Streamflow prediction in ungauged basins located within data-scarce areas using XGBoost: role of feature engineering and explainability-Reference-Cited by-同舟云学术

Streamflow prediction in ungauged basins located within data-scarce areas using XGBoost: role of feature engineering and explainability

Published:2023-08-17 Issue: Volume: Page:1-22
ISSN:1571-5124
Container-title:International Journal of River Basin Management
language:en
Short-container-title:International Journal of River Basin Management

Author:

Alipour M. H.¹

Affiliation:

1. Toronto, Canada

Publisher

Informa UK Limited

Subject

Water Science and Technology

Link

https://www.tandfonline.com/doi/pdf/10.1080/15715124.2023.2245809

Reference59 articles.

1. Alipour, M. (2019). Streamflow prediction in ungauged basins located within data-scarce regions [Doctoral dissertation]. University of Central Florida, Orlando, FL.

2. A framework for streamflow prediction in the world’s most severely data-limited regions: Test of applicability and performance in a poorly-gauged region of China

3. Streamflow prediction under extreme data scarcity: a step toward hydrologic process understanding within severely data-limited regions

4. Flow alteration by diversion hydropower in tributaries to the Salween river: a comparative analysis of two streamflow prediction methodologies

5. Map correlation method: Selection of a reference streamgage to estimate daily streamflow at ungaged catchments

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