EGU22-13414
https://doi.org/10.5194/egusphere-egu22-13414
EGU General Assembly 2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

The potential of crowdsourced personal weather stations for hydrological forecasting in a Dutch lowland catchment

Claudia Brauer1, Romy Lammerts1, Lotte de Vos1,2, and Aart Overeem2
Claudia Brauer et al.
  • 1Hydrology and Quantitative Water Management Group, Wageningen University, The Netherlands
  • 2Royal Netherlands Meteorological Institute

Accurate and real-time available rainfall data are indispensable for flood forecasting and warning. Crowdsourced personal weather stations have a high spatiotemporal resolution (in our case 9 km2 and 5 min) and are available in near-real-time, but are prone to errors. In this study, we (1) assessed the accuracy of rainfall observations from personal weather stations in a Dutch lowland catchment (Oude IJssel, 1210 km2) and (2) used these PWS data as input to a rainfall-runoff model (WALRUS) to assess their potential for discharge forecasting.

 

The catchment-averaged rainfall depths measured by personal weather stations slightly overestimated the reference with a bias of only 0.03 mm, which is much lower than the underestimation of the real-time available (unadjusted) radar product (-0.16 mm). Quality control of PWS did not reduce the bias, but time series varied less and correlated better with the reference. For individual stations, quality control reduced the bias with 11% while retaining 85% of the data.

 

Discharge simulations using quality-controlled personal weather stations (NSE=0.98, using simulations with gauge-adjusted radar rainfall data as reference) were better than before quality control (NSE = 0.95) and much better than the real-time available (unadjusted) radar product (NSE=0.70).

 

To conclude, rainfall data from personal weather stations are suitable for real-time hydrological applications, especially after quality control.

 

How to cite: Brauer, C., Lammerts, R., de Vos, L., and Overeem, A.: The potential of crowdsourced personal weather stations for hydrological forecasting in a Dutch lowland catchment, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-13414, https://doi.org/10.5194/egusphere-egu22-13414, 2022.