Bluespot Modelling

I followed a tutorial that walked me through the process of identifying and analyzing bluespots in Denmark starting from preparing the data, to modelling rainfall, all the way to visualizing a rainfall event's impact on the city. Bluespots are depressions in the terrain that collect a substantial amount of water during rainfall. By looking at the location of bluespots, we can identify areas that are at risk of flooding severely during heavy rain or massive snow melt. By looking at the connections between bluespots we can see where currents may form and plan infrastructure to carry this water away in safer ways. After learning about this process I applied it to the city of Hamilton, Ontario, where I reside.

I learned a lot about spatial analysis by identifying bluespots in the East Hamilton Basin along with the streams that connect them and flow rainfall out into the Hamilton Harbour. The analysis I conducted is far from perfect. To accurately model the flow of water we must start with an accurate Digital Terrain Model (DTM), building footprints, and existing hydrological infrastructure such as sewers and the location of sewer grates. On top of this the Digital Terrain Model must be made hydrologically accurate by manually adding flow paths below overpasses, bridges, in place of culverts, and any other area that may not be represented adequately in the DTM. I found much of this information on the Open Hamilton data portal, and after modifying some areas of the DTM to emulate bridges and overpasses I was able to simulate the flow of water. To create the layouts above, I picked symbology that worked for all rainfall events and then used Python and ArcPy to programmatically update and export a layout for rainfall from 10mm to 100mm.