Abstract
AbstractRemote sensing models that measure evapotranspiration directly from the Penman‐Monteith or Priestley‐Taylor equations typically estimate the soil evaporation component over large areas using coarse spatial resolution relative humidity (RH) from geospatial climate datasets. As a result, the models tend to underperform in dry areas at local scales where moisture status is not well represented by surrounding areas. Earth observation sensors that monitor large‐scale global dynamics (e.g., MODIS) afford comparable spatial coverage and temporal frequency, but at a higher spatial resolution than geospatial climate datasets. In this study, we compared soil evaporation parameterized with optical and thermal indices derived from MODIS to RH‐based soil evaporation as implemented in the Priestley Taylor‐Jet Propulsion Laboratory (PT‐JPL) model. We evaluated the parameterizations by subtracting PT‐JPL transpiration from observation‐based flux tower evapotranspiration in agricultural fields across the contiguous United States. We compared the apparent thermal inertia (ATI) index, land surface water index (LSWI), normalized difference water index (NDWI), and a new index derived from red and shortwave infrared bands (soil moisture divergence index [SMDI]). Relationships were significant at the 95% confidence band. LSWI and SMDI explained 18–33% of variance in 8‐day soil evaporation. This led to a 3–11% increase in explained ET variance. LSWI and SMDI tended to perform better at the irrigated sites than RH. LSWI and SMDI led to markedly better performance over other indices at a seasonal time step. L‐band microwave backscatter can penetrate clouds and can distinguish soil from canopy moisture content. We are presently fusing red‐SWIR‐RADAR to improve soil evaporation estimation.
Highlights
Earth system scientists increasingly use Earth observation to estimate evapotranspiration (ET) for water resources management, food security analysis, drought monitoring, assessing the impact of land use/cover feedbacks on climate, and greenhouse gas emissions accounting (Fisher et al, 2017)
Soil evaporation is an important component of evapotranspiration, in dry regions of the world, but has proved to be more difficult to estimate than transpiration with Earth observation data
Shortwave infrared, thermal, and microwave Earth observation have been used to improve the simulation of soil evaporation, because they estimate soil moisture supply more directly and are at a higher spatial resolution than more traditional climate‐based parameterizations
Summary
Earth system scientists increasingly use Earth observation (remote sensing) to estimate evapotranspiration (ET) for water resources management, food security analysis, drought monitoring, assessing the impact of land use/cover feedbacks on climate, and greenhouse gas emissions accounting (Fisher et al, 2017). We can partition evapotranspiration into three components: water movement through the canopy or transpiration, evaporation from the soil and waterbodies, and evaporation from the canopy or other surfaces following a wetting event. Soil evaporation is considerable in agroecosystems and other moisture‐limited ecosystems (Zhang et al, 2017). Studies estimate positive trends in ET globally that are partially offset by declining trends in soil evaporation in moisture‐limited areas due to rainfall variability and change (Jung et al, 2010; Zhang et al, 2016). Studies link much of the uncertainty in simulations used to estimate ET and ET trends to the partitioning of ET between transpiration and soil evaporation (McCabe et al, 2019; Vereecken et al, 2015; Vinukollu et al, 2012)
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