AGU2011: A framework to understand spatial and temporal connectivity dynamics at hill slope and catchment scales (invited)

An invited talk at AGU Fall Meeting 2011:

Sim M Reaney1, Louise Bracken1, Stuart N Lane2, David Milledge1, Christopher Williams1
INSTITUTIONS (ALL): 1. Department of Geography, Durham University, Durham, United Kingdom. 2. Faculté des géosciences et de l’environnement, Université de Lausanne, Lausanne, Switzerland.

Hydrological connectivity describes the ease with which water can move across the landscape and is a central factor in determining catchment hydrological and water quality behaviour. The strength of the connectivity is determined by the interactions between the driving rain storm events and the physical structure of the landscape and leads to threshold changes in behaviour. Being able to determine the connectivity is key to predicting: 1. how the catchment will respond to storms events to generate flood events and 2. the distribution of critical source areas for diffuse pollution. A new framework to consider the spatial and temporal interactions of material as it moves through the landscape is presented. This framework is based on the understanding of the spatial patterns and temporal dynamics of the sources, stores, pathways, connections and consumers of material. Examples will be presented that use this framework to understand hydrological and sediment connectivity patterns at both the hill slope and landscape scale. The hill slope scale application considers the movement of overland flow across the surface. The analysis makes predictions of the probability of a connection between each point on the hill slope and river channel. The landscape scale approach considers the  combined impact of spatial patterns of the hydrological connectivity with spatial patterns of fine sediment risk to give a diffuse pollution risk map at the landscape scale. These examples show how the crossing of a connectivity threshold changes the system response and that understanding the connectivitypatterns at the hill slope and landscape scale is essential for understanding environmental systems.