A Gamified Digital Platform for Sustainable Farming Practices: Simulation, Statistical Analysis, and Water Resource Management Implications

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This is an unedited manuscript accepted for publication and provided as an Article in Press for early access at the author’s request. The article will undergo copyediting, typesetting, and galley proof review before final publication. Please be aware that errors may be identified during production that could affect the content. All legal disclaimers of the journal apply.

Year : 2026 | Volume : 13 | Issue : 01 | Page : 13 24
    By

    Ms. Bh. Pramodaki,

  • Prof. Nagesh Bhadrirajub,

  1. Student, (Computer Science and Systems Engineering), Andhra University College of Engineering, Visakhapatnam, Andhra Pradesh, India
  2. Adjunct Professor, Andhra University College of Engineering, Marine Engineering Department, Visakhapatnam, Andhra Pradesh, India

Abstract

Sustainable farming practices play a critical role in enhancing agricultural water-use efficiency, conserving limited water resources, and ensuring long-term food security under increasing environmental and climatic pressures. Despite their importance, farmer participation in conventional agricultural extension and training programs remains limited due to low engagement and a lack of sustained motivation. To address this challenge, this study proposes a gamified digital decision-support platform aimed at promoting sustainable agricultural and water management practices through behavioral incentive mechanisms, including points, badges, challenges, and leaderboards. The effectiveness of the proposed platform is evaluated through a Python-based simulation involving 100 virtual farmers over a 30-day period. The simulation models user participation, incentive accumulation, and adoption behavior related to water-efficient practices such as optimized irrigation scheduling and resource-conscious farming. The results indicate a substantial improvement in user engagement, with average cumulative scores ranging from 180 to 220, and an estimated adoption rate of approximately 44–45% for sustainable, water-aware farming practices during the simulation period. Statistical analysis reveals strong positive correlations between daily participation frequency, incentive accumulation, and the likelihood of adopting sustainable practices, highlighting the effectiveness of gamification in influencing behavioral change. The findings demonstrate that gamified digital platforms can serve as effective tools for enhancing farmer engagement while providing quantifiable indicators of learning and adoption. The proposed framework offers a scalable, data-driven approach to agricultural water management education and supports informed decision-making for water resource engineers, planners, and policymakers. Future work will focus on real-world deployment of the platform and its integration with IoT-enabled water monitoring and precision irrigation systems to facilitate real-time feedback, adaptive learning, and improved water resource management strategies.

Keywords: Application programming interface, artificial intelligence, convolutional neural network, graphical user interface, internet of things, intersection over union, machine learning, mean absolute error, normalized difference vegetation index, recurrent neural network, root mean square error

[This article belongs to Journal of Water Resource Engineering and Management ]

How to cite this article:
Ms. Bh. Pramodaki, Prof. Nagesh Bhadrirajub. A Gamified Digital Platform for Sustainable Farming Practices: Simulation, Statistical Analysis, and Water Resource Management Implications. Journal of Water Resource Engineering and Management. 2026; 13(01):13-24.
How to cite this URL:
Ms. Bh. Pramodaki, Prof. Nagesh Bhadrirajub. A Gamified Digital Platform for Sustainable Farming Practices: Simulation, Statistical Analysis, and Water Resource Management Implications. Journal of Water Resource Engineering and Management. 2026; 13(01):13-24. Available from: https://journals.stmjournals.com/jowrem/article=2026/view=236382


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Regular Issue Subscription Original Research
Volume 13
Issue 01
Received 09/01/2026
Accepted 21/01/2026
Published 27/01/2026
Publication Time 18 Days
177

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