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@ARTICLE{Zhao:902320,
      author       = {Zhao, Haojin and Montzka, Carsten and Baatz, Roland and
                      Vereecken, Harry and Franssen, Harrie-Jan Hendricks},
      title        = {{T}he {I}mportance of {S}ubsurface {P}rocesses in {L}and
                      {S}urface {M}odeling over a {T}emperate {R}egion: {A}n
                      {A}nalysis with {SMAP}, {C}osmic {R}ay {N}eutron {S}ensing
                      and {T}riple {C}ollocation {A}nalysis},
      journal      = {Remote sensing},
      volume       = {13},
      number       = {16},
      issn         = {2072-4292},
      address      = {Basel},
      publisher    = {MDPI},
      reportid     = {FZJ-2021-04177},
      pages        = {3068 -},
      year         = {2021},
      abstract     = {Land surface models (LSMs) simulate water and energy cycles
                      at the atmosphere–soil interface, however, the physical
                      processes in the subsurface are typically oversimplified and
                      lateral water movement is neglected. Here, a
                      cross-evaluation of land surface model results (with and
                      without lateral flow processes), the National Aeronautics
                      and Space Administration (NASA) Soil Moisture Active/Passive
                      (SMAP) mission soil moisture product, and cosmic-ray neutron
                      sensor (CRNS) measurements is carried out over a temperate
                      climate region with cropland and forests over western
                      Germany. Besides a traditional land surface model (the
                      Community Land Model (CLM) version 3.5), a coupled land
                      surface-subsurface model (CLM-ParFlow) is applied. Compared
                      to CLM stand-alone simulations, the coupled CLM-ParFlow
                      model considered both vertical and lateral water movement.
                      In addition to standard validation metrics, a triple
                      collocation (TC) analysis has been performed to help
                      understanding the random error variances of different soil
                      moisture datasets. In this study, it is found that the three
                      soil moisture datasets are consistent. The coupled and
                      uncoupled model simulations were evaluated at CRNS sites and
                      the coupled model simulations showed less bias than the
                      CLM-standalone model (−0.02 cm3 cm−3 vs. 0.07 cm3
                      cm−3), similar random errors, but a slightly smaller
                      correlation with the measurements (0.67 vs. 0.71). The
                      TC-analysis showed that CLM-ParFlow reproduced better soil
                      moisture dynamics than CLM stand alone and with a higher
                      signal-to-noise ratio. This suggests that the representation
                      of subsurface physics is of major importance in land surface
                      modeling and that coupled land surface-subsurface modeling
                      is of high interest},
      cin          = {IBG-3},
      ddc          = {620},
      cid          = {I:(DE-Juel1)IBG-3-20101118},
      pnm          = {2173 - Agro-biogeosystems: controls, feedbacks and impact
                      (POF4-217)},
      pid          = {G:(DE-HGF)POF4-2173},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:000689918200001},
      doi          = {10.3390/rs13163068},
      url          = {https://juser.fz-juelich.de/record/902320},
}