Understanding Runoff and Erosion Dynamics

Soil erosion by water is leading to an accelerated loss of the world's food-producing lands, threatening global food security. Models are a vital component of attempts to understand the impact of agricultural processes, land-use and climate change on soil erosion. However, current approaches to modelling soil erosion, despite a long heritage, have shown little overall improvement in their predictive capability. All models are constrained by the experimental base upon which they rests, much of which, for soil erosion, dates from experiments and technologies of a generation ago. Thus far, technological limitations have constrained experimental work to steady-state measurements for what is actually a highly dynamic process. For example, experiments to derive the parameters of soil-erosion models typically use constant-intensity rainfall and then apply these parameters to model erosion under temporally varying natural rainfall, although we now have evidence that parameters derived in this way will make incorrect predictions for temporally varying natural rainfall. A way out of this impasse is to use optical diagnostic techniques, developed in the field of mechanical engineering, which enable the study of highly dynamic multiphase flows. Recent developments in pulsed laser-illumination sources and digital camera technology allow the recording of particle/flow interactions at rates up to 20,000 frames per second. Using these techniques it is now possible to make a step change in our understanding of the dynamics of processes of soil erosion. This research will (i) refine existing high-speed, high-resolution imaging and PIV techniques to track sediment particles of 0.063 mm to 2.0 mm simultaneously in shallow overland flows that typify soil erosion; (ii) use these refined techniques to develop datasets of high resolution and high accuracy that will characterize the dynamics of the different components of the detachment, transport and deposition processes in shallow overland flows; (iii) make these datsets available to the wider soil-erosion community for their own model development and testing; (iv) use the data obtained to develop submodels within an existing soil-erosion model (MAHLERAN) which we have previously developed that are capable of representing dynamic properties of erosion processes, rather than steady-state conditions; and (v) test the revised version of MAHLERAN against existing datasets for unsteady conditions. The work will provide an important contribution to key NERC Strategy areas such as Living with Environmental Change and the analysis of the impact of environmental change on ecosystem services, with consequences in terms of sustainability, global poverty and carbon sequestration. The research will also lead to the production of more effective tools for environmental managers to implement practices of integrated river-basin management as required under current legislation such as the EU Water Framework and Nitrates Directives.