7.0 detailed instream sediment modeling...sed2d is a sediment transport numericalmodel developed by...

USACE - Detroit District 125 St. Joseph River Great Lakes Hydraulics and Hydrology Office Sediment Transport Modeling Study

7.0 DETAILED INSTREAM SEDIMENT MODELING

7.1 Model Description – RMA2 & SED2D

A detailed hydrodynamic model (RMA2) and an associated sediment transport model (SED2D) were set up to evaluate sediment movement through the harbor and into the nearshore zone. The main objectives of this exercise were to provide estimates of sediment movement through the harbor over long time periods and to evaluate the impact of dredging the inner harbor on sediment discharges to the nearshore zone. RMA2 is a two-dimensional, depth-averaged, finite element hydrodynamic numerical model. It computes water surface elevations and horizontal velocity components for subcritical, free-surface flow in two-dimensional flow fields. Norton, King and Orlob (1973) developed the original RMA2 model for the US Army Corps of Engineers. Many subsequent enhancements have been made, culminating in the current version (v.435) of the code. The program has been applied to calculate water levels and flow patterns in rivers, reservoirs, and estuaries. RMA2 has the following capabilities:

• Simulate wetting and drying events; • Account for effects of the earth’s rotation; • Apply wind stress involving frontal (storm) passages; • User selectable turbulent exchange coefficients, Manning’s n-values, etc; • Model up to 5 different types of flow control structures; • Provides for user defined computational guidelines; • Accepts a wide variety of boundary conditions.

The sediment transport model, SED2D is coupled with the RMA2 model. SED2D is a sediment transport numerical model developed by the U.S. Army Corps of Engineers Waterways Experiment Station. It has the ability to compute sediment loadings and bed elevation changes when supplied with a hydrodynamic solution computed by RMA2. SED2D can be used to model sand bed types or clay bed types with up to ten clay layers. It is possible to model both steady-state and transient flow types, just as with RMA2.

7.2 Model Setup

The RMA2-SED2D model domain was set up for an area including the lower St. Joseph River up to approximately 3 miles upstream from the inner harbor; the Paw Paw River for approximately 2 miles upstream from the inner harbor; the inner and outer harbor; and the lake for approximately 2.5 miles upstream and downstream from the harbor, and for 1 mile offshore (Figure 7.1). The model bathymetry was set up to represent three different scenarios:


• 2002 bathymetry using survey data provided by the USACE (Figure 7.2). This is the reference condition for these model runs;

• 1907 bathymetry (Figure 7.3), representing conditions almost 100 years before present; and

• 2002 bathymetry, with the inner harbor dredged to an approximate depth of 20 ft (Figure 7.4).

The primary inputs to the RMA2 model (in addition to bathymetry) are lake level data downstream and river flow data at the upstream boundaries in the St. Joseph and Paw Paw Rivers. The most complete set of continuous flow data is available from the USGS gage at Niles, with a record from 1930 to present. Records of Total Suspended Solids (TSS) or Suspended Sediment Concentration (SSC) are coincident with this record, both at Niles and in other nearby locations. Part of these datasets is shown in Figure 7.5. A broad range of conditions needed to be modeled using the RMA2-SED2D system. To increase the efficiency of analysis, RMA2 was run in steady-state mode under different lake level and river flow conditions. 10 different river flows in the St. Joseph River were modeled, along with 3 different lake levels, and 3 different flows in the Paw Paw River, to give a total of 90 (10 x 3 x 3) model runs for each scenario. The different flow conditions are summarized in Table 7.1.

Table 7.1: River Flow and Lake Level Conditions Modeled in RMA2 Boundary Condition Description Comments Flow in the St. Joseph River at the upstream boundary

10 different flow conditions (1-10)

Ranging from low flow (Run 1) to an extreme flood with over a 10-year return period (Run 10)

Flow in the Paw Paw River at the upstream boundary

3 different flow conditions (H, M, L)

H, M, L based on 90th percentile, Mean, and 10th percentile respectively of available record

Lake level at the downstream model boundary

3 different flow conditions (H, M, L)

H, M, L based on 90th percentile, Mean, and 10th percentile respectively of available record


Figure 7.1: RMA2-SED2D Model Domain, St. Joseph River

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USACE – Detroit District 132 St. Joseph River Great Lakes Hydraulics and Hydrology Office Sediment Transport Modeling Study

7.3 Model Input Data

Analysis of available flow data at Niles, in the Paw Paw and at the mouth of the harbor, where the records are coincident in time, is shown in Figure 7.6. This shows a close correlation between discharge in the two rivers and at the harbor mouth. Flow at the mouth is larger than the sum of the two river flows, reflecting input from the watershed between Niles and the mouth. Interpolation between flow at the mouth and flow at the upstream boundary of the model in the St. Joseph River yielded a relationship between flow at Niles and at the model boundary (Figure 7.7). This was then used to derive the 10 different flow conditions on which the run scenarios were based. Once the hydrodynamic solution has been created by running RMA2, sediment transport is computed using SED2D. SED2D requires an initial sediment concentration and, sediment input at the upstream boundaries of the model. These were calculated from a sediment rating curve established for Niles and nearby TSS and SSC data (Figure 7.8). SED2D was then run for each of the 90 flow/lake level scenarios examined by RMA2, and for each of the 3 bathymetric configurations. Additional analysis of the river discharge and mean annual sediment load data produced a distribution of the amount of sediment transported by river flows of different magnitude (Figure 7.9). This shows that most sediment is transported in flows ranging from 3,500-4,900 ft3/s (100-140 m3/s). These flows have return periods in the range of 0.5-1.0 years. However, higher magnitude events than the annual flood are the only times at which sand can be transported through the harbor and into the littoral zone (see below). Further analysis of the long-term flow record at Niles (Figure 7.10) shows that between 1950 and 1980, there were no floods with a return period of great than 5 years, so little sand would have been supplied to the littoral system from the harbor.

7.4 Model Results

Figures 7.11a-7.11e show predicted velocities and fine sand concentrations for different river flows in the harbor. A change in color from red/yellow to blue (no sand transport) indicates that deposition is occurring. Under low flows (Figure 7.11a), no sand is reaching the inner harbor from the St. Joseph River, and any sand in the Paw Paw River is being deposited upstream from the inner harbor. Under mean flow conditions (these occur most of the time and account for most of the sediment transport through or deposited in the system), deposition is still upstream from the inner harbor, and no sand reaches the harbor or lake. This is primarily due to the wide, deep, low gradient channel upstream from the harbor acting as a very efficient sediment trap under these conditions. It is only once flow is above the 1-year return period level that sand is transported into the inner harbor (Figure 7.11c), and even at this stage, the amount deposited in the inner harbor is small compared to that deposited in the main channel upstream. Once a flow approaching a 2- to 5-year return period occurs, sand is moved through the inner harbor


and deposited in the outer harbor (Figure 7.11d). It is only during flows with a 2- to 5-year return period that sand transported by the river reaches the harbor entrance (Figure 7.11e). Only rarely (during an event with a greater than 5-year return period) is sand transported out into the littoral zone. It should be noted that an event of this magnitude was not observed between 1950 and 1980. The pattern of deposition and transport outlined above was also observed when the model was run for the scenario with the harbor dredged to 20 feet (Figure 7.12) and for the 1907 bathymetry (Figure 7.13). This suggests that the same patterns of transport and deposition occur independently of bathymetric variation (i.e. dredging activity and natural channel morphological change). However, dredging activity will increase trapping in the inner and outer harbor, even though the majority of sediment will be trapped upstream. Output from SED2D was then used to produce a set of look-up tables of sediment load for different flow and lake level scenarios. Daily sediment load from 1930 to present was derived by cross-referencing the look-up tables with the time series of river flows and lake level, thus giving a long-term prediction of sediment transport through the harbor. Table 7.2 shows a summary of predicted quantities of sediment entering and leaving the inner harbor. For the 2002 bathymetry, over the long term, the inner harbor traps approximately 50% of the sediment that enters, and 50% is transported to the outer harbor and lake. However, during the period from January 1988 to December 1997, the inner harbor trapped 67% of the entering sediment. This likely reflects an increased occurrence of flood events with a 1- to 3-year return period during this time. This would cause increased deposition in the inner harbor, which would correspond to a condition between that shown in Figure 7.11c and in Figure 7.11d. The trapping efficiency for the scenario with a dredged channel is similar to the 2002 reference condition, at approximately 50% over the long term. For the 1907 scenario, trapping efficiency in the inner harbor is lower, at approximately 45%. This reflects the shallower conditions in the inner harbor at this time, so more sediment was moved through the inner harbor during lower magnitude events.

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Table 7.2: Harbor Sediment Budget

2002 bathymetry - no dredging (present condition)

Time Period Duration (Years)

% Leaving Inner Harbor

% Deposited in Inner Harbor

Oct 1930- Sept 2003 73 45% 55% Jan 1980 - Dec 2000 21 48% 52% Jan 1978 - Dec 1997 20 48% 52% Jan 1988 - Dec 1997 10 33% 67%

2002 bathymetry - inner harbor dredged to 20 feet





1907 bathymetry





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8.0 CONCLUSIONS

Land use, land use change, and the presence of dams are key factors in sediment yield and sediment delivery in this watershed. Cultivated and grazed land has been shown to be the greatest non-point source of sediment, while development of agricultural land has caused an increase in the flashiness of river flow in the upper watershed. However, the influence of dams on flow characteristics in the lower watershed had led to decreased flashiness further downstream. Future urban and suburban development in the lower watershed may increase sediment yield (especially from construction sites) and sediment delivery to the lower river. This may combine with greater riverbed and bank erosion from a flashier river regime to increase sediment supply to the harbor area, potentially increasing harbor sedimentation and therefore increasing dredging requirements. This situation is compounded in this system as the harbor is a very efficient sediment trap, and RMA2-SED2D model results suggest that sandy sediment is only flushed through the harbor during higher river flows. These factors serve to stress the importance of appropriate choices of BMPs in this watershed, and highlights the utility of using a SWAT-based modeling approach for evaluating their implementation.

Comparison of watershed baseline conditions (such as drainage area; effective precipitation, etc.) with empirical relationships established by other studies gave estimates of sediment yield of around 200-300 t/km2/yr. Sediment delivery to the watershed outlet estimated from empirical relationships would be around 110,000 t/yr, although this would not include the trapping influence of dams in the watershed, so it is an over-estimate compared to the SWAT model output, harbor dredging records and available flow and sediment transport data. The values generated from empirical relationships are very rough estimates, but they could be reasonable when treated as a first approximation if the influence of dams could be taken into account. However, the large drainage area of the St. Joseph Watershed and the presence of a large number of dams mean that existing empirical relationships cannot be relied on to provide an accurate estimate of sediment delivery in the watershed.

8.1 SWAT Model Results

Prior to European settlement, the watershed was heavily forested with meadows, lakes and wetlands. During this period there would have been very little sediment delivered to the river mouth. Land cover conditions in 1830 were estimated by a review of the notes of the General Land Office section surveyors (Dickmann and Leefers, 2003). The SWAT model output suggests that delivery of sediment to the mouth of the river has declined during the twentieth century as a result of land use change, and also that dam construction throughout the watershed has led to a drastic reduction of sediment delivered to the river mouth.


The predictions of the SWAT evaluation of historic sediment delivery suggest that prior to development, sediment yield was around 72,000 cy/yr, and delivery to the harbor was around 28,000 cy/yr. By 1992, sediment yield was 884,000 cy/yr, reflecting the influence of agricultural land development, and delivery to the harbor was 57,000 cy/yr. The sediment delivery ratio in 1992 is much lower than the pre-development case, reflecting the presence of dams in the watershed.

The estimated pre-development sediment delivery value of 28,000 cy/yr suggests that sediment transport in the St Joseph Watershed was much lower than modern values. Very little sediment was delivered to the harbor by the Paw Paw River prior to development. The low sediment loads are corroborated by Lt. Berrien’s observations in 1835 that very little sediment was delivered to the river mouth, even under spring flood conditions.

The next major human impact on river sand supplies to the river mouth from the watershed was the large scale logging activities through the latter half of the 1800’s. With the removal of large areas of tree cover, runoff would have reached the tributaries and St. Joseph River much more quickly increasing the intensity of flood flows. Therefore, this elimination of large areas of tree cover would have resulted in increased riverbank and bed erosion and an associated significant increase in sediment eroded from the watershed. However, in 1850 the first major dam was constructed at South Bend, and since then, dam construction has caused most, if not all, of the sand generated by the watershed to be intercepted and trapped before it reaches the harbor mouth.

There are 190 dams in the St. Joseph River Watershed (Michigan Department of Natural Resources, 1999). Since 1850, 65 major dams have been constructed in the St. Joseph Watershed. In 1850 the first major dam was constructed at South Bend and this would have intercepted most, if not all, of the sand generated from the part of the watershed located upstream of the dam (76% of the total watershed area). These large dams are efficient sediment traps because the sediment is not only trapped by the physical structure of the dam, but settles out in the slow moving water impounded for distances reaching several miles upstream from the dam. For example, the Twin Branch Dam impounds over 9 miles of main river, and has velocities that rarely exceed 1.5 ft/s. River flow data from 1930 was compared with a sediment transport capacity curve, from which an average annual sediment transport capacity in the Twin Branch Reservoir for particles in excess of 0.25 mm diameter of 22 tons per year was determined. This means that any sediment (i.e. almost all of it) in excess of this amount will be trapped in the reservoir behind Twin Branch Dam.

In addition to using standard empirical relationships to examine trapping efficiency, the SWAT model was used to evaluate the effect of dams on sediment movement through the watershed and sediment delivery to the harbor mouth. These runs were undertaken for the 1992 land cover data, as it is the most recent complete dataset. The presence of dams in the watershed reduces total sediment supply to the inner harbor from 283,000 cy/yr to 57,000 cy/yr: a reduction of 226,000 cy/yr, or 80%, between the two scenarios. Sediment


supply from the Paw Paw River remains at approximately 15,000 cy/yr due to the negligible influence of dams on this tributary.

The estimate of reservoir sedimentation compares well with empirical estimates from other sources. Chanson (1999) provides reservoir sedimentation rates in the continental US with a mean value of 10,310 cy/mi2/yr. With the surface area of BASINS dams in the watershed being 15.94 square miles, multiplication of these values gives an empirical estimate of reservoir sedimentation of 165,000 cy/yr. This value compares well to the 226,000 cy/yr predicted by the SWAT model.

SWAT is a very useful tool for long-term, large-scale watershed modeling. The input data for SWAT are readily available and the model can be calibrated to measured data with a reasonable amount of effort. The ability of SWAT to simulate nutrients and contaminants makes it a valuable tool for comprehensive watershed management in the future.

8.2 BMP Results

The St. Joseph Watershed SWAT model was used to evaluate the effects of various agricultural BMPs on soil erosion and sediment loads in the Baugo Creek subwatershed. Since this subwatershed (and the St. Joseph Watershed as a whole) is mainly agricultural, urban BMPs that are available for sediment management in more developed areas were not evaluated in this study. Due to the size of the St. Joseph Watershed, the detailed BMP modeling evaluated the Baugo Creek Watershed in Indiana. However, any subwatershed in the St. Joseph Watershed SWAT model could be evaluated using the techniques described herein. The Baugo Creek subwatershed was selected for study because it is known to have several water quality problems, including high erosion rates and sediment loads. It is listed on the EPA 303(d) list for pathogen impairments, and sedimentation has been observed where the creek joins the St. Joseph River. Several scenarios were tested in the Baugo Creek SWAT model. These scenarios demonstrate how different tillage practices lead to differences in sediment delivery. Two conventional tillage scenarios were simulated with the Baugo Creek SWAT model; one representing conventional till on both corn and soybean crops, and the second scenario has soybeans in no-tillage. Conservation tillage refers to any tillage and planting practice that leaves at least 30% residue coverage on the soil surface after planting. The conservation tillage scenario simulated in the Baugo Creek SWAT model involved fall chisel and spring disk on corn that would leave 30-40% residue coverage and no-till on soybeans. The no-till scenario simulated in the SWAT model had both corn and soybeans in the no-till system. The results from the tillage scenario runs (see Section 6.3) demonstrate the dramatic effects of


conservation tillage and no-till systems on reducing sediment yield and sediment delivery from the Baugo Creek subwatershed. Similar scenarios run on other subwatersheds in the system are likely to generate similar results, and could be undertaken using the SWAT model supplied with this report. The results show that switching corn from conventional to conservation tillage can decrease the sediment delivered to the stream by over 50% and converting from conventional to no till can reduce sediment yield by more than 80%. The Baugo Creek Watershed itself had approximately 20,200 acres of corn in production in 2003. On average corn under conventional tillage practices yields an average 3.6 metric tons/acre of sediment per year. By implementing conservation tillage practices, total sediment yield from the Baugo Creek Watershed alone could be reduced from 73,000 metric tons/yr to 36,000 metric tons/yr with conservation tillage or 14,544 metric tons/yr with no tillage.

Crop rotation may reduce of soil loss from agricultural land. A common rotation in use in the Baugo Creek subwatershed is corn-soybean 2-year rotation. By rotating between corn and soybeans, tillage generally only occurs every-other year before the corn is planted. Crop rotation was shown to be an effective BMP in reducing sediment yield on both corn and soy crops in the Baugo Creek subwatershed. Edge-of-field filter strips are another way to reduce the amount of sediment reaching receiving waters. At the time of this study, the SWAT model only contained a very basic routine to simulate filter strips. This was implemented in the Baugo Creek SWAT model to show the amount of sediment reduction obtained with just a 10-meter strip was close to 50%.

8.3 Hydrodynamic and Sediment Transport Modeling of the Harbor

A detailed hydrodynamic model (RMA2) and an associated sediment transport model (SED2D) were set up to evaluate sediment movement through the harbor and into the nearshore zone. The main objectives of this exercise were to provide estimates of sediment movement through the harbor over long time periods and to evaluate the impact of dredging the inner harbor on sediment discharges to the nearshore zone. The RMA2 – SED2D model domain was set up for an area including the lower St. Joseph River up to approximately 3 miles upstream from the inner harbor; the Paw Paw River for approximately 2 miles upstream from the inner harbor; the inner and outer harbor; and the lake for approximately 2.5 miles upstream and downstream from the harbor, and for one mile offshore. Additional analysis of the river discharge and mean annual sediment load data produced a distribution of the amount of sediment transported by river flows of different


magnitude. This showed that most sediment is transported in flows ranging from 3,500-4,900 ft3/s (100-140 m3/s). These flows have return periods in the range of 0.5-1.0 years. Under mean flow conditions, most deposition is upstream from the inner harbor, and no sand reaches the harbor or lake. This is primarily due to the wide, deep, low gradient channel upstream from the harbor acting as a very efficient sediment trap under these conditions. It is only once flow is above the 1-year return period level that sand is transported into the inner harbor, and even at this stage, the amount deposited in the inner harbor is small compared to that deposited in the main channel upstream. Output from SED2D was then used to produce a set of look-up tables of sediment load for different flow and lake level scenarios. Daily sediment load from 1930 to present was derived by cross-referencing the look-up tables with the time series of river flows and lake level, thus giving a long-term prediction of sediment transport through the harbor.


9.0 References/Data Used

Alberta Transportation. 2003. Design Guidelines for Erosion and Sediment Control for Highways. Appendix B. Supporting information for RUSLE. Arnold, J.G. 1992. Spatial Scale Variability in Model Development and Parameterization. Ph.D. Dissertation, Purdue University, West Lafayette, IN, 183 pp. Arnold, J.G., Allen, P.M., and Bernhardt, G.T. 1993. A Comprehensive Surface-Groundwater Flow Model. Journal of Hydrology Vol. 142: 47-69. Arnold, J.G., Williams, J.R., Griggs, R.H., and Sammons, N. B. 1990. SWRRB - A Basin Scale Simulation Model for Soil and Water Resources Management. Texas A & M Press. Bagnold, R.A. 1977. Bed Load Transport by Natural Rivers. Water Resources Research Vol. 13: 303-12. Baird, 2004. Response to Summary Judgment Motion; Banks versus USA. Baker, D. B., Richards, R. P., Loftus, T. T., and Kramer, J. W. 2004. A New Flashiness Index: Characteristics and Applications to Midwestern Rivers and Streams. Journal of the American Water Resources Association Vol. 40(2):503-522. Brown, M.T. et. al. 1987. Buffer Zones for Water Wetlands, and Wildlife: A Final Report on the Evaluation of the Applicability of Upland Buffers for the wetlands of the Wekiva Basin. Prepared for the St. Johns River Water Management District by Center for Wetlands, University of Florida, Gainesville, FL. Chanson, H. 1999. The Hydraulics of Open Channel Flow: An Introduction. Butterworth-Heinemann, Oxford. 495 pp. Cotter, A.S., et al. 2003. Water quality model output uncertainty as affected by spatial resolution of input data. J. of American Water Resources Association 39(4):977-986. De Graves, A. 2004. St. Joseph River Draft Watershed Management Plan. Friends of the St. Joe River Association, Athens, Michigan. Deardorff, J.W. 1977. A Parameterization of Ground Surface Moisture Content for Use in Atmospheric Prediction Models. J. Appl., Meteor. Vol 16: 1182-1185. DeGraves, A. 2005. St. Joseph River Watershed Management Plan Draft. Friends of St. Joe River Association. Dickmann, D.L. and Leefers, L.A. 2003. The Forest of Michigan. The University of Michigan Press, Ann Arbor, Michigan.


Di Luzio, M., Srinivasan, R., Arnold, J.G. 2004. A GIS-Coupled Hydrological Model System for the Watershed Assessment of Agricultural Nonpoint and Point Sources of Pollution. Transactions in GIS Vol. 8(1): 113-136. Downer, C.W., and Ogden, F.L. 2002. GSSHA Users Manual, US Army Engineer Research and Development Center. EPA, 2005. BASINS: Better Assessment Science Integrating Point and Nonpoint Sources. http://www.epa.gov/docs/ostwater/BASINS/ EPA, 2005. Digital Elevation Model of the St. Joseph Watershed. http://www.epa.gov/waterscience/ftp/basins/gis_data/huc/04050001/; EPA, 2005. 1978 Land Cover Data for the St. Joseph Watershed. http://www.epa.gov/waterscience/basins/metadata/giras.htm EPA, 2005. STATSGO Soils Data & Dam Data (BASINS). http://www.epa.gov/waterscience/ftp/basins/gis_data/huc/04050001/ Gray, D.M. 1970. Handbook on the Principles of Hydrology. National Research Council of Canada, Water Information Center Inc., Water Research Building, Manhasset Isle, Port Washington, N.Y., pg 11050. He, C., Shi, C., and Agosti, B., 1988. Modeling Non-point Source Pollution Potential of the Dowagiac River Watershed, Michigan. Prepared for Cass County Conservation District, Cassopolis, Michigan. Hong, Y., Adler, R., Hossain, F., and Scott Curtis, S. 2006. Estimate Gridded and Time-variant Runoff Curve Numbers using Satellite Remote Sensing and Geospatial Data. Submitted to Journal of the American Water Resources Association. Jha, M., P.W. Gassman, S. Secchi, R. Gu, and J.G. Arnold. 2004. Effect of watershed subdivision on SWAT flow, sediment, and nutrient predictions. J. of American Water Resources Association 40(3):811-825. Julien, P.Y. 1995. Erosion and Sedimentation, Press Syndicate of the University of Cambridge, New York, NY. Kilinc, M., and Richardson, E.V. 1973. Mechanics of Soil Erosion from Overland Flow Generated by Simulated Rainfall. Hydrology papers No. 63, Colorado State University, Fort Collins, Colorado, 80523.


Kirby, M.J., and Hampton, D.R. 1997. The Hydrology and Hydrogeology of the Dowagiac River Watershed – Southwest Michigan. Department of Geology/Institute for Water Sciences Western Michigan University, a report to Cass County Conservation District. Knighton, D. 1998. Fluvial Forms and Processes. Oxford University Press, New York. 383 pp. Knisel, W.G. 1980. CREAMS: A Field-Scale Model for Chemical, Runoff, and Erosion from Agricultural Management Systems. Conservation Research Report 26, U.S. Department of Agriculture, Washington, D.C. Langbein, W.B., and Schumm, S.A. 1958. Yield of Sediment in Relation to Mean Annual Precipitation. Transactions of the American Geophysical Union Vol. 39: 1076-84. Leonard, R.A., Knisel, W.G., and Still, D.A. 1987. GLEAMS: Groundwater Loading Effects of Agricultural Management Systems. Trans. Amer. Soc. of Agric. Engrs Vol. 30: 1403-1418. Linsley, R.K., Kohler, M.A., and Paulhus, J.L.H. 1982. Hydrology for Engineers, Third Edition, McGraw Hill, New York, NY. Michigan Dept. of Environmental Quality, Surface Water Quality Division. October 1998. Guidebook of Best Management Practices for Michigan Watersheds. Michigan Dept. of Environmental Quality Nonpoint Source Projects website. 2005a. http://www.michigan.gov/deq/0,1607,7-135-3313_3682_3714-101788--,00.html Michigan Dept. of Environmental Quality Nonpoint Source Projects website. 2005b. http://www.deq.state.mi.us/documents/deq-ess-nps-hog-creek-planning.pdf Michigan Department of Natural Resources. 1999. St. Joseph River Assessment. Michigan Department of Natural Resources Fisheries Division, Fisheries Special Report 24, Lansing, Michigan. Michiana Area Council of Governments, 2005. Section 319 website. http://www.macog.com/MACOGHOM/Environmental/Sec31901.htm National Agroforestry Center. Agroforestry Notes: How to Design a Riparian Buffer for Agricultural Land. Rocky Mountain Station, NE: January, 1997. Neitsch, S.L., Arnold, J.G., Kiniry, J.R., Srinivasan, R., Williams, J.R. 2002a. Soil and Water Assessment Tool User’s Manual, Version 2000. Blackland Research Center. Texas Agricultural Experiment Station, Temple, Texas.


Neitsch, S.L., Arnold, J.G., Kiniry, J.R., Williams, J.R. & King, K.W. 2002. Soil and Water Assessment Tool Theoretical Documentation. USDA-Agricultural Research Service, Temple, Texas. http://www.brc.tamus.edu/swat/downloads/doc/swat2000theory.pdf

NOAA, 2005, National Climatic Data Center, Daily Precipitation Data, http://dipper.nws.noaa.gov/hdsb/data/archived/legacy/dlytran.html

NOAA, 2005, National Climatic Data Center, Hourly Precipitation Data, http://dipper.nws.noaa.gov/hdsb/data/archived/legacy/hlytran.html

NOAA, 2004. Meteorological data for the St. Joseph Watershed. http://dipper.nws.noaa.gov/hdsb/data/archived/legacy/dlytran.html NOAA NWS. Date Unknown. 1990 – 1995 Daily Precipitation Records for St. Joseph Watershed rain gages. http://dipper.nws.noaa.gov/hdsb/data/archived/legacy/dlytran.htm. NOAA NWS. Date Unknown. 1990 – 1995 Daily Temperature Records for St. Joseph Watershed rain gages. http://dipper.nws.noaa.gov/hdsb/data/archived/legacy/dlytran.htm. Norton, W.R., King, I.P. and Orlob, G.T. 1973. A Finite Element Model for Lower Granite Reservoir. Walla Walla District, U.S. Army Corps of Engineers, Walla Walla, WA. Richter, B.D., J.V. Baumgartner, J. Powell, and D.P. Braun. 1996. A method for assessing hydrologic alteration within ecosystems. Conservation Biology 10:1163-1174. Santhi, C., J.G. Arnold, J.R. Williams, W.A. Dugas, and L. Hauck. 2001. Validation of the SWAT model on a large river basin with point and nonpoint sources. J. of American Water Resources Association, 37(5):1169-1188. Southwestern Michigan Commission, 1998. Growth and Development Issues in the Dowagiac River Watershed. 63 pp Trimble, S.W. and Crosson, P. 2000. ‘U.S. Soil Erosion Rates - Myth or Reality’, Science 289: 248-250. USACE. 2005. Clinton River Sediment Transport Modeling Study. U.S. Army Corps of Engineers, Great Lakes Hydraulics and Hydrology Office, Detroit District. Contract No. DACW35-01-D-0009/0012. 161pp U.S. Army Corps of Engineers (USACE) New England Division. 1991. Buffer Strips for Riparian Zone Management. US Army Engineer Research and Development Center. Design Recommendations for Riparian Corridors and Vegetated Buffer Strips. Vicksburg, MS: April 2000.


USDA-Agricultural Research Service, Grassland, Soil & Water Research Laboratory. 2005. SWAT website homepage (http://www.brc.tamus.edu/swat/index.html). USDA NRCS, National Cartography & Geospatial Center. Date Unknown. National Elevation Dataset 1-degree Tiles. http://www.lighthouse.nrcs.usda.gov/gateway/gatewayhome.html. USDA-NRCS. 2000. Erosion and Sedimentation on Construction Sites. Urban Technical Note No. 1. USDA. 1992. STATSGO - State Soils Geographic Data Base. Soil Conservation Service, Publication Number 1492, Washington D.C. U.S. Soil Conservation Service. 1986. Urban Hydrology for Small Watersheds. USDA (U.S. Department of Agriculture) Technical Release 55. USEPA. 1998. State Soil Geographic (STATSGO) Database in BASINS. http://www.epa.gov/OST/BASINS. USEPA Office of Water/OST. 1998. 1:250,000 Scale Quadrangles of Landuse/Landcover GIRAS Spatial Data of CONUS in BASINS. http://www.epa.gov/OST/BASINS/. USEPA Office of Water/OST. 1998. National Inventory of Dams in BASINS. http://www.epa.gov/OST/BASINS/. USGS 2005. 1992 National Land Cover Dataset. http://edc.usgs.gov/products/landcover/nlcd.html USGS. 2000. National Land Cover Dataset circa 1992. http://landcover.usgs.gov/natllandcover.asp. USGS, 2005a. Digital Elevation Model & Land Use Data. http://seamless.usgs.gov/ USGS, 2005b. USGS Suspended Sediments Database. http://webserver.cr.usgs.gov/sediment/ USGS & EPA. Date Unknown. National Hydrography Dataset Reach File for the St. Joseph Watershed. http://www.epa.gov/waterscience/ftp/basins/gis_data/huc/04050001/04050001_nhd.exe. USGS, 2004. Cropland by County Since 1850 and Population Since 1790: A Record of Settlement and Agricultural Disturbance to the Land. http://landcover.usgs.gov/cropland/index.asp


USGS. Unknown. 1990 – 1995 Discharge Records for St. Joseph gages. http://waterdata.usgs.gov/nwis/sw. Walling, D.E. 1983. The Sediment Delivery Problem. Journal of Hydrology Vol. 65: 209-37. Walling, D.E., and Kleo, A.H.A. 1979. Sediment Yields of Rivers in Areas of Low Precipitation: a Global View, in The Hydrology of Areas of Low Precipitation, Proceedings of the Canberra Symposium, December 1979. IAHS-AISH Publication 128, 479-93. Williams, J.R., Jones, C.A., and Dyke, P.T. 1984. A Modeling Approach to Determining the Relationship Between Erosion and Soil Productivity. Trans. ASAE Vol. 27:129-144. Vache, K.B., J.M. Eilers, and M.V. Santelmann. 2002. Water quality modeling of alternative agricultural scenarios in the U.S. Corn Belt. J. of American Water Resources Association 38(3):773-787. Van Liew, M.W. and J. Garbrecht. 2003. Hydrologic Simulation of the Little Washita River Experimental Watershed Using SWAT. Journal of American Water Resources Association 39(2):413-426. Virginia Riparian Forest Buffer Panel. Riparian Buffer: Implementation Plan. VA: July, 1998. Wesley, K.J, and Duffy, J.E., 1999. St. Joseph River Assessment. Prepared for the State of Michigan Department of Natural Resources, Fisheries Division. Fisheries special report #24. Ann Arbor, Michigan. pp215. Yang, C.T. 1973. Incipient Motion and Sediment Transport. Journal of Hydraulic Division. ASCE, 99 No. HY10:1679-1704.

7.0 detailed instream sediment modeling...sed2d is a sediment transport numericalmodel developed by...

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