Smart River Water Level and Quality Surveillance

Author

Akanksha Kishor Banait, Neha Wanjari, Shruti Bhagat, Sakshi Pathe, Viplove Tatkade, Prof. Samiksha Dongre

Abstract

 Effective river surveillance requires more than the presentation of isolated environmental measurements. River stage, water quality, geographic location, observation time, data availability, and the physical context of a monitoring station should be accessible within a unified interface if the information is to support rapid interpretation. This paper presents Smart River Water Level and Quality Surveillance, a software-based Web-GIS environmental monitoring and decision-support platform that integrates hydrological and physicochemical river observations into a station-centric surveillance workflow.

The platform acquires periodically refreshed environmental telemetry from an authoritative government monitoring source and transforms incoming records through station aggregation, parameter normalization, river-name inference, spatial organization, visual condition assessment, and a project-specific weighted composite water-quality score. The dashboard supports twelve hydrological and physicochemical parameters: river stage, water depth, pH, water temperature, dissolved oxygen, biochemical oxygen demand, chemical oxygen demand, turbidity, electrical conductivity, nitrate, chloride, and total organic carbon.

The developed system extends conventional telemetry display through interactive Web-GIS navigation, State–River–Station filtering, parameter-level status indicators, station-associated monitoring imagery, responsive desktop/mobile layouts, light and dark themes, multi-tier data failover, printable PDF-compatible environmental monitoring reports, and CSV export. An administrative module allows authorized users to create additional monitoring locations using externally obtained field or laboratory measurements, place stations geographically through a map interface, upload station imagery, manage locally entered records, and perform controlled parameter-response testing.

A processed project snapshot containing 468 telemetry records associated with 40 distinct monitoring stations was used to demonstrate the system workflow. The project also includes a verified archive of 23 station-associated monitoring photographs for visual ground-context support. The platform demonstrates how a software environmental-informatics layer can improve the accessibility, interpretability, resilience, and extensibility of existing river-monitoring information without requiring deployment of an additional independent sensor network.

Keywords

River Monitoring, Water Quality, Water Level, Web-GIS, Environmental Surveillance, River Stage, Environmental Informatics, Composite Water-Quality Score, Decision Support System, Responsive Web Application.

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References

[1] C. Moreno, R. Aquino, J. Ibarreche, I. Pérez, E. Castellanos, E. Álvarez, R. Rentería, L. Anguiano, A. Edwards, P. Lepper, R. M. Edwards, and B. Clark, “RiverCore: IoT Device for River Water Level Monitoring over Cellular Communications,” Sensors, vol. 19, no. 1, article 127, 2019. doi: 10.3390/s19010127.

[2] K. S. Adu-Manu, F. A. Katsriku, J.-D. Abdulai, and F. Engmann, “Smart River Monitoring Using Wireless Sensor Networks,” Wireless Communications and Mobile Computing, vol. 2020, article 8897126, 2020. doi: 10.1155/2020/8897126.

[3] M. S. U. Chowdury, T. B. Emran, S. Ghosh, A. Pathak, M. M. Alam, N. Absar, K. Andersson, and M. S. Hossain, “IoT Based Real-time River Water Quality Monitoring System,” Procedia Computer Science, vol. 155, pp. 161–168, 2019. doi: 10.1016/j.procs.2019.08.025.

[4] T. A. Teixeira, L. B. F. Nascimento, W. Cavalcante, I. M. F. Ono, R. C. S. Gomes, A. L. Printes, A. M. F. Sobrinho, and I. G. Torné, “Development and Experimental Validation of an Autonomous IoT-Based Monitoring System for Real-Time Water Quality Assessment in the Amazon River,” Sensors, vol. 26, no. 12, article 3967, 2026. doi: 10.3390/s26123967.

[5] S. Singh, S. Rai, P. Singh, and V. K. Mishra, “Real-time water quality monitoring of River Ganga (India) using internet of things,” Ecological Informatics, vol. 71, article 101770, 2022. doi: 10.1016/j.ecoinf.2022.101770.

[6] A. Krishan, A. Khursheed, and R. K. Mishra, “Evaluation of water quality using water quality index, synthetic pollution index, and GIS technique: a case study of the river Gomti, Lucknow, India,” Environmental Science and Pollution Research, vol. 29, 2022. doi: 10.1007/s11356-022-21493-3.

[7] Central Pollution Control Board, Government of India, “Designated Best Use Water Quality Criteria,” Water Quality Monitoring Programme. Relevant Class-B criteria used in the interface interpretation: pH 6.5–8.5, DO ≥ 5 mg/L, BOD ≤ 3 mg/L.

[8] Central Pollution Control Board, Ministry of Environment, Forest and Climate Change, Government of India, Real-Time Water Quality Monitoring Stations (RTWQMS), upstream environmental telemetry source used by the developed platform.

[9] J. N. Halls, “River run: An interactive GIS and dynamic graphing website for decision support and exploratory data analysis of water quality parameters of the Lower Cape Fear River,” Environmental Modelling & Software, vol. 18, no. 6, pp. 513–520, 2003. doi: 10.1016/S1364-8152(03)00026-4.

[10] K. A. Salewicz and M. Nakayama, “Development of a web-based decision support system (DSS) for managing large international rivers,” Global Environmental Change, vol. 14, suppl., pp. 25–37, 2004. doi: 10.1016/j.gloenvcha.2003.11.007.

[11] R. K. Horton, “An index number system for rating water quality,” Journal of the Water Pollution Control Federation, vol. 37, no. 3, pp. 300–305, 1965.

[12] R. M. Brown, N. I. McClelland, R. A. Deininger, and R. G. Tozer, “A water quality index—do we dare?,” Water & Sewage Works, vol. 117, no. 10, pp. 339–343, 1970.

[13] Central Water Commission, Ministry of Jal Shakti, Government of India, Report on Water Quality Hot-Spots in Rivers of India, 4th ed., Aug. 2024.

[14] Ministry of Water Resources, Government of India, “Real Time Water Quality Monitoring Stations,” Press Information Bureau, 17 July 2014.

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