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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.

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Trend detection in hydrological time series by segment regression with application to Shiyang River Basin

TL;DR: In this article, a segmented regression with constraints method is introduced to model both trend analysis and abrupt change detection, which can detect both shift trends and abrupt changes simultaneously and have weak ability to detect multiple change points together.
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Hydrological projections of future climate change over the source region of Yellow River and Yangtze River in the Tibetan Plateau: A comprehensive assessment by coupling RegCM4 and VIC model

TL;DR: In this article, a high-resolution regional climate model, RegCM4, under three representative concentration pathways (RCPs): 2.6, 4.5, and 8.5 was used to forecast future climate change in the Tibetan Plateau.
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An extension of three-parameter Burr III distribution for low-flow frequency analysis

TL;DR: The research is motivated by low-flow frequency analysis in water resources research and three commonly used parameter estimation methods were evaluated, including the method of moments, probability-weighted moments (or L-moments) and maximum likelihood method.
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Investigating the variation and non-stationarity in precipitation extremes based on the concept of event-based extreme precipitation

TL;DR: In this paper, the authors proposed a concept of event-based extreme precipitation (EEP) by considering the continuity of EP and defined the statistical variables for the characteristics of an EEP event by taking account of local tolerance capacity.
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Integrated water system simulation by considering hydrological and biogeochemical processes: model development, with parameter sensitivity and autocalibration

TL;DR: In this paper, a classic hydrological model (the time variant gain model: TVGM) was extended to an integrated water system model by coupling multiple water-related processes in hydrology, biogeochemistry, water quality, and ecology, and considering the interference of human activities.