Multi-year surface radiative properties and vegetation parameters for hydrologic modeling in regions of complex terrain—Methodology and evaluation over the Integrated Precipitation and Hydrology Experiment 2014 domain


Journal Article

© 2019 The Authors Study region: Southeast US (SE US). Study focus: This study probes the propagation of errors in standard remote-sensing vegetation products caused by cloud contamination and the impact of time-variant radiative properties for correctly describing land-surface properties in hydrologic models. Spatiotemporally-varying quality-controlled vegetation attributes (i.e., leaf area index and fractional vegetation coverage) and surface radiative properties (i.e., longwave broadband emissivity and shortwave broadband albedo) were derived from MODIS (Moderate Resolution Imaging Spectroradiometer) products over the SE US at 1 km × 1 km and hourly resolutions from 2007 to 2013. The data sets are publicly available. The impact of uncorrected standard vegetation products and static treatments of radiative properties was assessed systematically clearly illustrating improvements in simulated water and energy fluxes using the developed landscape attributes with a fully-distributed uncalibrated hydrologic model. New hydrological insights for the region: Through simulations in the Southern Appalachian Mountains, we found that the spatiotemporal variability of radiative properties significantly influences the diurnal cycle of the surface energy budget with marked differences in sensible heat fluxes (up to 10–20%). Better performance of streamflow simulations achieved by using the improved vegetation attributes is tied to changes in rainfall interception and evapotranspiration, reflecting the importance of SE forests in the regional water cycle. The largest improvements in streamflow simulations result from larger corrections to MODIS products in the inner mountain region where cloudiness is persistent.

Full Text

Duke Authors

Cited Authors

  • Tao, J; Barros, AP

Published Date

  • April 1, 2019

Published In

Volume / Issue

  • 22 /

Electronic International Standard Serial Number (EISSN)

  • 2214-5818

Digital Object Identifier (DOI)

  • 10.1016/j.ejrh.2019.100596

Citation Source

  • Scopus