Supply Management Research Articles

Runoff variability in the Truckee-Carson River basin from tree rings and a water balance model

Abstract Regional warming and associated changes in hydrologic systems pose challenges to water supply management in river basins of the western United States, and call for improved understanding of the spatial and temporal variability of runoff. We apply a network of total-width, subannual width and delta blue intensity tree-ring chronologies in combination with a monthly water balance model to identify droughts and their associated precipitation (P) and temperature (T) footprints in the Truckee-Carson River basin (TCRB). Stepwise regression gave reasonably accurate reconstructions, from 1688 to 1999, of seasonal P and T (e.g., R2 = 0.50 for May-Sept T). These were disaggregated to monthly values, which were then routed through a water balance model to generate “indirectly” reconstructed runoff. Reconstructed and observed annual runoff correlate highly (r = 0.80) from 1906 to 1999. The extended runoff record shows that 20th century droughts are unmatched in severity in a 300-year context. Our water balance modeling reconstruction advances the conventional regression-based dendrochronological methods as it allows for multiple hydrologic components (evapotranspiration, snowmelt, etc.) to be evaluated. We found that imposed warming (3 °C and 6 °C) generally exacerbated the runoff deficits in past droughts but that the impact could be lessened and sometimes even reversed in some years by compensating factors, including changes in snow regime. Our results underscore the value of combining multi-proxy tree-ring data with water balance modelling to place past hydrologic droughts in the context of climate change.

SWASTHA: Revolutionizing Medical Supply Management in Sri Lankan Healthcare

SWASTHA: Revolutionizing Medical Supply Management in Sri Lankan Healthcare

Assess The Workload Management Model and Enhanced Quality Control in The Central Sterile Supply Department:  A Study Protocol.

Introduction The Central Sterile Supply Department (CSSD) plays a crucial role in ensuring the safety and efficacy of medical instruments and equipment used in healthcare settings. Effective workload management and quality control are essential for maintaining high standards of patient care and minimizing the risk of healthcare-associated infections. This study protocol aims to assess the implementation and impact of a new workload management model and enhanced quality control measures in a CSSD setting. Methods The study will employ a mixed-methods approach, including quantitative analysis of workload data, qualitative interviews with CSSD staff, and observational assessments of workflow and quality control procedures. The workload management model under investigation involves the allocation of resources based on demand patterns and the implementation of scheduling algorithms to optimize staff efficiency. Enhanced quality control measures include the implementation of advanced sterilization technologies, rigorous inspection protocols, and continuous staff training initiatives. Results The study expects to provide insights into the effectiveness of the workload management model in optimizing resource allocation and improving staff productivity. Additionally, it aims to evaluate the impact of enhanced quality control measures on the reliability and safety of instrument sterilization processes. Findings from this study will inform recommendations for further improvements in CSSD operations and contribute to the advancement of best practices in sterile supply management. Conclusion The successful implementation of an effective workload management model and enhanced quality control measures in the CSSD is crucial for maintaining patient safety and ensuring the efficient functioning of healthcare facilities. By systematically evaluating the implementation and impact of these interventions, this study protocol seeks to contribute to the ongoing improvement of CSSD operations and the enhancement of healthcare quality.

Drivers of Sustainable supply chain for sustainable development in industry

This analysis explores the different elements that constitute sustainable supply chains used by companies as genre on the road to sustainable development across different industries. The analysis of a body of literature and empirical data is carried out by a critical objective to determine the fundamental aspects of sustainability practices. The research suggests that we should have the necessary knowledge of these drivers for the stage to be raised of the environmental responsibility, social equity and economic development. Strategies are detailed to enable stakeholders throughout industries in adopting sustainable supply chain methods. Through this process, the long-term resilience of supply chains and the sustainability of the profitable position are promoted. The results are of this type, clarifying the crucial role of sustainable supply chain in reaching the global sustainability targets and promoting sustainability model for the companies and societies all over the world. Through this research we strive to add to the already established supplies chain management literature and aid the change process management in the pursuit of sustainable development in the different industries. Result of the cocreation with this domain has brought up meaningful implications to the literature. One of the new concepts we are proposing is a dynamic setting for a three-level model serving as a tactical plan for strategic sustainable supply management. Our study has contributed a theoretical framework that distinguishes practical facts of supply chain management and is for the purposes of future research and appraisals in terms of UN 17 Sustainable Development Goals

Water, energy and environment nexus: Quantitative assessment for integrated power plants with renewable energy

The population increase and the demand for water and energy, accompanied by the implications of environment pollution for natural and human resources, indicate the critical necessity for a coherent movement towards nexus between water, energy, and environment. Due to the fact that power generation industry is responsible for a significant proportion of water and fuel consumption and Carbon dioxide emissions within the world, in this research, the application of the hybrid renewable system in a thermal power plant has been assessed based on the approach of analyzing the link between energy, water and environment. The design of the solar system and the assessment of carbon balance during the power plant lifetime have been conducted in PVsyst application in 2022. Moreover, ReCipe environmental model has been used for assessing the effect of decrease in carbon emission on the ecosystem. The findings of the research indicate that the replacement of at least 2 % of the nominal capacity of the fossil fuel power plant with the renewable one, prevents the emission of 1431.28 tons of carbon dioxide yearly. This amount equals to 380.34 cubic meters of reserve in fossil fuel consumption and 391.73 tons of crude oil. The results also showed that in addition to preserving natural resources, the hybrid cycle design leads to significant water demand reduction which equals to 3842 cubic meters with the capacity to supply underground water sources. Due to the interests of preserving water and energy resources and decreasing carbon emission in power plant industry, within the framework of nexus approach, management of energy supply by replacing resources and using water and heat recovery technologies and application of energy demand management policies based on energy efficiency and environmental implications is recommended.

Utility of decision tools for assessing plant health risks from management strategies in natural environments.

Increased imports of plants and timber through global trade networks provide frequent opportunities for the introduction of novel plant pathogens that can cross-over from commercial to natural environments, threatening native species and ecosystem functioning. Prevention or management of such outbreaks relies on a diversity of cross-sectoral stakeholders acting along the invasion pathway. Yet, guidelines are often only produced for a small number of stakeholders, missing opportunities to consider ways to control outbreaks in other parts of the pathway. We used the infection of common juniper with the invasive pathogen Phytophthora austrocedri as a case study to explore the utility of decision tools for managing outbreaks of plant pathogens in the wider environment. We invited stakeholders who manage or monitor juniper populations or supply plants or management advice to participate in a survey exploring their awareness of, and ability to use, an existing decision tree produced by a coalition of statutory agencies augmented with new distribution maps designed by the authors. Awareness of the decision tree was low across all stakeholder groups including those planting juniper for restoration purposes. Stakeholders requested that decision tools contain greater detail about environmental conditions that increase host vulnerability to the pathogen, and clearer examples of when management practices implicated in pathogen introduction or spread should not be adopted. The results demonstrate the need to set clear objectives for the purpose of decision tools and to frame and co-produce them with many different stakeholders, including overlooked groups, such as growers and advisory agents, to improve management of pathogens in the wider environment.

Optimizing Solar Evaporation Efficiency: Integrating Controllable Water Supply and Efficient Salt Collection Methods

Solar desalination presents a promising solution for providing high-purity fresh water in regions lacking sophisticated energy infrastructure. Specifically, the efficiency of solar-energy driven interfacial evaporation relies on achieving a balance between supplied solar energy and the energy demand for evaporation through water supply management. Another significant challenge for practical application is salt crystallization on the photoabsorber surface. To address these issues, two strategies are proposed: I) Construction of a 3D solar evaporator that achieves a balance between supplied energy and the heat energy required for interfacial evaporation (demand energy) by optimizing the height of the support structure. II) Implementation of a tunable 2D water supply path made of cotton. This not only facilitates optimal water supply for interfacial evaporation but also functions as a salt collection layer, enabling efficient salt collection post-desalination. With the specific design of the proposed 3D solar evaporator, our device achieves a remarkable efficiency approaching its performance limit (94%) with an evaporation rate of 2.30 kg m-2 h-1, along with efficient salt collection and scalability. This work presents a novel approach for fabricating a cost-effective solar evaporator capable of consistently delivering affordable fresh water in remote areas.

Total quality management implementation practices and customer satisfaction: the role of innovative employee behavior and employee empowerment

This study shed additional understanding on how Total Quality Management (TQM) practices affect customer satisfaction through the innovative behavior of employees. Based on quantitative data from the 5 Teaching Hospitals in Ghana, this study employed a multistage sampling procedure to analyze the relationship between innovative employee work behavior and total management commitment, Training and Education, Performance Management System, Supplier Management, and innovative employee work behavior. We find that these relationships are positive and that the relationship between TQM practices and customer satisfaction is mediated by innovative employee work behavior. In addition to theoretical contributions to the field of TQM and healthcare systems, these results have managerial implications for hospital professionals who work at prioritizing the adaptation of TQM practices.

Development of a Framework to Improve the Provision of Water, Sanitation, and Hygiene in Healthcare Facilities of Mwandi District in Western Province

Healthcare facilities (HCFs) require safe water, sanitation, hygiene, environmental cleaning, and waste management (WASH) in the provision of quality services to promote, restore, maintain, and improve health. However, the unavailability of studies on the challenges and opportunities of WASH services in HCFs of Mwandi District has limited the potential for improved health care and quality of life. Without proper elucidation, this has the potency to dissuade women from using HCFs for childbirth and healthcare, potentially increasing maternal mortality rates. To examine the challenges and opportunities in accessing safe WASH services in HCFs in Mwandi District, more of Qualitative techniques were utilized to gather data from 8 HCFs in Mwandi District. This involved initial observations employing the WASH Status Checklist, followed by focus group discussions with expectant mothers and 23 key informant interviews. Thematic analysis was used to analyse the data.  The results showed that only half of the investigated facilities provided basic water services, hampered by water salinity issues. Even though most facilities had improved sanitation facilities, they, however, do not meet the basic sanitation standards. This was primarily due to issues such as corroded pipes, insufficient accessible toilets for people with disabilities, and the absence of menstrual hygiene facilities. Many facilities lacked gender-segregated staff facilities. Most of the facilities had functional hand hygiene facilities but also did not meet the basic standards due to a lack of soap for hand washing. A significant number encounter inefficiencies in cleaning protocols, and the majority face poor infrastructure conditions. The findings further revealed that these challenges stem from inadequate prioritization and funding for Water, Sanitation, and Hygiene (WASH) initiatives. The existing knowledge often concentrates on individual components, the findings stress the necessity for an integrated approach that collectively addresses water supply, sanitation, hygiene, and waste management. This holistic perspective can significantly contribute to the development of more effective guidelines and policies, offering a nuanced understanding of the interconnected nature of WASH components. Furthermore, the research sheds light on the pivotal role of localized political will, specifically highlighting the influence of Health Centre Advisory Committees (HAHC) in shaping governance at the community level, especially concerning WASH projects. The study offers a comprehensive overview of challenges and sustainability opportunities related to WASH services, crucial for their effective functioning. It emphasizes the necessity for heightened awareness and increased budget allocation for the sustainable maintenance of WASH services

Assessment of Factors Impacting Water Supply Services in Lusaka District: A Case of Lusaka Water Supply and Sanitation Company

The water supply situation in Lusaka district faces numerous challenges related to reliability, accessibility, and sustainability of water supply services. Despite a population of 3,079,964, only 134,807 household connections were established by LWSC in 2022. With a record 4.5% population increase from 2022 to 2023, the demand for water stands at over 420,000 cubic meters per day, while LWSC produces 250,000 cubic meters per day. Groundwater, accounting for 57% of LWSC's water, is threatened by land development and pollution. Meanwhile, 45% of the population relies on site sanitation, contributing to groundwater pollution, the very source LWSC is dependent upon. Lusaka faces low or no water supply, an average of 18 hours per day. Despite existing research on the peri-urban water supply, a gap remains in addressing the challenges of rapidly growing urban areas like Lusaka. This study aims to fill this gap by providing a comprehensive analysis focusing on the unique challenges faced by LWSC, such as land development, population growth, and climate change. The research will offer practical solutions for sustainable water supply management in Lusaka and similar contexts. The research philosophy employed for this study is interpretivism, as it allows for a deep understanding of the subjective experiences and perceptions of experts involved in the water supply sector in Lusaka. This approach aligns with the qualitative nature of the research, which aims to explore and understand the complex interactions between various factors influencing water supply services in the district. The findings of the study reveal that climate change, population growth, and land development are significant factors influencing water supply services in Lusaka. Erratic rainfall patterns and prolonged droughts have led to challenges in water availability and quality, while rapid population growth has increased the demand for water supply services, putting pressure on the existing infrastructure. Unplanned land development has also led to challenges in water supply services, particularly in areas with shallow water tables that are vulnerable to groundwater pollution. The study recommends investing in climate-resilient infrastructure, diversifying water sources, enhancing water conservation practices, and strengthening land use planning regulations to address these challenges and ensure the sustainability of water supply services in Lusaka.

Factors Affecting the Pharmaceutical Supply Chain: A Systematic Review

Background: Medicine plays a crucial role in societal health, and even minor disruptions in the supply chain can lead to crises. An organized supply chain ensures that patients receive their medications in the best possible conditions. Objectives: This study aims to identify and categorize key variables associated with the pharmaceutical supply chain. Methods: We conducted a systematic review of all studies on drug supply chain management, adhering to the PRISMA guidelines. The search was carried out in both international and national databases from January 30, 2000, to March 30, 2023. We used specific keywords related to the drug supply chain for this search. We excluded articles, letters to the editor, and editorials from the review and ultimately qualitatively examined 34 studies. The quality of these articles was assessed using the CASP checklist. Results: We identified key variables and classified them into five categories: monitoring and control (16 variables), information technology and intelligence (4 variables), human capital (10 variables), physical and financial resources (16 variables), and suppliers (4 variables). Conclusions: It is imperative for health policymakers to develop effective strategies in monitoring and control, information technology and intelligence, human capital, physical and financial resources, and management of drug suppliers. These strategies are essential for the efficient supply and distribution of drugs within the supply chain.

Eco-Energetical analysis of circular economy and community-based virtual power plants (CE-cVPP): A systems engineering-engaged life cycle assessment (SE-LCA) method for sustainable renewable energy development

Amidst the escalating complexity of energy demands and climate concerns, natural calamities, and the Black Swan phenomenon have all presented formidable obstacles to the advancement and implementation of renewable energy sources. In light of the present backlog of studies in energy technology, the three primary issues identified and resolved in this study are inadequate analysis of the actual situation, absence of evidence of sustainable development, and flawed systematic methodology. This study proposes a novel renewable energy development initiative known as the circular economy and community-based virtual power plant (CE-cVPP). By integrating community participation and circular economy principles, this initiative aims to foster sustainable development and facilitate resilient progress. The principal focuses of the model are community renewable energy supply, energy demand, and community participation management. The sustainable framework is constructed upon the principles of circular economy theory. The systems engineering-based life cycle assessment (SE-LCA) method is proposed as an innovative approach to whole life cycle assessment that is grounded in systems engineering. Its purpose is to facilitate a systematic implementation and empirical evaluation of the sustainability of energy, the environment, and the economy. On the basis of disparities in renewable energy sources and a variety of spatiotemporal dimensions, CE-cVPP is categorised into four representative groups. We present a business community model for energy and environmental analysis that is based on a hospital in Harbin. The results suggest that the overall lifecycle primary energy conservation rate is 67.21%, which is an exceptional outcome that significantly promotes sustainable development in comparison to conventional methods. This improves environmental and human health protection as the full lifecycle emission reduction ratios for atmospheric pollutants are 53.50% (SO2-eq.), 51.69% (PM2.5-eq.), and 74.85% (CO2-eq.). Consideration is given to raw materials, equipment construction, equipment operation, tariffs on six pollutants, and material recycling when calculating the total cost. The annual total cost savings ratio for the full lifecycle is 54.21% when compared to the traditional system. This research possesses methodological and theoretical applicability to the energy and power sectors.

Hybrid modeling of karstic springs: Error correction of conceptual reservoir models with machine learning

Abstract The simulation of spring discharge is of high interest for water supply management. Accurate modeling and prediction of spring discharge can help water authorities and managers optimize water use, face seasonal variability, and prepare for possible drought conditions. Therefore, developing reliable simulation models and forecasting tools for spring discharge is essential for the effective management of groundwater resources relying on karstic springs. While the use of complementary modeling approaches has been explored in various hydrological contexts, its application to spring discharge modeling remains relatively unexplored. Previous studies on spring discharge modeling have predominantly focused on either conceptual/distributed models or data-driven models separately, without fully investigating the potential advantages of combining these two approaches. Consequently, there is a research gap in understanding the potential benefits and effectiveness of integrating these models for spring discharge modeling. This study developed and evaluated a hybrid modeling approach integrating a conceptual hydrological model with a machine learning technique to simulate spring discharge from the largest karst aquifer supplying the city of Bordeaux, France. Specifically, the study combined the five-parameter GR5J reservoir model with a random forests data-driven model in a hybrid framework. Model performance was assessed through comparison with….

The Impact of CSR on Supply Chain Management in Enterprises

Corporate social responsibility (csr) adoption is gaining increasing prominence as a strategic imperative for enterprises seeking to drive transparency, collaboration, and sustainability through their supply chains due to its perceived importance. This paper undertakes a qualitative analysis of peer-reviewed academic literature and industry reports to examine the linkages between measurable csr policies. This helps in deducing means for supply managers to control ethical sourcing, supplier codes of conduct, and social audits and resultant performance improvements across interconnected supply chain entities due to followership of acceptable socially conscious activities. Henceforth, the analysis provides a valid view that integrative csr priorities propagate positive transformations. The transformation refers to improved vendor relationships, logistics, and distribution networks. Those are achieved through enhancing climate resilience, reducing risks, and enabling cost efficiencies. The csr actions, however, need to be structured by mechanisms around supplier capability building, compliance enforcement, and monitoring systems, which are uncovered as vital framing elements allowing csr commitments. However, equitable integration frameworks across entities with varying maturity levels require additional investigation.

Using artificial intelligence to improve poultry productivity – a review

Abstract A recent study investigated the potential applications of artificial intelligence (AI) in poultry farming. One area where AI can be helpful is in the early detection of diseases. By analyzing data from various sources, such as sensor readings and health records, AI algorithms can identify potential disease outbreaks or health risks in flocks, allowing farmers to take timely preventive measures. Another area where AI can be applied is in controlling the environmental conditions of farms. By analyzing data from sensors that monitor temperature, humidity, ventilation, and lighting conditions, AI algorithms can help farmers create a comfortable and healthy environment for birds, improving their growth and reducing their stress. AI can also optimize the management of healthcare supplies for poultry. By analyzing the nutritional requirements of birds and the availability and prices of different ingredients, AI algorithms can help farmers optimize feed formulations, reducing waste and environmental impacts. Finally, the study explored the use of robots in poultry care. Robots can be used for cleaning, feeding, and monitoring individual birds. By automating these tasks, farmers can reduce labor costs and improve the efficiency of their operations. Overall, the study highlights the potential benefits of using AI and robotics in poultry farming, including early disease detection, improved environmental conditions, optimized feed formulations, and increased automation.

An AcciMap approach to analyse the Chinese melamine milk scandal

PurposeThe 2008 Chinese melamine milk scandal resulted in six reported fatalities and affected around 300,000 children, of whom 54,000 were hospitalised. Previous studies have used linear approaches to examine the root causes of the melamine milk scandal.Design/methodology/approachIn the present study, we applied a systems approach to the melamine milk scandal to identify the complex systems-level failures across the supply chain leading to the incident and why food fraud incidents such as this occurred in the dairy sector. Additionally, systemic failures associated with food fraud vulnerability factors were considered (i.e. opportunities, motivation and control measures).Findings48 contributory factors of influence were identified and grouped across six sociotechnical levels across the Chinese dairy system, from government to equipment and surroundings. Lack of vertical integration (processes and communication) contributed to the failure. When viewed from a broader perspective, the melamine milk scandal can be linked to a series of human errors and organisational issues associated with government bodies, the dairy supply chain, individual organisations and management decisions and individual actions of staff or processes.Practical implicationsThis approach is of value to policymakers and the industry as it supports public health investigations of food fraud incidents and proactive food safety management.Originality/valueTo the best of our knowledge, this is the first study to analyse a food safety or fraud incident using the AcciMap approach and the food fraud vulnerability assessment (FFVA) technique. AcciMap analysis is applied to both unintentional and intentional aspects of the incident.

Demand forecasting for platelet usage: From univariate time series to multivariable models.

Platelet products are both expensive and have very short shelf lives. As usage rates for platelets are highly variable, the effective management of platelet demand and supply is very important yet challenging. The primary goal of this paper is to present an efficient forecasting model for platelet demand at Canadian Blood Services (CBS). To accomplish this goal, five different demand forecasting methods, ARIMA (Auto Regressive Integrated Moving Average), Prophet, lasso regression (least absolute shrinkage and selection operator), random forest, and LSTM (Long Short-Term Memory) networks are utilized and evaluated via a rolling window method. We use a large clinical dataset for a centralized blood distribution centre for four hospitals in Hamilton, Ontario, spanning from 2010 to 2018 and consisting of daily platelet transfusions along with information such as the product specifications, the recipients' characteristics, and the recipients' laboratory test results. This study is the first to utilize different methods from statistical time series models to data-driven regression and machine learning techniques for platelet transfusion using clinical predictors and with different amounts of data. We find that the multivariable approaches have the highest accuracy in general, however, if sufficient data are available, a simpler time series approach appears to be sufficient. We also comment on the approach to choose predictors for the multivariable models.

Groundwater Sustainability and Land Subsidence in California’s Central Valley

The Central Valley of California is one of the most prolific agricultural regions in the world. Agriculture is reliant on the conjunctive use of surface-water and groundwater. The lack of available surface-water and land-use changes have led to pumping-induced groundwater-level and storage declines, land subsidence, changes to streamflow and the environment, and the degradation of water quality. As a result, in part, the Sustainable Groundwater Management Act (SGMA) was developed. An examination of the components of SGMA and contextualizing regional model applications within the SGMA framework was undertaken to better understand and quantify many of the components of SGMA. Specifically, the U.S. Geological Survey (USGS) updated the Central Valley Hydrologic Model (CVHM) to assess hydrologic system responses to climatic variation, surface-water availability, land-use changes, and groundwater pumping. MODFLOW-OWHM has been enhanced to simulate the timing of land subsidence and attribute its inelastic and elastic portions. In addition to extending CVHM through 2019, the new version, CVHM2, includes several enhancements as follows: managed aquifer recharge (MAR), pumping with multi-aquifer wells, inflows from ungauged watersheds, and more detailed water-balance subregions, streamflow network, diversions, tile drains, land use, aquifer properties, and groundwater level and land subsidence observations. Combined with historical approximations, CVHM2 estimates approximately 158 km3 of storage loss in the Central Valley from pre-development to 2019. About 15% of the total storage loss is permanent loss of storage from subsidence that has caused damage to infrastructure. Climate extremes will likely complicate the efforts of water managers to store more water in the ground. CVHM2 can provide data in the form of aggregated input datasets, simulate climatic variations and changes, land-use changes or water management scenarios, and resulting changes in groundwater levels, storage, and land subsidence to assist decision-makers in the conjunctive management of water supplies.

Supply Chain Limitations in the South African Engineering Sector-Supply Chain Professionals Views

The engineering industry has several obstacles as the worldwide economy slows, including macroeconomic hardship, lack of resources, organizational deficiencies, and an overall incapacity to respond to major concerns. In the past few years, they have gotten increasingly intense and serious. Empirical supply chain administration studies identify impediments that hinder the engineering industry in emerging nations, such as South Africa. This research aims to investigate supply chain limitations in the South African engineering industry. The literature was evaluated as well as interviews that were semi-structured and were used to get thoughts from 15 senior supply chain professionals. To examine qualitative data, ATLAS.ti (version 7) software was used for content analysis. The conversations revealed six topics, such as a shortage of capital in supply chains, innovative supply chain process restrictions, supply chain administration changes, supply chain cooperation, supply chain administration, and scheduling administration. engineering companies should use systems to manage their supply chains, integrated options, and collaboration managing project techniques and technology. The findings reveal a shortage of expenditure in supply management processes and the fact that engineering companies are still lacking a strategic perspective on managing their supply chains. However, it seems that supply chain tactics may improve an organization's efficiency and business performance in engineering companies.

Modeling and Estimation of Reference Evapotranspiration using Machine Learning Algorithms: A Comparative Performance Analysis

Fresh, clean water is necessary for human health. Currently, the agriculture sector uses the majority of freshwater for irrigation without using planning or optimization techniques. Evapotranspiration, which may have a major impact in planning water supply management and crop yield improvement, is an element of the hydrological cycle. Accurate anticipation of reference evapotranspiration (ETO) is an intricate job due to its nonlinear behavior. Machine learning approach based model may be an intelligent tool to predict the accurate ETO. This study investigates and compares the predictive skills of three regression based supervised learning algorithms: decision tree (dtr), and random forest (rfr), and k-nearest-neighbors (knnr) along with tuning their hyper-parameters like how many neighbors there are in knnr, minimum samples in dtr at a leaf node and quantity of trees in the rfr scenario to forecast ETO. Every model's performance is quantified on four different groups of meteorological parameters. Groups are created based on close correlation of meteorological parameters with ETo. In this investigation, analysis is carried out on daily meteorological information of New Delhi, India for the periods from 2000 to 2021. The predicted results of the knnr, dtr and rfr models on four groups of meteorological inputs (twelve different models) are compared with ETO obtained from the FAO-PM56 equations. The study's conclusions show that the k-nearest-neighbors and random forest regression-based models outperform the decision tree regression models concerning performance. The finest performance noted by knnr and rfr models with r2 (coefficient of determination) of 0.99 and rmse of 0.21 and 0.22 mm/day respectively whereas dtr model noted r2 of 0.98 and rmse of 0.40 mm/day. Therefor these models may provide scientists, engineers, and farmers with more potent choices for managing water resources and scheduling irrigation.