World's Best Scientists 2026 revealed!

D-Index & Metrics

Environmental Sciences

D-Index
54
Citations
9364
World Ranking
4087
National Ranking
141

Research.com Recognitions

  • 2019 - Member of the European Academy of Sciences
  • 2013 - Fellow of the American Society of Mechanical Engineers
  • Member of the European Academy of Sciences and Arts
  • The Canadian Academy of Engineering
  • Member of the European Academy of Sciences and Arts
  • The Canadian Academy of Engineering

Overview

Quan J. Wang is affiliated with the University of Melbourne in Australia. Their professional career reflects involvement in the academic research community with a focus that can be inferred from their recognized memberships and honors.

Throughout their career, Quan J. Wang has been acknowledged by various prestigious scientific and engineering organizations. They were named Member of the European Academy of Sciences in 2019. In 2013, they were honored as a Fellow of the American Society of Mechanical Engineers. Additionally, they hold membership in the European Academy of Sciences and Arts and the Canadian Academy of Engineering.

Their profile does not include specific details regarding research papers, co-authorship, or publication venues. Likewise, there is no information provided on particular fields or subfields of study, book publications, or main topics of work.

Available data centers primarily around academic recognition and professional association memberships, indicating active engagement and acknowledgment within the scientific and engineering communities at an international level.

Best Publications

  • The Genetic Algorithm and Its Application to Calibrating Conceptual Rainfall-Runoff Models

    Q. J. Wang

  • A review of advances in flash flood forecasting

    H. A. P. Hapuarachchi;Q. J. Wang;T. C. Pagano

  • A Bayesian joint probability modeling approach for seasonal forecasting of streamflows at multiple sites.

    Q. J. Wang;D. E. Robertson;F. H. S. Chiew

  • A Review of Quantitative Precipitation Forecasts and Their Use in Short- to Medium-Range Streamflow Forecasting

    Lan Cuo;Thomas C. Pagano;Q. J. Wang

  • Using genetic algorithms to optimise model parameters

    Q.J. Wang

  • LH moments for statistical analysis of extreme events

    Q. J. Wang

  • How Suitable is Quantile Mapping For Postprocessing GCM Precipitation Forecasts

    Tongtiegang Zhao;James C. Bennett;Q. J. Wang;Andrew Schepen

  • Multisite probabilistic forecasting of seasonal flows for streams with zero value occurrences

    Q. J. Wang;D. E. Robertson

  • The POT model described by the generalized Pareto distribution with Poisson arrival rate

    Q.J. Wang

  • A log-sinh transformation for data normalization and variance stabilization

    Q. J. Wang;D. L. Shrestha;D. E. Robertson;P. Pokhrel

  • The utility of L-moment ratio diagrams for selecting a regional probability distribution

    Murray C. Peel;Q. J. Wang;Richard M. Vogel;Thomas A. McMAHON

  • Post-processing rainfall forecasts from numerical weather prediction models for short-term streamflow forecasting

    D. E. Robertson;D. L. Shrestha;Q. J. Wang

  • An ANN-based emulation modelling framework for flood inundation modelling: Application, challenges and future directions

    Haibo Chu;Haibo Chu;Wenyan Wu;Quan J. Wang;Rory Nathan

  • Evidence for Using Lagged Climate Indices to Forecast Australian Seasonal Rainfall

    Andrew Schepen;Q. J. Wang;David Robertson

  • Monthly versus daily water balance models in simulating monthly runoff

    Q.J. Wang;T.C. Pagano;S.L. Zhou;H.A.P. Hapuarachchi

  • Estimation of the GEV distribution from censored samples by method of partial probability weighted moments

    Q.J. Wang

  • Merging Seasonal Rainfall Forecasts from Multiple Statistical Models through Bayesian Model Averaging

    Q. J. Wang;Andrew Schepen;David E. Robertson

  • Evaluation of numerical weather prediction model precipitation forecasts for short-term streamflow forecasting purpose

    D. L. Shrestha;D. E. Robertson;Q. J. Wang;T. C. Pagano

  • DIRECT SAMPLE ESTIMATORS OF L MOMENTS

    Q. J. Wang

  • Artificial neural network based hybrid modeling approach for flood inundation modeling

    Shuai Xie;Wenyan Wu;Sebastian Mooser;Q.J. Wang

  • Unbiased estimation of probability weighted moments and partial probability weighted moments from systematic and historical flood information and their application to estimating the GEV distribution

    Q.J. Wang

Frequent Co-Authors

Thomas A. McMahon
Thomas A. McMahon University of Melbourne
Andrew W. Western
Andrew W. Western University of Melbourne
Murray C. Peel
Murray C. Peel University of Melbourne
Florian Pappenberger
Florian Pappenberger European Centre for Medium-Range Weather Forecasts
Quanxi Shao
Quanxi Shao Commonwealth Scientific and Industrial Research Organisation
Enli Wang
Enli Wang Commonwealth Scientific and Industrial Research Organisation
Francis H. S. Chiew
Francis H. S. Chiew Commonwealth Scientific and Industrial Research Organisation
Jeffrey P. Walker
Jeffrey P. Walker Monash University
Richard M. Vogel
Richard M. Vogel Tufts University
Deli Chen
Deli Chen University of Melbourne

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

Exploring Environmental Sciences in the USA opens doors to various interdisciplinary career paths. Students often complement their studies with related online degrees to enhance their expertise and employability. For example, pursuing dsw programs online can lead to impactful roles in community planning and environmental justice, blending social work with ecological awareness.

Those seeking flexibility might consider cheapest online general studies degree programs, which provide broad interdisciplinary knowledge useful for environmental policy and education roles. Similarly, some students prefer the easiest bachelor degree to get options that still offer valuable environmental insights while fitting varied academic strengths and schedules.

For a more specialized focus, a geoscience online degree directly aligns with core environmental science principles. This path prepares students for careers in natural resource management, environmental consulting, and earth sciences research.

Choosing the right online program can provide the practical skills and academic foundation needed to thrive in the dynamic field of environmental science.

Best Scientists Citing Quan J. Wang

Trending Scientists