Abstract
The Danish Meteorological Institute operates a radar network consisting of five C-band Doppler radars. Quantitative precipitation estimation (QPE) using radar data is performed on a daily basis. Radar QPE is considered to have the potential to signifi cantly improve the spatial representation of precipitation compared with rain-gauge-based methods, thus providing the basis for better water resources assessments. The radar QPE algorithm called ARNE is a distance-dependent areal estimation method that merges radar data with
ground surface observations. The method was applied to the Skjern River catchment in western Denmark where alternative precipitation estimates were also used as input to an integrated hydrologic model. The hydrologic responses from the model were analyzed by comparing radar- and ground-based precipitation input scenarios. Results showed that radar QPE products are able to generate reliable simulations of stream flow and water balance. The potential of using radar-based precipitation was found to be especially high at a smaller scale, where the impact of spatial resolution was evident from the stream
discharge results. Also, groundwater recharge was shown to be sensitive to the rainfall product selected. Radar QPE appears to have unprecedented potential in optimizing precipitation input to distributed hydrologic models and thus model predictions.
ground surface observations. The method was applied to the Skjern River catchment in western Denmark where alternative precipitation estimates were also used as input to an integrated hydrologic model. The hydrologic responses from the model were analyzed by comparing radar- and ground-based precipitation input scenarios. Results showed that radar QPE products are able to generate reliable simulations of stream flow and water balance. The potential of using radar-based precipitation was found to be especially high at a smaller scale, where the impact of spatial resolution was evident from the stream
discharge results. Also, groundwater recharge was shown to be sensitive to the rainfall product selected. Radar QPE appears to have unprecedented potential in optimizing precipitation input to distributed hydrologic models and thus model predictions.
| Original language | English |
|---|---|
| Journal | Vadose Zone Journal |
| Volume | 10 |
| Issue number | 1 |
| Pages (from-to) | 8-24 |
| Number of pages | 17 |
| ISSN | 1539-1663 |
| DOIs | |
| Publication status | Published - 26 Feb 2011 |