Traditional Irrigation Methods Research Articles

Reinforcement Learning Algorithm for Optimising Durian Irrigation Systems: Maximising Growth and Water Efficiency

This study presents a Reinforcement Learning-based algorithm designed to optimise irrigation for Durio Zibethinus (i.e., durian) trees, aiming to maximise tree growth and reduce water usage. Traditional irrigation methods, as well as current machine learning models, often focus only on soil moisture and weather data, neglecting critical factors like actual tree growth. This study proposed a reinforcement learning irrigation (RL-Irr) algorithm incorporating tree growth stages, soil moisture, and weather conditions to determine precise irrigation needs. The algorithm was developed by calibrating the AQUACROP model using data from actual durian plantations where rain-fed irrigation (rain-fed) was practised. Daily irrigation volumes were calculated based on real-time soil moisture, weather forecasts, and weekly tree growth measurements. The reinforcement learning method was used to optimise irrigation schedules, with rewards based on soil moisture, tree growth, rainfall, and weather conditions. The algorithm was tested using AQUACROP simulations and compared against soil moisture balance irrigation (SMB-Irr) and rain-fed. The results showed that the RL-Irr reduced water use by up to 75 percent while maintaining tree growth. These findings suggest the algorithm could significantly improve water efficiency in durian farming, though real-world applications should consider potential model limitations.

Assessment of Farmer’s Attitude towards Drip and Traditional Irrigation System in Junagadh District, Gujarat

Cotton (Gossypium herbaceum) is a leading natural fiber crop that is cultivated for its soft, fluffy staple fiber. Drip irrigation is a method of irrigation wherein water is carried to the plant under low pressure, through small diameter plastic pipes and delivered at the root zone drop by drop through an emitting device. The research was conducted in Junagadh district, utilizing a multistage sampling technique. A total of 160 farmers comprising 80 drip irrigation user and 80 conventional irrigation system users were surveyed. Likert’s scale with three point scale was used to analyse attitude towards the drip and traditional irrigation system by using 10 statements for each respondents. The farmers in the research area having positive attitudes toward the drip irrigationmethods as positive trend with value 66.25% was observed among drip respondents. This positive attitude reflects the behavioural intention towards the acceptance of irrigation systems. The study also revealed that 48.75% of the non-adopter farmers had the positive attitude toward the traditional irrigation methods whereas 51.25% of them had a negative and neutral attitude.

Water Use Efficiency in Rice Under Alternative Wetting and Drying Technique Using Energy Balance Model with UAV Information and AquaCrop in Lambayeque, Peru

In the context of global warming, rising air temperatures are increasing evapotranspiration (ETc) in all agricultural crops, including rice, a staple food worldwide. Simultaneously, the occurrence of droughts is reducing water availability, affecting traditional irrigation methods for rice cultivation (flood irrigation). The objective of this study was to determine ETc (water use) and yield performance in rice crop under different irrigation regimes: treatments with continuous flood irrigation (CF) and irrigations with alternating wetting and drying (AWD5, AWD10, and AWD20) in an experimental area in INIA–Vista Florida. Water balance, rice physiological data, and yield were measured in the field, and local weather data and thermal and multispectral images were collected with a meteorological station and a UAV (a total of 13 flights). ETc values obtained by applying the METRICTM (Mapping Evapotranspiration at High Resolution using Internalized Calibration) energy balance model ranged from 2.4 to 8.9 mm d−1 for the AWD and CF irrigation regimes. In addition, ETc was estimated by a water balance using the AquaCrop model, previously parameterized with RGB image data and field weather data, soil, irrigation water, and crops, obtaining values between 4.3 and 7.1 mm d−1 for the AWD and CF irrigation regimes. The results indicated that AWD irrigation allows for water savings of 27 to 28%, although it entails a yield reduction of from 2 to 15%, which translates into an increase in water use efficiency (WUE) of from 18 to 36%, allowing for optimizing water use and improving irrigation management.

IoT-Enabled Air Irrigation: A Data-Driven Approach to Sustainable Agriculture in Water-Scarce Regions

The escalating water scarcity crisis, particularly in arid regions like Maharashtra, India, poses a significant threat to agricultural productivity. Traditional irrigation methods often face challenges related to water wastage and inefficient distribution. To address these issues, this study proposes an innovative IoT-enabled smart “Air Irrigation" system. This novel approach involves dispersing water into the air to create a microclimate with optimal humidity levels, promoting plant growth and reducing water consumption.

Application of knowledge graph in smart irrigation district management decision making

Regarding the traditional irrigation and drainage management methods in China's irrigation districts, there are problems such as complex management processes, dispersed information systems, difficulty in resource sharing, diverse data sources, and insufficient intelligent auxiliary decision-making. In order to further realize refined intelligent management decision-making on issues related to smart irrigation districts, this article uses the basic information of 28 Yellow River diversion irrigation districts in Henan Province, as well as the overall plan reports and related issue management manuals of 7 management offices of the first and second phase projects of Zhaokou Irrigation District as data sources. Collect and organize data from irrigation areas, and use these to build a knowledge graph for management of issues in irrigation areas diverted from the Yellow River. At the same time, the BERT + BiLSTM + CRF model is used to intelligently identify entities such as irrigation projects and problem events in the Zhaokou Irrigation District inspection log text, and entity alignment technology is used to match the inspection text with entities in the knowledge graph. Finally, combined with the graph retrieval function, the intelligent generation of smart irrigation district management decision-making solutions is realized. The validation of specific irrigation district examples and analysis of the evaluation indexes of relevant models demonstrate the reliability of the problem management decision-making scheme proposed in this paper. This application effectively facilitates the integration of information data in the Yellow River diversion irrigation area and enables visual management of intelligent irrigation zones, presenting a novel concept for the informationization construction of China's irrigation areas.

Optimizing Irrigation Systems for Water Efficiency and Groundwater Sustainability in the Coastal Nile Delta

This study investigates the replacement of traditional surface irrigation methods with modern irrigation systems (MIS) including horizontal sprinkler, central pivot, surface drip, and subsurface drip aimed at improving water efficiency in the Nile Delta, Egypt. The primary objectives were to determine the optimal agricultural area for implementing MIS and to assess the effects of these systems on groundwater quantity and quality in the region. To achieve this, the LINDO software was employed to optimize land allocation for each irrigation method. At the same time, the SEAWAT code was utilized to simulate saltwater intrusion (SWI) in the Nile Delta aquifer. The transition from traditional surface irrigation to MIS resulted in significant water savings, reaching 2.15 × 10^9 m³. However, groundwater modeling indicated a decrease in groundwater levels, leading to an 8 % increase in aquifer salinity due to reduced infiltration of recharge water. These findings underscore the urgent need to revise outdated irrigation practices and enhance water management strategies in the Nile Delta to mitigate salinity issues in coastal aquifers. This research's outcomes are crucial for decision-makers and stakeholders in selecting appropriate irrigation methods, particularly in arid and semi-arid regions, to ensure sustainable water use and agricultural productivity.

A Comparative Analysis of Land, Water and Energy Requirements for Hydroponic and Conventional Cultivation of Horticultural Crops

The increasing global population and limited availability of arable land have necessitated the development of efficient and sustainable agricultural practices. Hydroponic cultivation has emerged as a promising alternative to conventional soil-based farming, particularly for horticultural crops. This review paper presents a comprehensive comparative analysis of the land, water, and energy requirements for hydroponic and conventional cultivation methods. The study aims to evaluate the sustainability and resource efficiency of these two approaches in the context of horticultural crop production. A thorough literature review was conducted, focusing on peer-reviewed articles, research reports, and case studies that compared hydroponic and conventional cultivation in terms of their resource utilization. The analysis encompassed various horticultural crops, including leafy greens, fruiting vegetables, and herbs. Key parameters such as land use efficiency, water consumption, nutrient management, energy inputs, and yield were examined. The findings revealed that hydroponic systems exhibited significantly higher land use efficiency compared to conventional farming. Vertical stacking and intensive production in controlled environments allowed for greater crop yields per unit area. Furthermore, hydroponic cultivation demonstrated superior water use efficiency, with recirculating systems reducing water consumption by up to 90% compared to traditional irrigation methods. Precision nutrient management in hydroponics minimized nutrient waste and runoff, contributing to enhanced resource conservation. However, the energy requirements for hydroponic cultivation were found to be higher than those for conventional farming, primarily due to the need for artificial lighting, climate control, and pumping systems. Strategies for optimizing energy efficiency, such as the use of renewable energy sources and energy-efficient equipment, were explored.

Suggestion for Farmers to the Adoption of Solar Pumps in Jodhpur District of Rajasthan, India

The Jodhpur district of Rajasthan is where the research investigation was conducted. There are seven tehsils in the Rajasthani district of Jodhpur. The two tehsils with the most solar pumps built were Osian and Balesar. Ten villages from each selected tehsil were selected based on which villages would most benefit from solar pumps. Due to their abundance of solar pumps, twenty communities were picked, and among them, one hundred twenty-five (125) responders were chosen. The research paper outlines some recommendations for enhancing the program's management as well as issues farmers ran across when adopting solar pumps. The adoption of solar pumps in agriculture is a promising and sustainable solution to address multiple challenges faced by farmers and the environment. Traditional irrigation methods often rely on fossil fuels or grid electricity, contributing to environmental degradation and high operational costs. Solar pumps, powered by renewable energy, offer a compelling alternative that can enhance agricultural productivity, reduce carbon emissions, and improve the livelihoods of farmers. This article explores the benefits of adopting solar pumps and provides suggestions for their widespread implementation.

IoT-based smart irrigation management system to enhance agricultural water security using embedded systems, telemetry data, and cloud computing

Agriculture, the key sector for food production, faces challenges exacerbated by the growing global demand for food and the scarcity of water resources. Traditional irrigation methods often lead to inefficient use of water, resulting in wastage. Moreover, unpredictable weather conditions and the need to adopt sustainable farming practices are driving us to develop advanced irrigation systems. This paper proposed a smart irrigation management system using new technology like 1) embedded systems, 2) Internet of Things (IoT), 3) telemetry data, 4) cloud computing, communication protocol, and 5) sensors to collect and process real-time data of the smart agriculture. This new technology and intelligent algorithm are used in this paper to improve agricultural practices. The architecture of the proposed scheme comprises three layers: 1) IoT devices, 2) ThingsBoard cloud, and 3) the dashboard, each playing a pivotal role in ensuring seamless data flow, secure communication, and enhanced user interaction. The algorithm orchestrates system operations, incorporating sensor data reading, JavaScript Object Syntax (JSON) payload creation, and secure telemetry data transmission via Hypertext Transfer Protocol (HTTP) protocol to the ThingsBoard cloud. Pump activation decisions are governed by predefined thresholds, preventing an over-irrigation system. The evaluation of system performance involves deploying temperature, humidity, moisture, and water level sensors in a testing field. Further, before data is sent to the cloud, sensor values are calibrated using a functional map. Tests carried out with temperature, humidity, and water level sensors demonstrate the system's dynamic efficiency. By visualizing and analyzing environmental information via ThingsBoard, the results provide real-time data on environmental parameters of the system proposed, improving the efficiency of water use and the sustainability of farming practices. In addition, the system features e-mail notifications for alerts. The integration of e-mail notifications reinforces monitoring and management practices by alerting farm owners and users. This study showcases the efficacy of the proposed paper in enhancing sustainability, water usage, and supporting smart agriculture practices. Further, this paper integrates embedded systems, IoT, cloud computing, and advanced algorithms to optimize and enhance crop productivity and contribute to global food and water security.

Efficacy of sonic and ultrasonic activation on irrigant penetration in different tapered preparations: An in vitro study

ABSTRACT Background: The traditional syringe needle irrigation method would compromise on cleaning the intricacies of the complex root canal system. Current literature has focused on the benefits of various irrigant activation techniques. The present study aims to evaluate the irrigant penetration in extracted single-rooted teeth using various irrigant activation systems in different tapered preparations. Materials and Methods: One hundred and twenty-four single-rooted teeth were selected for the present study. They were standardized at the level of cementoenamel junction and shaped to 30 size using 4% and 6% taper rotary instruments under a standard irrigation regimen. Once the complete root canal preparations were done based on activation protocols, they were divided into four groups as Group 1: Four percent preparation sonic activation (n = 31), Group 2: Six percent preparation sonic activation (n = 31), Group 3: Four percent preparation ultrasonic activation (n = 31), and Group 4: Six percent preparation ultrasonic activation (n = 31). A radiopaque solution in conjunction with radiography was utilized to evaluate the penetration of irrigants into the canal. Radiographs were taken after dye injection to measure the length of irrigant penetration in each technique. Results were statistically analyzed using SPSS software. One-way ANOVA and Post hoc Tukey tests were performed. Results: The results of the study revealed that ultrasonic activation after 6% taper instrumentation was better followed by ultrasonic activation after 4% taper instrumentation (P < 0.05). The results revealed a statistically significant difference (P < 0.05) between the irrigation techniques. Conclusion: Ultrasonic irrigant activation proved to be a better and an effective technique for cleaning the root canal.

A Review of Drip Irrigation’s Effect on Water, Carbon Fluxes, and Crop Growth in Farmland

The substantial depletion of freshwater reserves in many pivotal agricultural regions, attributable to the dual pressures of global climate change and the excessive extraction of water resources, has sparked considerable apprehension regarding the sustainability of future food and water security. Drip irrigation, as an efficient and precise irrigation method, reduces water loss caused by deep percolation, soil evaporation, and runoff by controlling the irrigation dosage and frequency, thus improving the efficiency of water resource utilization. Studies have shown that compared with traditional irrigation methods, drip irrigation can significantly decrease water consumption, optimize the water–energy relationship by reducing soil evaporation, increase the leaf area index, and promote crop growth, thereby enhancing plant transpiration. Although more wet and dry soil cycles from drip irrigation may increase soil CO2 emissions, it also enhances crop photosynthesis and improves crop net ecosystem productivity (NEP) by creating more favorable soil moisture conditions, indicating greater carbon sequestration potential. The advantages of drip irrigation, such as a short irrigation cycle, moderate soil moisture, and obvious dry and wet interfaces, can improve a crop’s leaf area index and biomass accumulation, improve root dynamics, promote the distribution of photosynthetic products to the aboveground parts, and thus enhance crop yields. This study highlights the potential for the application of drip irrigation in arid regions where resource optimization is sought, providing strong technical support for the achievement of sustainable agricultural development. Future research needs to consider specific agricultural practices, soil types, and environmental conditions to further optimize the implementation and effectiveness of drip irrigation.

Flow prediction of irrigation well pump based on experimental and big data analytics

Abstract Currently, China’s agricultural irrigation consumes a huge amount of water, and traditional agricultural irrigation methods lead to low irrigation efficiency and serious water resource waste. Agricultural irrigation water management is also difficult to achieve refined management due to the lack of accurate monitoring of water use data and information in various irrigation areas. To find a more convenient flow measurement method, this paper proposes using data-driven monitoring of water pump characteristic parameters to predict flow rate. Three big data-based methods for predicting the flow rate of irrigation well pumps were compared, including RBF neural network, Support Vector Machine (SVM), and Extreme Learning Machine (ELM). The results indicate that the Extreme Learning Machine (ELM) model not only has short time consumption but also high prediction accuracy, laying the foundation for the application of big data technology in water management and high-quality irrigation water management that can save water.

A Review of Precision Irrigation Water-Saving Technology under Changing Climate for Enhancing Water Use Efficiency, Crop Yield, and Environmental Footprints

Water is considered one of the vital natural resources and factors for performing short- and long-term agricultural practices on Earth. Meanwhile, globally, most of the available freshwater resources are utilized for irrigation purposes in agriculture. Currently, many world regions are facing extreme water shortage problems, which can worsen if not managed properly. In the literature, numerous methods and remedies are used to cope with the increasing global water crises. The use of precision irrigation water-saving systems (PISs) for efficient water management under climate change is one of them and is a highly recommended approach by researchers. It can mitigate the adverse effects of changing climate and help enhance water use efficiency, crop yield, and environmental footprints. Thus, the present study aimed to comprehensively examine and review PISs, focusing on their development, implementation, and positive impacts on sustainable water management. In addition, we searched the literature using different online search engines and reviewed and summarized the main results of the previously published papers on PISs. We discussed the traditional irrigation method and its modernization for enhancing water use efficiency, PIS monitoring and controlling, architecture, data sharing communication technologies, the role of artificial intelligence for irrigation water-saving, and the future prospects of the PIS. Based on the brief literature review, the present study concluded that the future of PISs seems bright, driven by the need for efficient irrigation water management systems, technological advancements, and increasing environmental awareness. As the water scarcity problem intensifies due to climate change and population growth, the PIS is poised to play a critical role in optimizing and modernizing water usage, increasing water use efficiency, and reducing environmental footprints, thus ensuring sustainable agriculture development.

An Affordable System Solution for Enhancing Tree Survival in Dry Environments

Water scarcity inhibits plant growth, especially in arid regions. Traditional irrigation methods often lack efficiency and sustainability. This study investigates AquaTrap, a biomimetic design, as a potential solution. The study highlights AquaTrap’s advantages by analyzing its design and previous research on bioinspired water harvesting. It highlights its ability to increase water efficiency and support sustainable plant growth in dry areas. Biomimicry inspires AquaTrap’s design, which mimics natural systems to capture and deliver water to plant roots. To collect condensation while repelling water, the stack uses superhydrophobic materials. Plant roots then receive this accumulated water for growth. Compared to traditional methods, AquaTrap offers many advantages. Its stand-alone design eliminates complex infrastructure and minimizes evaporation. Additionally, delivering water directly to the roots reduces waste and increases water efficiency. This technology holds promise for introducing new vegetation, restoring plant life, and promoting sustainable agriculture in arid regions. Further research is needed to explore the potential of AquaTrap in a variety of field conditions, optimize it for different plants and environments, and evaluate its economic feasibility for widespread use. AquaTrap also has significant potential for sustainable forestry, as it can significantly increase the survival and growth of trees in water-scarce environments. System solution opportunities and modular structure provide crucial support during the most critical adaptation period of afforestation. By reducing water consumption and increasing efficiency, it supports the establishment and maintenance of healthy forests, which are vital for ecosystem resilience and biodiversity.

Optimizing Irrigation Efficiency using Deep Reinforcement Learning in the Field

Agricultural irrigation is a significant contributor to freshwater consumption. However, the current irrigation systems used in the field are not efficient. They rely mainly on soil moisture sensors and the experience of growers but do not account for future soil moisture loss. Predicting soil moisture loss is challenging because it is influenced by numerous factors, including soil texture, weather conditions, and plant characteristics. This article proposes a solution to improve irrigation efficiency, which is called DRLIC (deep reinforcement learning for irrigation control). DRLIC is a sophisticated irrigation system that uses deep reinforcement learning (DRL) to optimize its performance. The system employs a neural network, known as the DRL control agent, which learns an optimal control policy that considers both the current soil moisture measurement and the future soil moisture loss. We introduce an irrigation reward function that enables our control agent to learn from previous experiences. However, there may be instances in which the output of our DRL control agent is unsafe, such as irrigating too much or too little. To avoid damaging the health of the plants, we implement a safety mechanism that employs a soil moisture predictor to estimate the performance of each action. If the predicted outcome is deemed unsafe, we perform a relatively conservative action instead. To demonstrate the real-world application of our approach, we develop an irrigation system that comprises sprinklers, sensing and control nodes, and a wireless network. We evaluate the performance of DRLIC by deploying it in a testbed consisting of six almond trees. During a 15-day in-field experiment, we compare the water consumption of DRLIC with a widely used irrigation scheme. Our results indicate that DRLIC outperforms the traditional irrigation method by achieving water savings of up to 9.52%.

Effect of Raised Flat Bed and Ridge Planting on Wheat Crop Growth and Yield under Varying Soil Moisture Depletions

Crop yields remain significantly low in underdeveloped countries, such as Pakistan, primarily due to the prevalent use of traditional farming methods by most farmers. Resource-saving strategies, like ridge and raised flat bed systems, could boost water use efficiency and production per acre. However, further research is needed to investigate the effectiveness of these methods, along with different levels of soil moisture depletion (SMD), on wheat development in the climatic conditions of Sindh Province. Thus, field trials were undertaken at Sindh Agriculture University’s Tandojam for two years (2022 and 2023) during the wheat growing seasons. The experiment included six treatments, viz., T1 (raised flat bed method under 40% depletion), T2 (ridge method under 40% depletion), T3 (raised flat bed method under 50% depletion), T4 (ridge method under 50% depletion), T5 (raised flat bed method under 60% depletion), and T6 (ridge method under 60% depletion). The bed planter was employed to make raised flat beds, and the ridges were prepared using a ridge planter. Wheat variety (TJ-83) was sown. Under all treatments, the plant population, plant height, and seed index were statistically significant (p < 0.05), although spike length, grain spikes−1, and grain weight spikes−1 were non-significant at different SMD levels. To compute water saving through the ridge and raised flat methods, the recommended delta value for wheat crops under the traditional method was used as a benchmark. Both irrigation technologies conserve water compared to traditional irrigation methods. The T5 treatment conserved the most water, followed by T6. Under a 60% depletion level, the ridge approach produced the highest yield of 2175 kg ha−1, compared to 601 kg ha−1 with the raised flat bed method. The best crop water productivity (CWP) of 1.34 kg m−3 was achieved under T6, whereas raised flat beds attained the lowest CWP of 0.27 kg m−3 under T1. In terms of wheat grain production and CWP, the ridge furrow method outperformed the raised flat bed furrow method. Based on the results, it is recommended that farmers should use the ridge furrow method and allow a 60% depletion of soil moisture to obtain a high yield of wheat crops.

Impact of Drip Irrigation on Crop Growth, Yield, Water Productivity, and Weed Dynamics: A Review

The global water scenario indicates efficient water management practices are required to sustain agricultural productivity. The scarcity of groundwater resources is a global issue that is caused by increasing global population and climate change in the form of global warming. To alleviate the issue, the major water-consuming area implemented drip irrigation projects. It is recognized for its water-saving potential and gained prominence in crop cultivation. This study aimed to investigate the effect of drip irrigation on the growth, yield, water productivity, and weed dynamics of various crops. Results revealed that wheat under drip irrigation exhibited enhanced growth parameters, including increased plant height, leaf area index, and dry matter accumulation attributed to optimized soil moisture content. Drip irrigation significantly improved yield and yield attributes compared to traditional irrigation methods. Importantly, drip irrigation increased water productivity while reducing water use per unit of production. These findings highlight the potential of drip irrigation to reduce water shortages and increase crop output in the current global water context.

Micro Irrigation in Rice: A Review

Rice (Oryza sativa) is the most important staple food crop over half of the world’s population and it provides 21 per cent of global human per capita energy. In India, rice is widely grown as the second food crop occupying about 43 million hectares of area. Water scarcity is a major constraint in the development of rice farming in some parts of the world. The water required to produce unit kg of rice is as high as 4000-5000 liters under conventional methods of water application (Transplanting under submerged conditions). During the crop growth period of rice, the amount of water usually applied to field is often much more than the actual field requirement because of adopting traditional flood irrigation methods. In order to meet the growing demand for water it is necessary to use water efficiently and reduce the loss of water. One such practice to conserve water is adoption of micro irrigation to a water loving crop like rice to reduce the wastage of water and to increase the water use efficiency. Micro irrigation is defined as the application of small quantities of water directly above and below the soil surface, usually as discrete drops, continuous drops or tiny streams through emitters placed along a water delivery line.

Optimisation of water use in Kyrgyzstan agriculture: Analysis of modern and traditional irrigation methods to minimise losses and increase efficiency

Optimisation of water use in Kyrgyzstan agriculture: Analysis of modern and traditional irrigation methods to minimise losses and increase efficiency

Impact of Drip Irrigation in Sugarcane Cultivation in Mandya District of Karnataka, India

This study investigates the impact of drip irrigation on sugarcane cultivation in Mandya district, Karnataka, considering the challenges posed by traditional flood irrigation methods and the increasing demand for water resources. The research compares the adoption of drip and flood irrigation, analyzing socio-economic characteristics, cropping patterns, and the comparative economics of sugarcane cultivation under both methods. Externality concept and Partial budgeting technique was emphasized to estimate the additional benefit derived from drip irrigation over flood irrigation. The study reveals that drip irrigation leads to higher water use efficiency, improved crop quality, and environmental sustainability. The adoption of drip irrigation in sugarcane cultivation results in significant economic benefits, with higher net returns and increased yields then farmers following flood irrigation. The findings highlight the positive externality associated with drip irrigation, contributing to water conservation, reduced labor costs, and increased agricultural sustainability with an additional benefit of around Rs. 41,000 derived due to drip adoption over flood irrigation in Sugarcane cultivation. As Karnataka faces evolving challenges in agriculture, the widespread adoption of drip irrigation emerges as a pivotal factor in ensuring the prosperity of sugarcane cultivation and addressing environmental concerns.