@article{AbonKneisCrisologoetal.2016,
  author    = {Abon, Catherine Cristobal and Kneis, David and Crisologo, Irene and Bronstert, Axel and David, Carlos Primo Constantino and Heistermann, Maik},
  title     = {Evaluating the potential of radar-based rainfall estimates for streamflow and flood simulations in the Philippines},
  series = {GEOMATICS NATURAL HAZARDS \& RISK},
  volume    = {7},
  journal   = {GEOMATICS NATURAL HAZARDS \& RISK},
  publisher = {Routledge, Taylor \& Francis Group},
  address   = {Abingdon},
  issn      = {1947-5705},
  doi       = {10.1080/19475705.2015.1058862},
  pages     = {1390 -- 1405},
  year      = {2016},
  abstract  = {This case study evaluates the suitability of radar-based quantitative precipitation estimates (QPEs) for the simulation of streamflow in the Marikina River Basin (MRB), the Philippines. Hourly radar-based QPEs were produced from reflectivity that had been observed by an S-band radar located about 90 km from the MRB. Radar data processing and precipitation estimation were carried out using the open source library wradlib. To assess the added value of the radar-based QPE, we used spatially interpolated rain gauge observations (gauge-only (GO) product) as a benchmark. Rain gauge observations were also used to quantify rainfall estimation errors at the point scale. At the point scale, the radar-based QPE outperformed the GO product in 2012, while for 2013, the performance was similar. For both periods, estimation errors substantially increased from daily to the hourly accumulation intervals. Despite this fact, both rainfall estimation methods allowed for a good representation of observed streamflow when used to force a hydrological simulation model of the MRB. Furthermore, the results of the hydrological simulation were consistent with rainfall verification at the point scale: the radar-based QPE performed better than the GO product in 2012, and equivalently in 2013. Altogether, we could demonstrate that, in terms of streamflow simulation, the radar-based QPE can perform as good as or even better than the GO product - even for a basin such as the MRB which has a comparatively dense rain gauge network. This suggests good prospects for using radar-based QPE to simulate and forecast streamflow in other parts of the Philippines where rain gauge networks are not as dense.},
  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}
}