Dimensioning of riparian buffer zones in agricultural catchments at national level

Intensive agricultural production interferes with natural cycles of nutrients (mostly nitrogen and phosphorus) and may lead to water quality degradation due to excessive nutrient loadings. To mitigate this effect at the landscape level establishment of buffering vegetated strips is an efficient measure.

Recommending optimal widths for riparian buffer zones to reduce the agricultural runoff is still a challenging task, in particular when considering the spatial variability of the landscape. Empirical-based approaches include assessment of terrain, soil types, land use and vegetation, and are often realised in computationally expensive hydrological simulation. However, trade-offs have to be made between spatial resolution and areal extent. Another elegant empirical-based approach are nomographs, where via triangulation of a specific slope length, terrain slope and soil type recommended buffer width can be easily calculated. Mander and Kuusemets (1998) already developed such a nomograph for Estonian catchments in 1998, yet, a computational use case has not been explored.

We implemented the nomograph as a GIS algorithm in Python/QGIS to retrieve the recommended buffer width at national level. We synthesized a specific slope length via a weighted average of flow length, local flow accumulation and LS factor, and then use the specific slope length, slope derived from 5 m spatial resolution DEM and soil texture classes as inputs for the algorithm. We applied this algorithm and calculated recommendable buffer strip widths for the whole of country of Estonia, over an area of approx. 43,000 km². We evaluated the uncertainty of the results as well the algorithm’s sensitivity to input weights.

The developed algorithm is applicable in any region with relevant adjustments to local soil types. The result directly informs policy making by being able to more specifically decide and explain variations of buffer zone widths along water bodies.