Irrigation Water Management Research Articles

Literature review on optimization of transboundary water for irrigation

ABSTRACT Transboundary water resources are essential for agricultural sustainability and regional development, and they are intrinsically linked to achieving the United Nations' SDGs and the water-food-energy nexus (WFE-NEXUS) concept. Despite challenges such as conflicting allocation and climate change impacts, effective transboundary water management for irrigation is crucial to meeting the SDGs of eradicating hunger, providing clean water and sanitation, offering affordable and sustainable energy, and taking climate action. This work synthesizes approaches to transboundary water for irrigation optimization, highlighting the significance of a holistic plan that considers both technical and social factors. Remote-sensing technologies, data forecasting, hydrology and hydraulic modelling, and water resource modelling all contribute to maximize water allocation and policy creation, particularly when paired with collaborative government features. This integrated approach to transboundary water for irrigation optimization fosters long-term development by improving livelihoods, resilience, and inclusive growth through efficient resource management.

Comprehensive Review of Crop Water Requirement Estimation Techniques: Approaches, Challenges, and Future Directions

In order to meet the growing demand for water, water scarcity is a significant issue that needs attention. Agriculture crops are not getting enough water because of this problem. Consequently, figuring out how much water a given crop needs requires using the right method. Accurate crop water requirements must be measured in order to schedule irrigation effectively, which in turn leads to efficient crop water management. To restore the lost moisture and promote the best possible growth for plants, irrigation is used. Water management and irrigation scheduling fundamentally depend on an accurate calculation of the crop's crop water requirements (ETc). Accurate evapotranspiration measurements are necessary for effective irrigation water management. Evapotranspiration (ET), a process that measures the amount of water lost from soil and crops through transpiration and evaporation processes, respectively, is dependent on a variety of meteorological factors. A significant factor in determining crop water requirements and irrigation schedules is reference evapotranspiration. There exist multiple theories and methodologies for estimating reference evapotranspiration, ranging from empirical to physical based. Reference Evapotranspiration is referred to the idea behind ET is to calculate ET based on a reference surface that is comparable to a deep surface of green grass that is consistently growing, completely covering the surface with enough water, and looking stable. The goal of irrigation futures is to choose a suitable model for estimating reference crop evapotranspiration. In order to calculate the amount of water needed for a crop, multiply ETo by the crop coefficient (Kc), which is dependent on the phases and length of a crop's growth. Regression, fuzzy logic, Penman-Monteith, Blaney-Criddle, Hargreaves, ANN and WNN, and other conventional and non-traditional methods are used to estimate ETo.

Innovative Solar Water Pump with Automatic Water Level Regulator for Efficiency Rice Field Irrigation

Nowadays, most of human activities are related to the use of technology. The invention of various innovative ideas that simplify human life is essential. One of the uses advancement technologies can applied in agricultural field, especially for irrigation processes since it becomes the critical step in agricultural activity since it ensures that plants receive an adequate water. Due to the importance of irrigation, this community service activity aimed to provide information on how to build a solar pump for irrigation purposes and implement an innovative solar water pump with automatic water level control to improve the efficiency of irrigation of rice fields in Bekiung Village. The system is designed using solar panels as the main energy source, minimizing dependence on conventional electricity and fossil fuels. With the integration of water level sensor and automatic control system, the pump is able to adjust the water supply in real-time based on the actual needs of rice plants. Field tests show that the system is able to provide water consistently and efficiently, reducing water and energy wastage. The implementation of this technology not only improves irrigation efficiency, but also supports environmentally friendly sustainable agriculture. The results of this study are expected to serve as a model for other villages facing similar challenges in irrigation water management.

Examining the Barriers to Redesigning Smallholder Production Practices for Water-Use Efficiency in Numbi, Mbombela Local Municipality, South Africa

Smallholder farmers in South Africa face issues related to water shortages and poor irrigation water management. This study investigated barriers to improving water-use efficiency (WUE) in smallholder production practices in Numbi, South Africa. The objectives were to identify barriers in redesigning production practices for higher agricultural productivity and analyze the relationship between irrigation water supply and the adoption of WUE methods. From a population of 7696 people, 141 smallholder farmers were sampled using a simple random sampling technique through Taro Yamane’s sample size formula. The data were analyzed using Pearson’s correlation coefficient and descriptive statistics. Unreliable water supply (M = 3.78, SD = 0.85), poor soil water retention (M = 3.78, SD = 0.85), lack of water-efficient irrigation systems (M = 3.91, SD = 0.71), lack of water storage facilities (M = 3.85, SD = 0.93), limited access to credit (M = 4.09, SD = 0.85), income instability due to market fluctuations (M = 3.96, SD = 0.91), inadequate knowledge of irrigation management (M = 4.00, SD = 0.84), and harsh climatic factors were identified. A positive correlation (r = 0.339, n = 141, p < 0.001) between irrigation water source and WUE techniques was evident, indicating that irrigation water source had an insignificant impact on WUE methods. Resolving these barriers requires a holistic approach focusing on investments in irrigation infrastructure and targeted education initiatives by extension agents and other stakeholders, as this can enhance agricultural productivity.

An improved optical trapezoid model to identify wetlands and irrigation water ponds in the arid irrigation district using Google Earth Engine

ABSTRACT In arid regions, wetlands support ecosystem with high biodiversity and productivity. Meanwhile, irrigation during the fallow period often results in the temporary formation of water ponds in the cropland, which plays a critical role in agricultural productivity. The prompt identification of wetlands and irrigation water ponds in irrigation districts is important for the protection of local wetland ecosystem and the effective management of irrigation water. Utilizing the OPtical TRApezoid Model (OPTRAM) for soil moisture estimation, we have proposed an improved version of OPTRAM aimed to identify wetlands and irrigation water ponds in irrigation district using Sentinel-2 data through Google Earth Engine platform. Different criteria were used for the identification of wetland and irrigation water pond, given the greater diversity associated with wetlands. Parameters for the wet edge determined from OPTRAM were used to identify wetlands, while an additional threshold was added to the model and calibrated in accordance with the irrigated area to identify irrigation water ponds. The improved OPTRAM was applied in Hetao Irrigation District (HID) of Northwest China from 2016 to 2023, where autumn irrigation applied in late autumn after crop harvesting was considered. The identified distributions of wetland and autumn irrigation were validated with observations from field survey and statistical data, and were also compared with other remote sensing products. Results show that the proposed model is effective in identifying both wetlands and irrigation ponds. Considering the wetlands, the distances from identified boundaries to the actual boundaries obtained from field surveys were calculated, revealing the mean absolute error of 6.99 m, alongside a validation accuracy ratio of 0.94 for points located within wetlands. For autumn irrigation extent, the overall accuracy is 0.90 based on the observations from field survey, with mean absolute relative errors for irrigated areas across four sub-irrigation districts recorded as 20.55%, 8.10%, 12.83%, and 11.38%, respectively, when compared with statistical data. The majority of wetlands within HID are small in size and scattered, with different trends observed in the wetland areas of sub-irrigation districts and Wuliangsuhai Lake. Autumn irrigated croplands are mainly concentrated in Jiefangzha sub-irrigation district while being scattered across other sub-irrigation districts, depicting an overall decreasing trend in the autumn irrigated area. In summary, the proposed model performed well in identifying both wetlands and irrigation ponds, and can offer valuable support for the conservation of wetland ecosystem and irrigation management.

Simulating Agricultural Water Recycling Using the APEX Model

Irrigation plays a vital role in many agricultural crop production regions. Drainage water recycling (DWR) is a popular irrigation water management system that collects excess water drained from cropland fields and stores it in on-site reservoirs for reuse. The efficacy of these systems varies by location, climate, irrigation frequency, and crop demands. Simulating this system would be beneficial for assessing the impact of water and land management practices on agriculture and natural resources. This study presents the development of computational algorithms for DWR simulation with the Agricultural Policy Environmental eXtender (APEX) model, along with the results for 39 testing sites where both reservoir and drainage systems are adopted. Simulating a DWR system with the revised reservoir module, the APEX model simulates irrigation water reuse ranging between 29% and 93%; sediment reduction of around 66%; nitrogen loss reduction of 23% and 73% for the mineral and organic forms, respectively; and phosphorus loss reduction of 22% and 79% for the soluble and sediment-transported forms, respectively. In conclusion, the results provided by the APEX model for sediment loss reduction align with field data, but discrepancies for nitrogen and phosphorus losses emerged from this test.

Impact of Climate and Socio-Economic on Irrigation Water Management and Agricultural Water Productivity

Water security and food security are fundamental pillars of sustainable social and economic development [...]

Assessment of upscaling methodologies for daily crop transpiration using sap flows and two-source energy balance models in almonds under different water statuses and production systems

Abstract. Daily transpiration (Td) is crucial for both irrigation water management and increasing crop water productivity. The use of the remote-sensing-based two-source energy balance model (TSEB) has proven to be robust in estimating plant transpiration and evaporation separately for various crops. However, remote sensing models provide instantaneous estimations, and so daily upscaling approaches are needed to estimate daily fluxes. Daily upscaling methodologies have not yet been examined to upscale solely transpiration in woody crops. In this regard, this study aims to evaluate the proper image acquisition time throughout the day and four methodologies used to retrieve Td in almond trees with different production systems and water statuses. Hourly transpiration (Th) was estimated using the TSEB contextual approach (Th–TSEB) with high-resolution imagery five times during two diurnal courses. The tested methodologies were the following: the simulated evaporative fraction variable (EFsim), irradiance (Rs), reference evapotranspiration (ETo), and potential evapotranspiration (ETp). These approaches were first evaluated with in situ sap flow (T–SF) data and were then applied to the Th–TSEB. Daily T–SF showed significant differences among production systems and levels of water stress. The EFsim and ETp methods correlated better with measured T–SF and reduced the underestimation observed using the Rs and ETo methods, especially at noon in the severely water-stressed trees. However, the daily upscaling approaches applied in the TSEB (Td–TSEB) failed to detect differences between production systems. The lack of sensibility of Th–TSEB among production systems poses a challenge when estimating Td in canopies with discontinuous architectural structures. The use of ETp as a reference variable could address this issue as it incorporates various aerodynamic and radiative properties associated with different canopy architectures that influence the daily Th–SF pattern. However, more accurate ETp estimates or more advanced ETp models are needed.

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.