This document summarizes a study investigating the impact of land use and flow conditions on total suspended sediment (TSS) in streams draining into an estuary. The hypothesis is that urban and agricultural land use will increase sediment levels in streams compared to forested areas, particularly during storm events. Data on TSS, flow, and land use were collected from 15 sites over time. Preliminary results found strong correlations between TSS and flow during storms but no clear relationships between TSS and other factors like slope or land use. Further analysis of storm data from forested sites is needed to fully test the hypothesis.

1. Moussa Albert Siri
Mentor: Dr Wilfred Wollheim
Departement of Natural
resources and the environment

2. Problem: There is an increasing change in sediment
deposition in coastal environment
Sediment input in coastal area is via streams and rivers
Sediment input in streams and rivers is impacted by:
-Land use
-Stream slope (low in many coastal watersheds)
-Flow conditions (most important)

3. Goal: understand variation in total suspended sediment
(TSS) due to land use and flow in streams draining to an
important estuary.
Hypothesis: Urban and agricultural land use will add more
sediments into streams than least disturbed lands (forested
lands) particularly during storm events.

4. -Stream transport capacity: high at steep slope
and decrease as slope decreases (Armanini et al.
2015, and Brandt S. A. 2000).
-Agricultural and urban vs. forested lands (Lenat and
Crawford 1993, and Buck et al. 2003)
-Slope impacts stream power and its transport
capacity (Yu et al. 2015).
Lanes Law: Stream power = Dischage (Q) x Slope
Note: in low slope, stream power ≈ discharge

5. Connection to our study
-study area with shallow slope (low impact on
TSS)
-TSS more important in streams in urban and
agricultural areas during storm events
-flow will mainly impact TSS particularly during
storm events

6. 15 sites and at least 152 water samples filtered and weighed

7. -flow measurement couple times (record
stage at each sampling)
Field work
-manual sampling every other week
-use of auto-samples during storm
sampling

8. Data analysis
Lab processing
-Sediment filtration
-Hobo's data download

9. R2
= 0.06317
0
5
10
15
20
25
0 0.005 0.01 0.015 0.02 0.025 0.03 0.035 0.04
TSS(mg/L)
Stream Slope (ft/mile)
TSS vs. Stream Slope: R2 value indicates that there is no correlation between TSS
and the slope of the stream. As mentioned before, stream slopes are very shallow
in the study area. They don't impact stream transport capacity. Slope is estimated
using 10 and 85 method (ft/mile).

10. R² = 0.1347
0
5
10
15
20
25
0 1 2 3 4 5 6
TSS(mg/L)
Basin Slope (30m DEM (%))
TSS vs. Basin Slope: R2 value indicates that basin slopes do not impact TSS
concentration in streams.

11. R² = 0.1474
0
5
10
15
20
25
0 10 20 30 40 50 60
TSS(mg/L)
Forest Cover (%)
TSS vs. Forest Cover: R2 value indicates also that there is no signifant correlation
between TSS and forest cover. However, the presence of consecutive high TSS
concentration at least forest cover areas suggest some support to the role of forest
cover on TSS concentration in streams.

12. TSS and Discharge vs. Time: This figure shows TSS vs. time (blue graph) and
dischage vs. time (red graph) during storm of June 05, 2016. The figure shows a
strong relationship between TSS and stream discharge during storm events.
0
200
400
600
800
1000
1200
1400
1600
1800
2000
0
20
40
60
80
100
120
140
160
2016-06-05 0:00 2016-06-05 12:00 2016-06-06 0:00 2016-06-06 12:00 2016-06-07 0:00 2016-06-07 12:00 2016-06-08 0:00
StreamDischargeQ(L/s)
TSS(mg/L)
Time (hours)

13. 0
20
40
60
80
100
120
140
160
0 200 400 600 800 1000 1200 1400 1600 1800 2000
TSS(mg/L)
Discharge (L/s)
TSS vs. Discharge: Hysteresis graph indicates that the TSS concentration increases
faster in the stream than the discharge at the beginning of the storm, but inversely,
TSS decreases faster than the discharge at the end of the storm (Storm of June 05,
2016).

14. TSS and Discharge vs. Time: This figure shows TSS vs. time (blue graph) and
dischage vs. time (red graph) during storm of June 28, 2016. Here also, the figure
shows a strong relationship between TSS and stream discharge during the storm
events.
-0.02
0.00
0.02
0.04
0.06
0.08
0.10
0.12
0.14
0.16
0.18
-20.00
0.00
20.00
40.00
60.00
80.00
100.00
120.00
140.00
160.00
2016-06-28 12:00 2016-06-29 00:00 2016-06-29 12:00 2016-06-30 00:00 2016-06-30 12:00 2016-07-01 00:00
DischargeQ(L/s)
TSS(mg/L)
Time (2 hours)

15. TSS vs. Discharge: Hysteresis graph indicates that the TSS concentration increases
faster in the stream than the discharge at the beginning of the storm, but inversely,
decreases faster than the discharge at the end of the storm (Storm of June 28, 2016).
-20.00
0.00
20.00
40.00
60.00
80.00
100.00
120.00
140.00
160.00
-0.02 0.00 0.02 0.04 0.06 0.08 0.10 0.12 0.14 0.16 0.18
TSS(mg/L)
Discharge (L/s)

16. However, plot of TSS versus forest cover shows some support to
the hypothesis (high TSS in least forest area, and low TSS in most
forested area
Base flow conditions:
The results show no significant correlation between TSS and
stream slope. There is no significant connection between TSS and
basin slope either and also no between TSS and forest cover.

17. Storm flow conditions:
Increase of TSS, due to storm event, is consistent with the
hypothesis, but by itself is not sufficient to support or refute the
hypothesis
-There is a strong correlation between flow level and TSS during
storm events in agricultural/urban whatershed
-Storm event data, already collected from forested sites, are
being processed. In order to test the hypothesis, these data will
be used to compare land use impacts on TSS during storm
events.

18. -my Mentor Dr Wilfred Wollheim and his research team for their
support during this research
-the McNair Program for giving me the opportunity to conduct this
research
-ESPCoR NEST project for its contribution to this proct
-Emily Balcom and Chris Cook for their precious help in the field
My acknoledgments go to:
-my family for its patient and understanding

19. -Armanini, A., Fraccarollo, L., & Rosatti, G. (2009). Two-dimensional simulation of
debris flows in erodible channels. Computers & Geosciences, 35(5), 993-1006.
-Buck, O., Niyogi, D. K., & Townsend, C. R. (2004). Scale-dependence of land use
effects on water quality of streams in agricultural catchments. Environmental
Pollution, 130(2), 287-299.
-Lenat, D. R., & Crawford, J. K. (1994). Effects of land use on water quality and
aquatic biota of three North Carolina Piedmont streams. Hydrobiologia, 294(3),
185-199.
-Yu, B., Zhang, G. H., & Fu, X. (2014). Transport Capacity of Overland Flow with High
Sediment Concentration. Journal of Hydrologic Engineering, 20(6), C4014001.
-Brandt, S. A. (2000). Classification of geomorphological effects downstream of
dams. Catena, 40(4), 375-401.a