An Earth Observation–Based Workflow for Flood Monitoring at Nature-Based Solution Sites

Nature-based solutions (NBS) for flood mitigation requires robust, scalable, and transferable monitoring approaches to assess their effectiveness across spatial and temporal scales. Here, we present an open-access, satellite-based Earth observation (EO) monitoring tool designed to quantify surface water dynamics and water retention associated with NBS implementation. The tool integrates multi-sensor satellite data, including Sentinel-1 synthetic aperture radar (SAR) and Sentinel-2 optical imagery, within a flexible, automated workflow capable of near–real-time monitoring at high spatial (<10 m) and temporal resolution.

The workflow addresses key challenges in NBS monitoring, including small site extents, rapid hydrological responses, and the need for efficient, reproducible methods. It integrates complementary Earth observation indicators for surface water detection, combining optical indices (e.g. Normalised Difference Water Index) with SAR backscatter metrics sensitive to open water and flooded vegetation to enable continuous, all-weather monitoring. The framework is flexible and site-adaptive, allowing threshold calibration using local ground knowledge, historical flood information, and ancillary datasets, thereby improving reliability beyond globally fixed thresholds. Data are structured into spatio-temporal data cubes, supporting pixel-level analysis, aggregation over user-defined regions of interest, and integration of ancillary open datasets for contextual interpretation and future extension toward soil moisture and drought indicators.

The tool is demonstrated using a UK catchment with established NBS interventions, where EO-derived surface water patterns during recent storm events indicate preferential inundation of upstream retention features and limited flooding in downstream vulnerable areas. The monitoring system is implemented as a modular, open-source framework that automatically retrieves, processes, and structures EO and ancillary datasets into spatio-temporal data cubes, enabling both scripted analyses and interactive visualisation through dashboards.

This EO-based tool provides a transferable, transparent, and scalable approach for evaluating NBS performance in data-sparse environments. Designed for long-term use beyond project lifetimes, the workflow is fully open-source, computationally efficient, and adaptable across diverse European contexts, with the potential for integration into broader multidimensional monitoring and decision-support frameworks for flood risk management.