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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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Analysis of trends of annual and seasonal precipitation from 1956 to 2000 in Guangdong Province, China
TL;DR: In this paper, the trends of annual, seasonal and monthly precipitation in southern China (Guangdong Province) for the period 1956-2000 are investigated, based on the data from 186 high-quality gauging stations.
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A probabilistic method for streamflow projection and associated uncertainty analysis in a data sparse alpine region
Weiwei Ren,Tao Yang,Tao Yang,Pengfei Shi,Chong-Yu Xu,Chong-Yu Xu,Ke Zhang,Ke Zhang,Xudong Zhou,Xudong Zhou,Quanxi Shao,Philippe Ciais +11 more
TL;DR: In this article, a probabilistic model was built upon an advanced Bayesian Neural Network (BNN) approach directly fed by the large-scale climate predictor variables and tested in a typical data sparse alpine region, the Kaidu River basin in Central Asia.
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Comprehensive assessment of dam impacts on flow regimes with consideration of interannual variations
TL;DR: In this paper, the entire signatures of hydrograph variations of Miyun Reservoir in northern China were described by forty flow regime metrics that incorporate magnitude, variability and frequency, duration, timing, and rate of change for flow events based on a long-term synchronous observation series of inflow and outflow.
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A balanced calibration of water quantity and quality by multi-objective optimization for integrated water system model
TL;DR: In this paper, a combined auto-calibration multi-process approach was proposed for the integrated water system model (HEQM) using a multi-objective evolutionary algorithm to ensure that the model performance among inseparable or interactive processes could be balanced by users based on the Pareto front.
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Streamflow forecasting using functional-coefficient time series model with periodic variation.
TL;DR: Wang et al. as mentioned in this paper proposed a functional-coefficient model with a periodic component, which enjoys an invariance property under data differencing, and applied it to Australian streamflows in three typical climate conditions.