Hydrological Model Data for Cascading Lakes in Bengaluru, India

High-resolution observed data at 15-minute intervals were used to calibrate a hydrological model simulating runoff and sewage flows across 44 interconnected lakes in Bengaluru, India. The dataset, authored by Rashmi Kulranjan and last updated in March 2026, supports analysis of lake behavior under varying management scenarios. It was created to investigate how upstream-downstream interactions, temporal changes, and human interventions shape lake function.

Use Cases

• Calibrating hydrological models based on high-resolution 15-minute interval observed data
• Simulating runoff and sewage flows across interconnected lakes under varying management scenarios
• Analyzing lake sensitivity to seasonal and catchment-level characteristics based on spatial position in the cascade
• Developing diagnostic typologies linking lake function to inflow type and temporal changes

Strengths

• Model calibrated with high-resolution observed data at 15-minute intervals
• Simulates flows across 44 interconnected lakes
• Analyzes lake behavior under varying management scenarios

Limitations

• Column-level documentation is absent; field semantics must be inferred after download
• Row count is unknown, which may limit suitability assessment
• Data is contained in a 192.5 KB DOCX file, suggesting limited scope

Provenance

Source

figshare

Collection Method

Hydrological modeling using observed data

Freshness

Last updated 2026-03-19 12:07:15

Geography

Hebbal-Nagavara Valley in Bengaluru, India