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Karst Landscape Influence on the Planetary Boundary Layer Atmosphere

Karst landscapes cover approximately 20% of the ice-free land area worldwide. The soluble nature of the bedrock within a karst landscape allows for the formation of caverns, joints, fissures, sinkholes, and underground streams, which affect the hydrological behavior of the region. Currently, the Noah Land-Surface Model (Noah- LSM), coupled with the Weather Research and Forecasting (WRF) model, does not provide a representation of the physical behavior of a karst terrain. Previous research has attempted to model karst behavior through soil moisture and land cover/land use changes to determine the influence this unique landscape may have on atmospheric phenomenon. This highlights the need to study the potential influence that karst landscapes may have on model simulations. For this study, several factors were taken into account while studying karst and meteorology: the verification of a current operational forecasting model against observational data over five years (2007 to 2011), the formation of a karstlike soil type for use within an operational forecasting model, and model behavior once this karst-like soil type was added to the operational forecasting model.
The verification of a currently operational forecasting model, the North American Mesoscale (NAM), indicated that, overall, the karst regions may exhibit an influence on local winds (greater error) and precipitation (frequency and forecasting). When developing a realistic karst-like soil proxy for use in the Noah-LSM, hydraulic conductivity values show a variation ranging from around 10-7 and 10-5 m s-1 for the karst bedrock within Tennessee and Kentucky. Sandy loam and clay soils were used, along with bedrock parameters, to determine an average soil parameter type for the epikarst bedrock located within this region. The model study demonstrated that the addition of karst highlighted the potential influence on precipitation distribution and energy fluxes, through RMSD and R2 values taken at a 95% confidence interval.

Identiferoai:union.ndltd.org:WKU/oai:digitalcommons.wku.edu:theses-2647
Date01 July 2016
CreatorsSullivan, Zachary S.
PublisherTopSCHOLAR®
Source SetsWestern Kentucky University Theses
Detected LanguageEnglish
Typetext
Formatapplication/pdf
SourceMasters Theses & Specialist Projects

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