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@ARTICLE{Pomon:878269,
      author       = {Poméon, Thomas and Wagner, Niklas and Furusho, Carina and
                      Kollet, Stefan and Reinoso-Rondinel, Ricardo},
      title        = {{P}erformance of a {PDE}-{B}ased {H}ydrologic {M}odel in a
                      {F}lash {F}lood {M}odeling {F}ramework in
                      {S}parsely-{G}auged {C}atchments},
      journal      = {Water},
      volume       = {12},
      number       = {8},
      issn         = {2073-4441},
      address      = {Basel},
      publisher    = {MDPI},
      reportid     = {FZJ-2020-02738},
      pages        = {2157 -},
      year         = {2020},
      note         = {This study is part of the RealPEP (Near-Realtime
                      Quantitative Precipitation Estimation and Prediction
                      https://www2.meteo.uni-bonn.de/realpep/doku.php) P4 project
                      (Evaluation of QPE and QPN improvements in a flash flood
                      nowcasting framework with data assimilation), funded by the
                      Deutsche Forschungsgemeinschaft (German Research Foundation)
                      under Grant No. FU 1185/1-1.},
      abstract     = {Modeling and nowcasting of flash floods remains
                      challenging, mainly due to uncertainty of high-resolution
                      spatial and temporal precipitation estimates, missing
                      discharge observations of affected catchments and
                      limitations of commonly used hydrologic models. In this
                      study, we present a framework for flash flood hind- and
                      nowcasting using the partial differential equation
                      (PDE)-based ParFlow hydrologic model forced with
                      quantitative radar precipitation estimates and nowcasts for
                      a small 18.5 km2 headwater catchment in Germany. In the
                      framework, an uncalibrated probabilistic modeling approach
                      is applied. It accounts for model input uncertainty by
                      forcing the model with precipitation inputs from different
                      sources, and accounts for model parameter uncertainty by
                      perturbing two spatially uniform soil hydraulic parameters.
                      Thus, sources of uncertainty are propagated through the
                      model and represented in the results. To demonstrate the
                      advantages of the proposed framework, a commonly used
                      conceptual model was applied over the same catchment for
                      comparison. Results show the framework to be robust, with
                      the uncalibrated PDE-based model matching streamflow
                      observations reasonably. The model lead time was further
                      improved when forced with precipitation nowcasts. This study
                      successfully demonstrates a parsimonious application of the
                      PDE-based ParFlow model in a flash flood hindcasting and
                      nowcasting framework, which is of interest in applications
                      to poorly or ungauged watersheds.},
      cin          = {IBG-3},
      ddc          = {690},
      cid          = {I:(DE-Juel1)IBG-3-20101118},
      pnm          = {255 - Terrestrial Systems: From Observation to Prediction
                      (POF3-255) / SFB 986 MGK - Integriertes Graduiertenkolleg
                      (MGK) (221133179)},
      pid          = {G:(DE-HGF)POF3-255 / G:(GEPRIS)221133179},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:000564898000001},
      doi          = {10.3390/w12082157},
      url          = {https://juser.fz-juelich.de/record/878269},
}