Design Of Irrigation Systems Research Articles

The Population and Isolates of Potential ACC Deaminase-Producing Rhizobacteria from Rhizospheric Soil of Peanut under Different Moisture Levels

ACC deaminase-producing rhizobacteria play an important role in enhancing plant growth and health, particularly under environmental stress conditions. This study focused on isolating and determining the population of potential ACC deaminase-producing rhizobacteria from the rhizosphere of peanut plants (Arachis hypogea L.) grown under varying moisture levels. Bacterial populations were measured using the Standard Plate Count (SPC) method on Dworkin-Foster (DF) medium supplemented with ACC as the sole nitrogen source. The isolated bacteria were screened based on their ability to grow after 24 hours of incubation on the selective medium. Results showed that bacterial colonies on nutrient agar (NA) medium varied in color, while colonies on the selective medium were uniformly white. The total population of rhizobacteria generally declined as soil moisture decreased, nevertheless, the sample from 80% available water had fewer bacteria than those of the sample from 50%. In an additional experiment, 9 out of 11 selected isolates were found to potentially produce ACC deaminase, with 5 of these being diazotrophic bacteria. This study contributes valuable information for designing irrigation systems in sustainable land management, particularly concerning plant-beneficial microbes that produce ACC deaminase and help plants tolerate environmental stressors.

Evaluation of water distribution and uniformity of sprinkler irrigation based on harmonic analysis and finite element method

A model that describes the water distribution of a single fixed spray plate sprinkler (FSPS) based on the harmonic analysis was proposed. The relationship between the pressure head, nozzle diameter, mean sprinkler irrigation depth, and amplitude was established. An analytical model for evaluating the sprinkler irrigation uniformity coefficient of a multi-sprinkler combination was developed by introducing a weighting coefficient. In conjunction with the sprinkler irrigation system's finite element hydraulic calculation model, the impact of the pipe diameter, sprinkler number, and sprinkler spacing on system energy loss, pressure head, and sprinkler irrigation system uniformity was assessed. The results demonstrated that under varying pressures and nozzle diameters, the Camargo and Sentelhas coefficient (c) between the measured and fitted mean value of the sprinkler irrigation depth of a single FSPS was greater than 0.99, while the c between the measured and fitted amplitude value was approximately 0.93. Under different combinations of nozzle, pressure head, and sprinkler spacings, the measured, derived, and calculated values of 54 sprinkler irrigation uniformity combinations were basically consistent. The uniformity of the combined FSPS under a linear-move sprinkler system was significantly affected by nozzle diameter, pipe diameter, sprinkler spacing, and inlet pressure head at 0.01 level. The number of sprinklers also had a significant impact at 0.05 level. The findings of this study could serve as a theoretical foundation for the proper design of linear-move sprinkler irrigation systems.

Design of Scheduled Fog Irrigation System with ESP 32 in Mustard Seedbed (Brassica juncea L.)

Plants receive water from the fog irrigation system in the form of tiny, mist-like water particles. Currently, irrigation technology has advanced, nurseries can be automatically irrigated. In this research, the ESP32 microcontroller is used to create the electronic circuits for the automation of the fog irrigation control system in a mustard green nursery. This study's methodology combines direct field observation with an experimental or trial approach. Water flow (ml/minute), water use efficiency (%), plant height (cm), number of leaves, and scheduled fog irrigation system performance are among the measured parameters. In this investigation, four different treatments were used: manual irrigation using a watering can, two-time, three-time, and one-time irrigation. All is going according to plan with this mist watering system. With an average height of 4.58 cm and an average number of leaves of 3.24, the mist irrigation system had the highest water use efficiency of 77.35% during the test. It was also found that mist irrigation produced the highest amount of mustard leaves in the three-times-per-day treatment. Keywords: ESP32, Fog irrigation, Green mustard, Nurseries.

An explainable hybrid framework for estimating daily reference evapotranspiration: Combining extreme gradient boosting with Nelder-Mead method

Accurate estimation of reference evapotranspiration (ETo) is essential for effective water resources management, irrigation system design, and various hydrological and agricultural applications. This study employed extreme gradient boosting (XGBoost) model, signal decomposition techniques, and XGBoost coupled with Nelder–Mead (NM) method to enhance ETo prediction across two meteorological stations in Iran. This study proposed a novel framework which lies in its comprehensive integration of advanced techniques to create a model that is both interpretable and highly accurate for ETo estimation. For this aim, sixty meteorological variables were categorized into solar and cloud-based, temperature-based, wind and humidity-based, and pressure-based groups to analyze their effect on ETo estimation. Feature selection methods, including the Gradient Boosting Machine, Kendall’s Tau, and Relief Algorithm, were employed to identify the most influential predictors. Variables with normalized weights equal to or greater than 0.9 were selected for model input, resulting in the top 10% of variables being utilized. The XGBoost models were then developed using these selected inputs (level 1), a wavelet-based hybrid was developed according to the most effective features (level 2), and the XGBoost model was coupled by NM algorithm (level 3) for ETo estimation. Results of estimated ETo by levels 1 to 3 were compared with four common empirical approaches. The results indicated that Kendall’s Tau-based feature selection provided the most accurate predictions in Shiraz, achieving an RMSE of 0.721 (mm/day) for solar and cloud-based variables during the test phase. Additionally, the application of wavelet analysis further refined the model inputs, which enhanced ETo estimation in most variable groups. Integrating the NM algorithm with XGBoost demonstrated significant improvements in ETo estimation, where it could improve RMSE to 0.091 and 0.155 (mm/day) for testing section in Fasa and Shiraz, respectively.

FUNDAMENTALS OF DESIGNING INTELLIGENT IRRIGATION SYSTEMS

Smart irrigation systems integrate technology with agriculture to optimize water usage, reduce waste, and increase crop yields. This article explores the design of smart irrigation systems, discussing the essential components, methodologies, and technological innovations that enhance the efficiency and effectiveness of irrigation practices. The study identifies key challenges in system design and proposes solutions based on current trends in sensor technology, data analytics, and automation. The results of this investigation highlight the importance of interdisciplinary collaboration and innovative strategies to create robust, scalable, and sustainable irrigation solutions.

Assessing the performance of various infiltration models to improve water management practices

AbstractInfiltration plays a key role in stormwater management and irrigation scheduling. A review of previous studies reveals that the effectiveness of infiltration models varies significantly depending on soil characteristics and field conditions. Accurate predictions depend on selecting appropriate models for specific sites because of soil spatial variability. This requires extensive testing and recording of infiltration rates at each location. This study assesses various infiltration rate measurement models to enhance water management efficiency. Infiltration rate measurements were conducted at three sites in Dehradun using a double-ring infiltrometer. Well-established models, such as Philips JR, Green, Ampt, Horton, Kostiakov, modified Kostiakov, and the Soil Conservation Service (SCS) model, were evaluated. Data from infiltration tests were used to calibrate these models, facilitating better irrigation system design and stormwater management. In assessing their effectiveness and efficiency, key evaluation criteria such as Nash–Sutcliffe efficiency (NSE), R-squared (R2), root mean square error (RMSE), mean absolute error (MAE), and mean bias error (MBE) were employed. Our findings highlight the superiority of the Philips JR model, offering the highest overall accuracy with the highest average value R2 = 0.9557 and NSE = 0.9553, lowest MAE = 0.6717 cm/h, MBE = − 0.0160 cm/h and RMSE = 1.0077 cm/h. These results underscore the model’s ability to synthesize infiltration data effectively, even in the absence of direct measurements. This insight positions the Philips JR model as a valuable tool for estimating infiltration rates in similar conditions.

Optimalisasi Waktu Produksi Jamur Tiram Melalui Implementasi Sistem Penyiraman Berbasis IoT di UD Zaida Jamur Tiram

The optimization of oyster mushroom production time through the implementation of an Internet of Things (IoT)-based irrigation system at UD Zaida Jamur Tiram aims to enhance efficiency and production quality. This program integrates IoT technology to automate the irrigation process, allowing real-time control and monitoring of environmental conditions. Methods include the design and installation of an automatic irrigation system, technical training for operators, and performance evaluation through production data analysis. Results show a significant increase in time efficiency and consistency in oyster mushroom quality. The implementation of this IoT system is expected to support the sustainability and competitiveness of the oyster mushroom industry at UD Zaida.

Study on Soil Moisture Status of Soybean and Corn across the Whole Growth Period Based on UAV Multimodal Remote Sensing

Accurate estimation of soil moisture content (SMC) in the field is a critical aspect of precise irrigation management. The development of unmanned aerial vehicle (UAV) platforms has provided an economically efficient means for field-scale SMC measurements. However, previous studies have mostly focused on single-sensor estimates of SMC. Additionally, the lack of differentiation between various crops and their growth stages has resulted in an unclear understanding of how crop types and growth stages affect the accuracy of SMC estimation at different soil depths. Therefore, the purpose of this paper was to use UAV multimodal remote sensing and a machine learning algorithm to estimate the SMC in agricultural fields and investigate estimation’s effectiveness under different scenarios. The results indicated the following: (1) The multispectral remote sensing method provided higher accuracy in SMC estimation compared to thermal infrared remote sensing. Moreover, the integration of multimodal data improved the accuracy of SMC estimation, enhancing the coefficient of determination (R2) by approximately 14% over that achieved through the use of multispectral data alone and 39% over that of thermal infrared data alone. (2) Across the entire growth period, the optimal soil depths of SMC estimation for soybean were 10 cm and 20 cm (average R2 were 0.81 and 0.82, respectively), while for corn, they were 10 cm, 20 cm, and 40 cm (average R2 were 0.59, 0.60, and 0.55, respectively). (3) The SMC estimation model performed better for both crops during the first three growth stages, with accuracy declining in the maturity stage. These results demonstrate that this approach can provide relatively accurate root zone SMC estimates for different crops throughout their main growth periods. Thus, it can be employed for SMC monitoring and precision irrigation system design.

Multifactor analysis of the infiltration characteristics of film hole irrigation under muddy water conditions

Film hole irrigation under muddy water conditions is a new and effective water-saving irrigation technology. In order to determine the influence of multiple factors on the infiltration process of film hole irrigation under muddy water conditions, 12 sets of indoor infiltration tests were conducted to investigate the effects of four key influencing factors (muddy water sand content, hole diameter, soil bulk density, and infiltration time) on the infiltration characteristics of irrigation with film holes under muddy water conditions, in this study. Based on the experimental data, accurate and effective soil water infiltration and vertical and horizontal wetting front transport models were constructed. Based on the modeling results, the standard regression coefficients of each influencing factor against the fitted parameters were calculated and the effects of the factors on the fitted parameters were analyzed. Error analysis showed that both models could effectively simulate the soil water infiltration process under experimental conditions. Infiltration time was the dominant factor influencing the cumulative infiltration per unit of film hole area, followed by hole diameter, muddy water sand content and lastly, soil bulk density. Infiltration time was also the main influencing factor of the vertical wetting front transport distance, followed by soil bulk density, muddy water sand content, and lastly, hole diameter. Similarly, infiltration time exerted the greatest effect on the horizontal transport distance, followed by hole diameter, soil bulk density and muddy water sand content. The model validation revealed that both the calculated and measured values were distributed around the 1:1 line, reflecting the accuracy of the models. The results of this study can provide theoretical support for the design of film hole irrigation systems under muddy water conditions.

Evaluation and comparison of infiltration models for estimating infiltration capacity of different textures of irrigated soils

Accurate estimation of infiltration rates is crucial for effective irrigation system design and evaluation by optimizing irrigation scheduling, preventing soil erosion, and enhancing water use efficiency. This study evaluates and compares selected infiltration models for estimating water infiltration rates in the Shillanat-iv irrigation scheme in northern Ethiopia. Soil samples were collected to determine textural classes using hydrometer soil texture analysis and the United States Department of Agriculture (USDA) textural triangle. The soil textural map of the study was created using the inverse distance weight interpolation technique in ArcGIS version 10.4. Infiltration rates were measured using the double-ring infiltrometer for five soil textures: clay loam, loam, sandy clay loam, clay, and sandy loam. Six infiltration models (Kostiakov, Modified Kostiakov, Revised Modified Kostiakov, Philip, Horton, and Novel) were employed and evaluated using statistical parameters. Model calibration and validation were conducted using data from 38 points within the study area. The parameter values of the infiltration models were optimized using SPSS statistical software using least-squares errors. The results showed that, Revised Modified Kostiakov, Modified Kostiakov, and Novel infiltration models demonstrated superior capability in estimating infiltration rates for clay loam, loam, and sandy loam soil textures, respectively. Horton's model outperformed other models in estimating infiltration rates for both sandy clay loam and clay soil textures. The appropriately fitted infiltration models can be utilized in designing the irrigation system to estimate the infiltration rate of soil textures within the selected irrigation scheme and at similar sites with comparable soil textures.

REDUCING OF WATER AND ENERGY RESOURCES CONSUMPTION IN IRRIGATION BASED ON RESOURCE OPTIMISATION

The need for further development of irrigation practices on the basis of nature oriented and ecologically efficient solutions is considered primarily regarding the saving of water and energy resources for the adaptation of irrigated agricultural production to the current global challenges and threats, the achievement of sustainable development goals. It is shown that there is an objective need to change methodological approaches to the assessment of overall efficiency and justification of optimal solutions in design, reconstruction, and operation projects of irrigation systems based on the principles of resource optimization. On the basis of the indicator of the level of irrigation sufficiency (introduced by the authors), which reflects the reduction of the studied watering and irrigation rates in relation to their design values, a study of the impact of reducing the use of water and energy resources under different modes of sprinkler irrigation on the corresponding decrease in the level of cultivated crops productivity was carried out. At the same time, it was experimentally determined that the intensity (rate) of the decrease in the cultivated crops productivity, which occurs due to the decrease in the usage of water and energy resources during the application of irrigation, is significantly lower than the intensity (rate) of the decrease in the usage of the resources themselves. The studied options for reducing the consumption on water and energy resources as a whole turned out to be economically profitable when with a decrease in water and electricity usage by 27–48% there is more than two times lower decrease in the costs of gross products by 10,80–18,06% with the achievement of a net income of 11,4 to 5,7 thousand UAH. The influence of various options of reducing water and electricity consumption on the discounted investment payback period shows that several options may be acceptable, for which the investment payback period does not exceed 10 years, and the choice of the optimal solution requires taking into account the conditions of a specific object, limitations of water resources, and the interests of investors and land users. At the same time, the ecological component of the overall efficiency of irrigation practices consists in the decrease in the use of water and energy resources that a priori reflects the decrease in the negative impact of irrigation on the environment. Thus, reducing the usage of water and energy resources is a fully justified decision on the way to adapt irrigated agriculture production to the modern conditions and requirements, and the presented results can be a scientific basis for the implementation of this approach while practically applying irrigation.

Robotic irrigation complex for crop cultivation in irrigated areas

Intelligent technologies used in digital agriculture, such as remote sensing, serve as a necessary tool for collecting bio-object data. It has been established that data collected through remote sensing and the Internet of Things (IoT), including comprehensive imaging of agricultural bio-objects, and their subsequent analysis will help solve numerous challenges in agricultural production. (Research purpose) The research aims to develop and validate a robotic irrigation complex for crop cultivation. This system will optimize irrigation processes by considering various environmental factors such as soil moisture, air temperature, wind speed, and other relevant conditions. (Materials and methods) The paper evaluates the signifi cance of developing a design that can optimize the process of crop cultivation and details the applications and databases integrated within the central computing center. The central computing hub monitors the current state of the irrigation area, performs calculations and develops management decisions. Utilizing mobile communications, this hub receives, processes, and transmits commands to the control panels of sprinklers, the pumping station, and the dispatcher for the machine-tractor team. (Results and discussion) The research has validated the design and main components of a robotic irrigation system for crop cultivation. Furthermore, an algorithm has been established to orchestrate the processes of data collection, calculation, and the control and management of operations. It was found that such a complex would optimize the irrigation process, reduce costs and resource consumption in the irrigated area, and decrease environmental pollution. (Conclusions) The implementation of a robotic irrigation complex will reduce water consumption, as well as material and energy costs associated with irrigation. By maintaining soil moisture within optimal ranges, this complex will enable the consistent production of high-quality crops under various weather conditions.

“Design and analysis of bamboo fiber-based anchor spray irrigation system for sustainable water management in agriculture”

“Design and analysis of bamboo fiber-based anchor spray irrigation system for sustainable water management in agriculture”

IoT Based Smart Irrigation System

In recent years, the integration of Internet of Things (IoT) technology into agriculture has shown great potential for enhancing irrigation practices, thereby improving crop yield and water efficiency. This paper presents the design, implementation, and performance evaluation of an IoT-based smart irrigation system tailored for agricultural applications. The proposed system employs various sensors to monitor soil moisture levels, weather conditions, and crop water requirements in real time. Data collected from these sensors are transmitted wirelessly to a central control unit, which utilizes an intelligent algorithm to optimize irrigation scheduling and water distribution. The system also incorporates remote monitoring and control capabilities, allowing farmers to access and manage irrigation operations from anywhere via a web or mobile interface. Experimental results demonstrate the effectiveness of the IoT-based smart irrigation system in conserving water, reducing energy consumption, and enhancing crop productivity. Moreover, the scalability, reliability, and cost-effectiveness of the proposed solution make it suitable for deployment in both small-scale and large- scale agricultural settings. Key Words: IoT, smart irrigation, agriculture, soil moisture sensor, wireless communication, optimization, remote monitoring

Interactive Computer Program for Design of Subsurface Drip Irrigation System

Interactive Computer Program for Design of Subsurface Drip Irrigation System

ESTIMATION OF SOIL WETTING PATTERN USING DIFFERENT IRRIGATION REGIMES IN CONJUCTION WITH SUPER ABSORBENT POLYMER

The design and management of irrigation systems require soil water movement and distribution knowledge. Finding the actual ability of drip irrigation to supply sufficient water uniformly and timely requires optimizing the operational management parameters. The objective of the study was to estimate the water distribution pattern with drip irrigation under different irrigation frequencies, durations and Belsap super absorbent polymer. A factorial experimental design layout of drip irrigation system was set up in Noiwet, Mogotio Sub County, Baringo County. The same quantity of water with three irrigation frequencies were applied once daily, after two days and three days and three durations which were full, half and a third the irrigation time. The total number of treatments were 18 with three replications making a total of 54 experiments. The wetted depths and widths of the soil were measured directly in the field using a ruler immediately after irrigation. ANOVA statistical analysis was carried out to determine the significance of the treatments on the soil wetting pattern of the clay soil. The results from the study revealed that the super absorbent polymer had no effect on the soil wetting pattern while the decrease in the irrigation frequency and increase in irrigation duration led to an enlargement in both the diameter and depth of the soil wetted zone. Information on depths and widths of wetted zone of soil under drip irrigation have a great significance in the design and management of drip irrigation system for delivering required quantity of water and chemicals to plants.

Sustainable Groundwater Management Through Micro Irrigation: A Critical Review on Challenges and Solutions

Abstract Groundwater plays a vital role in global water resources, supporting agricultural, industrial, and domestic water supply systems. However, the long-term sustainability of groundwater is increasingly threatened due to the widespread adoption of irrigation systems especially micro irrigation. Micro irrigation is a widespread agricultural technique that involves water application to crops through drip irrigation and sprinkler systems. This method has gained widespread adoption due to its ability to deliver water efficiently to crops. This review paper examines the impacts of micro irrigation on groundwater sustainability, focusing on its effects on groundwater quantity, quality, and overall sustainability. The findings reveal that micro irrigation can significantly contribute to groundwater conservation by reducing water losses. However, improper management practices, such as over-irrigation or incorrect application rates, can lead to excessive groundwater extraction, depletion of aquifers, and declining water tables. Applying fertilizers and pesticides in micro irrigation systems may lead to groundwater pollution, thereby affecting water quality and posing a risk to human health. This review article emphasizes the significance of appropriate design, installation, and upkeep of micro irrigation systems to minimize potential adverse effects on groundwater. Furthermore, regulatory frameworks, policies, and educational programs are crucial in promoting sustainable groundwater management practices in micro irrigation. The present review highlights the significance of adopting balanced water use practices, enhancing water management techniques, and implementing relevant regulations to ensure the sustainable utilization of groundwater resources in micro irrigation systems.

Design of an IOT-based saffron crop irrigation system

Saffron is a highly prized and globally demanded spice.Still, the rate of production is unable to keep up with the exponentially rising demand due to a variety of reasons. One of the major problems faced in increasing saffron growth is the lack of understanding of the best circumstances. Factors like Temperature, humidity, and light intensity play a vital role in the growth and development of plants, and continuous monitoring and control of these factors are necessary to ensure optimal growth. To address this issue this paper introduces an integrated automated system designed to empower farmers in optimizing production while simultaneously facilitating data collection for research purposes, aimed at enhancing both the quantity and quality of agricultural yields using the utilization of sensors and a live data streaming application. It allows for efficient management of saffron's growing operations and enables more accurate adjustments. The sensors can be remotely located in the saffron growing areas and connected to the app via wireless connections, allowing farmers to monitor these factors and suggest changes continuously. Using this system, farmers can ensure that the conditions for saffron plant growth are optimal at all times, leading to increased production. The developed app utilizes technologies such as ReactJS and Google Firebase, and also allows for real-time data streaming, enabling farmers to view the current conditions at any time and make adjustments accordingly. Additionally, a user-friendly mobile application is developed to enable farmers to easily oversee their cultivation conditions. This paper bridges the gap between existing research by integrating the factor of luminous intensity and its effect on Saffron during it’s budding and growth stage, an area which is severely under researched and finds almost negligible mainstream integration in similar prototype models. Furthermore, the paper underscores the potential for future machine learning models by highlighting the provision for follow-up studies using the data collected through the prototype, thus fostering ongoing advancements in agricultural research and technology.

OPTIMAL DESIGN OF A PUMPED IRRIGATION SYSTEM OPERATING IN SHIFTS

The optimization of pumping systems is important because it improves energy efficiency, increases production, reduces operating and maintenance costs, and contributes to sustainability. To address this challenge, it is essential to effectively manage irrigation systems. In this research, an optimization algorithm was used to minimize the economic cost of irrigation system design. The implemented methodology includes the following steps: determining the fictitious continuous flow rate (qfc) and the number of shifts, functionally designing the irrigation network with pumping operations in shifts, and finally designing the network using Linear Programming (LP). Inputs to the model include network topology, set point pressures, design speed ranges, and pump characteristic curve. The model output provides the diameters of the irrigation system lines. In consequence, this methodology was applied in the irrigation system of the community of San Pedro de la Bendita in the province of Loja. The study demonstrates a significant cost reduction in the hydraulic design of the irrigation network when operating in shifts using LP compared to the cost of a conventional hydraulic design.

Sustainable Water Management of Drip-Irrigated Asparagus under Conditions of Central Poland: Evapotranspiration, Water Needs and Rainfall Deficits

Water is a valuable yet scarce resource in agriculture. Optimizing crop production relies on irrigation, but within the framework of sustainable agriculture, efforts should prioritize reducing irrigation water usage. Unfortunately, climate change increases plant water requirements, consequently heightening the need for irrigation. The aim of the research was to estimate the water needs of asparagus during the fern growth period (21 June–31 August) using the Blaney–Criddle method. The study also aimed to determine trends in changing water needs and estimate precipitation deficits. Calculations were carried out for the years 1981–2020 across four provinces in central Poland. The research indicated that water needs varied between 233 mm and 242 mm, depending on the province. Over the forty-year period, all provinces displayed an increasing trend in water needs, with a rise of 3.1 mm to 6.2 mm per decade. Between 21 June and 31 August, rainfall deficits occurred with varying intensity in all provinces during normal, medium dry and very dry years. The values of water needs and rainfall deficit, calculated as a result of the research, are of key importance in the design, construction, and management of drip irrigation systems for asparagus plantations in central Poland.