← Back to Authors

Boris Faybishenko

Affiliation: Lawrence Berkeley National Laboratory

ORCID: 0000-0003-0085-8499

Works: 23 total (9 publications, 14 datasets, 0 documents)

Local Knowledge Graph (30 entities)

Loading graph...

Works (23)

All (23)Publications (9)Datasets (14)

Sort:Date (Newest)Most Cited

Imputation of contiguous gaps and extremes of subhourly groundwater time series using random forests

2022Journal of Machine Learning for Modeling and ComputingDOI: 10.1615/jmachlearnmodelcomput.2021038774Cited 31 times

Statistical framework to assess long-term spatio-temporal climate changes: East River mountainous watershed case study

2022Stochastic environmental research and risk assessmentDOI: 10.1007/s00477-022-02327-7Cited 8 times

Challenging problems of quality assurance and quality control (QA/QC) of meteorological time series data

2021Stochastic environmental research and risk assessmentDOI: 10.21203/rs.3.rs-510046/v1Cited 9 times

Modeling the Impact of Riparian Hollows on River Corridor Nitrogen Exports

2021Frontiers in WaterDOI: 10.3389/frwa.2021.590314Cited 30 times

Depth- and time-resolved distributions of snowmelt-driven hillslope subsurface flow and transport and their contributions to surface waters.

2019Water Resources ResearchDOI: 10.1029/2019wr025093Cited 41 times

Assessment of Spatiotemporal Variability of Evapotranspiration and Its Governing Factors in a Mountainous Watershed

2019WaterDOI: 10.3390/w11020243Cited 39 times

Challenges in Building an End-to-End System for Acquisition, Management, and Integration of Diverse Data From Sensor Networks in Watersheds: Lessons From a Mountainous Community Observatory in East River, Colorado

2019IEEE AccessDOI: 10.1109/access.2019.2957793Cited 36 times

Geochemical exports to river from the intra-meander hyporheic zone under transient hydrologic conditions: East River Mountainous Watershed, Colorado

2018Water Resources ResearchDOI: 10.1029/2018wr023377Cited 87 times

The East River, Colorado, Watershed: A mountainous community testbed for improving predictive understanding of multiscale hydrological-biogeochemical dynamics

2018Vadose Zone JournalDOI: 10.2136/vzj2018.03.0061Cited 230 times