Abstract
The Rangeland Department in the Kamloops District from the Government of British Columbia has recently raised concerns regarding the observation on the reduction of the number and the surface area of the grassland ponds in the Lac du Bois Grasslands Protected Area. This study aims to distinguish between the ponds with stable groundwater inputs (i.e. connected ponds) and the ponds with unstable groundwater inputs (i.e. perched ponds) to assist the government in determining reliable water sources. This research started by categorizing ponds with different surface areas as either low resilience or threatened resilience. Different terrain models were created using Light Detection and Ranging (LiDAR) data in addition to the calculation of the topographic wetness index (TWI). The classifications were validated using Google Earth and drone imagery. An overall of 121 ponds was discovered with 86 of them considered as low resilience, while the remaining 27 ponds being threatened resilience. For the low resilience ponds, 19 of them were identified as perched ponds, 47 as connected ponds, and 20 as intermediate ponds with the risk of having unstable groundwater connection that requires further analysis in the field. For the threatened resilience ponds, 5 of them were found to be perched ponds, 17 as connected ponds, and 5 as intermediate ponds. The outcome of the pond distribution indicates that the perched ponds were more likely to be found in an area with a flat slope, surrounded by grass, and low canopy coverage. Additionally, the calculated TWI was unable to differentiate between the pond types as the median groundwater levels are spatially dependent on the local topographic features.
MGEM Student: Helen Liang
Community Partner: BC Ministry of Forests, Lands, Natural Resource Operations, and Rural Development – Range Branch
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Liang, Helen, 2021, “Using Light Detection and Ranging (LiDAR) and Google Earth imagery to identify whether ponds are connected to stable ground water inputs”, https://doi.org/10.5683/SP2/4WYNM9, Scholars Portal Dataverse, V1