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Deb Agarwal — RMBL Knowledge Commons

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Deb Agarwal

Affiliation: Lawrence Berkeley National Laboratory

ORCID: 0000-0001-5045-2396

Works: 9 total (8 publications, 1 dataset, 0 documents)

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Knowledge graph centered on Deb Agarwal with 60 nodes and 286 connections. Top connected: The East River, Colorado, Watershed: A mountainous, climate change, snowpack persistence, groundwater storage dynamics, leaf water content.

Works (9)

All (9)Publications (8)Datasets (1)

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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

BASIN-3D: A brokering framework to integrate diverse environmental data

2022Computers & GeosciencesDOI: 10.1016/j.cageo.2021.105024Cited 15 times

Balancing the needs of consumers and producers for scientific data collections

2021Ecological InformaticsDOI: 10.1016/j.ecoinf.2021.101251Cited 9 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

Article

The Colorado East River Community Observatory Data Collection

2021Hydrologic ProcessesDOI: 10.1002/hyp.14243Cited 17 times

Quality Assurance and Quality Control (QA/QC) of Meteorological Time Series Data for Billy Barr, East River, Colorado USA

2021DOI: 10.15485/1823516

The East River Community Observatory Data Collection: Diverse, multiscale data from a mountainous watershed in the East River, Colorado

2020AuthoreaDOI: 10.22541/au.160157556.64095872Cited 7 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

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