A digital twin of forests for natural flood management in Wales, UK

Natural flood management (NFM) involves the use of natural processes and environments to mitigate flood risk. Large tracts of upland areas in Wales are used for commercial forestry. Appropriate management of the forest structure, species and age diversity, and harvesting schedules in these areas has the potential to provide significant NFM benefits, which have not yet been fully explored. In this study, we sought to develop a digital twin of the forests in the Afon Pennal catchment, located near Machynlleth in mid-Wales, through a novel instrumental setup to collect the canopy throughfall data in real-time and combine it with satellite-derived forest parameters to simulate the impact of forest management on the river’s streamflow response. The Afon Pennal catchment is owned and managed by Natural Resources Wales and consists of both managed and unmanaged forest areas at differing stages of maturity. We attached LoRaWAN® sensors to 22 tipping bucket rain gauges placed under different types of forest canopy at five locations within the catchment, which enabled real-time data collection at a 5-minute interval. Remotely sensed data from the European Space Agency’s Sentinel-2 satellite was used to obtain the Leaf Area Index (LAI) and Fractional Vegetation Cover (FVC) values at a daily temporal resolution. These data were used to train an integrated model representing the forest canopy interception and catchment hydrological processes and then simulate river streamflow under various forest-type configurations and harvesting scenarios. Our results show that the integrated model has the capability to model streamflow based on remotely sensed LAI and FVC values, making it a potentially valuable tool for aiding and informing forest management planning in the future.