GEOG 566

         Advanced spatial statistics and GIScience

May 22, 2017

Tutorial 2: Examining Hydrograph Relationships

Filed under: 2017,Tutorial 2 2017 @ 2:12 pm


How does upstream-downstream connectivity, drainage area, and position within the catchment affect the relationship between different stage gage sites?


I chose to look at the relationships between the hydrographs for four sites that have upstream-downstream connectivity but have different upstream drainage areas and are located on different tributaries. I used ArcGIS to obtain the drainage areas and Excel to analyze the hydrographs. The four sites are as follows: Site 26 is the site with the largest drainage area, on Mainstem Mill Creek. The “Mainstem” site is also located on the mainstem, with a slightly smaller drainage area. Site 36 and South Fork are located on different tributaries, Gunn Creek and South Fork Mill Creek respectively, but have approximately the same drainage area. This drainage area is significantly smaller than either Site 26 or Mainstem (Figure 1).


First I used NetMap’s Watershed Delineation tool to create upstream drainage area polygons for each of the four sites I was interested in, using the attribute table to obtain the total area of each polygon (Table 1).

Then I graphed the difference in stage heights over time between Site 26, the largest site, and each of the other three sites to examine patterns in the hydrographs, creating three “stage difference” graphs. I removed any periods of missing data (especially a two-week period in February at the Mainstem site). I also graphed the raw hydrograph data for comparison (Figure 2).

Finally I combined the three stage difference graphs into one plot for easy comparison.


First I compared the hydrograph patterns of Mainstem (MS) and South Fork (SF) since they are on the same tributary. Both graphs showed little difference with Site 26 during baseflow conditions. The 26 v MS graph was relatively flat which makes sense since Site 26 and MS have more similar drainage area sizes and are expected to behave more similarly since the amount of water going through them is more similar and they are closer together geographically. However, the MS site still had some high peaks during the two highest floods which indicates other sources of water that are influencing the hydrograph. The 26 v SF graph had high positive peaks during floods which indicates that there is a large source of water going through Site 26 that is not being accounted for in the SF hydrograph, probably from the Mainstem site (Figure 3).

Then I compared the reactions of Mainstem and Site 36 since they were a similar distance from Site 26 but with different drainage areas. The 26 v. 36 graph looked very similar to the 26 vs. SF graph which suggests that drainage area has a greater influence on the similarity of hydrographs than distance (Figure 3).

Finally I compared Site 36 and South Fork since they have similar drainage areas but are on different tributaries that both drain into Site 26. The two graphs were very similar in shape which further enforced the fact that drainage area was a primary driving factor. The two tributaries seem to be functioning relatively similarly despite differences in geographic location. The Site 36 hydrograph was more similar to Site 26 during baseflow conditions which makes sense since they are closer together in terms of streamwise distance and therefore the floodwave changes less between the two points (Figure 3).


When examining the patterns in these graphs, it is obvious that there is a portion of the hydrograph that is still missing. Most of the variability in peak flows is accounted for in the Mainstem hydrograph, but there are still minor peaks during the big floods. Little of the variability is accounted for in the Site 36 and South Fork hydrographs. Looking at the map, I hypothesize that North Fork Mill Creek, which is not instrumented, represents the differences in the hydrographs that are currently not being accounted for. It would be interesting to install a LevelLogger on this tributary in the future to see if it completes the picture.

This was an interesting analysis that allowed me to further explore my data and how my study basin reacts to precipitation events. It was useful in illustrating the influences of drainage area and stream connectivity on hydrographs in different parts of the basin, and pinpointing where there is still potentially missing data that could give a more complete picture of my watershed. It is still a pretty qualitative analysis in that I could not derive any real statistics from what is happening with my hydrographs, but it paints a clear picture of what’s going on and inspires further questions.

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