Streamflow prediction in ungauged basins by regressive regionalization: A case study in Huai River Basin, China

Jiyun Song, Jun Xia, Liping Zhang, Zhihua Wang, Hui Wan, Dunxian She

Research output: Contribution to journalArticlepeer-review

13 Scopus citations

Abstract

Streamflow information is of great significance for flood control, water resources utilization and management, ecological services, etc. Continuous streamflow prediction in ungauged basins remains a challenge, mainly due to data paucity and environmental changes. This study focuses on the modification of a nonlinear hydrological system approach known as the time variant gain model and the development of a regressive method based on the modified approach. This method directly correlates rainfall to runoff through physically based mathematical transformations without requiring additional information of evaporation or soil moisture. Also, it contains parsimonious parameters that can be derived from watershed properties. Both characteristics make this method suitable for practical uses in ungauged basins. The Huai River Basin of China was selected as the study area to test the regressive method. The results show that the proposed methodology provides an effective way to predict streamflow of ungauged basins with reasonable accuracy by incorporating regional watershed information (soil, land use, topography, etc.). This study provides a useful predictive tool for future water resources utilization and management for data-sparse areas or watersheds with environmental changes.

Original languageEnglish (US)
Pages (from-to)1053-1068
Number of pages16
JournalHydrology Research
Volume47
Issue number5
DOIs
StatePublished - Oct 2016

Keywords

  • Huai River Basin
  • Regressive regionalization
  • Streamflow prediction
  • Ungauged basins

ASJC Scopus subject areas

  • Water Science and Technology

Fingerprint

Dive into the research topics of 'Streamflow prediction in ungauged basins by regressive regionalization: A case study in Huai River Basin, China'. Together they form a unique fingerprint.

Cite this