The Application of Extreme Stochastic Inputs to a Transport Model in the Context of Global Climate Change

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Date

2011

Authors

Haerer, Drew

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Medina, Miguel A

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Abstract

Global climate is predicted to have significant impacts on the chemical, biological, and physical characteristics of wetlands and the watersheds in which they are contained. In particular, climate prediction models suggest a significant increase in extreme precipitation events - both more frequent and more intense flood and drought occurrences. A wetland model that incorporates surfacewater-groundwater interactions (WETSAND2.0) was used to investigate the potential impacts of these stochastically generated extreme events on wetland flow regimes in an urban watershed. The results predict increases in streamflow and flooding as well as drought conditions on a near yearly basis. However, the model also shows that the impact on the Sandy Creek-Duke University watershed will not be as extreme as many suggest. Although flooding will occur, it will be relatively minor and comparable to historic flows. And although droughts are also predicted, the balance of wet and dry in this wetland watershed can actually be a positive for the environment. Therefore watersheds, no matter the spatial scale, must be analyzed individually. Although some comparisons can be made between similar regions, the effects of extreme precipitation events vary greatly depending on watershed characteristics.

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Citation

Haerer, Drew (2011). The Application of Extreme Stochastic Inputs to a Transport Model in the Context of Global Climate Change. Master's thesis, Duke University. Retrieved from https://hdl.handle.net/10161/5059.

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