EGU General Assembly 2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

Developing a novel monitoring system to determine rainfall interception from different forest types

Matt Cooper1, Max Dickens2, Sopan Patil1, and Huw Thomas3
Matt Cooper et al.
  • 1School of Natural Sciences, Bangor University, Bangor United Kingdom (
  • 2School of Computer Science and Electronic Engineering, Bangor University, Bangor, United Kingdom (
  • 3Forest Research, Talybont Research Office, Brecon, United Kingdom (

Natural Flood Management (NFM) seeks to utilise natural processes within the landscape to reduce flood risk and is increasingly being viewed as a sustainable, cost effective, and complementary addition to flood defence infrastructure.  One NFM measure is to increase the proportion of forested lands within catchments draining to the communities at risk. Tree cover has good potential to reduce flood risk by increasing canopy evaporation, enhancing below and above ground flood storage and slowing the flow of water towards streams.  However, the extent to which these mechanisms are superior for forestry, compared to other land uses, and how they vary throughout the year and for different forest types remains difficult to predict, which is a major gap in our ability to quantify how forest cover can help reduce flood risk.


Here, we present a study that utilises LoRaWAN, a developing wireless sensor network technology, to provide real time collection of canopy interception and streamflow data at the Pennal catchment in Wales, UK.  LoRaWAN is an emerging Low Power Wide Area Network (LPWAN) protocol designed for Internet of Things (IoT) applications. The capability of LoRaWAN to operate under harsh attenuation and interference conditions make it well suited to the forest catchment area which is characterised by dense vegetation and varied topography.


This study will utilise a network of tipping bucket rain gauges and stream flow monitors distributed in different forest types and densities. The rain gauges and water level monitors are the end devices (IoT things) in the network which perform a direct communication with LoRaWAN Gateways, from which the data is ‘pushed’ to a server for storing and assimilation. The data will be used to develop and validate a coupled canopy and soil hydrology model.  This will guide forest management and aid in quantifying the effects of natural flood management techniques, initially within the Pennal catchment, with a view to expanding to the regional scale.

How to cite: Cooper, M., Dickens, M., Patil, S., and Thomas, H.: Developing a novel monitoring system to determine rainfall interception from different forest types, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-15950,, 2021.