Skip to main content
ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Hydrology and Remote Sensing Laboratory » Research » Publications at this Location » Publications at this Location

Publications at this Location

ARS scientists publish results of their research projects in many formats. Listed below are the publications from research projects conducted at this location.

Clicking on a publication title will take you to more information on the publication. Clicking on the reprint icon Repository URL will take you to the publication reprint.

2022 | 2021 | 2020 | 2019 | 2018 | 2017 | 2016 | 2015 | 2014 | 2013 | 2012 | 2011 | 2010 |

2022 Publications
(listed by order of acceptance date)

Current View: All Publications

Show All Publications || Peer Reviewed Journal Publications Only

Displaying 1 to 20 of 27 Records
Next->>

NRCS curve number method: A comparison of methods for estimating the curve number from rainfall-runoff data Reprint Icon
(Peer Reviewed Journal)
(10-Jun-22)
Evaluation of satellite leaf area index in California vineyards for improving water use estimation Reprint Icon
(Peer Reviewed Journal)
(29-Apr-22)
Improving the spatiotemporal resolution of remotely sensed ET information for water management through Landsat, Sentinel-2, ECOSTRESS and VIIRS data fusion Reprint Icon
(Peer Reviewed Journal)
(29-Apr-22)
Downscaling UAV land surface temperature using a coupled wavelet-machine learning-optimization algorithm and its impact on evapotranspiration and energy balance components estimated by the TSEB model
(Peer Reviewed Journal)
(22-Apr-22)
A grass growth model adapted to urban areas: a case study with bahiagrass (Paspalum notatum flugee) in San Carlos, Brazil Reprint Icon
(Peer Reviewed Journal)
(20-Apr-22)
Comprehensive evaluation and error-component analysis of four satellite-based precipitation estimates against gauged rainfall over mainland China Reprint Icon
(Peer Reviewed Journal)
(13-Apr-22)
Inductive predictions of hydrologic events using a Long Short-Term Memory Network and the Soil and Water Assessment Tool Reprint Icon
(Peer Reviewed Journal)
(5-Apr-22)
Quasi-global machine learning-based soil moisture estimates at high spatio-temporal scales using CYGNSS and SMAP observations Reprint Icon
(Peer Reviewed Journal)
(4-Apr-22)
Stormwater management adaptation pathways under climate change and urbanization
(Peer Reviewed Journal)
(2-Apr-22)
Improved daily evapotranspiration estimation using remotely sensed data in a data fusion system Reprint Icon
(Peer Reviewed Journal)
(1-Apr-22)
Thermal hydraulic disaggregation of SMAP soil moisture over continental United States Reprint Icon
(Peer Reviewed Journal)
(30-Mar-22)
Evaluating different metrics from the thermal-based Two-Source Energy Balance model for monitoring grapevine water stress Reprint Icon
(Peer Reviewed Journal)
(26-Mar-22)
Application of a remote sensing three-source energy balance model to improve evapotranspiration partitioning in vineyards Reprint Icon
(Peer Reviewed Journal)
(15-Mar-22)
Can surface soil moisture information identify landscape evapotranspiration regime transitions Reprint Icon
(Peer Reviewed Journal)
(14-Mar-22)
The complementary uses of Sentinel1A SAR and ECOSTRESS datasets to identify vineyard growth and conditions: a case study in Sonoma County, California Reprint Icon
(Peer Reviewed Journal)
(28-Feb-22)
Estimation of bell pepper evapotranspiration using two-source energy balance model based on high-resolution thermal and visible imagery from unmanned aerial vehicles Reprint Icon
(Peer Reviewed Journal)
(17-Feb-22)
The vertical turbulent structure within the surface boundary layer above vineyards in California’s Central Valley during GRAPEX Reprint Icon
(Peer Reviewed Journal)
(7-Feb-22)
Impact of advection on Two-Source Energy Balance (TSEB) canopy transpiration parameterization for vineyards in the California Central Valley Reprint Icon
(Peer Reviewed Journal)
(26-Jan-22)
Applications of a thermal-based two-source energy balance model coupled to surface soil moisture Reprint Icon
(Peer Reviewed Journal)
(24-Jan-22)
LAI estimation across California vineyards using sUAS multi-seasonal multi-spectral, thermal, and elevation information and machine learning Reprint Icon
(Peer Reviewed Journal)
(22-Jan-22)
Next->>