Irrigation Water Management Research Articles

Magnetized Irrigation and its Potential in Sustainable Agriculture: A Review

Magnetisation in agriculture is not a conventional method. It has tremendous implications in the crop production as well as mitigating the poor quality soil and water conditions. This reviews looks into the changes that occur in the properties of water on magnetization and the changes in the physico-chemical of soil that are affected by magnetic water. The practical application of magnetic irrigation in agriculture are reviewed based on recent researches. Magnetisaton positively influences the seed germination, seedling establishment, vegetative growth and yield of treated plants. Magnetic irrigation boosts the anti-oxidant and enzyme activity, enhances the plant metabolism and synthesis of plant pigments for coping up the adverse growth conditions. The remediation of poor quality irrigation water and waste water management are another fields where magnetization can be effectively utilized. Magnetic water can be used to alleviate abiotic stresses such as salinity and drought stresses. Magnetised irrigation is a suitable alternative for reduced water requirement and improved water use efficiency. Hence magnetised irrigation is a promising scientific method to boost crop production, while being sustainable and environmentally safe.

An Integrated Approach to the Regional Estimation of Soil Moisture

Automatic or smart irrigation systems benefit irrigation water management. However, measurement sensor networks in automatic irrigation systems are complex, and maintenance is essential. Regional soil moisture estimation avoids the multiple measurements necessary when deploying an irrigation system. In this sense, a fuzzy estimation approach based on decision-making (FEADM) has been used to obtain soil moisture point estimates. However, FEADM requires intelligent weather adjustment based on spatial features (IWeCASF) to perform regional soil moisture estimation. The IWeCASF-FEADM integrated approach for regional soil moisture estimation is developed in this work. IWeCASF provides the inputs for FEADM. FEADM is performed R times; R is the number of checkpoints at which a point estimate is obtained. In this way, regional estimation is achieved when the set of R soil moisture point estimates is completed. Additionally, IWeCASF-FEADM considers the irrigation water records, which are not included in either method individually. This method can detect when the soil moisture is deficient in a region, allowing actions to prevent water stress. This regional estimation reduces an irrigation system’s operational and maintenance complexity. This integrated approach has been tested over several years by comparing the results of regional soil moisture estimation with measurements obtained at many points in the study region.

Irrigation Water Management and Food Security in Nigeria

Food security remains a persistent challenge in Nigeria, a country with a rapidly growing population and a heavy reliance on rain-fed agriculture. Effective irrigation water management is crucial to improving agricultural productivity and addressing this critical issue, particularly in the face of climate change and increasing water scarcity. This study investigates the current state of irrigation water management and its impact on food security in Nigeria. The research employs a mixed-methods approach, combining an extensive literature review with field surveys, interviews, and focus group discussions with key stakeholders, including farmers, water resource managers, policymakers, and subject matter experts. The findings reveal significant gaps in Nigeria's existing irrigation water management system, including outdated infrastructure, inefficient water distribution, limited access to irrigation technology, and poor coordination among relevant government agencies and agricultural extension services. The study explores the multifaceted relationship between irrigation water management and food security, highlighting the impact of water availability, quality, and accessibility on crop yields, livestock production, and overall agricultural output. The analysis also examines the socioeconomic and environmental implications of poor irrigation water management, such as reduced farm incomes, food price volatility, and environmental degradation. Based on the research findings, the study proposes a comprehensive framework for sustainable irrigation water management in Nigeria. This framework emphasizes the integration of technological innovations, policy reforms, institutional strengthening, and community-based approaches to enhance the efficiency, equity, and resilience of the irrigation system. Key elements of the framework include modernizing irrigation infrastructure, promoting precision agriculture techniques, improving water governance and stakeholder coordination, and enhancing the capacity of farmers and water user associations. The implications of this study are far-reaching, as it provides policymakers, development agencies, and agricultural practitioners with a thorough understanding of the critical role of irrigation water management in achieving food security in Nigeria. The proposed framework offers a roadmap for the implementation of sustainable irrigation practices, which can contribute to increased agricultural productivity, improved rural livelihoods, and enhanced national food security. The findings of this research also offer valuable insights for other developing countries facing similar challenges in the realm of irrigation water management and food security.

Modern Drip Irrigation Technology on Tomato and Head Cabbage Production and Its Economic Feasibility at Misrak Silti District, Siltie Zone, Ethiopia

In Ethiopia various techniques were applied to improve on-farm irrigation water management under surface irrigation, especially on furrow irrigation system for last many years, however, it was very difficult to achieve threshold limit of water use efficiency, wisely use of scarce water resources in irrigated field, crop water productivity, precisely controlled application of irrigation water to plant roots, uniform water delivery to all plants, crop yield and its quality, regulate flow, deliver optimum crop water requirement, field water losses, groundwater withdrawal and save labor. It is great practical significance and series of measures using drip irrigation system to solve mentioned problems in irrigated field, because the irrigated agriculture is largest water-consuming sector in this area. This study was aimed to demonstrate drip irrigation technology, prove its economic feasibility and create skills of farmers and extension experts on implementation of the drip system on tomato (Galila 555) and head cabbage (Copen Hagen) productions within groundwater source area on Balo koriso main station in Misrak Silti woreda, Siltie zone, southern Ethiopia. The activity was done for four consecutive years (2019 to 2022 G. C) on fixed plot of 2500 square meter area in collaboration with Agricultural Research Institute and Techno serve project. During demonstration all the costs were considered to economic feasibility including initial investment cost. The study found that the use of drip irrigation saved 3690 m<sup>3</sup>/ha of water compared with use of furrow irrigation. This saved water may irrigate additional 2ha area of land by drip irrigation. This study also revealed that, a net income of 313066.04 ETB/ha in single irrigation season was obtained using modern drip irrigation technology. The farmers and local experts recognized noticeable saving water, fuel cost, irrigating time and labour, good crop performance from demonstrated drip irrigation system and shown interest to use the technology abundantly. Therefore, scaling up locally manageable drip irrigation system around the study area through comprehensive training of farmers and supportive staffs and allowing sufficient local market for drip kits and incentives or loan will be economically feasible and affordable to increase income and saves irrigation water.

Soil amendments and water management to improve attenuation and recovery of wastewater originated nutrients through a vegetation filter

Vegetation filters (VFs) are on-site wastewater (WW) treatments that can be considered as a nature-based solution (NbS). They are green infrastructures that provide several environmental benefits such as non-potable water reuse, contamination reduction, biomass production, landscaping improvements and CO2 fixation, among others. However, nutrient leaching, especially nitrate, partially exists. To overcome this limitation, operational parameters related to the irrigation water management and soil amendments were tested in a real system receiving WW from an office building operated along 4 years.The attenuation of N is improved (up to 83%) in the vadose zone by boosting biodegradation. Lower hydraulic loads and more frequent irrigation events using drippers and the incorporation of woodchips as a layer above the topsoil promote denitrification processes. Changes in organic carbon characteristics also confirm that biodegradation is enhanced.P attenuation is a result of abiotic processes, mainly driven by chemical equilibriums between the liquid and the sorbed and/or precipitated phase and, when uncontrolled changes in the WW quality occurs, removal efficiency is negatively affected. However, only 10% of the samples collected at 45 cm depth present concentrations above 2 mg/L. The woodchips application does not seem to ameliorate P removal regardless of the application method.The implemented measures allow higher soil water content, infiltration and groundwater recharge and prevents aquifer contamination.

Development of soil water content retrieving method for irrigation agriculture areas using the red-edge band of Gaofen-6 satellite

Soil water content (SWC) is an essential index that reflects water conditions in the soil surface during drought, and changes in SWC are critical in guiding agricultural irrigation management. Remote sensing is a crucial means of monitoring SWC, and the red and near-infrared bands of optical remote sensing data are often used to monitor SWC through remote sensing retrieval. With the development of remote sensing technology, red-edge band has also been used to retrieve SWC. It exhibits higher sensitivity to changes in vegetation and SWC, relatively more precise differentiation between vegetation and soil, and more accurate SWC detection. However, there has been relatively little research regarding the use of the red-edge band for retrieving SWC. In this study, we developed a novel method, based on the principle of spectral space and the calculation of modified perpendicular drought index, to calculate the soil water index using the red-edge band of the Gaofen-6 (GF-6) satellite by comparing the retrieval accuracy of GF-6 using different combinations of red, near-infrared, and red-edge bands. Based on the measured SWC in the Shijin Irrigation District of Hebei Province, an SWC retrieval model was established using linear regression. Moreover, the new method was used to retrieve SWC from GF-6 and Sentinel-2 with the same central wavelength, and the reliability of the new method was compared and analyzed. The results revealed that the combination of red band and red-edge band 2 with a central wavelength of 0.74 μm substantial. improved the retrieval accuracy of SWC. Our study provides a new method for retrieving SWC using optical remote sensing, which can effectively improve retrieval accuracy and provide data support for agricultural irrigation monitoring and water management.

Machine learning-based estimation of evapotranspiration under adaptation conditions: a case study in Heilongjiang Province, China.

The prediction of evapotranspiration (ET0) is crucial for agricultural ecosystems, irrigation management, and environmental climate regulation. Traditional methods for predicting ET0 require a variety of meteorological parameters. However, obtaining data for these multiple parameters can be challenging, leading to inaccuracies or inability to predict ET0 using traditional methods. This affects decision-making in critical applications such as agricultural irrigation scheduling and water management, consequently impacting the development of agricultural ecosystems. This issue is particularly pronounced in economically underdeveloped regions. Therefore, this paper proposes a machine learning-based evapotranspiration estimation method adapted to evapotranspiration conditions. Compared to traditional methods, our approach relies less on the variety of meteorological parameters and yields higher prediction accuracy. Additionally, we introduce a 'region of evapotranspiration adaptability' division method, which takes into account geographical differences in ET0 prediction. This effectively mitigates the negative impact of anomalies or missing data from individual meteorological stations, making our method more suitable for practical agricultural irrigation and ecosystem water resource management. We validated our approach using meteorological data from 25 stations in Heilongjiang, China. Our results indicate that non-adjacent geographical areas, despite different climatic conditions, can have similar impacts on ET0 prediction. In summary, our method facilitates accurate ET0 prediction, offering new insights for the development of agricultural irrigation and ecosystems, and further contributes to agricultural food supply.

Future Reference Evapotranspiration Trends in Shandong Province, China: Based on SAO-CNN-BiGRU-Attention and CMIP6

One of the primary factors in the hydrological cycle is reference evapotranspiration (ET0). The prediction of ET0 is crucial to manage irrigation water in agriculture under climate change; however, little research has been conducted on the trends of ET0 changes in Shandong Province. In this study, to estimate ET0 in the entire Shandong Province, 245 sites were chosen, and the monthly ET0 values during 1901–2020 were computed using the Hargreaves–Samani formula. A deep learning model, termed SAO-CNN-BiGRU-Attention, was utilized to forecast the monthly ET0 during 2021–2100, and the predictions were compared to two CMIP6 climate scenarios, SSP2-4.5 and SSP5-8.5. The hierarchical clustering results revealed that Shandong Province encompassed three homogeneous regions. The ET0 values of Clusters H1 and H2, which were situated in inland regions and major agricultural areas, were the highest. The SAO-CNN-BiGRU-Attention and SSP5-8.5 forecasting results generally displayed a monotonically growing trend during the forecast period in the three regions; however, the SAO-CNN-BiGRU-Attention model displayed a declining tendency at a few points. According to the SAO-CNN-BiGRU-Attention and SSP5-8.5 results, during 2091–2100, H1, H2, and H3 will reach their peaks; the SSP2-4.5 results show that H1, H2, and H3 will peak in 2031–2040. At the end of the forecast period, for Clusters H1, H2, and H3, the prediction rate of SAO-CNN-BiGRU-Attention increased by 1.31, 1.56%, and 1.80%, respectively, whereas SSP2-4.5’s prediction rate increased by 0.31%, 0.95%, and 1.57%, respectively, and SSP5-8.5’s prediction rate increased by 10.88%, 10.76%, and 10.69%, respectively. The prediction results of SAO-CNN-BiGRU-Attention were similar to those of SSP2-4.5 (R2 > 0.96). The SAO-CNN-BiGRU-Attention deep learning model can be used to forecast future ET0.

Water Requirement and Irrigation Scheduling of Potato (<i>Solanum tuberosum </i>L.) by Using CROPWAT 8.0 at Welmera District, Central Highland of Ethiopia

In Welmera district, due to poor management of irrigation water, determination of crop water requirements and appropriate irrigation scheduling is important to prevent over or under-irrigation. The 30-year climatic data (1993- 2023) collected from Holeta Agricultural Research Center were used to estimate potato water requirements and irrigation scheduling using CROPWAT 8.0 model. The results shows that, the CWR, NIR and GIR for potato crop was 444.9 mm, 371.7 mm and 619.5 mm respectively. For the early January planted potato, irrigation should be given fourteen times (1-Jan, 9-Jan, 19-Jan, 29-Jan, 5-Feb, 12-Feb, 19-Feb, 26-Feb, 5-Mar, 11-Mar, 19- Mar, 26-Mar, 31-Mar and last irrigation on 10-Apr) with a gross irrigation water amount of 24.2 mm, 19.9 mm, 23.3 mm, 24.2 mm, 26.9 mm, 35.5mm, 38 mm, 43.5 mm, 43.4 mm, 40.8 mm, 41.9 mm, 39.5 mm, 40.2 mm and 42.9 mm depth respectively. The results obtained from this study can be useful in preventing over or under-irrigation and for future planning of water resource, thereby helping to save water in meeting the CWRs, and can be used as a guide for farmers to select the amount and frequency of irrigation for the crop being studied.

Field-grown lettuce production optimized through precision irrigation water management using soil moisture-based capacitance sensors and biodegradable soil mulching

AbstractScientists, environmentalists, and farmers are currently in pursuit of sustainable agricultural practices that can effectively ensure global food security while simultaneously mitigating environmental degradation. A field experiment was conducted to elucidate the impact of low-cost capacitance soil moisture-based sensors on lettuce (Lactuca sativa L.) irrigation water conservation, agro-physiological aspects, and nutritional characteristics. The experiment also involved the use of five different types of soil mulching films: white geotextile (WGup), green geotextile (GGup), black plastic (BPup), white geotextile for both above and below ground (WGup-down), green geotextile for both above and below ground (GGup-down), in addition to un-mulched soil (control). The findings demonstrated that the application of WGup, BPup, WGup&down, and GGup&down resulted in a significant improvement in irrigation water conservation, with WGup exhibiting the highest savings at 41.86%, while the control group exhibited the least amount of water savings at 19.87%. Moreover, the highest productivity levels were observed in plants mulched with GGup&down, reaching 47,944.68 kg ha−1, whereas the lowest productivity was recorded in plants mulched with green geotextile GGup at 22,377.89 kg ha−1. In terms of irrigation water productivity (IWP), the order of effectiveness was BPup > GGup-down > WGup > WGup-down > GGup > Control, with BPup achieving the highest IWP at 60.19 kg m−3 and the control treatment reporting the lowest at 27.80 kg m−3. The percentage of the irrigation water applied for crop evapotranspiration (Irc) showed that the control treatment saved the least amount of irrigation water, saving only 19.87%, while the best treatment was WGup, achieved the highest percentage of irrigation water savings at 41.86%. Additionally, mulched plants exhibited higher levels of nutrients (N, P, Ca, Mg, Fe, Mn, and Zn), ascorbic acid (AsA), and total phenol content (TPC), while showing lower nitrate content in the leaves compared to non-mulched plants. Overall, the utilization of soil moisture-based capacitance sensors and biodegradable mulching films has proven to be highly effective and low cost by 16.633 US$ year−1 to enhance irrigation water productivity, growth performance, nutritional quality, and overall productivity of lettuce crops, thereby contributing to the sustainability of lettuce production in arid regions.

Quantifying energy fluxes in Tarai region of India during post-monsoon season: Insights from METRIC model, ET station and remote sensing

Accurate evapotranspiration (ET) assessment is crucial for agricultural water management, encompassing crop water requirements, irrigation scheduling, water budgeting and drought monitoring. This study integrates remote sensing-based surface energy balance model with in-situ ET measurements to evaluate surface energy fluxes and ET in Pantnagar, Tarai region. The Mapping Evapotranspiration at high Resolution with Internalized Calibration (METRIC) model, using high-resolution remote sensing data, was validated against observations from an ET station equipped with large aperture scintillometer and micrometeorological tower, situated in sugarcane farm at Govind Ballabh Pant University of Agriculture & Technology (GBPUA&T), Pantnagar. On November 13, 2021, METRIC and Landsat-9 satellite data estimated an instantaneous ET of 7.39 mm day-1, closely aligned with the observed value of 6.72 mm day-1 recorded by the ET station. The findings confirm the METRIC model's high accuracy for spatial ET estimation and its associated micrometeorological variables. This study underscores the utility of the METRIC model, ET station and remote sensing in determining ET and energy flux which may be further utilised in the estimation of crop water requirement, energy fluxes and irrigation water management for sugarcane cultivation in the Tarai region.

Participatory evaluation and demonstration of furrow irrigation systems with full irrigation application on Onion (Allium cepa L.) yield, yield component and water use efficiency at Docha Dembela in Demba Gofa woreda, South Ethiopia

Poor irrigation water management is one of the major factors limiting crop production in Ethiopia. Field experiment was conducted at farmers filed at Docha Dambal kebele in Demba Gofa woreda, Gofa zone, South Ethiopia for two consecutive years (2019 & 2020) to evaluate and demonstrate the effect of furrow irrigation systems on onion yield and water use efficiency. The treatments consisted of three furrow irrigation systems (conventional, alternative and fixed). The irrigation treatments were laid out in randomized complete block design with six replications and participant farmers were used as a replication. Results indicated that highest mean value of marketable bulb yield (27758.2 kg ha-1) was brought under Conventional furrow system. However the lowest mean value of marketable bulb yield was recorded from the fixed furrow system (20482.5). However, Superior water use efficiency of 13.33kg/m3 was recorded from alternative furrow irrigation system. The lowest water use efficiency (7.78 kg/m3) was recorded from the Conventional furrow system. Therefore, It could be concluded that alternate furrow irrigation system maximized water use efficiency of onion with tolerable yield penalty at the study area. This result is important for farmers to irrigate supplemental lands with water saved, thus achieving a more efficient and rational use of land and water resources in the water limited area. If areas with no water scarcity, conventional furrow system could be a potential approach for promoting onion bulb yield under field conditions.

Modelling soil water and nutrient dynamics under different irrigation techniques of onion production

ABSTRACT Irrigation remains important to meet the needs of the people by increasing agricultural productivity. However, its water productivity in developing countries is low due to inefficient irrigation water management. The main objective of this study was to evaluate soil water, crop growth and nutrient dynamics under different irrigation techniques. Hydrus-1D model was used to simulate soil water content (SWC), actual evapotranspiration (ETa) and soil leachates. The model performance was evaluated by comparing the measured and simulated treatment variables. The Hydrus-1D performance showed good agreement between the observed and simulated SWC (R2 = 0.55–0.81; NRMSE = 0.01-0.09; d-index = 0.95-0.99) and with a very good agreement for nitrate-nitrogen (NO3–N) leaching (R2 = 0.97, d index = 0.99 and NRMSE = 0.02). Similarly, performance in simulating PO4-P were acceptable (R2 = 0.88; d index = 0.99; NRMSE = 0.04). The value of SWC (cm3 cm−3) ranged from 0.30 to 0.38 at 10 cm and from 0.27 to 0.37 at 20 cm soil depths. The seasonal drainage water was reduced to 86%, 87%, and 54 %, respectively for AFI, FFI, and OHI treatments compared with CFI treatment. The NO3–N leaching was reduced by 41%, 71%, and 83% under AFI, FFI, and OHI compared with CFI while phosphate – P (PO4-P) leaching was 60%, 66%, and 79.6%, respectively, lower in AFI, FFI, and OHI than CFI. The highest seasonal ETa (421.95 mm) was found in CFI while the lowest (335.22 mm) was found in AFI treatment. Besides, the highest IWP (9.11 kg/m3) was obtained from AFI technique indicating that that AFI was the most efficient irrigation technique in saving both nutrient and water under onion production. Hydrus-1D could be a successful tool for predicting water and nutrient transport management decisions to improve water and nutrient management.

A synoptic review of deficit irrigation methods: sustainable water-saving strategies in vegetable cultivation

ABSTRACT It is elusive and highly challenging to sustain the productivity of vegetable commodities under limited available natural resources and anticipated future climatic scenarios. Amongst available natural resources, water remains the most limiting factor. Present vegetable cultivation practices involve the utilization of excessive quantities of water, thereby leading to the wastage of precious water resources. Therefore, sustainable management of irrigation water is crucial for future vegetable cultivation, as most vegetable crops are vulnerable to water scarcity at different growth stages, which can result in yield and post-harvest quality losses. Adoption of deficit irrigation (DI) is one of the sustainable irrigation water management approaches. DI is a sustainable water-saving approach, as irrigation water is applied in limited or lower quantities than the actual evapotranspiration-based crop water requirement. Strategic application of water at the right time and quantity with the right technique can greatly improve water use efficiency and water productivity. It could also enhance the post-harvest quality with marginal yield loss. Yield losses whatsoever could be compensated by expanding agricultural areas in water-scarce zones by adopting the DI strategy. This review discusses the concept and types of DI and examines its implications for the morpho-physiology and productivity of commercially important vegetable crops.

Water Requirement and Irrigation Scheduling of Selected Vegetable Crops Grown in Welmera District, Central Highland of Ethiopia

Accurate quantification of irrigation water requirement at different physiological growth stages of crops is important to prevent over or under irrigation. A study was carried out to determine the crop water requirement and irrigation scheduling of the selected vegetable crops grown under irrigated conditions at Holeta, Central Highland of Ethiopia. The crops include, cabbage, and tomato. By using the 30-year climatic data, the crop evapotranspiration (ETc), reference crop evapotranspiration (ETo), and irrigation water requirement for each crop were determined using the CROPWAT model. The study shows that the total CWR of cabbage, and tomato was estimated to be 426.6mm, and 497.7mm respectively, and the total GIR of cabbage, and tomato was found to be 598.3 mm, and 691.7 mm respectively. for early January planted cabbage, irrigation should be given twelve times ( 1-Jan, 9-Jan, 16-Jan,24-Jan, 2-Feb, 11-Feb, 21-Feb, 5-Mar,15-Mar, 25-Mar, 2- Apr and last irrigation on 12-Apr) with a gross irrigation water amount of 59.8mm, 32.5mm, 31.5mm, 35.2mm,42.2mm,43.3mm,48.1mm, 52mm, 51.3mm, 49.5mm, 51mm, and 51.7mm depth respectively. Similarly for early January planted tomato, irrigation should be given twelve times (1-Jan, 5-Jan, 10-Jan, 16-Jan, 21-Jan, 29-Jan, 6-Feb, 15-Feb, 26-Feb, 12-Mar, 26-Mar, and the last irrigation on 10-Apr) with a gross irrigation water amount of 53.9mm, 19.3mm, 25.5mm, 30.7mm, 30.6mm, 36.4mm, 47.8mm, 58.5mm, 73.4mm, 83.5mm, 80.9mm, 80.7mm irrigation depth respectively. This study might be useful to prevent over or under irrigation which will help in effectively planning and management of irrigation water in the district.

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.

Correction to: Enhancing Sugarcane Productivity through Scientific Irrigation Water Management in Western India

Correction to: Enhancing Sugarcane Productivity through Scientific Irrigation Water Management in Western India

Penggunaan CROPWAT 8.0 untuk Menentukan Kebutuhan Air Irigasi Tanaman Tomat pada Tanah Regosol di Kawasan Ternate Utara, Provinsi Maluku Utara

Tomato is an important crop in Ternate, North Maluku Province, Indonesia. This study aimed to determine the irrigation water requirements for tomato cultivation on Regosol soil in the North Ternate region using the CROPWAT 8.0 model. Climate data, crop data, and soil data were collected and processed using the CROPWAT 8.0 program. The results showed that the irrigation water requirements varied significantly between the rainy and dry seasons. During the rainy season, the total irrigation water requirement ranged from 60 to 107 mm, while in the dry season, it was much higher, ranging from 130 to 187 mm. This difference was primarily due to the low rainfall during the dry season. Simulations of planting at different periods showed relatively minor variations in crop water requirements, reflecting the stable weather conditions throughout the year in Ternate. The findings of this study can assist local tomato farmers in managing irrigation water more efficiently and effectively, thereby improving crop productivity and reducing the risk of water shortage.

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.

Effect of Gender and Generation on the Adoption of Irrigation and Good Farming Practices in Bontanga and Golinga Irrigation Schemes in Northern Ghana

This study examined the challenges faced by men, women, and different age groups in irrigation water management and farming practices in the Bontanga and Golinga irrigation schemes. The results of the study revealed that there are significant differences in irrigation and farming practices between men and women as well as between older and younger farmers. For men, the main challenges were; limited access to financial resources for investing in modern irrigation technologies and equipment, inadequate knowledge and awareness of sustainable farming practices and water management insufficient government support, and lack of policies tailored to their specific needs. For women, these were gender inequalities and limited access to land, water, and productive resources, lack of control and decision-making power over irrigation water allocation, and limited access to training and extension services to enhance their farming skills. Youth recognized limited interest and involvement in agriculture due to the perception of low profitability and lack of modernization, inadequate access to education and training opportunities in agricultural practices and water management, and insufficient support and mentorship programs to encourage youth participation in farming.