Watershed Analyses
Jeff Kopaska and David Knoll
A lake’s
watershed is an important feature, which partially determines the structure of
the lake. The size, topography,
geology, and climate of the drainage basin influence the types and quantities
of materials that are transported to the lake.
Fertile agricultural landscapes, of which Iowa is a prime example, have
large amounts of available nutrients that can be moved off of the landscape and
into lakes. Therefore, fertile
landscapes tend to have fertile lakes.
Different types of land uses within a watershed may also impact lakes in
multitude of different ways. Thus, it
is important to look at a lake’s watershed to determine the ways in which the
watershed is influencing the lake.
B. Tributary analyses
1. Introduction. Streams, drainage ditches, storm drains, and marsh outlets all carry water off of different areas of the Clear Lake watershed. That water moves through the landscape, picking up and carrying with it nutrients and sediment, all of which ultimately ends up in the lake. Sampling the different tributaries to Clear Lake allows the determination of how much water, nutrient, and sediment is carried to the lake. It also facilitates the determination of the total nutrient and sediment contributions of different areas of the watershed to the lake.
2. Methods. A network of stream sampling stations were established throughout the watershed to identify areas contributing greatest nonpoint source nutrient and sediment loads to Clear Lake. This network was comprised of thirty-seven sampling stations spatially distributed across the watershed (Fig. 1). Previously established methods for diagnostic surveys were followed in regard to sampling frequency. Grab samples of water were collected from each site (when they were flowing) during each sampling event, and nutrients were analyzed in the laboratory. Laboratory analytical techniques used are outlined in Standard Methods for the Analysis of Water and Wastewater (APHA 1994). Mean values for nutrient and sediment concentrations for all sites from the period of study are shown in Tables 1 and 2. Additional tables of raw data are presented in Appendix 8.
3. Results and Conclusions. Clear Lake is provided most of its surface water from Ventura Marsh. One additional area is an important supply of surface water in the Clear Lake watershed. This area lies to the north and west of Clear Lake, and drains into the western basin of the lake. Each of these areas had multiple sampling sites. The differences in nutrient and sediment concentrations in tributary water for these areas are shown in Tables 3, 4, and 5. These data show that the flows into the lake from the northwest tributary and Ventura Marsh have similarly high concentrations of phosphorus. The inflows to Ventura Marsh and the northwestern tributaries have similar concentrations of nitrogen, as well. Comparing Tables 4 and 5, it can be seen that Ventura Marsh acts to decrease the concentration of nitrogen in water leaving the marsh, but it increases the concentrations of total phosphorus and total suspended solids exiting the marsh.
Urban and residential areas are common in the Clear Lake watershed, and multiple sampling sites were located at the outlets of the storm drains that remove water from these areas. The storm drains from the rural residential area along the south shore of Clear Lake contained the highest concentrations of phosphorus (Table 6). Storm drains from Clear Lake and Ventura contained similar levels of phosphorus. Storm drains from Ventura and the south shore had the highest concentrations of suspended solids.
Public concern about potential human sewage inputs to Clear Lake led to the testing of selected tributaries for caffeine. The results of these tests are found in Table 7 and Appendix 10. Six of the twelve sampling sites tested for caffeine showed detectable, quantifiable level of caffeine at least once during the period of study. Site 20 (Fig. 1) was the most consistent, having quantifiable detections in four of the five tests. Site 26 had the highest concentration in any detection, at 500 nanograms/liter. Additional information concerning caffeine in storm drains is discussed in Chapter 6.
C. Nutrient
and sediment loads
1. Introduction. It is important to know where the highest concentrations of pollutants occur, but knowledge of the mass or volume delivered through that point is of even greater utility. The nutrient load that a lake receives determines many of the chemical characteristics of that lake. The common human saying “you are what you eat” also applies to lakes, because lakes reflect their inputs. Nutrient and sediment loading to a lake includes inputs of nutrients (e.g. phosphorus and nitrogen) and sediments from sources such as surface runoff, precipitation and groundwater. Other sources of nutrients and sediments that are part of the lake’s nutrient budget but are not included in this chapter are dryfall (aeolian inputs) and nitrogen fixation by cyanobacteria.
2. Methods. The annual input of phosphorus and nitrogen to the lake from surface runoff was estimated by summation of the inputs of all tributary streams to the lake. Surface runoff was calculated from discharges measured on tributary streams in the watershed. Grab samples of water were collected from each site at the time that discharges were measured, and nutrients were analyzed in the laboratory. Discharge was measured and samples were collected in the field periodically (two times per month in April-September, once per month in October-March). Measured flux was multiplied by 86,400 (the number of seconds in one day) to determine daily flux (m3/day). The average of daily fluxes from two consecutive sampling dates was applied to the period between the two measurement dates to calculate periodic flux (m3). Periodic fluxes were summed to estimate total annual water flux. Additionally, discharge was continuously monitored at two locations in the watershed, one agricultural and one urban tributary (Appendix 10). Flow data from continuously monitored sites were combined with basin areas and rainfall volumes to determine runoff coefficients for these basins. Annual runoff volumes derived from rainfall and runoff coefficients were compared to estimated water fluxes calculated from measured discharges for regularly sampled tributaries. Excellent agreement (r2 = 0.96) was found between these two methods of determining water flux. Many tributaries in this watershed are ephemeral channels and do not flow regularly, thus it was difficult to accurately measure discharge from them. It was determined that using water flux calculated from drainage area, rainfall volume and runoff coefficient would be the most accurate method of estimating water flux, and this method was applied to all areas of the watershed. Periodic water fluxes (m3) were multiplied by average nutrient concentrations (mg/L) for that period to determine periodic nutrient flux (raw data can be found in Appendix 8). Periodic fluxes were summed to determine total annual nutrient flux.
Annual nutrient flux is reported in this section for the period August 1998 – July 1999, referred to as 1999, and August 1999 – July 2000, referred to as 2000. The 1999 period of study was much wetter than an average year, with 48.63 inches of precipitation. The 2000 period of study was significantly drier than an average year, with 28.11 inches of precipitation. In an average year, 32.57 inches of precipitation fall at Clear Lake. (Source: http://www.agron.iastate.edu/climodat/table.html)
Calculation of nutrient loading from precipitation requires quantification of rainfall volumes and nutrient concentrations in rainfall. Estimation of these nutrient inputs requires accurate measures of local nutrient deposition, but no data collection station is located near Clear Lake. To address this problem, local volunteers were solicited to collect rainwater samples for analysis by ISU. Local samples revealed higher than expected rainwater nutrient concentrations. On average, rainwater contained 0.169 mg/L of phosphorus, 2.03 mg/L of nitrogen, and 26 mg/L of silica (raw data in Appendix 11). These average values were multiplied by periodic precipitation on the lake surface, and summed to attain annual precipitation nutrient inputs. A summarization of annual nutrient and sediment influx and efflux is shown in Tables 8 and 9, and the raw data can be found in Appendix 8. A summarization of nutrient and sediment influx from different areas of the watershed is shown in Tables 10 and 11, with site and sub-basin locations shown in Figure 2. Graphic illustrations of data combined from Tables 8-11 are shown in Figures 3 - 5.
3. Results and Conclusions. Nutrient (phosphorus and nitrogen) and sediment fluxes are greatest through the agricultural areas of the watershed in 1999 and 2000. The city of Clear Lake is also a significant contributor of nutrients and sediment to the lake. Additionally, Ventura Marsh acts as a sink for nitrogen, but it exported more phosphorus, silica, and sediment than flowed into it during the course of this study.
External phosphorus loading was very high for Clear Lake, and was well above the state average for both lake loading and watershed loss rate (Tables 12 and 13). Previous studies of Iowa lakes produced phosphorus budgets by multiplying mean annual tributary total phosphorus concentration by annual runoff. This method underestimates the impact of episodic high flow events on nutrient budgets, and did not include rainfall and groundwater phosphorus contributions. Using the old method, annual phosphorus input into Clear Lake would have been estimated at 4,390 kg, while this studies’ calculation was 10,470 kg for 1999 and 4,968 kg for 2000. This could partially explain why phosphorus loading to Clear Lake seems to be much higher than phosphorus loadings calculated for other Iowa lakes (Table 3).
External nitrogen loading, found to be 11.0 g/m2 in 1999 and 3.2 g/m2 in 2000, was also high for this lake (Table 3). Clear Lake’s surface inputs are similar to other Iowa natural lakes located in agricultural landscapes, as seen in Table 4. Watershed loss of 33.1 kg/ha in 1999 and 9.5 kg/ha in 2000 of nitrogen is high. With 59% of the watershed in row crop production, and inputs of over 200 kg/ha of nitrogen fertilizer to the watershed’s cornfields, high nitrogen loss rates from the watershed are expected.
Viewing nutrient and sediment flux from the perspective of loss per hectare highlights problem areas. Tables 13 and 14 show yields of nutrients and sediment from different areas of the watershed. The south shore residential area loses the most phosphorus per unit area, but the entire watershed is remarkably similar in terms of areal phosphorus loss. Nitrogen losses are greatest from the north shore agricultural areas and the agricultural areas that flow into Ventura Marsh. Nitrogen amendment to crop fields in this area is generally 220-240 kg/ha, so these fields lost approximately 25% of the applied fertilizer during the wet period of 1998-1999. Sediment losses were relatively large from the city of Ventura in both time periods of the study. All agricultural areas (north shore, south shore, Ventura Marsh inflows) experienced high sediment losses in the wet period of 1998-1999, while the south shore agricultural and residential areas showed highest sediment losses in the drier 1999-2000 period.
Phosphorus and sediment loading to this lake during the course of this study seemed to be driven by three major factors. The first was major storm events that result in high fluxes of phosphorus and sediment to the lake. The second was high flows from Ventura Marsh in the wet portion of 1998-1999, which occurred prior to the fishery renovation. Water flowing from the marsh to the lake carried large amounts of phosphorus and sediment, probably due to the actions of wind and benthic fish in the marsh. The third factor driving phosphorus loading to the lake is rainfall (Tables 1 and 2). Rainfall in the Clear Lake area has an average phosphorus concentration of 0.169 mg/L, and the lake derived 53% of its water from direct precipitation onto the surface of the lake during the course of this study. Rainfall phosphorus accounted for around 20% of the lake’s phosphorus budget in the wet period (1998-1999), and 40% of the lake’s phosphorus budget in the drier period (1999-2000).
D. Basin characteristics and sources of
impact (nonpoint source)
1. Introduction. Watershed models are useful tools in the process of watershed management planning. They aid in the process of identifying areas which may be contributing large amounts of nutrients or sediment to a waterbody, and they are helpful in pointing our problem areas or “hotspots” in a watershed. This model is not intended to exactly predict nutrient loads from particular areas, but instead to determine areas with relatively lesser and greater nutrient export potential. Additionally, the model can be used as an index of the types of changes we might expect from land use manipulation.
2. Methods. Records from NRCS offices, aerial photography and field surveys were used to determine the land use within the drainage basin of Clear Lake. Figure 6 is a map showing the distribution of land use patterns in the watershed. The acreages and percentages of each land use in the Clear Lake drainage basin are shown in Table 16. From these data, it can be seen that the majority of the watershed is in row crops (corn and soybeans), with 59% of the area in this land use. Nearly 21% of the basin is in permanent herbaceous vegetation (pasture, grass, grassed waterways, hay, marsh), while 5% is in timber. Urban land use comprises 10% of the watershed, while roads cover 5% of the land area. The remainder of the watershed is in other uses such as farmsteads.
The data on land use combined with previously described information on soils and topography provided some of the input into a watershed analysis tool called the Agricultural Non-Point-Source Pollution Model (AGNPS). The AGNPS model was developed by the Agricultural Research Service (ARS) in cooperation with the Soil Conservation Service (now NRCS) and the Minnesota Pollution Control Agency. The model estimates runoff, sediment and nutrient transport from agricultural watersheds for specified rainfall events. The nutrients analyzed are nitrogen (N) and phosphorus (P), which are both common fertilizers and major sources of surface water pollution (USEPA 1994).
In order to perform a GIS analysis of AGNPS modeling results, the watershed is divided into cells, and inputs are made for each cell. These inputs include soil type, land slope, cropping practices, and curve number. Whether designated officially as "CRP" land or not, fields being grazed were designated as "pastureland", hayland was designated as "grassland" and cropland designations were based on their actual use during the period of study. Our estimates of "CRP" and other land uses may therefore differ somewhat from official tallies. Such discrepancies would have little impact on the predictions made here as AGNPS input parameters for several of these non-cropped categories are substantially similar. Wetlands, ponds and tile-inlet terraces are considered as depositional areas of sediment and sediment-related nutrients.
Our modeling effort started by dividing the Clear Lake watershed into eleven distinct sub-basins that were modeled separately from each other. In total 24,875 0.22-acre (900 m2) cells were used in the modeling effort. This area comprised the majority of the agricultural areas in the watershed. Data for the model were obtained from USGS topographic maps, Digital Elevation Models (DEMs), Iowa Cooperative Soil Survey soil maps and their associated attributes from the Iowa Soil Properties and Interpretations Database (ISPAID), visual inspections, the AGNPS User’s Guide (Young et al. 1994), soil nutrient data obtained during the course of this study, water quality data obtained during the course of this study and USDA Agricultural Handbook 537 (1978). General model input data found in the AGNPS User’s Guide included runoff curve numbers, overland Manning’s coefficients, surface condition constants and chemical oxygen demand factors. Input data from the USDA Agricultural Handbook 537 included soil erodability factors, cropping management factors, and conservation practice factors.
3. Results and Conclusions. The AGNPS model was applied according to present land use practices, verified through field observations of actual field uses in 2000 and was then modified to simulate future land use scenarios designed to reduce inputs to the lake from the watershed. We modeled one storm event to simulate the typical rain event-driven loading seen in Iowa watersheds. This event was a 2-inch, 24-hour storm, which climatic records show to occur at least once annually. Some model input parameters are shown in Table 17. The results of the present conditions modeling are shown in Table 18 and Figure 7. This table shows sediment yields are relatively low for the entire watershed. Sub-basins 2, 3, 4, 5 and 10 (Fig. 1) export the greatest masses of nitrogen and phosphorus to the lake. The model also predicts that sub-basin 11 loses the most nitrogen and phosphorus on a per unit area basis.
The results from modeling nutrient and sediment loss under current conditions seem to reflect the general trend of field observations. Field observations also show subbasins 2, 3, 4, 5 and 10 losing the largest masses of nutrients. Model calibration was not possible because no comparable rain events were sampled by the continuous monitoring stations. Results from a prior study, Rock Creek, indicate that AGNPS model output comes close to accurately modeling soluble nutrient transport and water movement in the watershed.
References
APHA (American Public Health Association). 1994. Standard methods for the examination of water and wastewater. Nineteenth edition. American Public Health Association, Washington, D.C.
Bachmann, R. W., M. R. Johnson, M. V. Moore and Terry A. Noonan. 1980. Clean lakes classification study of Iowa’s lakes for restoration. Final report. Iowa State University, Ames. 715 pp.
Bachmann, R. W., R. Lohnes, G. Hanson, G. Carper, D. Bonneau. 1983. Union Grove Lake restoration, diagnostic/feasibility study. Iowa Conservation Commission, final report.
Bachmann, R. W., T. Hoyman, L. Hatch, B. Hutchins. 1994. A classification of Iowa's lakes for restoration. Iowa Department of Natural Resources, final report.
Barfield, B. J., R. C. Warner, and C. T. Haan. 1981. Applied hydrology and sedimentology for disturbed areas. Oklahoma Technical Press, Stillwater.
Brune, G. M. 1953. Trap efficiencies of reservoirs. American Geophysical Union, 34(3): 408-418.
Coletti, J. 1996. Progress report to Leopold Center for Sustainable Agriculture. Agroecology Issue Team, Iowa State University, Ames.
Falconer, I. R. 1999. An overview of problems caused by toxic blue-green algae (Cyanobacteria) in drinking and recreational water. Environmental Toxicology 14: 5-12.
Haan, C. T., B. J. Barfield, and J. C. Hayes. 1994. Design hydrology and sedimentology for small catchments. Academic Press, San Diego, California.
Iowa Agricultural Statistics. 1997. Iowa crop and livestock county estimates. Iowa Department of Agriculture and Land Stewardship, Des Moines.
Iowa Administrative Code. 1990. Water quality standards, 61:1.
Iowa Department of Natural Resources. 1997. Rock Creek State Park ecosystem management plan; Des Moines.
Iowa State University, Department of Agronomy, Climatological Data Selection Page, http://www.agron.iastate.edu/climodat/table.html
Kohler, M. A., T. J. Nordenson, and D. R. Baker. 1959. Evaporation maps for the United States. U. S. Weather Bureau technical paper 37. 13pp.
Lee, K., T. M. Isenhart, R. C. Schultz, and S. K. Mickelson. 2000.
Multispecies Riparian Buffers Trap Sediment and Nutrients during
Rainfall Simulations. Journal of
Environmental Quality, 29:1200-1205.
Mitzner, L. 1999. Assessment of the impact of physical,
chemical and biological factors and angling upon bluegill and crappie
populations. Federal Aid to Fish
Restoration. Annual Performance
Report. F-160-R, Des Moines.
National Weather Service, Climatological Data. May 1998 - April 1999. Des Moines.
Roseboom, D. P., and W. White. 1990. The Court Creek restoration Project. Erosion control: technology in transition, proceedings of XXI Conference of the International Erosion Control Association. Washington, D. C. pp 25-40.
Tim, U. S., and R. Jolly. 1994. Evaluating agricultural nonpoint-source pollution using integrated geographic information systems and hydrologic/water quality model. Journal of Environmental Quality, 23:25-35.
United States Department of Agriculture. 1978. Agricultural Handbook 537. Washington, D.C.
United States Environmental Protection Agency. 1994. National Water Quality Inventory: 1994 Report to Congress, Executive Summary. United States Environmental Protection Agency, Washington, D.C.
USACOE (United States Army Corps of Engineers). 1984. Shore Protection Manual. Volume I. Department of the Army, Washington, D. C.
Young, R. A., C. A. Onstad, D. D. Bosch, and W. P.
Anderson. 1994. AGricultural Non-Point
Source pollution model, version 4.03,
user’s guide. United States Department
of Agriculture-Agricultural Research Service, North Central Soil Conservation
Research Laboratory, Morris, Minnesota.
TABLE 1. Summary
table of measurements made on all tributaries to Clear Lake during the
diagnostic study, July 1998 - September 2000.
All dates and sites combined.
Parameter |
Units |
Mean |
Standard Error |
n |
Total
Phosphorus |
mg/L as P |
500 |
20 |
868 |
Total
Nitrogen |
mg/L
as N |
6.7 |
0.4 |
868 |
Nitrate-Nitrogen |
mg/L
as N |
5.4 |
0.2 |
755 |
Silica |
mg/L
as N |
67 |
7 |
796 |
Total
Suspended Solids |
mg/L |
80 |
10 |
836 |
TABLE 2a. Summary table of measurements
made on individual tributaries to Clear Lake during the diagnostic study, July
1998 - September 2000. All dates
combined.
Site |
Total Phosphorus (mg/L) |
Total Nitrogen (mg/L) |
Total Suspended Solids
(mg/L) |
|
1 |
540 70 18 |
2.0 0.1 18 |
0.08 0.05 17 |
Mean Standard Error n |
2 |
666 102 18 |
2.0 0.2 18 |
0.05 0.03 17 |
Mean Standard Error n |
3 |
460 84 19 |
5.9 1.0 19 |
0.11 0.09 18 |
Mean Standard Error n |
4 |
445 80 19 |
3.6 0.4 19 |
0.014 0.003 18 |
Mean Standard Error n |
5 |
671 97 18 |
2.2 0.2 18 |
0.05 0.01 17 |
Mean Standard Error n |
6 |
508 104 17 |
1.8 0.2 17 |
0.05 0.01 16 |
Mean Standard Error n |
7 |
522 92 12 |
2.1 0.3 12 |
0.07 0.03 12 |
Mean Standard Error n |
8 |
971 416 19 |
8 1 19 |
0.09 0.03 16 |
Mean Standard Error n |
9 |
649 147 7 |
2.3 0.3 7 |
0.20 0.08 7 |
Mean Standard Error n |
10 |
465 69 15 |
3.4 0.5 15 |
0.08 0.04 12 |
Mean Standard Error n |
11 |
260 40 57 |
13.2 0.7 57 |
0.02 0.01 54 |
Mean Standard Error n |
12 |
508 216 2 |
0.8 0.2 2 |
0.1 0.1 2 |
Mean Standard Error n |
13 |
1310 590 2 |
2 2 2 |
0.02 0.01 2 |
Mean Standard Error n |
14 |
390 36 52 |
9.3 0.6 52 |
0.020 0.007 50 |
Mean Standard Error n |
15 |
330 41 53 |
9.8 0.5 53 |
0.014 0.004 52 |
Mean Standard Error n |
16 |
449 60 55 |
11.5 0.6 55 |
0.03 0.02 54 |
Mean Standard Error n |
17 |
411 54 57 |
14 6 57 |
0.017 0.005 56 |
Mean Standard Error n |
TABLE 2b. Summary table of measurements
made on individual tributaries to Clear Lake during the diagnostic study, July
1998 - September 2000. All dates
combined.
Site |
Total Phosphorus (mg/L) |
Total Nitrogen (mg/L) |
Total Suspended Solids
(mg/L) |
|
18 |
403 23 49 |
3.5 0.3 49 |
0.061 0.006 47 |
Mean Standard Error n |
19 |
328 40 56 |
8.5 0.4 56 |
0.028 0.009 55 |
Mean Standard Error n |
20 |
412 54 59 |
12.1 0.5 59 |
0.05 0.03 57 |
Mean Standard Error n |
21 |
1539 658 5 |
3 2 5 |
1 1 5 |
Mean Standard Error n |
22 |
1463 541 7 |
2.4 1.0 7 |
0.2 0.1 7 |
Mean Standard Error n |
23 |
536 55 37 |
2.6 0.4 37 |
0.4 0.2 36 |
Mean Standard Error n |
24 |
569 114 37 |
1.6 0.2 37 |
0.09 0.03 36 |
Mean Standard Error n |
25 |
489 59 32 |
1.9 0.2 32 |
0.03 0.01 31 |
Mean Standard Error n |
26 |
499 82 48 |
2.1 0.2 48 |
0.12 0.06 47 |
Mean Standard Error n |
27 |
458 66 43 |
5.5 0.3 43 |
0.07 0.02 42 |
Mean Standard Error n |
28 |
4077 1675 3 |
1.4 0.6 3 |
0.48 0.06 3 |
Mean Standard Error n |
29 |
896 170 4 |
1.8 0.3 4 |
0.4 0.2 4 |
Mean Standard Error n |
30 |
927 101 17 |
2.3 0.2 17 |
0.16 0.04 16 |
Mean Standard Error n |
31 |
797 173 16 |
2.0 0.2 16 |
0.08 0.02 15 |
Mean Standard Error n |
32 |
470 104 16 |
2.3 0.4 16 |
0.019 0.004 16 |
Mean Standard Error n |
33 |
719 96 17 |
3.0 0.3 17 |
0.06 0.01 17 |
Mean Standard Error n |
34 |
774 276 13 |
2.3 0.3 13 |
0.021 0.007 12 |
Mean Standard Error n |
TABLE 2c. Summary table of measurements
made on all tributaries to Clear Lake during the diagnostic study, July 1998 -
September 2000. All dates combined.
Site |
Total Phosphorus (mg/L) |
Total Nitrogen (mg/L) |
Total Suspended Solids
(mg/L) |
|
35 |
437 46 3 |
5 2 3 |
0.007 0.002 3 |
Mean Standard Error n |
36 |
150 30 2 |
2 1 2 |
0.011 0.004 2 |
Mean Standard Error n |
37 |
544 77 13 |
2.7 0.4 13 |
0.027 0.009 13 |
Mean Standard Error n |
TABLE 3. Summary table of measurements
made on the northwestern tributary (sites 12-17), during the diagnostic study,
July 1998 - September 2000. All dates
and sites combined.
Parameter |
Units |
Mean |
Standard Error |
n |
Total
Phosphorus |
mg/L as P |
400 |
50 |
221 |
Total
Nitrogen |
mg/L
as N |
11 |
1 |
221 |
Nitrate-Nitrogen |
mg/L
as N |
8.8 |
0.5 |
201 |
Silica |
mg/L
as N |
47 |
2 |
210 |
Total
Suspended Solids |
mg/L |
21 |
5 |
216 |
TABLE 4. Summary table of measurements
made on tributaries to Ventura Marsh (sites 19, 20) during the diagnostic
study, July 1998 - September 2000. All
dates and sites combined.
Parameter |
Units |
Mean |
Standard Error |
n |
Total
Phosphorus |
mg/L as P |
370 |
30 |
115 |
Total
Nitrogen |
mg/L
as N |
10.3 |
0.4 |
115 |
Nitrate-Nitrogen |
mg/L
as N |
9.2 |
0.4 |
105 |
Silica |
mg/L
as N |
54 |
5 |
109 |
Total
Suspended Solids |
mg/L |
38 |
7 |
112 |
TABLE 5. Summary table of measurements
made at the outfall of Ventura Marsh (site 18) to Clear Lake during the
diagnostic study, July 1998 - September 2000.
All dates and sites combined.
Parameter |
Units |
Mean |
Standard Error |
n |
Total
Phosphorus |
mg/L as P |
400 |
20 |
49 |
Total
Nitrogen |
mg/L
as N |
3.5 |
0.3 |
49 |
Nitrate-Nitrogen |
mg/L
as N |
0.7 |
0.1 |
44 |
Silica |
mg/L
as N |
64 |
5 |
46 |
Total
Suspended Solids |
mg/L |
61 |
6 |
47 |
TABLE 6. Summary table of measurements
made on urban storm drains to Clear Lake during the diagnostic study, July 1998
- September 2000. All dates combined.
Town (Sites) |
Total Phosphorus (mg/L) |
Total Nitrogen (mg/L) |
Total Suspended Solids
(mg/L) |
|
Clear Lake (1, 2, 4-7) |
560 40 102 |
2.3 0.1 102 |
50 10 97 |
Mean Standard Error n |
Ventura (9, 10) |
520 70 22 |
3.1 0.4 22 |
120 40 19 |
Mean Standard Error n |
South Shore
(28-37) |
900 150 55 |
2.2 0.2 55 |
110 25 53 |
Mean Standard Error n |
Table 7. Results of
tributary caffeine analyses during the diagnostic study, July 1998 - September
2000. Values are in
nanograms/liter. N/A indicates the
station was dry at the time of sampling, or no sample was taken; ** indicates
an estimated value, because the value is below the 40 ng/l minimum detection
limit; * indicates no detection of
caffeine in the sample.
|
Sampling Date |
||||
Sampling Site
|
08/19/98 |
08/24/99 |
02/08/00 |
08/22/00 |
09/27/00 |
11 |
<40* |
18** |
12** |
14** |
N/A |
14 |
N/A |
N/A |
N/A |
62 |
26** |
15 |
N/A |
94 |
N/A |
26** |
N/A |
16 |
<40* |
48 |
<40* |
37** |
<40* |
17 |
N/A |
N/A |
N/A |
20** |
35** |
18 |
<40* |
N/A |
N/A |
N/A |
N/A |
19 |
N/A |
<40* |
N/A |
<40* |
<40* |
20 |
290 |
<40* |
54 |
43 |
410 |
24 |
N/A |
48 |
N/A |
N/A |
N/A |
26 |
N/A |
16** |
N/A |
500 |
N/A |
27 |
N/A |
<40* |
N/A |
<40* |
N/A |
41 |
<40* |
N/A |
N/A |
N/A |
N/A |
Table
8. 1998-1999 nutrient and sediment influx and
efflux from Clear Lake.
|
Influx |
Rain |
Efflux |
Net Retention |
% Retention |
Water
(m3) |
19603696 |
18117733 |
12474557 |
|
|
TP
(kg) |
8082 |
2388 |
2545 |
7925 |
76 |
TN
(kg) |
122640 |
38953 |
28691 |
132902 |
82 |
TSi
(kg) |
1535948 |
474141 |
623728 |
1386361 |
69 |
TSS
(kg) |
1117816 |
141318 |
349288 |
909846 |
72 |
Table
9. 1999-2000 nutrient and sediment influx and
efflux from Clear Lake.
|
Influx |
Rain |
Efflux |
Net Retention |
% Retention |
Water
(m3) |
5520325 |
10472743 |
853721 |
|
|
TP
(kg) |
2963 |
2005 |
174 |
4794 |
96 |
TN
(kg) |
27321 |
19270 |
1964 |
44627 |
96 |
TSi
(kg) |
338451 |
268940 |
42686 |
564705 |
93 |
TSS
(kg) |
294896 |
144524 |
23904 |
415516 |
95 |
Table 10.
1998-1999 nutrient and sediment loading from different areas of the Clear
Lake watershed.
Watershed Area |
TP flux |
TN flux |
TSi flux |
TSS flux |
Water Flux |
|
kg |
kg |
kg |
kg |
m3 |
Clear Lake |
606 |
5,236 |
36,861 |
63,804 |
1,581,793 |
Ventura |
188 |
1,062 |
34,011 |
31,422 |
368,056 |
South Shore Urban |
219 |
1,052 |
34,375 |
9,939 |
379,393 |
South Shore Ag |
499 |
6,214 |
87,375 |
60,236 |
1,439,119 |
North Shore Ag |
1,448 |
43,365 |
290,773 |
170,100 |
4,030,369 |
Ventura Marsh Outflow |
3,523 |
37,975 |
739,235 |
618,527 |
9,217,061 |
Ventura Marsh Inflows |
2,381 |
78,640 |
513,762 |
472,010 |
7,018,543 |
Table 11.
1999-2000 nutrient and sediment loading from different areas of the
Clear Lake watershed.
Watershed Area |
TP flux |
TN flux |
TSi flux |
TSS flux |
Water Flux |
|
kg |
kg |
kg |
kg |
m3 |
Clear Lake |
204 |
503 |
11,752 |
19,504 |
335,109 |
Ventura |
49 |
185 |
4,298 |
8,691 |
65,498 |
South Shore Urban |
73 |
156 |
6,350 |
8,369 |
67,516 |
South Shore Agriculture |
209 |
1,715 |
26,139 |
53,629 |
408,379 |
North Shore Agriculture |
563 |
9,330 |
50,033 |
40,762 |
1,159,522 |
Ventura Marsh Outflow |
936 |
7,934 |
95,432 |
101,767 |
2,649,884 |
Ventura Marsh Inflows |
895 |
18,176 |
80,248 |
65,427 |
2,039,587 |
Table
12. Annual lake loading and watershed loss of
selected nutrients for Clear Lake.
|
1999 Lake Loading |
2000 Lake Loading |
1999 Watershed Loss |
2000 Watershed Loss |
Parameter
Measured |
g/m2 |
g/m2 |
kg/ha |
kg/ha |
Phosphorus |
0.71 |
0.34 |
2.13 |
1.00 |
Nitrogen |
11.0 |
3.2 |
33.1 |
9.5 |
Silica |
137 |
41 |
411 |
124 |
Suspended
Solids |
86 |
30 |
258 |
90 |
Table
13. Comparison of phosphorus and nitrogen
loadings among Iowa natural lakes.
|
Years of Study |
Watershed Phosphorus Loss |
Nitrogen Loading |
Lake |
|
kg/ha/yr |
g/m2/yr |
Black Hawk Lake |
1981-1982 |
0.32 |
6.94 |
Clear Lake |
1998-1999 |
2.13 |
11.0 |
Clear Lake |
1999-2000 |
1.00 |
3.2 |
Crystal Lake |
1998-1999 |
0.30 |
16.2 |
Okoboji
chain (6 lakes) |
1971-1973 |
0.35 |
N/A |
Table 14.
1999 subbasin nutrient and sediment loss from different area in the
Clear Lake watershed.
Site |
TP loss |
TN loss |
TSi loss |
TSS loss |
||||
|
kg/ha |
lbs/ac |
kg/ha |
lbs/ac |
kg/ha |
lbs/ac |
kg/ha |
lbs/ac |
Clear Lake |
2.3 |
2.0 |
20 |
18 |
138 |
124 |
240 |
214 |
Ventura |
3.0 |
2.7 |
17 |
15 |
546 |
487 |
504 |
450 |
South Shore Urban |
3.4 |
3.0 |
16 |
15 |
535 |
478 |
155 |
138 |
South Shore Agriculture |
2.1 |
1.9 |
26 |
23 |
365 |
326 |
252 |
225 |
North Shore Agriculture |
2.2 |
1.9 |
65 |
58 |
433 |
386 |
253 |
226 |
Ventura Marsh Outflow |
2.2 |
2.0 |
24 |
21 |
460 |
411 |
385 |
344 |
Ventura Marsh Inflows |
2.0 |
1.8 |
68 |
60 |
441 |
394 |
405 |
362 |
Table 15.
2000 subbasin nutrient and sediment loss from different area in the Clear
Lake watershed.
Site |
TP loss |
TN loss |
TSi loss |
TSS loss |
||||
|
kg/ha |
lbs/ac |
kg/ha |
lbs/ac |
kg/ha |
lbs/ac |
kg/ha |
lbs/ac |
Clear Lake |
0.8 |
0.7 |
2 |
2 |
44 |
39 |
73 |
65 |
Ventura |
0.8 |
0.7 |
3 |
3 |
69 |
62 |
139 |
124 |
South Shore Urban |
1.1 |
1.0 |
2 |
2 |
99 |
88 |
130 |
116 |
South Shore Agriculture |
0.9 |
0.8 |
7 |
6 |
109 |
98 |
224 |
200 |
North Shore Agriculture |
0.8 |
0.7 |
14 |
12 |
75 |
66 |
61 |
54 |
Ventura Marsh Outflow |
0.6 |
0.5 |
5 |
4 |
59 |
53 |
63 |
57 |
Ventura Marsh Inflows |
0.8 |
0.7 |
16 |
14 |
69 |
61 |
56 |
50 |
TABLE 16. Land use characteristics of Clear Lake watershed
drainage basin.
Land Use |
Total Hectares |
Total Acres |
Percent of Watershed Area |
Row Crop |
1969.9 |
4867.6 |
59% |
Urban |
335.4 |
828.9 |
10% |
Marsh |
294.1 |
726.6 |
9% |
Grass |
251.5 |
621.4 |
8% |
Trees |
182.5 |
451.0 |
5% |
Road |
152.1 |
375.8 |
5% |
Farmstead |
56.5 |
139.5 |
2% |
Pasture |
37.9 |
93.6 |
1% |
State Park |
26.8 |
66.1 |
1% |
CRP |
25.9 |
63.9 |
1% |
Hay |
9.2 |
22.7 |
<1% |
Terraces |
2.6 |
6.4 |
<1% |
TABLE
17.
Parameter |
Present Conditions |
Soil # N/# soil |
0.0025 |
Soil # P/# soil |
0.00072 |
N in soil pores (ppm) |
10.7 |
P in soil pores (PPM) |
0.34 |
Organic Matter (%) |
5 |
N fertilizer (#/ac) |
100 |
P fertilizer (#/ac) |
65 |
Table 18.
Calculated sediment and nutrient inputs to Clear Lake from single storm
event modeling present conditions.
Parameter |
2-inch, 24-hour Storm
Event |
|
|
Metric |
Imperial System |
Phosphorus |
|
|
Sediment associated |
1,598 kg |
3,523 lb |
Water soluble |
444 kg |
979 lb |
Nitrogen |
|
|
Sediment associated |
5,706 kg |
12,580 lb |
Water soluble |
1,542 kg |
3,399 lb |
Sediment |
261,274 kg |
288 tons |
Lake volume lost |
181 m3 |
0.09 ac-ft |