Improving how we measure and respond to rainfall

The ability to accurately measure the quantity and locations of rainfall is vital for water management processes to operate effectively. This is especially true in urban areas where the design and operation of storm sewer systems are highly sensitive to rainfall.

The challenge

While weather radars have the capacity to provide the spatial and temporal measurements required, they are prone to errors because they provide estimates of rainfall by sending electromagnetic pulses that measure the echoes from precipitation particles (e.g. rain, snow, hail, melting snow).  Rain gauge measurements can be more accurate at a point scale, however, they do not capture the variability of precipitation in different locations.

What we're doing

Researchers at the University of Bristol have found that by combining both approaches, they can select the most reliable sources of data from each, thereby countering the weaknesses and improving the quality of information used for hydrological modelling.

Their work is part of the QUICS (Quantifying Uncertainty in Integrated Catchment Studies) research consortium, which aims to improve our understanding of the different factors that contribute to hydrological uncertainty. The ultimate goal is to improve how water quality management decisions are made.

How it helps

This is important in the context of the EU Water Framework Directive (WFD), which aims to achieve good ecological status of all water bodies. WFD implementation studies can be carried out by using integrated water quality modelling in which uncertainty in models and data needs to be considered. 

Dr Miguel Rico-Ramirez from Bristol’s Department of Civil Engineering said:

“We have proposed innovative geo-statistical approaches to reduce and quantify uncertainty in radar rainfall. In this way, we are able to produce not only better rainfall products, but also a better representation of the uncertainty in the rainfall measurements. The result is a system that can be used for other models, whether hydrological or urban models, to improve decision making.”


  • Dr Miguel Rico-Ramirez, Department of Civil Engineering, University of Bristol, Bristol
  • Dr Francesca Cecinati, Department Architecture and Civil Engineering, University of Bath, Bath (formerly Department of Civil Engineering, University of Bristol, Bristol)
  • Prof. Dawei Han, Department of Civil Engineering, University of Bristol, Bristol



Miguel Rico-Ramirez Lead researcher profile

Dr Miguel A Rico-Ramirez, Senior Lecturer in Radar Hydrology and Hydroinformatics

Edit this page