Modelling the Distribution of Karst Topography, Nova Scotia, Canada

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P H I L I P C H I S H O L MA P P L I E D G E O M A T I C S R E S E A R C H G R O U P

MODELLING THE DISTRIBUTION OF KARST TOPOGRAPHY IN NOVA SCOTIA,

CANADA.

ACKNOWLEDGEMENTS

• I would like to thank David Colville at Applied Geomatics Research Group (AGRG) and Sean Basquill with the Nova Scotia Department of Natural Resources (NSDNR) for their expertise, assistance, and support throughout this project. • Nova Scotia Department of Natural Resources in

allowing for the opportunity to work with their datasets.

WHAT IS KARST TOPOGRAPHY?

• Karst topography is a very distinctive landscape which is shaped and controlled by the dissolving action of water on soluble bedrock.• Precipitation infiltrates the soil and flows into the

subsurface from areas of high to low elevations, infiltrating bedrock.• This type of landscape is characterized by vertical

shafts, disappearing streams, springs, sinkholes, caves, and underground aquifers.

KARST FORMATION

What is Karst? (2014)

WHY STUDY KARST TOPOGRAPHY?

• Little scientific research surrounding karst in Nova Scotia• Considered important ecosystems and are home

to rare species populations. • Mitigate negative impacts on habitats,

ecosystems and species populations. • This model may also serve useful for further

mapping of karst geo hazards.

KARST TOPOGRAPHY

Cape North, Victoria Co.Dunn’s Beach, Antigonish Co.

Sean Basquill, NSDNR (2014)

STUDY AREA

• The study area that was utilized for the completion of this project is the province of Nova Scotia, Canada. • The province is characterised by rolling hills,

flowing rivers and sharp cliffs.

OBJECTIVE

• Develop a predictive distribution model that best represents the prevalence of karst environments throughout Nova Scotia.

APPROACH

• Data attributes which are associated with the development of karst will be uncovered and selected from relevant datasets.• Using selections a model will be produced that

attempts to represent the distribution of karst environments.• A tool will be created in order to allow for

variability in the ranks applied to karst attributes within final output.

DATASETS

Dataset Name DescriptionSurficial_Geology Complete surficial geology layer of Nova Scotia

Geology Contains polygon coverage of the entire province of Nova Scotia which includes geological information for bedrock geology including group, formation and age.

Biosystems Polygon coverage containing biophysical information including topography, slope, relief, landform and drainage.

Streams Provincial stream network for Nova Scotia including an integrated stream network.

Water_Body Includes all lakes, double lined rivers and other water bodies (swamps not included).

“county name”_WAM

Wetland area mapping of counties within Nova Scotia. Cartographically derived sub surface water flow. WAM model predicts where water will naturally flow and/or accumulate in the landscape based on digital elevation (DEM) data and the known location of surface water bodies and wetlands.

DATA PREPARATION

• Prior to the analysis being completed several steps were taken in order to prepare the data.

Cape North, Cape Breton Sean Basquill, NSDNR (2014)

PRE PROCESSING

• Projecting and Clipping • Simplify data based on what attributes were most

pertinent to karst.• Fields within the chosen attribute table of concern

were selected by the attribute names using SQL queries

CHOICE OF VARIABLES (HYDROLOGIC)

• The streams layer was buffered by 3 meters • The wetland area mapping selection is composed

of subsurface groundwater flow from 2.01 - 10 meters. • The two variables combined encompass both

surface and groundwater characteristics.

CHOICE OF VARIABLES (SURFICIAL GEOLOGY/GEOLOGY)

• Group - Broken up into Upper, Middle and Lower• Age - Early Carboniferous• Thickness - 3-30 meters • Period - Quaternary• Parent Rock Type – Anhydrite and Limestone

CHOICE OF VARIABLES (LAND SURFACE)

• Drainage - well drained polygons • Texture - very coarse, coarse, and moderately

coarse were chosen due to their ability to drain surface water.• Slope - steep and rolling slopes located

throughout the province.• Sinkholes - Potential for Sinkholes

Selections for Model Description

Wetland Area Mapping Derived from the wetland area mapping shapefile. 2.1 – 10.0m. WAM is a "cartographically derived depth-to-water index." Therefore the values listed here represent the depth to the water table in these areas as well as the sub surface flow of water.

Streams 3m Buffer Derived from the provincial stream network. A 3 meter buffer around flowing water within the eastern portion of Nova Scotia.

Surficial Geology Origin Derived from the surficial geology layer. Mechanical and chemical disintegration of bedrock occurring before and during glaciation. Used for road base aggregate; severe limitations for crop use; generally forested; acid rain buffering capacity depends on rock type but generally poor.

Surficial Geology Period Derived from the surficial geology layer. Quaternary (Stage is either Holocene or Wisconsinan).

Surficial Geology Thickness Derived from the surficial geology layer. 3 - 30m thickness of surficial bedrock.

Surficial Geology Unit Description

Derived from the surficial geology layer. Bedrock of various types and ages; glacially scoured basins and knobs, overlain by thin, discontinuous veneer of till’s.

Geology Lower Windsor Group Derived from the Geology layer. Windsor Group (Lower).

Geology Middle Windsor Group Derived from the Geology layer. Windsor Group (Middle).

Geology Upper Windsor Group Derived from the Geology layer. Windsor Group (Upper).

Ground Texture VC, C, MC (Very Coarse, Coarse, Moderately Coarse) texture of ground material.

Slope S & R –Steep and Rolling (Characteristics of the slope) 16 - 60% slope.

Sinkholes Any region of the province with known sinkholes or known sinkhole potential

Soil Drainage Very well drained polygons.

Parent Rock Type Gypsum and Limestone parent materials.

DATA STORAGE

• To effectively store and manage data files a geodatabase (Karst_Project.gdb) was created

DATA PROCESSING - AUTOMATED MODEL

• Model constructed displaying the flow of geo processing operations and outputs generated. • Automated model was

created to allow for the addition of new variables and feature classes to the process of developing the predictive karst distribution output.

KARST DISTRIBUTION PREDICTOR

• Using the python script (Karst.py) a geo processing tool was created unique to this project • Allows a user to implement their knowledge of

karst topography into the models outputs by means of a hardwired ranking schema.

KARST DISTRIBUTION PREDICTOR

CUSTOM CODING (KARST.PY)

• Custom coding was implemented to ensure that the karst.py script worked in combination with the tool parameters.

RANKS OF PREDICTORS WITHIN THIS MODEL (KARST DISTRIBUTION TOOL)

Selections for Model (Feature Class)

Rank (0-10)

Wetland Area Mapping 4Streams Buffer 3 meters 6Surficial Geology Origin 2Surficial Geology Period 4Surficial Geology Thickness 4

Surficial Geology Unit Description

2

Geology Lower Windsor Group 4

Geology Middle Windsor Group 6

Geology Upper Windsor Group 8

Ground Texture 6Slope 1Sinkholes 9Soil Drainage 6Parent Rock Type 4

FINAL OUTPUT

• Since the user ranks will vary based on what is determined as important in karst development it is difficult to output a final suitability that is indicative of high, medium and low karst potential.• The final suitability displays a range of values

based on the user ranks applied within the karst distribution tool.

KARST DISTRIBUTION FINAL OUTPUT

CLASSIFICATION INTO HIGH, MEDIUM AND LOW KARST RISK

• New field added labelled Karst_Risk.• Karst_Risk field can be calculated using the field

calculator within an editing session.• Based on the classification there are 4390 high

risk polygons, 351,740 medium risk polygons and 372,774 low risk polygons.

Karst Risk Range of Values

Low 1 - 20

Medium 20 - 30

High 30 - 48

POINT LAYER VALIDATION (MRLU SINKHOLES)

• The model and tool outputs are rendered useless unless some form of validation can be performed.• The use of known sinkhole (MRLU Sinkholes)

locations within Nova Scotia was used to calculate the frequency of points within areas of high medium and low karst potential.

RESULTS OF MRLU SINKHOLE VALIDATION

Karst Risk MRLU Sinkhole Frequency

Low 29

Medium 78

High 1

Plaster Ponds, Victoria Co.

Sean Basquill, NSDNR (2014)

ANTIGONISH VALIDATION

RESULTS (HANTS KARST POTENTIAL)

RESULTS (INVERNESS COUNTY KARST POTENTIAL)

RESULTS (VICTORIA COUNTY KARST POTENTIAL)

DISCUSSION

• Relatively little research has focused on karst within Nova Scotia therefore it was somewhat difficult to obtain datasets that were at a scale, and up to date, that would reveal highly accurate results for a provincial model.

DECISIONS BETWEEN DATASETS

• Shown is a comparison between the soils drainage and the biosystems drainage to justify the choice between the two datasets.• Surficial Geology, Geology

and Biosystems.

DATA/DATA PROCESSING RECOMMENDATIONS

• It is clear that some of the datasets used are small scale and therefore the detail retained within the final outputs could be improved upon.• Variables can be categorized into hydrologic,

geology/surficial geology and land surface predictors of karst. • These variables are not divided equally amongst

the categories; therefore, the model outputs would be more accurate if a factor weight could be applied to each individual category.

SELECTION RECOMMENDATIONS

• Surficial geological thickness attribute (3-30 meters).• Streams buffer distance.

St. Croix River, Hants Co. Sean Basquill, NSDNR (2014)

CONCLUSION

• Intended to provide a means of attempting to model provincial karst distribution within Nova Scotia.• Methodology determined to be the best way to

approach the diminished understanding of karst distribution in a GIS environment.• The karst distribution tool allows for these

inconsistencies to be addressed.• This model and associated tool allow for a further

understanding of karst.• The karst.gdb should be considered a valuable asset

in attempting to determine and predict the distribution of karst topography.

REFERENCES

• Adams, G. C. (1991). Gypsum and Anhydrite Resources in Nova Scotia. NSDNR Economic Geography Series.• Adams, G. C. (1993). Gypsum and Anhydrite in Nova Scotia. Information Circular 16, 1-20.• Basquill, S. (2014). Geomorphological and Ecological Features of Karst in Nova Scotia. NSDNR • DeMont, G. J., Utting, D. J., Finck, P. W., & Broughm, T. (2010). Surficial Geology Mapping + Geohazard

Identification + Coastal Zone Mapping = Better Land-use Planning in Central Antigonish County. Mineral Resources Branch, Report of Activities 2009, 2010(1), 11-21.

• Ford, D. C. (1997). Principal Features of Evaporite Karst in Canada. Carbonates and Evaporites, 12(1).• Forest Ecosystem Classification. (2013). Retrieved February 25, 2014, from Nova Scotia Department of

Natural Resources website: http://novascotia.ca/natr/forestry/veg-types/• Government of Nova Scotia. (2006). Retrieved from Geography and Climate website:

https://www.novascotia.ca/playground/geography.asp• Karst Forest Group. (2010). Forest Ecosystem Classification for Nova Scotia, 91-96.• Karst is a Landscape. (2012, August 1). Retrieved from Kentucky Geological Survey website:

http://www.uky.edu/KGS/water/general/karst/karst_landscape.htm• Martinez, J., & Boehner, R. (1997). Sinkholes in Glacial Drift Underlain by Gypsum in Nova Scotia, Canada.

Carbonates and Evaporties, 12(1), 84-90.• The Nova Scotia Mineral Occurrence Database (MODB). (2014). Retrieved from Nova Scotia Department of

Natural Resources website: http://www.novascotia.ca/natr/meb/links/modblinks.asp• Public Data. (2013, August 15). Retrieved February 25, 2014, from Atlantic Canada Conservation Data Centre

website: http://www.accdc.com/home.html• Speer, D., & Vickory, B. (2006). Karst Topography. Retrieved January 26, 2014, from

http://www.uwec.edu/jolhm/Cave2006/Karst.html• Stenson, R., & Ford, D. (1993). Rillenkarren on Gypsum in Nova Scotia. Géographie physique et Quaternaire,

47, 239-243.• What is Karst? (2014). Retrieved from The University of Texas at Austin website:

http://www.esi.utexas.edu/outreach/caves/pdf/Whatiskarst.pdf

THANK YOU

QUESTIONS?