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IIT Tirupati Navavishkar I-Hub Foundation Website
Problem Statement
Efficient irrigation systems rely on well-laid underground pipelines, which are often difficult to detect once covered by soil and vegetation. Traditional pipe location methods require excavation or rely on as-built drawings, which may be inaccurate or unavailable. A non-invasive, high-resolution approach was needed to map the underground pipe network supporting the sprinkler system in a newly constructed lawn at IIT Tirupati.
Overview
A Ground Penetrating Radar (GPR) survey was conducted on the lawn area in front of Academic Building 1, IIT Tirupati to identify and map the subsurface pipe network responsible for the sprinkler irrigation system. A 500 MHz ultra-wideband antenna was used to capture shallow subsurface features with high clarity.
Engineering Impact
Successfully provided a non-invasive method for locating small-diameter irrigation pipes.
Enabled precise mapping of the sprinkler pipeline network for maintenance and future landscaping work.
Reduced reliance on excavation or incomplete as-built documentation.
Demonstrated GPR’s effectiveness for shallow utility detection in landscaped environments.
Conclusion
The 500 MHz GPR survey with 20 cm line spacing successfully detected and mapped the underground pipe network in the newly constructed lawn area in front of Academic Building 1, IIT Tirupati. The ability to resolve small-diameter pipelines at shallow depths highlights the utility of GPR for non-destructive utility detection, supporting both infrastructure maintenance and planning.
Methodology
System Configuration: 500 MHz broadband antenna, suitable for high-resolution shallow imaging of utility networks.
Survey Design: A grid-based survey with 20 cm line spacing was carried out to ensure adequate coverage and accurate reconstruction of the pipe network.
Processing Workflow: Standard GPR data processing including filtering, background removal, migration, and amplitude slice analysis was applied to highlight linear anomalies consistent with pipelines.
Key Findings
Pipe Network Detection: Continuous linear hyperbolic signatures corresponding to small-diameter pipes were clearly visible in both 2D profiles and depth slices.
Depth Estimation: The pipes were imaged at shallow depths (<1.5 m), consistent with irrigation infrastructure placement.
Network Mapping: The dense survey grid enabled reconstruction of the pipe layout, showing connectivity and distribution across the lawn.
Infrastructure Confirmation: The detected network matched the expected layout of the sprinkler system, validating the survey approach.
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