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Quanxi Shao

Researcher at Commonwealth Scientific and Industrial Research Organisation

Publications -  149
Citations -  6284

Quanxi Shao is an academic researcher from Commonwealth Scientific and Industrial Research Organisation. The author has contributed to research in topics: Climate change & Evapotranspiration. The author has an hindex of 40, co-authored 134 publications receiving 5164 citations. Previous affiliations of Quanxi Shao include University of Melbourne.

Papers
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Journal ArticleDOI

A modified hydrologic model for examining the capability of global gridded PET products in improving hydrological simulation accuracy of surface runoff, streamflow and baseflow

Zengliang Luo, +1 more
- 01 Jul 2022 - 
TL;DR: In this paper , a modified Soil and Water Assessment Tool (SWAT) was chosen to examine the capability of PET products in improving hydrological simulation in terms of surface runoff, streamflow and baseflow, together with the Shaying River Basin in China.
Proceedings Article

Monthly and seasonal streamflow forecasts using rainfall-runoff modeling and POAMA predictions

Enli Wang, +5 more
TL;DR: In this article, the authors explored the skills of forecasts for monthly and three-monthly total streamflows with a dynamic approach using a conceptual rainfall-runoff model SIMHYD for 31 catchments located in east Australia.
Journal ArticleDOI

A two-step calibration framework for hydrological parameter regionalization based on streamflow and remote sensing evapotranspiration

Zhengguang Xu, +4 more
- 01 Oct 2022 - 
TL;DR: Wang et al. as mentioned in this paper proposed a two-step calibration based parameter regionalization method, which combines spatial proximity method and RS ET based parameter calibration method to improve the accuracy of hydrological modeling in ungauged catchments.
Journal ArticleDOI

Uncertainty analysis for integrated water system simulations using GLUE with different acceptability thresholds

Yongyong Zhang, +7 more
- 01 Aug 2021 - 
TL;DR: In this paper, the authors investigated all the uncertainties of integrated water system simulations using the GLUE (i.e., generalized likelihood uncertainty estimation) method, including uncertainties associated with individual modules, propagated uncertainty associated with interconnected modules, and their combinations.
Journal ArticleDOI

Improvements in subseasonal forecasts of rainfall extremes by statistical postprocessing methods

Ming Li, +2 more
- 01 Dec 2021 - 
TL;DR: In this paper, the copula-based postprocessing (CPP) method was modified with a hybrid probability distribution to model low-to-medium and heavy rainfall separately and to allow the forecast of extreme rainfall events that have never occurred in observed records.