Spatial and Temporal Variability of Root-Zone Soil Moisture Acquired from Hydrologic Modeling and AirMOSS P-Band Radar

Wade T. Crow, Sushil Milak, Mahta Moghaddam, Alireza Tabatabaeenejad, Sermsak Jaruwatanadilok, Xuan Yu, Yuning Shi, Rolf H. Reichle, Yutaka Hagimoto, Richard H. Cuenca

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

The accurate estimation of grid-scale fluxes of water, energy, and carbon requires consideration of subgrid spatial variability in root-zone soil moisture (RZSM). The NASA Airborne Microwave Observatory of Subcanopy and Subsurface (AirMOSS) mission represents the first systematic attempt to repeatedly map high-resolution RZSM fields using airborne remote sensing across a range of biomes. Here, we compare 3-arc-sec (∼100 m) spatial resolution AirMOSS RZSM retrievals from P-band radar acquisitions over nine separate North American study sites with analogous RZSM estimates generated by the Flux-Penn State Integrated Hydrologic Model (Flux-PIHM). The two products demonstrate comparable levels of accuracy when evaluated against ground-based soil moisture products and a significant level of temporal cross correlation. However, relative to the AirMOSS RZSM retrievals, Flux-PIHM RZSM estimates generally demonstrate much lower levels of spatial and temporal variability, and the spatial patterns captured by both products are poorly correlated. Nevertheless, based on a discussion of likely error sources affecting both products, it is argued that the spatial analysis of AirMOSS and Flux-PIHM RZSM fields provides meaningful upper and lower bounds on the potential range of RZSM spatial variability encountered across a range of natural biomes.

Original languageEnglish (US)
Article number8586924
Pages (from-to)4578-4590
Number of pages13
JournalIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Volume11
Issue number12
DOIs
StatePublished - Dec 2018

Fingerprint

Soil moisture
Observatories
rhizosphere
Radar
observatory
soil moisture
Microwaves
radar
modeling
Fluxes
biome
microwave
moisture flux
spatial analysis
Byproducts
NASA
Remote sensing
spatial resolution
remote sensing
Carbon

All Science Journal Classification (ASJC) codes

  • Computers in Earth Sciences
  • Atmospheric Science

Cite this

Crow, Wade T. ; Milak, Sushil ; Moghaddam, Mahta ; Tabatabaeenejad, Alireza ; Jaruwatanadilok, Sermsak ; Yu, Xuan ; Shi, Yuning ; Reichle, Rolf H. ; Hagimoto, Yutaka ; Cuenca, Richard H. / Spatial and Temporal Variability of Root-Zone Soil Moisture Acquired from Hydrologic Modeling and AirMOSS P-Band Radar. In: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 2018 ; Vol. 11, No. 12. pp. 4578-4590.
@article{0a6ca9dc87014a40beb8350a9ac64510,
title = "Spatial and Temporal Variability of Root-Zone Soil Moisture Acquired from Hydrologic Modeling and AirMOSS P-Band Radar",
abstract = "The accurate estimation of grid-scale fluxes of water, energy, and carbon requires consideration of subgrid spatial variability in root-zone soil moisture (RZSM). The NASA Airborne Microwave Observatory of Subcanopy and Subsurface (AirMOSS) mission represents the first systematic attempt to repeatedly map high-resolution RZSM fields using airborne remote sensing across a range of biomes. Here, we compare 3-arc-sec (∼100 m) spatial resolution AirMOSS RZSM retrievals from P-band radar acquisitions over nine separate North American study sites with analogous RZSM estimates generated by the Flux-Penn State Integrated Hydrologic Model (Flux-PIHM). The two products demonstrate comparable levels of accuracy when evaluated against ground-based soil moisture products and a significant level of temporal cross correlation. However, relative to the AirMOSS RZSM retrievals, Flux-PIHM RZSM estimates generally demonstrate much lower levels of spatial and temporal variability, and the spatial patterns captured by both products are poorly correlated. Nevertheless, based on a discussion of likely error sources affecting both products, it is argued that the spatial analysis of AirMOSS and Flux-PIHM RZSM fields provides meaningful upper and lower bounds on the potential range of RZSM spatial variability encountered across a range of natural biomes.",
author = "Crow, {Wade T.} and Sushil Milak and Mahta Moghaddam and Alireza Tabatabaeenejad and Sermsak Jaruwatanadilok and Xuan Yu and Yuning Shi and Reichle, {Rolf H.} and Yutaka Hagimoto and Cuenca, {Richard H.}",
year = "2018",
month = "12",
doi = "10.1109/JSTARS.2018.2865251",
language = "English (US)",
volume = "11",
pages = "4578--4590",
journal = "IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing",
issn = "1939-1404",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
number = "12",

}

Crow, WT, Milak, S, Moghaddam, M, Tabatabaeenejad, A, Jaruwatanadilok, S, Yu, X, Shi, Y, Reichle, RH, Hagimoto, Y & Cuenca, RH 2018, 'Spatial and Temporal Variability of Root-Zone Soil Moisture Acquired from Hydrologic Modeling and AirMOSS P-Band Radar', IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 11, no. 12, 8586924, pp. 4578-4590. https://doi.org/10.1109/JSTARS.2018.2865251

Spatial and Temporal Variability of Root-Zone Soil Moisture Acquired from Hydrologic Modeling and AirMOSS P-Band Radar. / Crow, Wade T.; Milak, Sushil; Moghaddam, Mahta; Tabatabaeenejad, Alireza; Jaruwatanadilok, Sermsak; Yu, Xuan; Shi, Yuning; Reichle, Rolf H.; Hagimoto, Yutaka; Cuenca, Richard H.

In: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol. 11, No. 12, 8586924, 12.2018, p. 4578-4590.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Spatial and Temporal Variability of Root-Zone Soil Moisture Acquired from Hydrologic Modeling and AirMOSS P-Band Radar

AU - Crow, Wade T.

AU - Milak, Sushil

AU - Moghaddam, Mahta

AU - Tabatabaeenejad, Alireza

AU - Jaruwatanadilok, Sermsak

AU - Yu, Xuan

AU - Shi, Yuning

AU - Reichle, Rolf H.

AU - Hagimoto, Yutaka

AU - Cuenca, Richard H.

PY - 2018/12

Y1 - 2018/12

N2 - The accurate estimation of grid-scale fluxes of water, energy, and carbon requires consideration of subgrid spatial variability in root-zone soil moisture (RZSM). The NASA Airborne Microwave Observatory of Subcanopy and Subsurface (AirMOSS) mission represents the first systematic attempt to repeatedly map high-resolution RZSM fields using airborne remote sensing across a range of biomes. Here, we compare 3-arc-sec (∼100 m) spatial resolution AirMOSS RZSM retrievals from P-band radar acquisitions over nine separate North American study sites with analogous RZSM estimates generated by the Flux-Penn State Integrated Hydrologic Model (Flux-PIHM). The two products demonstrate comparable levels of accuracy when evaluated against ground-based soil moisture products and a significant level of temporal cross correlation. However, relative to the AirMOSS RZSM retrievals, Flux-PIHM RZSM estimates generally demonstrate much lower levels of spatial and temporal variability, and the spatial patterns captured by both products are poorly correlated. Nevertheless, based on a discussion of likely error sources affecting both products, it is argued that the spatial analysis of AirMOSS and Flux-PIHM RZSM fields provides meaningful upper and lower bounds on the potential range of RZSM spatial variability encountered across a range of natural biomes.

AB - The accurate estimation of grid-scale fluxes of water, energy, and carbon requires consideration of subgrid spatial variability in root-zone soil moisture (RZSM). The NASA Airborne Microwave Observatory of Subcanopy and Subsurface (AirMOSS) mission represents the first systematic attempt to repeatedly map high-resolution RZSM fields using airborne remote sensing across a range of biomes. Here, we compare 3-arc-sec (∼100 m) spatial resolution AirMOSS RZSM retrievals from P-band radar acquisitions over nine separate North American study sites with analogous RZSM estimates generated by the Flux-Penn State Integrated Hydrologic Model (Flux-PIHM). The two products demonstrate comparable levels of accuracy when evaluated against ground-based soil moisture products and a significant level of temporal cross correlation. However, relative to the AirMOSS RZSM retrievals, Flux-PIHM RZSM estimates generally demonstrate much lower levels of spatial and temporal variability, and the spatial patterns captured by both products are poorly correlated. Nevertheless, based on a discussion of likely error sources affecting both products, it is argued that the spatial analysis of AirMOSS and Flux-PIHM RZSM fields provides meaningful upper and lower bounds on the potential range of RZSM spatial variability encountered across a range of natural biomes.

UR - http://www.scopus.com/inward/record.url?scp=85059033892&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85059033892&partnerID=8YFLogxK

U2 - 10.1109/JSTARS.2018.2865251

DO - 10.1109/JSTARS.2018.2865251

M3 - Article

AN - SCOPUS:85059033892

VL - 11

SP - 4578

EP - 4590

JO - IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing

JF - IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing

SN - 1939-1404

IS - 12

M1 - 8586924

ER -