Modelling the ecohydrology of moorland hillslopes

This study reports a new ecohydrological approach to modelling moorland hillslopes, which extends previous work on moorland hillslopes and has wider relevance to the study of ecohydrological systems. A new conceptual and numerical model, MEMory is presented which considers soil memory and the effects of plants on soil structure as important features of moorland hillslopes. Representation of surface and subsurface patterns and how these may vary spatially and over time was considered essential to exploring the role of memory and an iterative process of model development and testing with field data was adopted. A numerical model was developed to demonstrate the effects of the rules and assumptions of the conceptual model on the behaviour of a modelled moorland hillslope. The numerical model successfully reproduced surface plant-age distributions of Calluna vulgaris L. (Hull) observed in the field. Field campaigns and laboratory-based investigation indicated variability in subsurface properties in relation to different Calluna plant age distributions, which provided some evidence to support the model’s predictions on subsurface variability. The numerical model was used to explore how patterns imposed by vegetation management practices may affect the ecohydrological behaviours of ecosystems. The model predicts that burning can have large effects on the hydrological conditions of moorland hillslopes. Use of a spatial model proved very important because the simulations highlighted model sensitivity to the size of management event and the location on the slope, in addition to the frequency of management events. The model simulations have provided useful predictions which could be tested in the field as part of future studies of the ecohydrology behaviours of moorland hillslopes. The study demonstrates the power of a conceptual model as a tool for understanding how a system works and suggests that numerical models could play a much greater role in the study of subsurface patterns and processes.