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Linking curve number with environmental flows: a novel approach
Shailendra Kumar Kumre1, Sabyasachi Swain2,3, Kumar Amrit4
1National Institute of Hydrology, Roorkee, 247667, India. skumre159@gmail.com.
Environmental Science and Pollution Research International
|October 21, 2024
Summary
Environmental flow, crucial for river health, can be predicted using the versatile Curve Number (CN) index. This study establishes a strong linear correlation between %AAF and CN across Indian river basins, aiding environmental flow management.
Area of Science:
- Hydrology
- Environmental Science
- Water Resource Management
Background:
- River flow regimes significantly impact aquatic ecosystems and ecosystem services.
- Environmental flows are essential for maintaining riverine ecosystem integrity.
- The Tennant's method is a standard for defining environmental flows.
Purpose of the Study:
- To correlate environmental flows (Tennant's method) with the Curve Number (CN) index.
- To investigate the relationship between %AAF and CN using rainfall-runoff data from Indian river basins.
- To assess the utility of CN for predicting environmental flows based on catchment characteristics.
Main Methods:
- Utilized rainfall-runoff data from 17 catchments across five major Indian river basins (Brahmani-Baitarani, Godavari, Mahanadi, Mahi, Narmada).
- Derived the relationship between percentage of average annual flow (%AAF) and Curve Number (CN) during the low flow season (October-June).
- Correlated CN with the Standard Flow Index (SQI), a variation of %AAF.
Main Results:
- A strong linear correlation (R > 0.7 for 16/17 catchments) was found between %AAF and CN.
- The %AAF increases linearly with increasing CN, and vice versa.
- Maximum correlation was observed in Dhariawad (R²=0.899) and Baronda (R²=0.814) catchments, indicating an excellent relationship.
Conclusions:
- The Curve Number (CN) index is a reliable predictor of environmental flows (%AAF) based on catchment characteristics.
- The established relationship provides a valuable tool for environmental flow assessment and management in data-scarce regions.
- The correlation between CN and SQI further validates the findings and the applicability of CN in hydrological studies.
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