53 Papers
159 Citations
Dan Lu is an academic researcher from Oak Ridge National Laboratory. The author has contributed to research in topics: Computer science & Uncertainty quantification. The author has an hindex of 16, co-authored 46 publications. Previous affiliations of Dan Lu include Florida State University.
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Papers
Machine learning assisted hybrid models can improve streamflow simulation in diverse catchments across the conterminous US
TL;DR: Model performance of hybrid models as measured by Nash–Sutcliffe efficiency (NSE) improved relative to standalone PB and LSTM models, and hybrid models provide highest improvement in catchments where PB models fail completely (i.e. NSE < 0).
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Analysis of regression confidence intervals and Bayesian credible intervals for uncertainty quantification
Dan Lu,Ming Ye,Mary C. Hill +2 more
TL;DR: The theoretical analysis shows that, for linear or linearized‐nonlinear models, confidence and credible intervals are always numerically identical when consistent prior information is used, and suggests that for environmental problems with lengthy execution times that make credible intervals inconvenient or prohibitive, confidence intervals can provide important insight.
Streamflow Simulation in Data-Scarce Basins Using Bayesian and Physics-Informed Machine Learning Models
TL;DR: P predictive capabilities of LSTM in poorly monitored watersheds with short observation records are investigated and it is demonstrated that when hydrologic variability in the prediction period is similar to the calibration period, L STM models can reasonably predict daily streamflow with Nash-Sutcliffe efficiency above 0.8, even with only two years of calibration data.
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Practical Use of Computationally Frugal Model Analysis Methods
Mary C. Hill,Dmitri Kavetski,Martyn P. Clark,Ming Ye,Mazdak Arabi,Dan Lu,Laura Foglia,Steffen Mehl +7 more
TL;DR: It is suggested that the strategy proposed in this paper would allow the environmental sciences community to achieve greater transparency and falsifiability of environmental models, and obtain greater scientific insight from ongoing and future modeling efforts.
Seasonal changes in GPP/SIF ratios and their climatic determinants across the Northern Hemisphere.
Anping Chen,Jiafu Mao,Daniel M. Ricciuto,Dan Lu,Jingfeng Xiao,Xing Li,Peter E. Thornton,Alan K. Knapp +7 more
TL;DR: In this article, the authors used the GPP/SIF ratio to investigate seasonal variations in the relationship between SIF and GPP over the Northern Hemisphere (NH) and found strong seasonal hump-shaped patterns for GPP and SIF ratio over northern latitudes, with higher values in the summer than in the spring or autumn.
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