EGU General Assembly 2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Gauging the ungauged: Estimating rainfall in urbanized river basins using ground-based and spaceborne sensors

Linda Bogerd1,2, Rose Boahemaa Pinto1, Tim van Emmerik1, and Remko Uijlenhoet1,3
Linda Bogerd et al.
  • 1Wageningen University & Research, Hydrology and Quantitative Water Management, Wageningen, Netherlands (
  • 2R&D Observations and Data Technology, Royal Netherlands Meteorological Institute (KNMI), De Bilt, The Netherlands
  • 3Department of Water Management, Faculty of Civil Engineering & Geosciences, Delft University of Technology, Netherlands

Accurate rainfall estimates in urban areas are vital for water management, pollution transport, and flood forecasts. To cover the high spatial (and temporal) variability of rainfall, uniformly distributed observation networks are required.

In many urban areas dedicated rainfall observations are limited because of low available budgets or unsuitable technology. Therefore, this study compared and assessed the accuracy of three “non-traditional” rainfall datasets in the Odaw (Accra, Ghana) river basin to help future modellers to decide which dataset is the best fit, for instance to predict floods. The Odaw river basin is one of the main drainage systems in Accra with a total catchment area of about 270 km2. Over the past three decades, the Odaw basin has been challenged with floods, but due to the lack of a good representation of rainfall measurements, the ability to accurately simulate or forecast floods in the basin is limited.

Two rainfall datasets are derived from satellite observations and one from crowdsourced rain gauges. The three estimates were all available for the study period (2020) and were analysed and compared at a thirty-minute time-interval. The first space-based product is the most recent version (V06B) of IMERG, the gridded multisatellite precipitation product of the Global Precipitation Measurement (GPM) mission; the second space-based product is the MSG-SEVIRI infrared satellite imagery, an innovative rainfall dataset based on geostationary data available day and night. The ground-based data was retrieved from ten TAHMO rain gauges. Because the satellite products consists of pixels while the TAHMO observations are point measurements, the stations were assigned to the pixels of the satellite products.

Results show that all three rainfall datasets revealed a systematic spatial variation, with on average more rainfall observed upstream than downstream. Although all datasets reproduced a similar annual accumulation, the rainfall intensity observed by the TAHMO stations (point measurements) were much higher, sometimes even more than twice as high. Days with high rainfall amounts (when the daily average TAHMO rain rate exceeded 15 mm/hr) were used as case studies, as these days were hypothesised to be related to flooding. During these days space-borne radar overpasses were used to get some impression about the spatial characteristics of the rainfall events. With this presentation we aim to demonstrate the applicability of freely available data to estimate rainfall at various temporal and spatial scales in (formerly) ungauged urbanized river basins.

How to cite: Bogerd, L., Pinto, R. B., van Emmerik, T., and Uijlenhoet, R.: Gauging the ungauged: Estimating rainfall in urbanized river basins using ground-based and spaceborne sensors, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11572,, 2022.