Q1. How Many Subcatchments Were Formed in Your Watershed Partitioning? What Was the Drainage s1

GEOG 591 Water GIS

Qi Zhang

Q1. How many subcatchments were formed in your watershed partitioning? What was the drainage area in hectares that you used to define the beginning of each channel?

There are 392 subcatchments. I defined drainage as 2750 cells. Regarding each cell has an area of 20ft*20ft, the total area would be

2750*20*20 = 1,100,000 ft2

Then convert in hectare unit, it would be

1,100,000 ft2 = 10.2193 hectares

The drainage line roughly matches the stream line with little discrepancy at the head of the stream. Regarding more detail of the results, I think the drainage should be defined as higher cells, such as over 3000 cells (3250 might work better).

Q2. Remember this is all a model. What key assumptions were made, and how would you want to improve the watershed delineation to better match field conditions?

As a whole, this model is based on a theory of rooted tree graph, which assumes that all points are on a unique connected path to outlet on a smooth impervious surface. Specifically, I presumed the high accuracy of stream network definition. So the stream defined by number of cells (or area) is crucial to the segment delineation which should be taken much care of.

To improve the delineation, I think it is important to improve the accuracy of defining stream by comparing with other data, such as digitized water flowing network (showed in blue lines) or the records/measurements of land cover. A proper threshold should be set up by testing or matching the current flow network several times, not losing main stream branch while not generating to much detail (small branches).

Q3. Make impervious cover and land cover zonal statistics maps with your catchment boundary shape file. According to the zonal maps and tables, what is the range of % impervious area for the catchments?

The tables have been saved under onyen folder in certain type (.dbf/.xlsx), named “zonalmean_imp”, “Zonalmajor_lc”, “hidtogram_lc”, respectively. I didn’t insert these tables here due to huge space.

Seeing the maps, I find that the majority of impervious surface locating east and south parts of the whole region, where the catchments have higher mean value for impervious area. These areas are big cities, such as Chapel Hill and Durham, so it is reasonable to identify higher frequency of impervious surface. Sorting the statistics of tables, the range of mean value for impervious surface would be roughly 0-60. The area of the impervious surface or urban area accounts for nearly half of the total region.