Simulating complex hydro-geomorphic changes in lake-catchment systems

Abstract

Management of lake-catchment systems is a long-term challenge for prevention of hazard risk and further sustainable development. Climate change and human activities are two important factors that concurrently affect the hydrology and sediment regimes within systems. Many soil conservation and sediment control techniques are known and widely studied based on experimental field plots. Catchments are complex dynamic systems. Spatially-distributed and process-based models provide powerful tools to simulate the complex behaviour of hydro-geomorphological processes in response to climate change and human impact on fluvial systems. Accordingly, this study addresses the principles, testing and application of an established cellular automata landscape evolution model (CAESAR) to study the dynamic non-linear behaviour of complex systems, past and present interactions among landscape elements and environmental controls, and potential future impacts. The results from a series of simulations of different systems (simple catchment, Old Alresford Pond, UK and Holzmaar, Germany) over different timescales (50 years to 5000 years), demonstrate a rapid catchment response to climatic drivers. This is characterised by variations, particularly peaks of modelled sediment discharge controlled by the magnitude and frequency of floods and droughts happened in a single year or a period of time. The effect of vegetation cover also plays an important role in accelerating the delivery of sediment or protecting the catchment from soil erosion. This erosional response is validated by comparing modelled sediment discharge and system evolution to magnetic susceptibility and accumulation rates of lake sediments, as well as documented data. The non-linear properties of complex systems, such as thresholds, feedback mechanisms and self-organised capability, are shown to exist in these simulations. This study also provides the probabilistic results of potential erosion risks in terms of future natural and human pressures. The modelling application permits a better understanding of the relationship between environmental forcings and complex dynamic system evolution processes. In addition, it allows investigations of the extent to which past and present human-environmental interactions generate subsequent impacts for the purpose of effective landscape management.

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Identifiers

ORCID for John Dearing: orcid.org/0000-0002-1466-9640

ORCID for David Sear: orcid.org/0000-0003-0191-6179

ORCID for Peter Langdon: orcid.org/0000-0003-2724-2643

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