@misc{PetrowHeistermannBronstert2017,
  author    = {Petrow, Theresia and Heistermann, Maik and Bronstert, Axel},
  title     = {Analysis of Flash Floods in Germany},
  series = {Hydrologie und Wasserbewirtschaftung},
  volume    = {61},
  journal   = {Hydrologie und Wasserbewirtschaftung},
  publisher = {Bundesanst. f{\"u}r Gew{\"a}sserkunde},
  address   = {Koblenz},
  issn      = {1439-1783},
  pages     = {212 -- 212},
  year      = {2017},
  language  = {en}
}
@misc{KneisAbonBronstertetal.2016,
  author    = {Kneis, David and Abon, Catherine Cristobal and Bronstert, Axel and Heistermann, Maik},
  title     = {Verification of short-term runoff forecasts for a small Philippine basin (Marikina)},
  series = {Hydrological sciences journal = Journal des sciences hydrologiques},
  volume    = {62},
  journal   = {Hydrological sciences journal = Journal des sciences hydrologiques},
  publisher = {Oxford Univ. Press},
  address   = {Oxford},
  issn      = {0262-6667},
  doi       = {10.1080/02626667.2016.1183773},
  pages     = {205 -- 216},
  year      = {2016},
  abstract  = {Storm runoff from the Marikina River Basin frequently causes flood events in the Philippine capital region Metro Manila. This paper presents and evaluates a system to predict short-term runoff from the upper part of that basin (380km(2)). It was designed as a possible component of an operational warning system yet to be installed. For the purpose of forecast verification, hindcasts of streamflow were generated for a period of 15 months with a time-continuous, conceptual hydrological model. The latter was fed with real-time observations of rainfall. Both ground observations and weather radar data were tested as rainfall forcings. The radar-based precipitation estimates clearly outperformed the raingauge-based estimates in the hydrological verification. Nevertheless, the quality of the deterministic short-term runoff forecasts was found to be limited. For the radar-based predictions, the reduction of variance for lead times of 1, 2 and 3hours was 0.61, 0.62 and 0.54, respectively, with reference to a no-forecast scenario, i.e. persistence. The probability of detection for major increases in streamflow was typically less than 0.5. Given the significance of flood events in the Marikina Basin, more effort needs to be put into the reduction of forecast errors and the quantification of remaining uncertainties.},
  language  = {en}
}