Coastal dune budgets depend on sediment input by wind from the beach. Calculation of aeolian transport is thus a primary factor to understand coastal dune evolution and beach-dune coupled dynamics. However, measuring aeolian sediment transport in coastal areas presents fundamental technical and conceptual limitations that make numerical modeling difficult. Wind tunnel experiments isolate and reduce the number of variables to study, which is a necessary procedure to clearly manifest mechanistic relationships between cause and effect. But even with refinement and inclusion of new variables, traditional sediment transport formulas derived from wind tunnel experiments do not usually work well in natural areas. Short-term experiments may include precise instrumentation to obtain high frequency, detail time series of variables involved in aeolian transport, but inferring information at larger scales is problematic without knowledge of the timing and magnitude of particular transport events. There are two primary problems in attempting to predict sediment inputs to coastal dunes over periods of weeks, months or years: 1) to determine an appropriate set of predictive equations that incorporate complexities such as surface moisture content, beach width and the presence of vegetation; and 2) to provide quantitative data on these variables for input into the model at this time scale. Remote sensing techniques and the use of GIS software open the possibility to monitor key parameters regulating sediment transport dynamics at high spatial and temporal resolution over time scales beyond short-term experiments. These were applied at Greenwich Dunes, Prince Edward Island National Park (Canada), in an attempt to measure factors affecting aeolian sediment input to the foredune at a medium scale. Three digital cameras covering different sections of the beach and foredune provide time series on shoreline position, fetch distances, vegetation cover, ice/snow presence, or superficial moisture content. The rectification of oblique images to UTM maps allows to keep the spatial variability of these factors, and thus to perform detailed analysis on their complex evolution. Auxiliary instrumentation such as anemometers, safires, or erosion-deposition pins completes the basic set up. Data is processed using ArcGIS 9.2 and PCI Geomatica 9.1, and managed by an ArcCatalog Geodatabase. The coupling of new technologies (digital imagery) with traditional instrumentation (e.g. anemometers), and the extensive GIS capabilities both in the spatial and temporal domain, permits a new set of questions in aeolian coastal research. The overall goal is to obtain information on what is the frequency and magnitude of transport events at the beach or what are the key parameters regulating them. Challenges remain in improving methodologies to measure sediment transport rates. Ironically enough, we are able to obtain high quality time series on the factors affecting aeolian transport at the beach, but actual transport rates are measured with rather rudimentary techniques or instrumentation not adapted to meso-scale monitoring. This information is needed to test new approaches in modeling and understanding aeolian sediment input from the beach to the foredunes.
|Publication status||Published - 2009|
|Event||American Geophysical Union (AGU) Joint Assembly - Toronto, Canada|
Duration: 24 May 2009 → 27 May 2009
|Conference||American Geophysical Union (AGU) Joint Assembly|
|Period||24/05/09 → 27/05/09|