National-scale geospatial modelling of recommended riparian buffer widths

Abstract

Determining optimal riparian buffer widths, especially considering landscape spatial heterogeneity, is challenging, often relying on computationally intensive hydrological models with limited scalability. Empirical nomographs, linking terrain, soil, and slope, offer a more tractable alternative. Building upon a nomograph developed for Estonian catchments in the earlier research, we present its first computational implementation within a geospatial modelling framework. We developed a geospatial modelling algorithm in Python to calculate recommended buffer widths based on slope, specific slope length (synthesised from flow length, slope length, and LS factor), and soil type, utilising high-resolution national datasets. This algorithm was applied to the entire territory of Estonia (approx. 43,000 km2). The model produces spatially explicit buffer width recommendations that reflect local variations in topography and soil conditions. The proposed framework provides a computationally efficient and scalable tool for supporting strategic planning, policy development, and prioritisation of riparian buffer implementation. While not intended for direct site-level design, it offers a robust first-order assessment of spatial patterns in buffer width requirements and can be further refined through local calibration and validation.