Soil erosion modelling can help define efficient and targeted mitigation strategies by identifying the long-term controlling factors and the areas where, and periods during which, soil is at high risk of erosion. However, to define such strategies, there remains a lack of modelling approaches a) able to provide with longer term baseline information which to measure the success or otherwise of mitigation strategies at the catchment scale and b) accessible and robust enough to be used, understood, and trusted by users with more or less expertise, including researchers, land managers and policy makers. In response, this project will improve the robustness and accessibility of quantitative methods for supporting agricultural land management. For this purpose, we will develop a parsimonious soil erosion modelling toolbox, iMPACt-erosion, to support agricultural land management in Europe at the catchment scale. The development philosophy will be based on three principles: robustness, transparency, and accessibility. For a robust model evaluation, model simulations will be compared to multi-decadal soil loss estimations estimated from fallout radionuclides and tree mound measurements. The toolbox and its code will be easy to read and understand by users with more or less expertise. The modelingl accessibility will be achieved by using interactive Jupyter Notebooks (jupyter.org) a modelling environment that combines executable code, rich media and interactive visualization of data and model results. This translates into a more fluent conversation between the user and the model and an easier exploration of the model results and the impact of possible agricultural management scenarios.
Objectives:
- to develop an accessible and transparent soil erosion modellling toolbox, iMPACt-erosion, to support agricultural land management in Europe at the catchment scale.
- to achieve greater confidence in modelling predictions by creating a robust evaluation framework both in terms of model behaviour, i.e. whether the ‘right’ parameters control the model response, and in simulating observed past changes and their corresponding measured/estimated erosion impacts over time scales that encompass at least several decades.
- to identify soil erosion controlling processes and vulnerable areas and periods to define targeted and effective mitigation strategies until 2100.
