 2019). However, the growing population and advanced irrigation technologies have significantly led to increased groundwater exploitation resulting in aquifer depletion. Exploitation of groundwater from fractured rock aquifers using wells to supply drinking water is more sustainable than the utilization of springs with low and variable discharge. In the case of drought and periods of critical condition of water usage, springs of fractured rock aquifers may dry up or decrease making them unreliable water resources to supply drinking water. Over recent decades, the use of fractured rock and karstic units as a remarkable water resource is known as a valuable source of freshwater worldwide. However, these aquifers are extremely vulnerable to contamination due to their unique hydrogeological characteristics and require more protection (Zarvash & Vaezi, 2014). These resources contribute to providing more than 70% of the rural population and around 50% of the urban population with drinking and household demand needs. Since the degree of development of karst landforms varies substantially from region to region, exploring groundwater potential zones in karstic or fractured rock domains across the world is important, which is mostly achieved using evaluating affecting factors in creating the groundwater occurrence. This evaluation is done by incorporating weighted factors such as Weighted Overlay, Weighted Sum, and Fuzzy Overlay and utilizing geographic information systems (GIS) or other remote sensing techniques, which is addressed frequently in literature summarized by Vaezihir and Tabarmayeh (2016); Seif and Kargar (2011); and Amiri et al. (2021). Considering the importance of such issue, this research aims to investigate the potential of karstic or fractured rock resources in West Azerbaijan to gain more insight into this valuable resource of groundwater. Materials and MethodsWest Azerbaijan province, with an area of 43,660 km² including Lake Urmia, is equivalent to 2.65% of the total area of Iran and located in the Alborz-Azerbaijan structural zone with a mean annual precipitation of about 370 mm. The maximum temperature of this province, dominated by a semi-arid and Mediterranean climate, is recorded in Shahin Dezh and Miandoab, and the minimum is measured in Chaldoran, and Tekab Metrological Stations, respectively. About 78% of the total area of West Azerbaijan province is formed by karstic units with more spatial distribution in the southern area. This karstic area encompasses 71% of the total province springs with 59% of the total discharge. In the current research, lithology unit types, fracture density, elevation, slope, aspect, drainage density, and vegetation coverage, along with the precipitation, area, and humidity index as the main factors were regarded as governing factors in the development of karst aquifers, have been considered to evaluate the potential groundwater resources. After the preparation of all affected layers using various data resources including available geological maps digital elevation map of West Azerbaijan Province obtained from the Geological Survey and Mineral Exploration of Iran, Landsat satellite data, the Fuzzy logistic and SUM and Weighted overlay technique has been used to prepared groundwater potential zone. Results and DiscussionThe groundwater potential zone were determined through combining 9 affected layers in developing the groundwater resource. The results obtained based on employing both weighted overlay and SUM were classified into 5 classes including low, very low, medium, high and very high potential zones. The index value in SUM methods estimated to be 16.24, 26.24, 24.24, 20.95, 12.13%, while it changes to 22.82, 24.13, 22.14, 16.23, and 14.67 respectively. Overlaying the location of springs as an indicators of groundwater resource on hardrock and karstic domain on generated maps showed that 30.9 and 33.08 percentage of springs fall in area with the high and very high potential zone, respectively. A significant differences on maps generated based on two mentioned technique, particularly in area classified as low potential zone with 24.13 and 16.24 percent in weighted overlay and SUM. ConclusionInvestigation of the groundwater potential zone by integrating the layer provided by Fuzzy logic technique through two SUM and weighted overlay methods indicated the province of Azerbaijan Arabi has a moderate level of classification. However, in some areas, there were significantly higher or lower potentials.
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.
Irrigation
A. Kazemi Choolanak; F. Modaresi; A. Mosaedi
Abstract
IntroductionPredicting river flow is one of the most crucial aspects in water resources management. Improving forecasting methods can lead to a reduction in damages caused by hydrological phenomena. Studies indicate that artificial neural network models provide better predictions for river flow ...
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IntroductionPredicting river flow is one of the most crucial aspects in water resources management. Improving forecasting methods can lead to a reduction in damages caused by hydrological phenomena. Studies indicate that artificial neural network models provide better predictions for river flow compared to physical and conceptual models. However, since these models may not offer reliable performance in estimating unstable data, using preprocessing techniques is necessary to enhance the accuracy and performance of artificial neural networks in estimating hydrological time series with nonlinear relationships. One of these methods is wavelet transformation, which utilizes signal processing techniques. Materials and MethodsIn this study, to evaluate the efficiency of discrete and continuous wavelet types in the Wavelet-Artificial Neural Network (WANN) hybrid model for monthly flow prediction, a case study was conducted on the Kardeh Dam watershed in the northeast of Iran, serving as a water source for part of Mashhad city and irrigation downstream agricultural lands. Monthly streamflow estimates for the upstream sub-basin of the Kardeh Dam were obtained from the meteorological and hydrometric stations' monthly statistics over a 30-year period (1991-2020). The WANN model is a hybrid time series model where the output of the wavelet transform serves as a data preprocessing method entering an artificial neural network as the predictive model. The combination of wavelet analysis and artificial neural network implies using wavelet capabilities for feature extraction, followed by the neural network to learn patterns and predict data, potentially enhancing the models' performance by leveraging both methods. The 4-fold cross-validation method was employed for the artificial neural network model validation, where the model underwent validation and accuracy assessment four times, each time using 75% of the data for training and the remaining 25% for model validation. The final results were presented by averaging the validation and accuracy results obtained from each of the four model runs. To evaluate and compare the performance of the models used in this study, three evaluation indices, Nash-Sutcliffe Efficiency (NSE), Root Mean Square Error (RMSE), and Pearson correlation coefficient (R), were employed. Results and DiscussionThe analysis of meteorological and hydrometric data in this study revealed that monthly streamflow in two time steps, T-1 and T-2, were the most effective predictive variables. Each of the two runoff variables of the previous month (Qt-1) and the previous two months (Qt-2) were analyzed by each of the Haar and Fejer-Korovkin2 discrete wavelet transforms and the two continuous Symlet3 and Daubechies2 wavelets at three levels. The results of each level of decomposition was given as input to the ANN model. The presented results at each decomposition level indicated that hybrid models could accurately predict lower flows compared to the single ANN model, and the estimation of maximum values also significantly improved in the hybrid models. Among the wavelets used, Haar wavelets exhibited the weakest performance, and the less commonly employed Kf2 wavelet showed a moderate performance. Since the Haar and Fk2 wavelets, with their discrete structure, did not perform well in decomposing continuous monthly streamflow data, continuous wavelet models outperformed discrete wavelet models. The hybrid models, combining wavelet analysis and artificial neural networks, demonstrated up to an 11% improvement over the performance of the single neural network model. ConclusionStreamflow is a crucial element in the hydrological cycle, and predicting it is vital for purposes such as flood prediction and providing water for consumption. The objective of this research was to evaluate the performance of different types of discrete and continuous wavelet models at various decomposition levels in enhancing the efficiency of artificial neural network (ANN) models for streamflow prediction. Since climate and watershed characteristics can influence the nature of data fluctuations and, consequently, the results of the wavelet model decomposition, choosing an appropriate wavelet model is essential for obtaining the best results. Considering the existing variations in the results of different studies regarding the selection of the best wavelet type, it is suggested to use both continuous and discrete wavelet types in modeling to achieve the best predictions and select the optimal results. Given that a lower number of input variables in neural network models lead to higher accuracy in modeling results, it is recommended to perform decomposition at a two-level depth to reduce input components to the neural network model, thereby reducing the model execution time.
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.
Irrigation
S. Habibi; M. Khoshravesh; R. Nouri Khajebelagh
Abstract
IntroductionIn today's world, challenges related to agriculture, food security, water and energy resources, productivity, and greenhouse gas emissions have emerged as significant issues for global societies. Through their international impacts, these challenges have led to economic, social, and environmental ...
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IntroductionIn today's world, challenges related to agriculture, food security, water and energy resources, productivity, and greenhouse gas emissions have emerged as significant issues for global societies. Through their international impacts, these challenges have led to economic, social, and environmental changes on a global scale. One of the most crucial issues that should be highlighted is the shortage of water resources. Water, as a vital factor in agriculture and food production, holds special importance. Therefore, in order to achieve sustainable agriculture, it is necessary to pay attention to the energy indicators, the efficiency of water consumption in the production of agricultural products and the amount of greenhouse gas emissions. In general, a combination of energy indicators, water efficiency and reduction of greenhouse gas emissions in agriculture can help to develop sustainable agriculture and preserve the environment and help to provide safe and accessible food for the society. The aim of the present study was to investigate the indicators of physical water, energy efficiency, and greenhouse gas emissions on alfalfa and barley crops in two different climates: a warm and arid climate (Shahr-e-Qom Plain, Qom) and a temperate and humid climate (Sari Plain, Mazandaran). This was done to assess the impact of climate on the outcomes of these indicators. Materials and MethodsTo investigate the physical water efficiency and evaluate energy indicators in this study, major agricultural products in Sari and Sharifabad Plains, including barley and alfalfa, were analyzed using cross-sectional data from the agricultural year 2021-2022. Initially, the sample size was determined based on the Cochran formula and the Bartlett method (2001). Subsequently, sampling was carried out using a questionnaire designed by the researchers themselves. The questionnaires totaled 250 (Sari Plain: 150, Sharifabad Plain: 100), and the collected information included the amount of input consumption and production quantity. The questionnaire, designed by the researcher, was validated for validity and reliability by experts and specialists. The inputs used in the study of water efficiency and energy indicators for the mentioned products in Sari and Sharifabad Plains included person-days of human labor, machine working hours, fuel consumption of machines, the quantity of nitrogen, phosphorus, potassium fertilizers per hectare, the quantity of various chemical pesticides (herbicides, fungicides, and insecticides) per liter per hectare, the amount of water consumption in cubic meters per hectare, and the amount of seed consumption in kilograms per hectare.Results and DiscussionThe results of the descriptive statistics of input consumption in Sari and Sharifabad Plains in barley and alfalfa crops showed that the highest input consumption of manpower in the cultivation of alfalfa crops in Sharifabad Plains with an average of 225 hours per hectare, the highest amount of fertilizer consumption related to the alfalfa crop in Sharifabad Plain is related to nitrogen fertilizer with an average of 130 kg per hectare, the highest amount of fuel consumption of machinery related to alfalfa crop in Sari Plain with an average of 405 liters per hectare, the highest amount of water consumption related to alfalfa crop in Sharifabad Plains with an average of 17500 cubic meters per hectare and the highest yield of alfalfa was obtained in Sharifabad Plains with an average of 11550 kg per hectare. The obtained results indicated that the highest input energy level in Sharifabad Plain for alfalfa was 5,674.50 MJ per hectare. The results of energy efficiency indicated that alfalfa production in Shahrifabad Plain had the highest value with 0.19 kilograms per MJ, while this index for alfalfa in Sari Plain was 0.13 kilograms per MJ. Additionally, the energy efficiency for barley in Shahrifabad Plain was 0.13 kilograms per MJ, and for Sari Plain, it was 0.12 kilograms per MJ, showing a somewhat similar level. The physical water use efficiency results revealed that the highest and lowest efficiency levels were observed for barley in Sari Plain, amounting to 0.96 kilograms per cubic meter, and for alfalfa in Shahrifabad Plain, amounting to 0.57 kilograms per cubic meter, respectively. Furthermore, this index for alfalfa in Sari Plain was 0.67 kilograms per cubic meter, and for barley in Shahrifabad Plain, was 0.8 kilograms per cubic meter. The results for greenhouse gas emissions demonstrated that the level of emissions in Sari Plain was higher than Sharifabad Plain, attributed to excessive fertilizer and pesticide use in Sari Plain. The highest greenhouse gas emissions in Sari Plain for alfalfa were 2681.65 kilograms of CO2 per hectare, while in Sharifabad Plain, was 2351.85 kilograms of CO2 per hectare. ConclusionThe overall results indicated that crop performance in humid regions was not higher than in dry and semi-arid regions, and this index depends on various parameters, including water consumption and managerial considerations. However, water consumption in temperate and humid regions is significantly lower than in dry and semi-arid areas due to higher precipitation. This result is increased efficiency in temperate and humid regions.
Irrigation
M. Zokaee Khosroshahi; K. Parvizi
Abstract
IntroductionWater is a critical factor for the growth and fruiting of the grapevines. Considering the water scarcity crisis in Iran and most parts of the world in recent years, it is necessary to apply methods such as deficit irrigation for the optimal management of water use in agriculture. It has been ...
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IntroductionWater is a critical factor for the growth and fruiting of the grapevines. Considering the water scarcity crisis in Iran and most parts of the world in recent years, it is necessary to apply methods such as deficit irrigation for the optimal management of water use in agriculture. It has been determined that by deliberately reducing water consumption in vineyards, it is possible to preserve the existing water resources and improve the water use efficiency. Materials and MethodsA research was carried out in summer 2023 in a randomized complete block design with three replications on 8-year-old vines of the Turkmen-4 variety, to investigate the effect of deficit irrigation levels on the quantitative and qualitative traits and water use efficiency of grapevines. The vines were planted with 2 x 4 meter intervals, were trained as a vertical trellis on a bilateral cordon system, and the vineyard was irrigated by drip irrigation. The experimental treatments included full irrigation (providing 100% of vine water requirement; as control), 25% deficit irrigation (providing 75% of vine water requirement) and 50% deficit irrigation (providing 50% of vine water requirement). Irrigation of the vineyard started from May 22 and continued until November 6 at 7-day intervals, according to the conventional procedure. The water requirement of each vine in non-stressed condition was calculated by a class A evaporation pan based on reference crop evapotranspiration (ETo) and crop coefficient (Kc) throughout the season. Then, the amount of water for each treatment was determined according to the irrigation levels in the treatments and applied in volume form. Results and DiscussionThe amounts of water consumption of control, 25% and 50% deficit irrigation treatments were 5140, 3855 and 2570 m3 per hectare, respectively. The results showed that irrigation levels had a significant effect on the berries length, berries diameter, cluster length, cluster width, berries weight, cluster weight, sugar percentage, chlorophyll index, relative water content, midday leaf water potential, vegetative growth, vine yield, yield index and water use efficiency. The 25% and 50% deficit irrigation treatments caused a decrease of 7.2% and 14.2% of the berry length compared to full irrigation, respectively. Also, these treatments caused a reduction of 8.3% and 13.9% of the berry diameter, respectively. While the 25% deficit irrigation treatment had no significant effect on the berries sugar content (°Brix), the 50% deficit irrigation treatment caused a significant decrease (5%) in sugar content compared to the control. Both relative water content and midday water potential of the leaves decreased significantly with the reduction of irrigation levels. Reducing the level of irrigation led to a significant decrease in the SPAD index and vine vegetative growth. Increasing the intensity of deficit irrigation had a significant negative effect on yield components including berry weight, cluster weight, vine yield and yield index. The highest and lowest yields were obtained from full irrigation and 50% deficit irrigation, respectively but the effect of 25% deficit irrigation on yield reduction was not significant. Although the 25% and 50% deficit irrigation treatments caused a 5.8% and 27.5% decrease in vine yield, respectively but these treatments increased water use efficiency by 34% and 44.5%, respectively compared to the control. The lowest water use efficiency was related to the control (3.53 kg of fresh fruit per cubic meter of water used), while the water use efficiency of vines under 25% and 50% deficit irrigation was 4.73 and 5.10 kg of fruit per cubic meter of water, respectively. The 25% and 50% deficit irrigation treatments had a statistically significant difference with the control in terms of water use efficiency, but the difference between the two was not significant. ConclusionIn the present study, reducing the volume of irrigation water led to a decrease in vine yield, but what is important is the low yield reduction rate compared to the amount of water consumption. The decrease in vine yield was 5.8% and 27.5%, respectively with a 25% and 50% decrease in water consumption. Also, with 25% and 50% reduction in water consumption, the yield index decreased by 6.1% and 27.3%, respectively. Meanwhile, the water use efficiency of vines increased by 34% and 44.5% in response to 25% and 50% deficit irrigation treatments, respectively. It is recommended to apply 25% deficit irrigation to increase the water use efficiency of Turkmen-4 grapes in climatic conditions of Malayer, but 50% deficit irrigation leads to a decrease in quality of grapes.
Irrigation
A. Noori; J. Omidvar; F. Modaresi; K. Davary; S. Nouri; A. Asadi
Abstract
IntroductionLimited fresh water resources and access to these resources as well as providing food security for the growing world population have led researchers to make extensive efforts in the field of optimal management of water consumption and determining the cultivation pattern in different regions. ...
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IntroductionLimited fresh water resources and access to these resources as well as providing food security for the growing world population have led researchers to make extensive efforts in the field of optimal management of water consumption and determining the cultivation pattern in different regions. Therefore, identifying cultivated crops in a region and determining their area can be very effective in land management and water allocation in these regions. With the growth and advancement of technology in the field of satellite and remote sensing in recent decades, the use of satellite images in order to identify types of land use and types of cultivated products has expanded greatly. Sentinel-1 (radar) and Sentinel-2 (multi-spectral) satellites have been very popular in agriculture due to their improved spatial resolution (10 meters) and appropriate time resolution (5 days for Sentinel 2 and 12 days for Sentinel 1).Materials and MethodsThe studied area is located downstream of the Fariman dam in an area of 22.51 square kilometers (5122 hectares) and the central coordinates are 35 degrees 41 minutes and 59 seconds north latitude and 59 degrees 50 minutes and 49 seconds east longitude. In order to classify satellite images and produce crop maps, ground observation data is needed to train the classification model and also evaluate the accuracy of the results. For this purpose, sample points were taken from different land uses in the region, using GPS. Since it was not possible to take enough samples for all land uses and crops in the determined border, a larger sampling area was selected. Then, all collected data were sorted and for each class, 70% of the data was randomly used to train the classification model and 30% was used to validate the obtained classification results. In the present study, Sentinel 2 satellite images for the first 6 months (crop season) of 2021 and 2022 and digital elevation image (DEM) of the study area were considered. According to the surveys conducted and the reports of the agricultural jihad of Fariman city, the main crops cultivated in the region include maize, tomato, sugar beet, wheat and barley. Therefore, according to the phenological stages of these products in the region, the appropriate time series of images was selected. The accuracy of the classified map was evaluated using the Kappa coefficient and overall accuracy.Results and DiscussionIn order to identify and separate the land use in the study area according to the major cultivated crops, first the agricultural calendar of the crops was determined. Then, satellite images were selected based on crop cultivation period. Based on the evaluation indexes of commission error, omission error, overall accuracy as well as the Kappa coefficient, it was observed that the identification of classes and land use was done well and with high accuracy, so that the overall accuracy for the classification map of 2022 is equal to 0.97 and the kappa coefficient value was 0.94. In order to compare land use changes during the two years 2022 and 2021, classification was also done for the images of the crop year 2021. Since the training samples of agricultural crops were not available separately and in sufficient numbers in the crop year of 2021, the classification map of this year was produced only based on the type of land use, and all crops in one class entered the classification model training process. The values of overall accuracy and kappa coefficient in 2021 were obtained as 0.97 and 0.95 respectively. According to the obtained results, the area of the orchard class has increased since 2021 compared to 2022. After repeated field visits to the study area and investigation of some land uses that had been changed and turned into orchard use, it was found that in some areas in 2022 there was the growth of villa gardens and in some areas the farmers have converted cropland to orchard (construction of an orchard). Even in some cases, the old orchard in the region was destroyed by the farmers and the land was fallow for 2 to 3 years (2021, fallow). In 2022, the farmer built a new orchard. It is also necessary to mention that fallow lands are included in the soil class depending on whether they are newly plowed or have no vegetation, and if weeds have grown on these lands, they are included in the rangeland class. ConclusionThe effective management of water resources from dams for agricultural purposes necessitates the identification of land use downstream of the dams, along with determining the types of crops and their respective areas. In this study, Sentinel 2 satellite images were employed to classify and delineate land use associated with agricultural cultivation downstream of the Fariman dam in Razavi Khorasan Province, spanning the crop years of 2021 and 2022. The results indicate that the Sentinel 2 satellite demonstrates a high capacity to differentiate between various types of land use and crops. The generated map depicting changes in land use and crop cultivation areas can be instrumental in water use planning and the allocation of water resources.
Irrigation
F. Mirchooli; I. Gholami; M. Boroughani
Abstract
IntroductionFlood is one of the most destructive natural disasters that has a negative impact on social, economic and environmental dimensions. Floods usually occur following a prolonged period of rain or snowmelt in combination with unfavorable conditions. In this regard, all over the world, the occurrence ...
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IntroductionFlood is one of the most destructive natural disasters that has a negative impact on social, economic and environmental dimensions. Floods usually occur following a prolonged period of rain or snowmelt in combination with unfavorable conditions. In this regard, all over the world, the occurrence of floods has intensified by 40% in the last two decades. In Asia, almost 90% of all human casualties caused by natural disasters are due to floods. The increase in flooding is usually due to increased environmental degradation such as urbanization, increased population growth, and deforestation. Periodic and regular occurrences of floods over a certain timeframe significantly amplify the detrimental impacts on living organisms. Urban areas in close proximity to rivers bear the brunt of these damages, owing to high population density, economic infrastructure, and transportation networks. However, these consequences can be alleviated through meticulous vulnerability analysis. One of the primary objectives pursued by researchers and policymakers is the precise modeling and zoning of floods to mitigate associated risks. Consequently, a myriad of methods and approaches have been devised for flood risk modeling and zoning to address this pressing issue. Among them, hydrological methods such as rainfall-runoff modeling and data-based techniques, which are unable to comprehensively analyze rivers and flood zones due to their one-dimensional nature. This is despite the fact that the morphology of the river is not stable and due to its high erosion potential, it also has a dynamic characteristic. In addition, these methods require fieldwork and large budgets for data collection. Hence, comprehensive flood management is necessary to reduce these effects. Therefore, this study was conducted with the aim of identifying areas sensitive to the risk of flooding in Famnat watershed located in Gilan province. Fomanat watershed is located in Gilan province and is considered a part of the first grade watershed of the Central Plateau. This area is located in the range of 36.89 to 37.57 degrees north latitude and 48.77 to 49.69 degrees east longitude. This region has an area of 3595 square kilometers, the highest point of which is 3088 meters and the lowest point is -69 meters. Materials and Methods To carry out the current research, firstly, by reviewing the sources and history of the research, as well as knowing the region, a map and layers of information related to the factors affecting flood susceptibility zoning were prepared. These layers include land use map, slope degree, geology, distance from waterway, digital map of height, direction, shape of land curvature, land curvature profile, rainfall and topographic humidity index, which are created using the collected data and also various additions in the environment. Geographic information system (Arcgis 10.4) was prepared. In this regard, machine learning models such as generalized linear model (GLM), multivariate adaptive regression model (MARS) and classification and regression tree model (CART) were used to zone the sensitivity of the watershed to floods. Also, among 100 flood events, 70% (70) were considered for training and 30% (30) for validation. In the following, using field survey and review of previous studies, 10 factors influencing the occurrence of floods in the watershed area were identified and used. Finally, the area under the ROC curve and the TSS index were used to evaluate the models.Results and Discussion The results of the evaluation of the most important factors affecting the sensitivity of the watershed to floods indicated that the distance from the river, the height and the curvature profile had the greatest impact on the sensitivity of the region, and on the other hand, the factors of slope, geology and topographic humidity index had the least impact. Based on the obtained results, the areas covered by very low, low, medium, high and very high classes in the CART model were 26.6, 17.6, 21.2, 0.1 and 34.0%, respectively. These results for the GLM model were 13.6, 12.7, 16.2, 25.1 and 32.4 percent, respectively. Based on the obtained results, the CART model performed better than other models, so that AUC for MARS model was equal to 0.76, CART model was equal to 0.9 and GLM model was equal to 0.84. Also, the better performance of CART model compared to other models was confirmed by other indicators. So, based on TSS, MARS model equal to 0.52, CART model equal to 0.77 and GLM model equal to 0.66 were obtained.ConclusionImplementing the findings of this study can facilitate the adoption of effective management strategies to mitigate losses and casualties. Moreover, in developing nations grappling with restricted access to hydrogeological and soil data, the utilization of geographic information systems (GIS) and data mining techniques assumes a pivotal role in conducting comprehensive studies. These technologies offer valuable insights and support decision-making processes, enabling proactive measures to address flood risks and enhance disaster resilience in vulnerable regions.
Irrigation
N. Jafari; Y. Dinpashoh
Abstract
IntroductionThe study of surface water quality control in water resources and environment management programs is very important. Surface water is one of the most important water sources that have crucial impact on agricultural, industrial, drinking and electricity production activities. Due to ...
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IntroductionThe study of surface water quality control in water resources and environment management programs is very important. Surface water is one of the most important water sources that have crucial impact on agricultural, industrial, drinking and electricity production activities. Due to insufficient water sources with good quality and the increase in population growth rate and as a result of the increase in demand, the study of water quality parameters is very important. The Water Quality Index (WQI) serves as a prominent indicator in classifying surface water quality. Moreover, in recent years, the TOPSIS method has gained traction for evaluating water quality. This approach, known for its simplicity, is increasingly utilized in prioritizing river water and assessing its quality. Through this index, various components of water quality are condensed into a single numerical value, effectively expressing overall water quality. To ascertain the weight index, Shannon's entropy method was employed. Furthermore, to assess water suitability for drinking, agriculture, and industrial purposes, Schuler, Wilcox, and Piper diagrams were utilized. These diagrams provide valuable insights into the quality of water, aiding in decision-making processes regarding its utilization across different sectors. Therefore, the results of this study also confirmed the effectiveness of the TOPSIS method in identifying contaminated stations.Materials and MethodsThis research focuses on evaluating the water quality of three stations within the Aji Chai river watershed on an annual basis. These stations are identified as Arzanag, Akhola, and Markid. The assessment spans the years 2003 to 2021 and aims to classify water quality for both drinking and agricultural purposes. Utilizing the standards set forth by the World Health Organization, the surface water quality index of the Aji Chai basin is investigated to ascertain its suitability for drinking purposes. Shannon's entropy theory was used to prevent expert judgments in determining the weight of each parameter. TOPSIS method was used to classify eleven qualities including TDS, EC, pH, HCO3-, Cl-, , Ca2+, Mg2+, Na+ , K+ and TH. In all the three stations water quality were ranked, based on TOPSIS numerical values. Also, in order to check the quality of drinking, agricultural and industrial water, Schuler, Wilcox and Piper diagrams were used. Results and DiscussionThe initial findings from the %RE error analysis revealed that throughout the entire statistical period (2003-2021), the %RE values were consistently close to zero, with the majority being positive. This suggests that the total number of cations surpasses the total number. In terms of the Shannon water quality index, the results indicate that Markid station exhibited the highest index value at 945.92, while Arzanag station displayed the lowest value at 127.365 among the surveyed stations. The results of the water quality index showed that Arzanag and Akhola stations are in an average condition (100 < EWQI < 150) and Markid station is in a very poor condition (EWQI > 200). According to Schuler's diagram, it was found that the water of Arzanag station is in the average level in terms of water quality, which is in a good position in terms of quality compared to the other two stations, while the water of Akhola station is in a good position. In the range of poor quality, Markid water was undrinkable, which ranked worst among the three stations. According to the Wilcox diagram, it was found that the water quality of Markid is very poor, which is even outside the boundary of the Wilcox diagram, while the water of Arzanag station was ranked 1st in terms of quality. Arzanag water is in C4S2 class in terms of quality. Finally, the water class of Akhola station was placed in the C4S4 class (in the Wilcox chart), which shows very low water quality. According to the TOPSIS method, the first priority in terms of water quality pollution belonged to Markid station. Two other stations, including Akhola and Arzanag, were ranked second and third in this respect. Therefore, the most important station in this basin is Markid station. ConclusionThe results of Shannon water quality index showed that among the stations, the highest index value is related to Markid station with a value of 945.92 and the lowest one is related to Arzanag station with a value of 127.365. According to Schoeller diagram, it was found that the water quality of Arzanag station is average, compared to the other two stations, it was in the right place and the water of Akhola station was in the range of poor quality. The quality of Markid water was found to be undrinkable, which was the worst one among all the three stations. The range of TOPSIS values in different stations is between 0.054 and 0.894, which belonged to the Arzanag and Markid stations, respective ly. According to the results of the Arzanag station, the best water quality condition and the Markid station were assigned the worst water quality condition among all the three stations.
Irrigation
Z. Bigdeli; A. Majnooni-Heris; R. Delearhasannia; S. Karimi
Abstract
Introduction
Water plays a crucial role in ensuring the sustainable development of any region. Given that our country consists primarily of arid and semi-arid regions, where the majority of rivers are also found, along with the critical state of groundwater extraction and the growing importance of surface ...
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Introduction
Water plays a crucial role in ensuring the sustainable development of any region. Given that our country consists primarily of arid and semi-arid regions, where the majority of rivers are also found, along with the critical state of groundwater extraction and the growing importance of surface water, It is crucial to have a deep understanding of the future condition of water resources within the country's watersheds (Fathollahi et al., 2015). By utilizing intelligent models, it becomes feasible to represent the inherent relationships between data that cannot be solved by conventional mathematical methods. Support vector machine (SVM) and Random Forest algorithms are two types of machine learning methods that utilize essential algorithms for making repeated and accurate predictions (Kisi & Parmarm, 2016). The most recent study conducted by Zarei et al. (2022) evaluated the risk of flooding using data mining models of SVM and RF (case study: Frizi watershed). By analyzing the results, it was found that both the SVM algorithm and the new random forest algorithm showed higher accuracy in predicting flooding risks, both in terms of the educational data and algorithmic performance. The purpose of this study is to simulate the precipitation-runoff process in the hydrometric stations at the end of the Maragheh plain (Khormazard station on the Mahpari chai river and Bonab station on the Sufichai river) in East Azerbaijan province using support vector machine and random forest modeling algorithms. This study has been conducted over a period of 43 years, making it one of the few research cases in this area.
Materials and Methods
The Maragheh Sufi chai basin is situated in the eastern region of Lake Urmia, within the East Azarbaijan province. It covers an area of 611.89 square kilometers and is located between longitudes 45° and 40´ to 46° and 25´and latitudes from 37° and 15´ to 37° and 55´ north. The average height of the basin is 1767 meters above sea level (Sharmod et al., 2015). Based on the substantial changes observed in the runoff trend in the data since 1994 (without any noticeable change in the precipitation trend), the available data was divided into two distinct periods. The first period spans from 1976 to 1994, and the second period covers the years 1995 to 2019. To simulate rainfall-runoff, first the average rainfall of Maragheh plain was calculated by polygonal method. Subsequently, this data was combined with the discharge output from Bonab and Khormazard stations, with a one-day time lag. These inputs were then utilized in two models, SVM (kernel function) and RF. For this purpose, 70% of the data was used for the training stage and 30% of the data was used for the validation stage. Then, the rainfall and runoff training sets from one day before were chosen as the predictor variables, while the runoff training set was designated as the target variable. Several combinations of runoff and rainfall inputs were evaluated for the purpose of modeling. The inputs consist of the monthly Q and P values that were recorded previously (Pt, Qt-1), while the output represents the current runoff data (Qt), with the subscript t indicating the time step. As a result, two input combinations were constructed from Q and P data (as seen in Table 3) and SVM and RF models were used for rainfall-runoff modeling to determine the optimal input combination.
Calculating average rainfall through the Thiessen Polygons method
Thiessen polygons, which are Voronoi cells, are used to define rainfall polygons that correspond to the surface area (Ai). These polygons are used to weight the rainfall measured by each rain gauge (ri). Consequently, the area-weighted rainfall is equivalent to:
(1)
Random Forest Algorithm
Random forest is a modern type of tree-based methods that includes a multitude of classification and regression trees. This algorithm is one of the most widely used machine learning algorithms due to its simplicity and usability for both classification and regression tasks.
Support Vector Machine (SVM) algorithm
Support vector machines works like other artificial intelligence methods based on data mining algorithm. The most important functions of the support vector machine model are classification and linearization or data regression.
Evaluation Criteria
To evaluate the models and compare their effectiveness, this research employs metrics such as the root mean square error (RMSE), correlation coefficient (r), explanation coefficient (R2) and Nash-Sutcliffe efficiency coefficient (NS) are used. Below are the relationships among these criteria:
(2)
(3)
(4)
(5)
Results and Discussion
Figure 6 displays the time series data for rainfall and runoff during the two study periods, before and after 1994.The analysis of the figures showed that for Bonab station, during the two study periods, the value of Kendall's statistic for precipitation variable was 0.044 and 0.028, respectively. For Khormazard station, this statistic value for the first and second period was 0.030, and 0.028, respectively. However, these values are not significant at the 95% level. This indicates that the annual rainfall for the two studied stations during these years is not statistically significant. Therefore, it is concluded that the annual rainfall in these stations between the years 1976 to 2019 did not show any significant trend. The variations observed during this period were deemed normal, suggesting that the time series of rainfall displayed fluctuating patterns. However, it should be noted that there were instances of both increasing and decreasing trends in certain years Examining the time series reveals varying trends Initially, the outflow from Bonab station (both a and b) displayed fluctuating patterns, followed by periods of both decreasing and increasing trends. However, in recent years, there has an increase in outflow from this station. The Mann-Kendall test statistic for the two study periods for this station is 0.325 and 0.512, respectively. These values are significantly different at the 95% level, indicating that the increasing trend of discharge for both time periods was statistically significant. The reason for this trend at the Bonab station, compared to other entrance stations to Lake Urmia, is the lower demand for water in the Sofichai basin for agricultural and industrial purposes, in contrast to other rivers. To explore the root cause of this issue, studies should be conducted to examine both underground and surface water sources, as well as the utilization of water in the agricultural and industrial sectors of this region. On the contrary, the trend observed at Khormazard station (c and d) is different. Unlike Bonab station, the discharge from Khormazard station exhibited a complete downward trend. The Mann-Kendall test statistic for the discharge variable during our two research periods were -0.269 and -0.412, respectively. At the 95% level, the decreasing trend of discharge in this station was found to be significant. On the other hand, it is apparent that the volume of discharge in this hydrometric station has decreased drastically since 1976 (d). Apart from 2007, when there was a sudden increase in discharge volume, the water inflow into lake Urmia has remained at its lowest level throughout the years. To analyze the Bonab and Khormazard stations during two distinct periods, rainfall and runoff statistics (average, minimum, maximum) for the first period (1976-1994) and the second period (1995-2019) are presented in Tables 4 and 5. Based on the data presented in both tables, the Bonab station displays the highest average rainfall and runoff values in the total data column, while the Khormazard station has the lowest average rainfall and runoff values.
As mentioned, in order to model rainfall-runoff data using SVM and RF models, a portion of the data was used for training purposes, while another portion was used for validation. Tables 5 and 6 present the values of the calculated statistical indicators associated with the results obtained from the training and validation sections for both SVM and RF models. According to the results of Tables 6 and 7, it is clear that in both study periods, the SVM model outperformed the RF model at the Bonab station. The SVM model demonstrated superior accuracy in simulating both flow rate and monthly rainfall. Conversely, at the Kharmazard station during these periods, the RF model displayed better performance compared to the SVM model. The modeling results in the test set for both stations revealed that the mutual correlation values for the first and second study periods at the Bonab station were 0.85 and 0.84, respectively. For the Kharmazard station, these values were 0.79 and 0.75, respectively.
Conclusion
The results indicate that for both periods at the Bonab station, the SVM model exhibited higher efficiency compared to the RF model. Conversely, at the Khormazard station, the RF model outperformed the SVM model for both periods. Mutual correlation values for the test sets were 0.85 and 0.84 for the first and second study periods at the Bonab station, respectively, for the SVM model test set. For the Khormazard station, these values were 0.79 and 0.75, respectively, for the RF model test set. Other notable findings of this research include the analysis of the time series data for rainfall and runoff over 43 years. Graphs obtained for both stations, along with the Mann-Kendall statistic for precipitation and flow parameters, revealed no discernible trend in precipitation during the two study periods. Instead, precipitation in these areas displayed fluctuating patterns However, the analysis of the time series and statistical values for the discharge of Sofichai and Mahpari chai rivers at the Bonab and Khormazard stations showed different results. In the Bonab station, the discharge exhibited fluctuations, with an increase observed in the second period. Conversely, at the Khormazard station, the discharge trend was downward in both study periods. The volume of Mahpari chai River outflow notably decreased in recent years, as evidenced by the Mann-Kendall statistic showing a decreasing trend.
Irrigation
M. Goodarzi; F. Abbasi; A. Hedayatipour
Abstract
IntroductionThe lack of water resources and increase in water demand are among the effective factors in the imbalance of the water resources in each region, and it is necessary to manage the proper use of available water resources in all activities. Water in the agricultural sector is one of the main ...
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IntroductionThe lack of water resources and increase in water demand are among the effective factors in the imbalance of the water resources in each region, and it is necessary to manage the proper use of available water resources in all activities. Water in the agricultural sector is one of the main factors of production, which should be conveyed by irrigation systems to the field level and made available for the plant roots. The necessity of macro-planning in water management and consumption imposes a comprehensive study of the amount of water consumed in the agricultural sector. Hence, this study was conducted with the objective of directly measuring and field-assessing the applied water, water productivity, and water footprint associated with the primary crops cultivated in Markazi Province, all managed by local farmers.MethodologyFor this purpose, 141 farms were selected in the major production areas of the main agricultural and horticultural crops of Markazi province with the coordination of the Agricultural Jihad centers. Then, the volume of water applied was measured without interfering in the irrigation scheduling of the users. To do so, first, the flow rate of the water source (canal, well, aqueduct or spring) was measured with a suitable device (flume and meter) in each of the selected farms. Then, by carefully monitoring the irrigation schedule of the farm, including the time of each irrigation, the number of irrigation throughout the year, as well as measuring the area under crop cultivation, the amount of water used by the crop was measured for each of the selected farms during the season. Also, based on the measured data, the amounts of blue, green and gray water footprints were determined for each of the examined crops. For this purpose, the blue, green and gray water footprints of different crops were calculated using the framework provided by Hoekstra and Chapagain (2008), and Hoekstra et al., (2011).Results and DiscussionThe irrigation intervals in the studied fields varied between 3 and 15 days with an average of 8 days and the average irrigation depth varied between 26.2 and 99 mm with an average of 67.8 mm in different crops. The results showed that the average volume of applied water for the studied crops in Markazi province was 10782 cubic meters per hectare. Also, the minimum and maximum amount of applied water for the evaluated crops was as follows: barley 3783 and 7232, alfalfa 10382 and 19797, beans 8280 and 17840, watermelon 5333 and 7174, walnuts 4420 and 29600, almonds 3850 and 13932, peaches 6872 and 17727, cherries 7050 and 14645, pomegranates 7156 and 20790, and grapes 5937 and 18168 cubic meters per hectare. Furthermore, the average value of irrigation water efficiency index and water footprint was as follows: barley 0.46 and 1642, alfalfa 0.92 and 700, bean 2924 and 0.24, watermelon 9.37 and 117, walnut 0.1 and 6706, almonds 0.16 and 6857, peach 2.48 and 242, cherries 0.73 and 875, pomegranates 1.33 and 636, and grapes 11.2 and 322. Based on the obtained results, the average total water footprint index was equal to 2102 cubic meters per ton. On average, the almond with a water footprint of 6857 cubic meters per ton had the highest share in allocating the water footprint in the crop production of the province. Whereas, the lowest water footprint related to the watermelon with a water footprint of 117 cubic meters per ton. he average values of the irrigation application efficiency index, irrigation water productivity, and water footprint for the examined farms were 72.5%, 1.79 kg/m3, and 2,102 m3/ton, respectively. In summary, the results indicate that the combined volume of irrigation water and beneficial rainfall in the irrigated fields within Markazi Province surpasses the actual water demand of the crops. This underscores the substantial impact of irrigation management on water utilization in the region.ConclusionOn average, the total volume of irrigation water and effective rainfall in irrigated fields and gardens in Markazi Province is more than the actual water requirement of the plant. In general, the results showed that irrigation management has a great impact on the amount of water use in the region. Based on the obtained results, considering that most of the farms and gardens receive water in an intermittent manner, in principle, no special attention is paid to the need for water and even effective rainfall, and the amount of water availability has the greatest impact on water consumption. Therefore, in order to reduce water consumption and improve water efficiency, it is suggested to manage the delivery of water to farmers during the season and according to their crop water needs. Also, the results of the water footprint can be used to improve water resource policies at the province level, land use studies, cropping pattern modification, and environmental sector policies.
Irrigation
A.H. Jalali; H. Salemi
Abstract
IntroductionCumin (Cuminum cyminum L.) is an annual and herbaceous plant, with a vertical, round, narrow and branched stem, with a height of approximately 30-60 cm. This plant belongs to the Apiaceae family. This family is known for having plants with aromatic taste. Iran and some countries along the ...
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IntroductionCumin (Cuminum cyminum L.) is an annual and herbaceous plant, with a vertical, round, narrow and branched stem, with a height of approximately 30-60 cm. This plant belongs to the Apiaceae family. This family is known for having plants with aromatic taste. Iran and some countries along the Mediterranean Sea are known as the primary origin for the cumin plant. In addition to Iran, cumin is cultivated in many countries such as Uzbekistan, Tajikistan, Turkey, Morocco, India, Syria, Mexico and Chile. About 300,000 tons of cumin seeds are produced in the world annually, of which China and Asian countries produce 70% and consume 90%. Short growing season (100 to 120 days), low water requirement and the possibility of rained cultivation, non-interference between cultivation and harvesting with other crops and no price fluctuation and proper economic justification are among the factors that interest farmers in cultivating this plant. In different regions, yields of 350 to more than 1000 kg of seeds are obtained from this plant, and 3350 cubic meters of pure water are needed for production. Materials and MethodsThis research was conducted in 2015 to 2017. The first year of the study included the collection and analysis of long-term climatic data of the region, and the second year included the implementation phase of the research. Analyzing meteorological data on the scale of decades and the cases of temperature, precipitation, wind speed, sunshine hours, relative humidity and evaporation from the pan were considered as criteria and by preparing the gradient equations, the rate of reference evaporation and transpiration was calculated. The required statistical information was obtained from 28 synoptic meteorological and climatology stations in Isfahan and some neighboring provinces. In the studies related to soil, apparent specific gravity and volumetric moisture content (field capacity and wilting point), soil salinity, soil texture and agricultural ability class of land in cultivation areas were considered. Soil-related information was used to calculate the soil evaporation coefficient (Ke), which describes the evaporation component in the trait (ETc). In fact, Ke is the basis for calculating the coefficient of reduction of evaporation from the surface layer (Kr) and the fraction of soil wet and exposed to air (few), and for its calculation, the presence of information related to soil characteristics is necessary. To calculate the soil characteristics, in addition to sampling from the fields in the research, the database of 1600 soil profiles in the soil and water research department of Isfahan province was also used. Results and DiscussionThe results showed that 18 cities in Isfahan province had cumin cultivation potential, which had a significant difference in terms of pure water requirement per hectare (5% level) and water consumption at different phenological stages (1% statistical level). In terms of water requirement per hectare, the cities of Isfahan province can be divided into three groups. Average water requirement per hectare in the first group (the cities of Golpayegan, Lenjan, Tiran and Karvan, Shahin and Shahr and Mime), the second group (the cities of Isfahan, Khomeini Shahr, Falavarjan, Shahreza, Kashan, Najaf Abad, Natanz), Mobarake, Dehaghan and Borkhar), and the third group (Aran and Bidgol, Ardestan, Khoor and Biabanak and Nain) were equal to 3000, 3240 and 3770 m-3 ha-1, respectively. The water requirement of the growth development stage in the cities of the third group was equal to 2029 m-3 ha-1, which was significantly different from the cities of the first and second groups (p < 1% level). According to the results, cumin might be a suitable plant for crop rotations in Isfahan province due to its low water requirement and tolerance to moisture stress. ConclusionThe water requirement for cultivating cumin in various regions of the province is notably lower compared to many common crops, such as wheat, barley, and safflower. In 10 out of the 18 cities included in the study, significant water savings of up to 3,240 cubic meters per hectare can be achieved by optimizing water transfer efficiency. For cumin cultivation, this water conservation can even reach 3,000 cubic meters in cities with cooler climates. Surprisingly, in the hot areas of Isfahan province, including Ardestan, Nain, Khoor, Biabanak, Aran, and Bidgol, it is feasible to grow cumin with a water consumption of just 3,770 cubic meters per hectare.
Irrigation
M. Koohani; J. Behmanesh; V.R. Verdinejad; M. Mohammadpour
Abstract
IntroductionLand-use changes and development of irrigated agricultural lands are very important factors that affect natural resources such as the quantity and quality of water resources and the environment. Land use change is attributed to two major processes. The first process is the change in land ...
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IntroductionLand-use changes and development of irrigated agricultural lands are very important factors that affect natural resources such as the quantity and quality of water resources and the environment. Land use change is attributed to two major processes. The first process is the change in land cover, which is related to the expansion or limitation of the area of land used (such as pasture, agricultural or urban land). The second process is a change in land cover management type (for example, changes in irrigation, fertilizer use, crop type, harvesting methods or surface impermeability). Recently the Urmia lake has been accompanied by a reduction in water resources and the continuation of this process can completely cause to dry Urmia Lake. One of the approvals of the Iranian government after the formation of the National Working Group for the Lake Urmia restoration program was to prevent the development of agricultural lands in this watershed since 2014. Unfortunately, no serious and effective action has been taken in this case yet, and this process has progressed to cause conflicts in this region. Game theory is one of the most important methods used in modeling and analyzing water and environmental resources conflicts.Materials and MethodsIn the present study, using GMCR + software, the water resources conflicts arising from agricultural land development has been analyzed. In this conflict, by accurately identifying the set of decision-makers and their strategies in the conflict process (Regional Water Company, Agriculture Organization, Justice, and Profiteering Farmers), the model was executed with 4 players, 6 options, and 64 states. Players' performance was assessed once as ideal behavior (importance to the environment, sustainable development, and preference of long-term over short-term interests) and then as the use of completing a questionnaire. Then 4 states in the ideal behavior as equilibrium states and 7 states in the condition of using the questionnaire results were extracted as equilibrium states. The conflict was also examined in the coalition state of 3 government organizations (Regional Water Company, Agriculture Organization, and Justice Organization). Finally, the most probable states of equilibrium in the game results were identified.Results and DiscussionIn the discussion concerning equilibrium points, it is crucial to consider that for resolving the dispute and the proposed solution, we need to examine not only the stability of these points but also the state's priority from the perspective of stakeholders. Based on the discussions and the output results of the conflict model using the GMCR+ model, the optimal response and conflict resolution can be found in scenario 12. This scenario holds a high priority for three key players: the Agricultural Organization, the Regional Water Company, and the Justice Department. However, it doesn't share the same level of priority with the Profiteering Farmers. The reason for this divergence lies in the preference for personal gain and profit pursuit over the broader interests of the entire catchment area.ConclusionIn recent years, despite the imposed restrictions, the Urmia Lake Basin has witnessed a notable increase in the cultivation of water-intensive crops. This shift has transformed arid lands into irrigated ones and altered agricultural areas into residential zones. According to the principles of the tax evasion game, when land development carries no moral or financial consequences for profit-driven farmers, and they are aware that regulatory institutions will not commit excessive resources to prevent and effectively combat the expansion of illegal farmlands, Profiteering Farmers will consistently engage in unauthorized development under any conflict scenario. In light of the revenue potential of this situation and the opportunity to enhance one's social standing, Profiteering Farmers will persist in unauthorized development regardless of the prevailing conflict circumstances. The findings underscore the critical role of the Regional Water Company and the Agricultural Organization. These entities must proactively employ their legal capacities to impede and deter the expansion of agricultural lands. Additionally, the Justice Organization assumes primary responsibility as a crime prevention factor, while its secondary role as a judicial enforcer within this conflict situation appears fitting. Therefore, all situations are stable for Profiteering Farmers. It seems that creating a platform and conditions in which Profiteering Farmers do not develop agricultural land themselves or do not develop land due to the protection of government institutions, can be very thoughtful and effective.
Irrigation
M. Babaei; M.T. Sattari
Abstract
IntroductionDevelopment of reservoirs helps to meet food and energy needs by supplying water for agriculture and hydropower plants. Efficient management of water resources is important and vital to overcome the problems of water leakage and meet agricultural, industrial and drinking needs. Each of these ...
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IntroductionDevelopment of reservoirs helps to meet food and energy needs by supplying water for agriculture and hydropower plants. Efficient management of water resources is important and vital to overcome the problems of water leakage and meet agricultural, industrial and drinking needs. Each of these requirements creates limitations in the way the reservoir is operated, which requires accurate information on the changes in the reservoir storage and other influential components during the operation period. In order to manage and plan water resources at country scale, using reservoir simulation models as a suitable tool in simulating processes related to dams, such as the operation of water reservoirs, will be very effective. Reservoir simulation models such as the HEC-ResSim model provide the opportunity to simulate the natural and hydrological processes related to the water resources system and the relationships between the supply and demand sectors by implementing a schematic structure of a real reservoir. Two scenarios of water savings of 20 and 30 percent were used in the current investigation. Additionally, using this method, the objectives of water resource management can be assessed.Materials and MethodsIn the present study, the use of the Latian reservoir in real conditions was simulated using the HEC-ResSim model. The simulation was carried out according to the river's inflow from 1968 to 2018, downstream water needs, energy production capacity by turbines, physical characteristics and reservoir building. The implementation of the HEC-ResSim model is summarized in three steps. The Watershed Setup module is used to introduce the general outline of the watershed. In this module, the shape and geographical location of the basin and related elements such as rivers, reservoirs, hydrometric stations and other projects in it should be specified. The Reservoir Network module is used to introduce the desired reservoir network and to enter the physical characteristics and how to use them. The Simulation module is designed to introduce the simulation period and display the model outputs. In this module, the simulation time and period and the operation pattern should be determined.Results and DiscussionAccording to the results obtained from the reservoir simulation model, the average storage capacity of Latian dam for the simulation period was estimated to be 41 million cubic meters, which shows a significant drop of 49% compared to the normal level (83 million cubic meters). Additionally, for the same period, it was estimated that the average discharge was equivalent to 5.4 cubic meters per second and the average inflow to the reservoir of the Latian dam was equal to 5.7 cubic meters per second. This is in contrast to the period's average demand, which for the area downstream of the Latian Dam is 12.1 cubic meters. The findings indicate that the reservoir of the dam frequently, and particularly at the conclusion of the simulation period, is unable to satisfy the needs of the downstream. Additionally, according to the findings of the current study, the Latian dam power plant's (Kalan) average annual hydro-electric energy production was projected to be 68,000 MWh, and the results show that in accordance with the policy of operating the Latian dam in the majority ofthe years, the Kalan power plant is able to supply the electricity required in the study area. According to the results, the average reservoir volume of Latian dam for the entire period in the first and second scenario was estimated to be 49 and 63 million cubic meters, respectively. Also, by applying the first and second water saving scenarios, the Latian dam reservoir will be able to generate 66,000 and 63,000 MWh of energy annually.ConclusionIn this study, the functioning and operation of the Latian dam reservoir was used by applying the Hec-ResSim reservoir simulation model. After entering data such as the elevation and length of the dam, surface-volume-elevation curve, evaporation from the surface of the reservoir, elevation and uncontrolled outlet coefficient, dam storage areas, rule curve, were simulated by the model. In the present study, the values of inactive volume and conservation volume of Latian Dam were estimated as 28 and 83 million cubic meters, respectively. The average water release of Latian dam for the first and second 25 years of operation was equal to 6.1 and 3.7 cubic meters per second, respectively, which met 50 and 32% of the downstream demand on average. The results indicate that the success rate of Latian dam in supplying drinking, industry and downstream environment for the period of operation is 42%. Also, 16 years out of 50 years of operation, Kalan hydropower plant has fully met 100% of the needs. On average, the large power plant is able to provide 80% of the energy needs of the study area for the entire simulation period.
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.
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
M. Goodarzi; J. Ghadbeiklou; A. Ghadiry; M.A. Khodshenas
Abstract
Introduction
Water is one of the most important factors of development in human societies, water scarcity, specially fresh water which is one of the main limitation for agricultural, economic and social development in most developing countries. Providing and implementing an optimal cropping pattern, ...
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Introduction
Water is one of the most important factors of development in human societies, water scarcity, specially fresh water which is one of the main limitation for agricultural, economic and social development in most developing countries. Providing and implementing an optimal cropping pattern, in addition to better management of water and soil resources, can lead to reducing production risk, increasing the ability to deal with crises, improving employment, better management of providing services to farmers, and providing the possibility of expanding agro-based industries. In many regions of the world, including in Iran, many studies have been done to improve the cropping pattern in different regions. Despite the existing problems in designing and implementing the appropriate cropping pattern in the plains, modifying the cropping pattern based on scientific principles and emphasizing the reduction of water consumption while reducing water consumption provides the possibility of sustainable agriculture and in terms of economic and social aspects. Implementing an optimized cropping pattern in the Farahan Plain is an undeniable necessity to preserve national resources. This study was conducted with the objective of optimizing the cropping pattern in the area, taking into account multiple criteria.
Methodology
In this research, considering the importance of determining the cropping pattern based on the multiple objectives of the decision makers, it was tried to determine the optimal cropping pattern by using mathematical programming and fuzzy logic by establishing a compromise between the objectives of the cropping pattern. The model considered for this study was in the framework of the goal of the maximum ideal distance (Fuzzy Composite Distance). Also, in order to use water resources sustainably, scenarios of cropping patterns are presented based on different conditions of water resources uses. Based on the basin's water resource stability, an optimal cropping pattern was developed to address the conditions of normal water resource exploitation, as well as sustainable and unsustainable scenarios. Each scenario corresponds to a specific period. To achieve this, a multi-objective planning approach was utilized, integrating water, food, energy, and economic profit indicators. The resulting optimal cropping pattern considers stable water resource utilization during normal, drought, and wet periods, ensuring sustainable conditions.
Results and Discussion
The results showed that the amount of water consumed by the optimal cropping pattern compared to the existing cropping pattern under normal, drought and wet conditions is reduced by 23.2, 29.2 and 18.1%, respectively. On the other hand, compared to the existing cropping pattern, the amount of calories produced by the optimal cropping pattern under normal, drought and wet conditions increases by 51.7, 61.9 and 45.2%, the average energy efficiency increases by 40.9, 42.8 and 35.8% and the net profit productivity increases by 43.3, 30.9 and 44.2 %, respectively. Based on the obtained results, it can be seen that in the optimal cropping pattern in drought conditions, the cultivated area of crops such as potatoes, onions, tomatoes, grain corn, sugar beets, beans, alfalfa and watermelons should reach to the zero or be at the lowest possible level. In normal and drought conditions, the cultivated area of these crops should be minimal. On the other hand, the area under cultivation of crops such as fodder sorghum, fodder corn, saffron, cumin, camellia and medicinal plants should be increased and the cultivation of these crops should be promoted at the region. Also, regarding horticultural products, the cultivated area of walnut, apple, peach, apricot and almond orchards should be minimized and replaced with plants such as grapes, oleaster, jujube, barberry, rose, and figs.
Conclusion
Based on the obtained results, it was found that the use of the optimal cropping pattern derived from the indicators of water, food, energy and economic profit is completely superior and preferred over the existing cropping pattern and single purpose optimal cropping pattern. In order to achieve sustainable water resource management, it is recommended to modify the cropping pattern during drought, normal, and wet periods based on the suggested optimal cropping pattern. The existing cropping pattern currently falls short in terms of achieving the four objectives of water, food, energy, and economic profit. Therefore, it is crucial to develop main plans and strategies in the Farahan Plain that align with the implementation of the proposed optimal cropping pattern. By doing so, it will be possible to optimize the allocation of water resources and achieve improved outcomes in terms of water availability, food production, energy efficiency, and economic profitability.
