Authors : Dr. Bharati Sahu; Dr. Nusrat Jahan; Deepika Rajwade; Aabha Patel

Volume/Issue : Volume 11 - 2026, Issue 7 - July

Google Scholar : https://tinyurl.com/5n8xrdjd

Scribd : https://tinyurl.com/mts3k7bm

DOI : https://doi.org/10.38124/ijisrt/26jul554

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.

Abstract : Water reservoir governance in Chhattisgarh faces a distinct structural paradox: an abundance of natural hydrometeorological resources coexisting with severe localized seasonal deficits, low creation-to-utilization ratios of irrigation potential, and complex inter-sectoral competing demands from agriculture, energy, and rapid urban centers. Traditional, fragmented governance frameworks managed across disconnected administrative bodies lack the institutional agility and the high-resolution, real-time data architectures needed to insulate the state's vulnerable socio-economic and agrarian frameworks from escalating climatic variability. From a political economy perspective, this paper evaluates the contemporary policy challenges, institutional bottlenecks, and distributive inequities plaguing reservoir governance in Chhattisgarh. We explore strategic pathways for a modern digital transformation by integrating advancements in the Internet of Things (IoT), Geographic Information Systems (GIS), and Artificial Intelligence (AI). We propose a unified framework for secure, resilient, and intelligent water management designed to optimize economic allocation efficiency and institutional accountability. This includes deploying real-time telemetry network layers for dynamic capacity monitoring, leveraging Geospatial AI (GeoAI) for structural resilience and climate change mitigation, and implementing rigorous cybersecurity frameworks to protect critical hydrological infrastructures from emerging digital vulnerabilities. Ultimately, the paper outlines a policy roadmap to shift the state's reservoir management from a reactive, manual operational paradigm to a predictive, data-driven governance model that secures equitable resource distribution and regional economic stability.

Keywords : Water Reservoir Governance; Digital Transformation; Chhattisgarh; Internet of Things (IoT); Geographic Information Systems (GIS); Geospatial Artificial Intelligence (GeoAI); Smart Water Management; Cybersecurity.

References :

1. Water Resources Department, Government of Chhattisgarh. (2012). Chhattisgarh State Water Resources Development Policy, 2012. Raipur, India.
2. Bano, S., & Verma, M. K. (2020). Assessment of irrigation potential created and utilized in the Mahanadi reservoir complex project, Chhattisgarh. International Journal of Current Microbiology and Applied Sciences, 9(6), 2411-2423.
3. Bardhan, P. (2016). The Political Economy of Development in India. Oxford University Press.
4. Kumar, A., & Singh, R. P. (2022). Competing water demands between thermal power plants and agriculture in the Mahanadi basin: A governance dilemma. Water Policy, 24(5), 789-805.
5. Hashmi, S. A. A. (2024). Securing Urban Small Water Bodies with Geospatial, IOT, and Cybersecurity. Zenodo, DOI: 10.5281/ZENODO.16790152.
6. Panda, R. (2021). Can Odisha and Chhattisgarh move beyond conventional approaches to save Mahanadi? Mongabay India Environmental Assessment Series.
7. Hashmi, S. A. A. (2024). Reporting Geographical Reservoir Level Changes to Higher Authority Using IoT. Zenodo, DOI: 10.5281/ZENODO.17084697.
8. Ostrom, E. (2015). Governing the Commons: The Evolution of Institutions for Collective Action. Cambridge University Press.
9. Saleth, R. M., & Dinar, A. (2014). The Institutional Economics of Water: A Cross-Country Analysis of Institutions and Performance. Edward Elgar Publishing.
10. Hashmi, S. A. A. (2025). The Python Paradigm: A Twenty-Five Year Retrospective on its Strategic Dominance Over Contending Languages and its Ascendancy as the Indispensable Engine of Modern AI, IoT, GIS, and Cybersecurity. Zenodo Preprint, DOI: 10.5281/ZENODO.17282464.
11. Hashmi, S. A. A. (2024). Real-Time Water Quality Mapping And Reporting System using IoT and GIS with Enhanced Cybersecurity. Zenodo, DOI: 10.5281/ZENODO.17085627.
12. Hashmi, S. A. A., Pandey, A. K., & Bhardwaj, V. (2025). Geospatial AI for Climate Change Mitigation and Urban Resilience. TIJER - International Research Journal of Engineering and Technology, 12(10), DOI: 10.5281/ZENODO.17288310.
13. Zhou, W., & Bhatia, S. (2025). Cyber-security threats to water distribution networks and reservoir SCADA systems: Defensive architectures and resilient monitoring protocols. Computers & Security, 148, 103640.
14. Li, S., & Da Xu, L. (2021). Securing cyber-physical critical infrastructures: Machine learning and cryptographic approaches in IoT-GIS configurations. IEEE Transactions on Industrial Informatics, 17(8), 5512-5524.
15. Shrivastava, R., & Dewangan, S. (2022). Groundwater depletion and agricultural vulnerability in the central plains of Chhattisgarh. Journal of the Geological Society of India, 98(3), 395-402.
16. Soni, P. (2019). Water resource management in Chhattisgarh state of India: Strategic challenges and policy directions. International Journal of Development and Economic Sustainability, 7(4), 62-72.
17. Mollinga, P. P. (2020). The rationalities of Indian hydro-politics: Water governance, state power, and digital infrastructure shifts. Water Alternatives, 13(1), 1-21.
18. Chen, Y., & Han, D. (2024). Big data analytics in hydro-meteorological forecasting: The strategic role of Python-based distributed frameworks. Environmental Modelling & Software, 171, 105890.
19. Xu, G., & Zhang, Y. (2023). IoT-enabled smart water management systems: A review of sensor technologies and data architectures. IEEE Internet of Things Journal, 10(5), 4112-4128.
20. Jan, F., Min-Allah, N., & Dâama, G. (2022). IoT-based smart water quality monitoring and warning systems: A systematic review. Sustainable Cities and Society, 77, 103561.
21. Ramsankaran, R., & Kulkarni, A. V. (2024). Geospatial AI (GeoAI) applications in surface water hydrology and reservoir sedimentation mapping. Remote Sensing of Environment, 301, 113912.
22. Nayak, S., & Thakur, S. K. (2023). Siltation analysis and capacity loss estimation of minor and major reservoirs in Chhattisgarh using multitemporal satellite data. Indian Journal of Soil Conservation, 51(1), 45-56.
23. Goodwell, A. E., & Kumar, P. (2023). Hydroinformatics and digital twins for reservoir operations under accelerated climate extremes. Water Resources Research, 59(2), e2022WR032415.
24. Mishra, A., & Khare, D. (2021). Impact of climate change on the hydrology of the Mahanadi River Basin, India. Journal of Water and Climate Change, 12(4), 1120-1135.
25. Gunduz, M. Z., & Ozdemir, R. (2023). Lightweight cryptographic frameworks for securing telemetry data in remote environmental monitoring applications. Ad Hoc Networks, 140, 103052.
26. Zhang, J., & Wang, X. (2023). Machine unlearning for privacy-preserving AIoT systems in critical public infrastructures. IEEE Network, 37(3), 88-95.