Phase 1 Report for Lower Mississippi River Basin Regional Sediment

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P:\23\62\880\Final Report\Phase I Report.doc i Lower Mississippi River Basin Regional Sediment Data Evaluation Project

Table of Contents Executive Summary...... EX-1 Background ...... EX-1 Phase I Project Goals and Purpose ...... EX-4 Phase I Conclusions and Recommendations ...... EX-4 Recommended Future Stream Monitoring at Basin Scale ...... EX-9 Task1–CompilationofExistingDataandBackgroundInformation...... 1-1 Compilation of Available Monitoring Data and Background Information ...... 1-1 Stream Sediment, Flow, Turbidity and Sediment-Related Variables ...... 1-1 Stream Biological Data ...... 1-2 Watershed Basin and Physical Stream Characteristics ...... 1-1 Assessment of Monitoring Methodology for Compiled Data ...... 1-3 Task2–ReviewandAnalyzetheExistingMonitoringDataandBackgroundInformation...... 2-1 Characterize the Streams in the Basin ...... 2-2 Extent of Relevant Data in the Basin and Integration of Sediment, Physical, and Biological Variables for Similar Streams ...... 2-6 Dimensionless Sediment Transport Curves ...... 2-7 Flow-Weighted Mean Concentrations by Season...... 2-13 Relationship Between Stream Embeddedness, Particle Size Data and Aquatic Habitat Quality . 2-16 Relationships and Sediment “Translators” for Sediment-Related Variables ...... 2-18 Relationships Between Sediment-Related Variables and Watershed Characteristics ...... 2-26 Relationship Between Bio-Indicators and Sediment Data ...... 2-29 Assess Groundwater Influences Related to Stream Sediment Data...... 2-32 Assess Citizen Stream Monitoring Program (CSMP) Data Set...... 2-33 Task3–ProposeAlternativeExpressionsoftheSedimentVariables...... 3-1 Types of Indicators to be Considered ...... 3-1 Alternative Methods to Address Variability ...... 3-9 Temporal Averaging Considerations ...... 3-9 Stream Classification ...... 3-12 Recommendations for Monitoring...... 3-14 Task6–ProposeAdditionalMonitoringDataCollectionattheBasinScale...... 4-1 Water Quality Monitoring in the Lower Mississippi River Basin...... 4-1 Sediment-Related Water Quality Variables ...... 4-4 Other Pertinent Water Quality Parameters...... 4-6 Physical and Biological Stream Variables ...... 4-6 Physical Classification of Streams...... 4-7 Ecological Use Classification of Streams...... 4-12 “Minimally Impacted-” or “Best Attainable-”Reference Stream Reaches...... 4-18 Recommended Basin-Wide Monitoring Program...... 4-22 Scope...... 4-22 Costs and Cost-Benefit Implications ...... 4-26 References...... REF-1

P:\23\62\880\Final Report\Phase I Report.doc ii List of Tables

Table EX-1 Summary of the LMR Watershed Characteristics...... EX-2 Table 1-1 Summary of Monitoring Sites by Lower Mississippi River Basin Watershed ...... 1 Table 1-2 Summary of Available Data for USGS Monitoring Sites in the Lower Mississippi River Basin Watershed ...... 3 Table 2-1 Summary of the LMR Watershed Characteristics...... 2 Table 2-2 Estimated Bankfull Discharge Rates from Flow Frequency Analysis ...... 9 Table 2-3 Results of LTRMP Total Suspended Solids Monitoring for Period of Record in Lower Mississippi River Basin...... 15 Table 2-4 Relationship Between Stream Embeddedness, Particle Size Data and Aquatic Habitat Quality ...... 17 Table 3-1 Results of LTRMP Total Suspended Solids Monitoring for Period of Record in Lower Mississippi River Basin...... 10 Table 4-1 Summary of Available Monitoring Data for Sediment-Related Variables/Lower Mississippi Basin Monitoring Sites by Monitoring Program/Agency ...... 2 Table 4-2 Summary of Monitored Sites within the Lower Mississippi River Basin, by Major Watershed (1967-present)...... 3 Table 4-3 Summary of Criteria for Physical Classification of Streams (from Rosgen, 1996) ....10 Table 4-4 Management Interpretations of various stream types (from Rosgen, 1996)...... 13 Table 4-5 Variables from stream surveys used to classify Minnesota rivers and streams ...... 14 Table 4-6 Minnesota river and stream classes with associated fish communities ...... 15 Table 4-7 Hilsenhoff Biotic Index (HBI) values for stream monitoring sites within the Lower Mississippi River Basin that rated either “Excellent” or “Very Good,” plus highest HBI scores reported for sites within other major watersheds that had ratings of “Good,” or lower...... 19 Table 4-8 Distribution of Agroecoregion Types within Major Watersheds of the Lower Mississippi River Basin...... 24 Table 4-9 Ongoing and Recommended Monitoring in the Lower Mississippi River Basin to Support Sediment TMDLs...... 27 Table 4-10 Allocation of Stream Monitoring Sites amongst Major Watersheds within the Lower Mississippi River Basin based on Aggregate Stream Mileage and Catchment Areas, according to Stream Order...... 30

P:\23\62\880\Final Report\Phase I Report.doc iii List of Figures Figure EX-1 Lower Mississippi River Basin Stream Orders...... EX-14 Figure 2-1 Lower Mississippi River basin watershed boundaries and geomorphology classifications...... 5 Figure 2-2 Example Plot of USGS Suspended Sediment versus Discharge...... 8 Figure 2-3 Dimensionless Suspended Sediment Transport Curve for Cedar River ...... 9 Figure 2-4 Dimensionless Suspended Sediment Transport Curve for Garvin Brook...... 10 Figure 2-5 North Fork Whitewater R. Dimensionless Suspended Sediment Transport Curve.....10 Figure 2-6 Root River Dimensionless Suspended Sediment Transport Curve ...... 11 Figure 2-7 South Fork Root R. Dimensionless Suspended Sediment Transport Curve ...... 11 Figure 2-8 Whitewater River Dimensionless Suspended Sediment Transport Curve...... 12 Figure 2-9 Superimposed Suspended Sediment Transport Curves for All USGS Sites...... 13 Figure 2-10 Scatterplot Matrix of Sediment-Related Variables ...... 20 Figure 2-11 Box Plot of Turbidity Readings by Major Watershed and Season...... 22 Figure 2-12 Box Plot of Turbidity Readings by Stream Class and Season ...... 23 Figure 2-13 Box Plot of Turbidity Readings versus Percentage of Fines in Stream Bed...... 24 Figure 2-14 Box Plot of Turbidity Readings from Impaired and Non-Listed Watersheds...... 25 Figure 2-15 Box Plot of Transparency Tube Readings from Impaired and Non-Listed Watersheds25 Figure 2-16 Lower Mississippi River Basin Agroecoregions and Minor Watersheds...... 27 Figure 2-17 Box Plot of Median Suspended Sediment Concentrations versus Watershed Area....27 Figure 2-18 Box Plot of Median Turbidity Readings versus Watershed Area ...... 28 Figure 2-19 Box Plot of Median Turbidity Readings for Each Level III Ecoregion...... 28 Figure 2-20 Scatterplot Matrix of Median Turbidity Readings and Biological Indices...... 29 Figure 2-21 Box Plot of HBI Ratings for Impaired Watersheds and Watersheds Not Listed for Turbidity ...... 30 Figure 2-22 Box Plot of ICI Ratings for Impaired Watersheds and Watersheds Not Listed for Turbidity ...... 30 Figure 2-23 Box Plot of ICI Ratings for Impaired Watersheds and Watersheds Not Listed for Turbidity ...... 31 Figure 2-24 Map of Karst Features and Minor Watershed Boundaries...... 33 Figure 2-25 Scatterplot Matrix of Sediment-Related and CSMP Variables from Overall Dataset.34 Figure 2-26 Box Plot of Turbidity versus Stream Appearance...... 35 Figure 2-27 Box Plot of Turbidity versus Recreational Suitability ...... 35 Figure 3-1 Scatterplot Matrix of Sediment-Related Variables ...... 4 Figure 3-2 Example Plot of USGS Suspended Sediment versus Discharge...... 8 Figure 3-3 Dimensionless Suspended Sediment Transport Curve for Cedar River ...... 8

P:\23\62\880\Final Report\Phase I Report.doc iv Figure 3-4 Box Plot of Dimensionless Suspended Sediment versus USGS Gage Site by Season12 Figure 3-5 Box Plot of Turbidity Readings by Stream Class and Season ...... 13 Figure 3-6 Box Plot of Median Turbidity Readings for Each Level III Ecoregion...... 14 Figure 4-1 Equal-width-increment method for collection of water samples (modified from Edwards and Glysson, 1998) ...... 5 Figure 4-2 Channel Parameters Defined (from Rosgen, 1996)...... 8 Figure 4-3 Delineation of Major Stream Types showing Profile, Cross-Sectional and Plan View Morphology (from Rosgen, 1996)...... 9 Figure 4-4 Location of preliminarily recommended reference sites, based on HBI scores...... 20 Figure 4-5 Agroecoregions within the Lower Mississippi River Basin area of Minnesota...... 23 Figure 4-6 Lower Mississippi River Basin Stream Orders...... 29

P:\23\62\880\Final Report\Phase I Report.doc v Executive Summary

Background The Lower Mississippi River (LMR) basin, including the Cedar River basin, is located in all or part of 17 counties and has 12 major watersheds covering about 4,650,100 acres. Bluffs, springs, caves and numerous trout streams exist in the eastern portion of the basin, where steep topography and erosive soils increase the potential for pollutant runoff and sedimentation of streams. Sinkholes and disappearing streams highlight the close connection between surface water and groundwater in this part of the basin. Average annual runoff ranges from 5.5 to about 8 inches, increasing from west to east. The abundant moisture greatly benefits crops but aggravates problems associated with soil erosion and sediment transport to surface water.

Two distinct areas of wind-deposited silt loam (loess) soils dominate the southeastern Minnesota. The first is the karst area on the eastern side and the second area is found on gently sloping to flatter fields located on the western edge of the basin. Loess soils are susceptible to erosion, particularly those on rolling landscapes with steep or long slopes. The soil has good water and nutrient-holding capacity but has much poorer internal drainage due to the fine-textured subsoil.

On the western side of the basin, lands are primarily cultivated, while the eastern landscapes are dominated by steep forested hill slopes and agricultural land. Major agricultural crops include corn, soybeans, and hay. About two-thirds of the land in the basin is under cultivation, about 13 percent is forested, and about 17 percent of the land use is open or pasture lands. Animal production includes dairy, beef cattle, hogs, sheep and lambs. Six of the top 10 beef cattle counties of the state are located in the basin.

The extent of pre-settlement wetlands in LMR Basin counties has been estimated to be approximately 880,000 acres. Good estimates of remaining wetland acreage are not readily available, but considerably less than half of the original wetlands are believed to exist today (Anderson and Craig, 1984). The vast majority of the original wetland acreage is located on the western side of the basin in Dodge, Freeborn, Mower, Steele, and Waseca counties. Seventy-nine percent of the landscape in southeastern Minnesota is classified as well-drained. Of the remaining lands that are poorly drained, much has been tiled for agricultural production.

The basin’s human population grew 11.9 percent between 1990 and 1998, from 539,787 to 603,997, according to Minnesota Planning Agency. Most of the growth has been in Dakota (23.3 percent),

P:\23\62\880\Final Report\Phase I Report.doc EX-1 Dodge (10 percent), Olmsted (11.8 percent) and Rice (10 percent) counties. Major population centers include the southern Metropolitan area of Dakota County in addition to Austin, Albert Lea, Faribault, Owatonna, Rochester, Red Wing and Winona. These and other urban areas are experiencing rapid population growth and commercial development.

In the southwestern portion of the LMR basin, Mississippi tributaries emerge as small streams out of a prairie landscape once rich in wetlands. The headwaters areas are now extensively drained to support productive agriculture. Further to the north of the basin, in the western Cannon River Watershed, remnants of the Big Woods hardwood forest intermingle with mixed crop and livestock farming in a rolling terrain interspersed with lakes and wetlands. Smaller streams in the eastern karst region of the basin often originate from groundwater discharge points such as springs or seeps. Table EX-1 describes the major river systems, their tributaries, and watersheds, located in the LMR basin.

Table EX-1 Summary of the LMR Watershed Characteristics

Drainage Area Number of Listed (square miles at mouth- Reaches for Turbidity – Stream/River & Watershed unless noted otherwise) 2004 List Root River 1660 3 Zumbro River 1414 1 Cannon River 1340 (at Welch) 1 Straight River 442 (at Faribault) 3 Cedar River 399 (at Austin) 2 Whitewater River 321 6 Vermillion River 195 (at Hastings) 1 Shell Rock River 190 (near Gordonsville) 1 Garvin Brook 46 1 Gilmore Creek 9 -

A summary of the number of reaches listed in each watershed based on the draft 2004 list is given in Table EX-1. The river reaches for the 2004 Impaired Waters List include nine (9) new turbidity impairments, seven of which are in the Cannon River watershed and two are in the Root River watershed. A broad overview of turbidity values shows that the water quality standard is exceeded for about 23% of samples taken in the Zumbro, from 47 to 75 percent of samples for Garvin Brook, and between 20 - 40% of samples in the Mississippi River downstream of the Root River confluence. The State of Minnesota currently uses turbidity as a numerical water quality standard under Minn. Rules

P:\23\62\880\Final Report\Phase I Report.doc EX-2 Chapter 7050. The numerical water quality standard for turbidity is 10 Nephelometric Turbidity Units (NTU) for Class 2A waters (cold water fishery, all recreation) and 25 NTU for cool and warm water fishery, all recreation.

There are currently no ambient stream water quality standards associated with water quality variables such as total suspended solids or suspended sediment concentration. A trend analysis was conducted by the Minnesota Pollution Control Agency (MPCA, Christopherson, 2001) for selected stream sites, which were sampled by the MPCA for Total Suspended Solids (TSS) over a period of several decades. The results for the major tributaries showed a decreasing trend for three and no trend for seven. Also, no streams exhibited an increasing trend.

The character of rivers and streams in the LMR Basin changes considerably along the main direction of flow, west to east. Lower portions of these rivers and tributaries are fed by ground water, making many streams sufficiently cold to support trout populations. Stream conditions may include a combination of swiftly moving current, streambeds formed of boulders, cobble and gravel, and stable flows of cool, oxygen-rich waters. Pools and undercut banks provide refuge during sunny days and low waters, while riffles provide a continuing source of food. Snowmelt and heavy rainfall can induce flash floods in this topography. As the rivers near the Mississippi Valley, gradients decline and stream velocities decrease, resulting in a loss of energy and deposition of a portion of their sediment load in stream channels and alluvial floodplains. In recent decades, however, dikes along the lower reaches of the Root and Zumbro have disconnected the rivers from their alluvial floodplains, making farming of the rich soil possible, at the cost of increased sedimentation of the Mississippi and the degrading of a rich ecosystem.

The problem of stream sediment pollution in the basin is multifaceted. While agricultural land uses dominate major expanses of the basin, the percentage of cultivated lands responsible for much of the soil erosion is rather small (USDA, 1997 and 2002). Of those cultivated lands, the vast majority are in the corn-soybean rotation, with soybeans becoming the dominant economic crop of necessity for many landowners. Sediment delivery from upland sources varies with soil types, slopes, and management factors. In addition to sediment pollution originating from agricultural lands, channels downstream from urbanizing or suburbanizing watersheds face increased flow and sediment loads, often causing stream channel instability, an effect of which is excessive streambank erosion. While some watershed scale monitoring programs have been initiated in the last 15 years, a comprehensive and sustainable stream monitoring and evaluation system does not currently exist. Stream pollution due to sediment inputs and altered hydrology results in degraded stream channels, a loss of

P:\23\62\880\Final Report\Phase I Report.doc EX-3 recreational opportunities, and decreased economic activity which result from activities such as fishing, canoeing, and tubing.

Phase I Project Goals and Purpose Given this set of complex circumstances, our problem is to define the best available and most feasible methods for the development of sediment-based TMDLs in the basin. The basic underlying premise of this effort is to maximize the use of existing data sets, learning from what we have already done, to the greatest extent possible.

The overall approach of this project is to fully utilize existing stream, landuse and land management data to better understand the issue of sediment pollution in streams. This project is not meant to cover the legal requirements for a TMDL for the 19 turbidity impaired reaches in the basin that are currently on the TMDL list. The project goals for this phase of the work include:

• Compile, organize, assess, and integrate relevant existing data sets on soil erosion, sediment transport, and surface water-sediment interactions.

• Propose alternative expressions of sediment variables that can be of assistance to both the TMDL development and watershed management processes.

• Define limitations and gaps in the data and methods that may significantly affect the stream improvement process. Propose a series of actions that can be pursued over time to “fill in” the identified gaps with newly collected data, or with currently existing data analyzed in a specific manner.

Phase I Conclusions and Recommendations The following data were compiled for this study:

• Stream sediment, flow, turbidity and sediment-related variables

• Stream biological data

• Watershed landscape and physical stream characteristics

All of the compiled data represented approximately 41,000 monitoring events for the period of record from all of the monitoring locations in the basin. Most of the larger watersheds have a significant number of monitoring locations. The CSMP sites are concentrated in the Cannon River, Mississippi River-Winona, Root River and Zumbro River major watersheds. There are approximately 1,000 monitoring locations throughout the basin.

P:\23\62\880\Final Report\Phase I Report.doc EX-4 Dimensionless sediment transport curves have been developed for six USGS gage sites that can be plotted together and superimposed to compare the rates of suspended sediment transport per unit change in discharge. Comparing the 95 percent confidence intervals developed for the slope of each of the curves results in the following conclusions:

• The rate of suspended sediment transport per unit discharge is significantly less for the Cedar River than for the South Fork Root, North Fork Whitewater and Root Rivers

• The rate of suspended sediment transport per unit discharge is significantly less for Garvin Brook than for the South Fork Root and North Fork Whitewater Rivers

• The rate of suspended sediment transport per unit discharge for the Whitewater River near Beaver is not statistically different than any of the other stations

Troendle et al. (2002) did not show significant differences in dimensionless sediment transport were attributable to Rosgen stream type, but they demonstrated that reference sediment transport functions for suspended sediment and bedload appear to function well for stable streams and indicate that departure can be demonstrated for unstable streams. As a result, Pfankuch (1975) stability ratings and Rosgen stream classifications would need to be developed for each of the six USGS gage sites to determine whether one of more of the sites represents a “reference” condition that can be used to assess the relative transport and stability of the remaining USGS sites.

The suspended sediment concentrations were further evaluated, on a seasonal basis, for the same six USGS sites that had been used to develop dimensionless sediment transport curves. The results show how the suspended sediment concentrations typically exceed the concentration expected for bankfull flows (1.0 in the dimensionless scale) in the early spring at Garvin Brook near Minnesota City (#05378235) and they are significantly higher than the other seasonal concentrations for all six sites. The concentrations at Garvin Brook drop significantly as you proceed from early spring to late spring and summer. The fall and winter concentrations are both significantly lower than the other seasons. The early spring concentrations in the Cedar River at Austin (#05457000) are also quite high relative to the expected bankfull flow concentration and are significantly higher than the other seasons. The late spring concentrations in the Whitewater River near Beaver (#05376800) are significantly higher than the early spring concentrations and the summer concentrations are also high. The other stations do not show much in the way of significant seasonal differences, but many of the observed concentrations are considerably lower than the concentration expected under bankfull flow conditions. Temporal variation should be considered in application of water quality standards, depending on the state of each of the watershed areas depicted. These watersheds should be further

P:\23\62\880\Final Report\Phase I Report.doc EX-5 assessed for stability and their state relative to “reference” conditions before it can be determined that temporal variation should be important.

The monthly LTRMP flow and TSS loading data was manipulated to determine the long-term average flow-weighted mean concentrations (FWMCs), by season. The results indicate that:

• The FWMCs are consistently lower in the winter and fall than the other three seasons for all of the monitoring locations

• The early spring, late spring and summer FWMCs are significantly higher for the southern watershed locations (Whitewater, Root and Zumbro Rivers) in comparison to the northern watersheds, with the Cannon River concentrations being slightly higher than the Vermillion River concentrations

• The early spring FWMCs for the Zumbro, Whitewater and Root River confluences with the Mississippi River are significantly higher than the late spring and summer concentrations, while the remaining watershed monitoring locations experience lower concentrations during early spring in comparison to the late spring and summer months. Comparing the downstream Whitewater and Root River FWMCs with the upstream watershed locations in the late spring and summer indicates that the TSS may be settling out before reaching the corresponding confluence monitoring locations, presumably due to the lower flows experienced during these seasons compared to the snowmelt runoff.

A high degree of correlation between turbidity and total suspended solids for the six rivers with LTRMP monitoring data was confirmed. The relationship between flow percentile, turbidity and TSS, varies by river, although all show a clear relationship of higher turbidity and TSS at higher flows. For the three rivers with the most reliable flow percentile values, the 25 NTU (Class 2B water quality) standard corresponds with roughly the 40th percentile for the Zumbro and Root rivers, and with the 20th percentile for the Cannon River. The Cannon appears to exhibit somewhat lower overall turbidity and TSS concentrations, and the turbidity standard appears to be violated about half as frequently, compared to the Zumbro and Root rivers. Based on hydrograph separation, the TSS and turbidity observations associated with greater than 50% of the flow indicate that surface- runoff processes, in addition to channel or in-stream processes (e.g. streambank erosion), represent important contributions to the observed TSS and turbidity.

Limited paired embeddedness, particle size and aquatic habitat quality data were available for this study. Of the four USGS sites with available data, Garvin Brook near Minnesota City had the lowest

P:\23\62\880\Final Report\Phase I Report.doc EX-6 percentage of fines (84%) and HBI score (3.9), combined with the highest coldwater fish IBI score (92.5). The biological metrics for Garvin Brook indicate that it has significantly better aquatic quality than the other three sites, but the percentage of fines and the particle size distribution data for the bed sediment is not significantly different than the Whitewater River and Stockton Valley Creek. Additional particle size distribution data should be collected for bed sediment to further evaluate the relationship between stream embeddedness and aquatic habitat quality in the basin.

TSS, turbidity and VSS are each significantly correlated with each other and VSS is also significantly correlated with chlorophyll-a. Chlorophyll-a does not significantly influence turbidity readings and TSS concentrations, based on the overall dataset. Regression analyses were done and showed that TSS explained 92% of the variance associated with the turbidity readings. Correlation analyses were also completed for all of the remaining sediment-related variables to test the statistical significance of the relationships using all of the paired water quality data collected in the basin. The results of these analyses indicate the following:

• TSS and turbidity are significantly correlated with several of the residue parameters

• Transparency tube readings are significantly correlated with TSS, turbidity, and VSS

• Turbidity is significantly correlated with the dimensionless suspended sediment concentrations (SSC) (r2 = 0.887). There were no data pairs between SSC and either TSS or transparency tube readings.

• TSS, VSS, turbidity, transparency tube readings and SSC are significantly correlated with instantaneous and average daily flow readings and inversely correlated with alkalinity

• No significant correlations exist between measures of sediment concentration and particle size distribution percentages which is likely due to the differences in how each measure is expressed and may be interpreted that the respective sediment size distributions remain the same with increasing or decreasing SSC

• Turbidity and transparency tube readings are significantly correlated with total organic carbon and transparency is inversely correlated with chlorophyll-a

• Transparency is significantly correlated with stream physical appearance ratings and transparency, TSS and turbidity are significantly correlated with the recreational suitability ratings

Fall and winter turbidity values are significantly lower than the other seasons for some of the major watersheds. In general, the turbidity readings for the Upper Iowa, Cannon, Cedar and Miss. R.-Lake

P:\23\62\880\Final Report\Phase I Report.doc EX-7 Pepin watersheds are less variable and significantly lower than the remaining watersheds. The readings for the Zumbro and Root River watersheds are significantly higher in the early spring and the readings in the Shell Rock River watershed are significantly higher than most of the remaining watersheds in the summer.

Turbidity readings for the coldwater streams were significantly lower than the warmwater streams for each season. For the coldwater streams, the turbidity readings were significantly higher in the early spring compared to the remaining seasons. For the warmwater streams, the summer, early and late spring readings are not significantly different than each other, but are significantly higher than the fall and winter readings.

A comparison of the ecoregion areas listed in the DNR stream survey database and the turbidity readings throughout the basin revealed that the North Central Hardwood Forest ecoregion appears to have significantly lower turbidity readings than the Western Corn Belt Plains ecoregion, which has significantly lower readings than the Driftless Area ecoregion.

Multiple linear regressions were evaluated to predict turbidity readings from watershed characteristics. The results showed that a significant relationship existed with the average watershed slope (r2 = 0.485). None of the other watershed or physical stream characteristics improved the predictive model for this dataset.

HBI scores may be more significantly impacted in the watersheds that are currently listed for turbidity, while the ICI scores are not significantly different when comparing watersheds that are listed for turbidity with those that are not listed. Multiple linear regressions showed that a significant relationship existed for the HBI scores with the average stream depth and the amount of shade (r2 = 0.499). None of the other physical stream characteristics improved the predictive model for this dataset. There were no significant relationships between the physical stream characteristics and the ICI scores or warmwater fish IBI scores. A significant relationship existed between the coldwater fish IBI scores and the average stream width (positive correlation), sinuosity (inversely correlated), and the severity of bank erosion (inversely correlated).

Incorporate the watershed characteristics into the multiple linear regression analyses indicated that a significant relationship existed for the HBI scores and the stream gradient (r2 = 0.359). None of the other physical stream or watershed characteristics improved the predictive model for this dataset. There was a significant relationship between the ICI scores and the watershed water erosion potential (inversely correlated), urban land use percentage (positively correlated), and the landlocked watershed percentage (inversely correlated), which explained 82 percent of the variance. There were

P:\23\62\880\Final Report\Phase I Report.doc EX-8 no significant relationships with the warmwater fish IBI scores. A significant relationship existed between the coldwater fish IBI scores and the stream run percentage (inversely correlated). This variable explained approximately 72 percent of the variance in the coldwater fish IBI scores at the minor watershed scale.

Sediment sampling has not specifically been done as part of springshed mapping (Fillmore County, 2002), but TSS samples collected throughout the South Branch Root River watershed indicated that the areas downstream of the karst features had lower median concentrations and higher maximum concentrations than the remainder of the watershed. The dataset compiled for this study indicates that the median sediment-related variable measurements are consistent with surrounding minor watersheds that are not influenced by karst features.

Currently, there are no recreational water quality standards associated with sediment-related variables. Current recreational water quality standards are only tied to measures of eutrophication. The CSMP data was evaluated to determine how well it corresponds to the other sediment-related variables and evaluate how other variables might be influencing the volunteer’s perceptions of stream appearance and recreational suitability. Slight increases in TSS, VSS and/or turbidity result in significant decreases in transparency tube readigns. There appears to be significant variability in the stream appearance and recreational suitability ratings for the corresponding transparency readings. Turbidity readings were not significantly different for stream appearance and recreational suitability ratings of 2 through 5. The turbidity readings were significantly lower for stream appearance and recreational suitability ratings of 1. Multiple linear regressions indicated that a significant inverse relationship exist between stream appearance and the transparency tube readings (r2 =0.548),aswell as between recreational suitability and the transparency tube readings (r2 = 0.322). The variability associated with each of the CSMP ratings likely is the result of the subjectivity of the volunteers.

Stream class (warmwater or coldwater) and location are also likely to play an important role in determining the best attainable conditions for each stream. As a result, “reference” stream reaches will need to be identified for each stream class in each ecoregion, at a minimum. Consideration should also be given to identifying reference reaches within each agroecoregion, as well.

Recommended Future Stream Monitoring at Basin Scale The damage to aquatic habitats by heavier sediment particles, due to sedimentation and embeddedness, cannot be accounted for by measuring turbidity or total suspended solids (TSS). Pool depth decreases as heavier particles settle out in the stream channel. In addition, the quality of

P:\23\62\880\Final Report\Phase I Report.doc EX-9 aquatic habitat is also dependent, to some degree, on factors such as stream stability, cover and shade.

Total Maximum Daily Loads (TMDLs) are intended to assess sources of pollutants that are causing impairments and allocate reductions from the sources so that a water quality standard can be achieved in the stream. A variety of factors can affect the selection of the appropriate TMDL indicators, including scientific and technical validity as well as practical management decisions (EPA, 1999). Indicators should be logically related to the applicable numeric and narrative water quality standards. Practical considerations include choosing indicators that can be suitably monitored using cost-effective means and selecting indicators that are consistent with data that is already available and for which information concerning reference and natural background conditions can be utilized. Other than turbidity, the following indicators also warrant consideration for the LMR basin:

• Water column indicators o Suspended sediment concentration o Total suspended solids o Transparency tube readings o Volatile suspended solids • Streambed sediment and channel indicators o Streambed particle size distribution indicators o Embeddedness or percentage of fines o Pool/riffle ratios o Width/depth ratios o Sinuosity o Gradient o Entrenchment o Bank stability o Percentage of pools o Shade o Cover • Biological indicators o Benthic invertebrate indices o Fish • Riparian/hillslope indicators

P:\23\62\880\Final Report\Phase I Report.doc EX-10 o Riparian buffer width and vegetation character • Recreational indicators o Stream appearance o Recreational suitability

Karr and Chu (1999) indicate that our monitoring must have a standard against which the conditions at one or more sites of interest can be evaluated. This standard, or reference condition, provides a baseline for comparison. Physical and biological integrity is the product of natural processes at a site in the relative absence of human influence. Programs that measure biological and geophysical conditions in near pristine environments provide information about the proper context in different areas. The value of a biologic index, for example, is that it enables us to detect and measure divergence from biological integrity (Karr and Chu, 1999). Future monitoring should be assessed along several gradients of human disturbance (sediment loading, flow and riparian shade, as examples) for representative regions of the basin. Comprehensive monitoring and data collection will provide a logical way to select reference conditions that are scientifically defensible and indicative of the best-attainable environment.

Previous stream ecoregion statistics were developed by the MPCA (Fandrei etal. 1988), but did not address stream biology. The MPCA conducted bioassessments of streams in the LMR basin during the summer of 2004. Fish IBI data will result from this effort and reference reaches may be identified through this process and by other ongoing work.

The selected “reference” condition for sediment or flow measurements, for example, would need to factor in natural variability and background levels. In the short term, the pollutant pathways associated with sediments need to be reviewed to develop cost-effective measurement and estimation schemes. A monitoring program needs to be developed that will also assess and classify stream reaches for physical and biological integrity at differing scales. To be cost-effective, the monitoring program should allocate resources at different scales, with various levels of intensity and funding. Finally, the results of the monitoring program will need to define the errors associated with the possible use of simpler (and more sustainable) sampling methods, in comparison to the more sophisticated (and more expensive) techniques.

A proposed water quality monitoring plan was developed for watershed streams within the Lower Mississippi River Basin of Minnesota for the next 25 years. It is comprised of four different monitoring programs, including:

P:\23\62\880\Final Report\Phase I Report.doc EX-11 Annual Monitoring Cost per to Occur in Monitoring Program Number of Sites Site Years: "Intensive" level monitoring at agroecoregion boundaries (base flow & storm event basis), including: - Continuous Flow Gaging - Suspended Sediment Concentration 1-5, 10, 15, - Turbidity 25 $50,000 20, and 25 - Suspended Particle Size Distribution - Nutrients (N & P) - Suspended Solids (TSS & VSS) - Benthic Macroinvertebrate Surveys "Volunteer" level monitoring (i.e., Citizens' Stream Monitoring Program, CSMP) at distributed sites, including: Starting with 133 sites and increasing - Stream Stage Measurement $800 1-25 to 200 sites by Year - Turbidity 10 -Precipitation "Intermediate" or "Volunteer +" level monitoring at distributed sites, including: - Continuous Flow Gaging - Turbidity Starting with 3 sites and increasing to 30 $4,000 1-25 - Suspended Particle Size Distribution sites by Year 10 - Nutrients (N & P) - Suspended Solids (TSS & VSS) - Benthic Macroinvertebrate Surveys Fish Surveys, including 1, 5, 9, 13, - Physical Stream Classification 25 $6,500 17, 21, and - Ecological Use Classification 25

A network of 200 monitoring stations is recommended for establishment, and allocation of stations amongst major watersheds that comprise the basin is recommended to be proportional to the aggregate stream mileage of each watershed. Further, distribution of monitoring stations within watersheds is recommended to be stream reach order based, according to reach catchment areas (see Figure EX-1). The preliminary distribution of recommended monitoring stations follows:

P:\23\62\880\Final Report\Phase I Report.doc EX-12 Numbers of Recommended Monitoring Sites per Watershed, by Stream order Watershed Name 1st Order 2nd Order 3rd Order 4th Order 5th Order Total CANNONRIVER 26 763042 CEDARRIVER 13 411019 MISSR&LPEPIN 11 411017 MISSR-LaCrescent 1 10002 MISSR-Reno 2 11004 MISS R-Winona 10 321016 ROOTRIVER 281052247 SHELLROCKRIVER 4 10106 UPPER IOWA RIVER 3 10004 WAPSIPINICAN RIVER 0 00000 WINNEBAGO RIVER 2 00002 ZUMBRORIVER 25 851241 TOTAL 125 40 21 10 4 200

Exact placement of stream monitoring sites is left to the discretion and best professional judgment of MPCA staff who are most familiar with these watersheds.

P:\23\62\880\Final Report\Phase I Report.doc EX-13 I MISS R & L PEPIN

52.5 0 5 10 15

Miles

Major Watersheds MISS R & L PEPIN Project Area Stream Order

CANNON RIVER 1 2 ZUMBRO RIVER 3 4 5 Catchment Stream Order 1 MISS R-Winona 2 MISS R-La Crescent 3 4 5

SHELL ROCK RIVER ROOT RIVER

Figure 4-6 Lower Mississippi River Basin Stream Orders WINNEBAGO RIVER CEDAR RIVER WAPSIPINICAN RIVER UPPER IOWA RIVER UPPER IOWA RIVER MISS R-Reno (Based on 250K DEM) Barr Footer: Date: 12/15/2004 3:33:37 PM File: User: I:\Projects\23\62\880\Gis\Maps\ArcMap\Watersheds_StreamOrder.mxd SAS Task 1 – Compilation of Existing Data and Background Information

The purpose of this section is to discuss the methodology used to compile and organize all existing relevant stream sediment and turbidity data (flows, suspended sediment concentration, total suspended solids, turbidity, particle size, bedload, transparency, substrate types, etc.), biological stream water quality data from existing sources (USGS, MPCA, STORET, MDNR, universities, literature, etc.), and other available sources (agency reports, university projects, citizen and local government projects) that could be readily discovered for the Lower Mississippi River basin. A bibliography is provided to document the literature and data sources reviewed as part of this project. This section is also intended to provide an assessment and interpretation of the various monitoring protocols or methodology that was used for the compiled environmental data.

Compilation of Available Monitoring Data and Background Information This section describes the types of data and background information obtained, the data sources and methodology used to manipulate and compile each type of data for future work tasks. The following data were compiled for this study:

• Stream sediment, flow, turbidity and sediment-related variables • Stream biological data • Watershed landscape and physical stream characteristics

Wherever possible, stream monitoring locations and watershed characteristics were obtained in a GIS format to facilitate mapping of the data for this project.

Before this project was initiated, the MPCA (Thompson, 2003) had compiled a preliminary list of data sources, sediment-related data availability, and periods of record for flow and water quality monitoring for each of the major watersheds in the basin. Using this document as a guide, Barr and the MPCA staff made individual contacts with each of the known sources of data and solicited additional data during the BALMM and Stakeholder Committee meetings held on June 16, 2004. The following sources of data were utilized in the overall compilation of data for this study:

• MPCA Environmental Data Access (EDA) o STORET (Legacy and Modern databases) Lake

P:\23\62\880\Final Report\Phase I Report.doc 1-1 River/Stream • CSMP • Other o Biological • USGS o National Water Information System Web Data o Suspended Sediment Database/Sediment Discharge Measurements • Metropolitan Council Environmental Services (MCES) • Winona State University (WSU) • Long-Term Resource Monitoring Program (LTRMP) • Cannon River Watershed Partnership (CRWP) Water Quality Master Database • CRWP Invertebrates • Dakota SWCD/Vermillion • Dakota SWCD/NCRWMO • Fillmore SWCD/Root River • East Side Lake • Lakeville/Farmington

The data compilation was initiated by obtaining and organizing the data downloaded from the MPCA’s Environmental Data Access (EDA) databases. The Biological, Legacy and Modern STORET data were extracted from the Access data tables and stored in an Excel format. In addition, the MPCA’s WQ Stations GIS coverage was obtained and used as the basis for mapping the station locations. The water quality and biological data from the remaining data sources were combined with the EDA data in Excel and the station locations were inserted in the MPCA’s WQ Stations GIS coverage. All of the compiled data represented slightly more than 41,000 monitoring events for the period of record for all of the monitoring locations in the basin.

Figure 1-1 shows all of the monitoring station locations, for each data source, within the Lower Mississippi River basin. Table 1-1 summarizes the number of monitoring sites in each of the major watersheds in the basin, by data source. There are more than 1,018 monitoring locations throughout the basin. Table 1-1 and Figure 1-1 show that most of the larger watersheds have a significant number of monitoring locations (greater than 90). Table 1-1 shows that the CSMP sites are concentrated in the Cannon River, Mississippi River-Winona, Root River and Zumbro River major watersheds. Data for lake monitoring locations within the mainstem flow of the monitored streams

P:\23\62\880\Final Report\Phase I Report.doc 1-2 Ramsey County 149 Sunfish Lake 494 Hennepin Summary of Monitoring Sites by Major Basin 55 County Washington Number of Sites 149 County 77 Inver Grove Heights 35W Eagan Dakota East Fillmore 35E CRWP CRWP Dakota SWCD/ RIVER/ Major Basin BIOLOGICAL CSMP SWCD/ Side SWCD LAKE LTRMP Lakeville MCES USGS WSU TOTAL Invertebrates WQ NCRWMO STREAM Carver Vermillion Lake /Root Ri ver County

Burnsville CANNON RIVER 11 23 99 40 0 0 0 0 23 1 0 1 139 9 0 359 13 CEDAR RIVER 0 0 0 0 0 08 0 4 0 0 0 105 3 0 120 Apple Valley Rosemount 55 MISS R & L PEPIN 9 0 0 0 6 00 02 5 5 1 54 80 90 Hastings MISS R-La Crescent 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 291 VERMILLION RIVER MISS R-Reno 0 0 0 0 0 00 00 1 0 0 12 20 15 Coates MISS R-Winona 0 0 0 39 0 0 0 0 2 3 0 0 85 14 85 228 Dakota ROOTRIVER 0 00240 00271100 721822165 County SHELL ROCK RIVER 0 0 0 0 0 00 017 0 0 0 13 20 32

Lakeville UPPER IOWA RIVER 0 0 0 0 0 0 0 0 1 0 0 0 5 0 0 6 Vermillion WAPSIPINICAN RIVER 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Sibley 316 Scott Farmington WINNEBAGO RIVER 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 3 County County ZUMBRORIVER 0 00410 00090 00 78141143 Ve rm i TOTAL 20 23 99 144 6 0 8 27 62 11 5 2 564 70 108 1162 llio n Ri 21 ve Hampton 50 r New Trier Miesville

Ch 3 u Red Wing b New Market C Major Watersheds r Trout Brook e 58 Elko e 292 k , P k N i 20 e n e o e r Dams on Rivers/Streams with Kittle Numbers r Cr t C k 19 h ee o VOTH DETENTION NO. 1 k g o B n r r i Frontenac State Park r d Creek a B Bullar Creek n p t Ple Chub S u asa Water Quality Stations c Randolph ntV h o alle r yCre LAKE BYLLESBY T ek ek Cannon Falls Miles re 19 BIOLOGICAL k C ee Cr pring d S 02.5 5 10 15 u M CRWP Invertebrates Goodhue Lonsdale Creek 19 County Wells ek CRWP WQ re Butler Northfield k C Creek Gilb Creek ok e e ert Heath o i e Cre Lake City r r r e Monitoring Station Locations i reek k Montgomery B Hay C ra C ek g P ller Cre k CSMP 56 e 58 Mi e in re ll k e W pr Dundas ELDON ANDERSON e dC S e 61 B n o r o lf ec Lower Mississippi Watershed C k C S e Dakota SWCD/NCRWMO r r e e a r e e k Dennison l C C 's BELLE CREEK R-1 Goodhue g in K Dakota SWCD/Vermillion T 99 63 ro u 21 t Le Sueur C B o 246 l ro Wabasha 60 East Side Lake County Bellechester d o S kC p Nerstrand Big Woods r e i re Rice ttl n e State Park Li g k County r, B Fillmore SWCD/Root River e r Nerstrand iv o GORMAN LAKE R o RICE LAKE n k no rk an Fo C th LAKE or , N reek ver y C S Gor Kilkenny CANNON RIVER Ri an pr Kellogg o lb ing k m br st A Cr an m eek ee C LTRMP Faribault u We r KING'S MILL DAM Fal Z Wabasha re ls Cr C e 299 eek Wanamingo k 60 g S k 860A Zumbrota County i e h b e Zumbro Falls 298 i M 60 el n 58 a Lakeville g Cr z e H g l pp P e Mazeppa Kenyon e n aC a i C r ZUMBRO RIVER rl r r p e e e W MCES C S e k ek r k e e eek e r r s e De C C n t e k y Ru k Dr Millville I a v n n S l d n Creek ve r i East India River/Stream; STREAM/Other Ri n i n MORRISTOWN POND k a o k nn C e k n Ca Zu e ee e m r r br e C Morristown o e C Cr Waterville r Tr Ri Hammond r ver e ZUMBRO LAKE d g , n C e No k n o o rth o k L e u USGS e B e k Sakatah Lake State Park r M m l t k id e dle m r d V e F a ork d al e 35 Pine Island H C i Elysian r l Minneiska g e C M y n WSU k i d ee 57 C Cr r u sh r Ru rk p Ada e k o S ms e e M e F Vk a e dl r lley r John A. Latsch id e Cre C M v ek Medford , l State Park 56 r i h ive 247 Plainview c R S ek s ro Oronoco Cre t D M mb 42 er a eer ed Zu eav L ing WAVRIN WETLAND fo West Concord B Va rd Plu lley C m Cr Cre re eek White ek ek water River River Elgin , Nort W tewater eek h Bra h to Whi Speltz M r nch it ry 10 Cree illik C e tar k h en C m Twribu e reek co iv c reek k a n WAT KINS L AKE Crane C r t R M a e Rol a a H Carley State Park rr lingrs ple e S tone Cr C t R tra B 248eek ree a i igh Rollingstone k v t C e w e reek l Rice Lake e r d Minnesota City it , 13 S d State Park Z h i Owatonna k k o le For um ee Elba u th Br Midd Cr W M MOREHOUSE PARK er, Sou n t , bro Riv k a h Waseca Zum og k e k b L B e e e ear Creek r r B r e e r o a BOLLER POOL n r Goodview C C Altura R c C Mantorville s h g e in iv n MANTORVILLE Winona i k Whitewater n e r p o r t G p m State Park s ilm Blue Earth o SR-2 ore C S g reek h n ClaremontD n T SOUTH BRANCH ZUMBRO RIVER i County o ch l dg o an l t e i r k S s Ce e B e o nter H n Byron Silver Creek dl e t e Kasson id R Stocktono t Cr 814A M r s e e Dodge Center U o c W ek n t 43a 6 C k 5 , Waseca # Steele Dodge s ib k h Tr t k E tc l Masten C Rochester o e i in reek un k e , e n e County o k r tyD County County C C h R r n k a c o V e C ou s ran Peterson Creek C c r e C r a e B ut r k e e de dl a e id o y e e P e e C Winona B 14 l r ,M r r r e r e Cr k e ive l l ic k R T e m C r n l MAYOWOOD LAKE te y C a i y y k Bear Creek itew County a e e T BR-1 h v l w Olmsted l PICKWICK d u W C V l Ho l W r a k r hitew a i n tl Eyota ate a r s V c r Lewiston e e R o County iver, e n V r k S e C o G uth B e r a r r ranc s PLEASANT VALLEY SITE NO. 8 d C m e h Utica k u h e e n c h ek C r C k B r Cre e n ley c l i a e y B Dover Saint Charles u a nt V a r sa k e a R d B Ple k , l Great River g B HUNDORF POND l k ek k er 843A e L r Cre t e a Bluffs State Park o lem e Ru s r ittl a e F S n e V e r C l W e r d WR-6A C k d , e i K 843A c l i k i l M e nn e e i r, y C e w e m re r k D v e M i o k 90 c ako Ditch #25 R M C i ta Cre County C ar H y P ek d i P k e e e l C da k Whi l i e n k tney Cree n e k C o k Dakota e e e ek r P r e e e re i r C r C on C M n r e us R e erg eC k r F k C C e r e e i k e C ld re v e k e C C r e e re w e e e e S s k o f pi r traig r C o k p e n i ht o e o s k R d l M k ive , l H k , C r o l e l e u n k W fi i r S e r ee i e e y e y G o r o a R d r R e e u e r W C 30 30 n C H g r l t h t s L Bu h l Ge y C Hayfield e e rna k t e n C u A der C e BLUMENTRITT DETENTION r a y s e F e y o ek r F g C l y o h n r o l L o e V R r e or d C r r r a 74 s C e l i c k 43 o k b e e C o l S T b b D e e C 218 k i r h r Cre n k o t t p s a C e y r e i Ellendale B a a k n y r r C l w e o e e S e l e g m ey v V Vo re a y n l C k i e o k l Blooming Prairie r p e m a R Ni 30 m k C e o P C e r a e e r C m e H i r C n d S e n V r ar Stewartville c e C a g k l r i a ea h e g l s n n k e t r C e L r re o 76 n e e g e k e k l e k r P R s r k e e P r Chatfield hue M RAUK DETENTION u ine C C c k r i t B B a v r s S on La Crescent o r C i e k e L e r B o r e e i 30 y r i g k k o e e e k S C k r pr e e e e in k r e k C g e r e e s e C C r r LAGOON PARK S r gs re k Geneva e nC 30 k e w O k t C K n o e F C ch e Rushford l o k Waltham o e an i l BAUMGARTNER GROUP POND x y C d r e o s e r ar y r le B r b

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r, o Le Roy o Iowa River, Upper e t n iv D Emmons Lyle d R a w Io Barr Footer: Date: 11/10/2004 4:27:44 PM File: I:\Projects\23\62\880\Gis\Maps\ArcMap\MonitoringStations.mxd User: GJW Table 1-1 Summary of Monitoring Sites by Lower Mississippi River Basin Watershed

Number of Sites

Fillmore Dakota Dakota East CRWP CRWP SWCD Lakeville/ RIVER/ Major Basin BIOLOGICAL CSMP SWCD/ SWCD/ Side LAKE LTRMP MCES USGS WSU TOTAL Invertebrates WQ /Root STREAM NCRWMO Vermillion Lake Farmington River

CANNON RIVER 11 23 99 40 2 0 0 0 23 1 0 1 99 9 0 319 CEDAR RIVER 0 0 0 0 0 0 8 0 4 0 0 0 105 3 0 120 MISS R & L PEPIN 9 0 0 0 0 4 0 0 2 5 5 1 54 8 0 90 MISS R-La Crescent 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 MISS R-Reno 0 0 0 0 0 0 0 0 0 1 0 0 12 2 0 15 MISS R-Winona 0 0 0 39 0 0 0 0 2 3 0 0 46 14 85 189 ROOT RIVER 0 0 0 24 0 0 0 27 1 1 0 0 48 18 22 141 SHELL ROCK RIVER 0 0 0 0 0 0 0 0 17 0 0 0 13 2 0 32 UPPER IOWA RIVER 0 0 0 0 0 0 0 0 1 0 0 0 5 0 0 6 WAPSIPINICAN RIVER 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 WINNEBAGO RIVER 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 3 ZUMBRO RIVER 0 0 0 41 0 0 0 0 9 0 0 0 37 14 1 102

TOTAL 20 23 99 144 2 4 8 27 62 11 5 2 420 70 108 1018

P:\23\62\880\Final Report\Phase I Report.doc 1-1 was also retained for this analysis (as shown in Table 1-1). Table 1-1 shows that there are 420 River/Stream monitoring locations, which include the MPCA’s milestone, Clean Water Partnership, Rural Clean Water Project Area and TMDL sites, as well as Metropolitan Waste Control Commission and EPA Clean Lakes sites.

Stream Sediment, Flow, Turbidity and Sediment-Related Variables As previously described, there are several groups collecting water quality data within the Lower Mississippi River basin and many of them have data on stream sediment, flow, turbidity and other related variables. Barr obtained and compiled all of the available data for the following sediment and sediment-related variables from each agency:

• Water column or suspended sediment concentration • Turbidity • Instantaneous flows corresponding to water quality monitoring results • Total suspended solids (TSS) • Volatile suspended solids (VSS) • Dissolved and settleable solids • Chlorophyll-a • Suspended sediment and bed sediment particle size distribution data • Bedload • Transparency • Dissolved and Total Organic Carbon • Settleable, volatile, filtered and filtrable residue • Physical appearance rating • Recreational suitability rating

Based on all of the compiled data, the USGS was the only agency collecting suspended sediment, bedload, residue, dissolved and settleable solids, and particle size distribution data for suspended and bed sediments. With the exception of the Citizen Stream Monitoring Program (CSMP), the remaining data sources were more likely to collect TSS, turbidity, chlorophyll-a, and occasional flow and VSS measurements. Data for CSMP sites typically consists of transparency, precipitation, stage, physical appearance and recreational suitability ratings, as well as occasional readings for turbidity and TSS. Based on the available data, it appears as though turbidity and TSS may be the only water quality constituents that can be used to develop relationships between the various datasets.

P:\23\62\880\Final Report\Phase I Report.doc 1-1 The USGS occasionally collected turbidity, TSS and instantaneous flow readings from the monitoring sites that they had used to collect suspended sediment data. Table 1-2 provides a summary of the available data for the USGS monitoring sites in the Lower Mississippi River basin. Turbidity data was occasionally collected for five of the USGS sites, of which, only three sites had suspended sediment data. TSS data was not collected simultaneously with any of the suspended sediment data at the USGS sites. Table 1-2 also shows that the USGS no longer collects suspended sediment data from any of the sites and only collects flow data from three sites in the basin.

One goal of this study was to develop dimensionless sediment transport curves by completing a regression analysis on the available pairs of suspended sediment concentration and instantaneous discharge data for as many of the USGS sites as possible. Table 1-2 shows that only six gage sites had more than 30 pairs of suspended sediment concentrations and instantaneous discharge readings. After meeting with the USGS staff, we determined that we could obtain enough of this data from their archives and the USGS web sites to develop sediment transport curves for the following six gage sites:

• NORTH FORK WHITEWATER RIVER NEAR ELBA, MN • WHITEWATER RIVER NEAR BEAVER, MN • GARVIN BROOK NEAR MINNESOTA CITY, MN • ROOT RIVER NEAR HOUSTON, MN • SOUTH FORK ROOT RIVER NEAR HOUSTON, MN • CEDAR RIVER NEAR AUSTIN, MN

The remaining USGS gage sites did not have adequate suspended sediment data or lacked a sufficient period of record for determining the expected bankfull flow discharge.

Stream Biological Data Barr compiled biological data from five different sources (WSU, MCES, Lakeville/Farmington, CRWP, and the EDA Biological data). The WSU data consisted of hard copies of field data sheets for both invertebrate and fisheries sampling. Barr staff entered the raw data into an Access database and subsequently calculated HBI and ICI scores, consistent with the methodology contained in Hilsenhoff (1987) and DeShon (1995), respectively. The published IBI scores taken from Mundahl (2001) were also entered into the overall Excel spreadsheet. The EDA Biological database only contained data collected by Schmidt and Talmage (2001). Barr entered the IBI scores from this source directly into the overall Excel spreadsheet. The other three sources of biological data consisted of invertebrate sampling, only. For these data sources, Barr entered the ICI and HBI

P:\23\62\880\Final Report\Phase I Report.doc 1-2 Table 1-2 Summary of Available Data for USGS Monitoring Sites in the Lower Mississippi River Basin Watershed

# of SS/ #SS Station Discharge Susp.Sed.Period Records Other Daily Flow Number Station Name Pairs of Record (days) Available Data Record 5345000 VERMILLION RIVER NEAR EMPIRE, MN 1 Turb, PSD 5345100 SOUTH BRANCH VERMILLION RIVER AT EMPIRE, MN 5346000 VERMILLION RIVER AT HASTINGS, MN Turb 5353800 STRAIGHT RIVER NEAR FARIBAULT, MN 2 12/68-9/71 359 PSD 1965-03 5355090 CANNON RIVER AT LAKE BYLLESBY NR CANNON FALLS PSD 5355200 CANNON RIVER AT WELCH, MN 4 PSD 5372800 S FORK ZUMBRO R ON BELT LINE AT ROCHESTER, MN 3 3/81-10/81 230 PSD 3-10/81 5372930 BEAR CREEK AT ROCHESTER, MN 2 3/81-10/81 227 PSD 3-10/81 5372950 SILVER CREEK AT ROCHESTER, MN 1 3/81-10/81 227 PSD 3-10/81 5372990 CASCADE CREEK AT ROCHESTER, MN 2 3/81-10/81 227 PSD 3-10/81 5372995 SOUTH FORK ZUMBRO RIVER AT ROCHESTER, MN 9 3/81-9/82 554 PSD 1981-03 5373000 SOUTH FORK ZUMBRO RIVER NEAR ROCHESTER, MN 1 5374000 ZUMBRO RIVER AT ZUMBRO FALLS, MN 6 3/71-8/75 314 PSD 1929-80 5374900 ZUMBRO RIVER AT KELLOGG, MN 5 8/75-9/81 2232 PSD 1975-90 5376000 NORTH FORK WHITEWATER RIVER NEAR ELBA, MN 187 10/67-9/68,4-7/91 13 Turb, PSD 1967-93 5376100 MIDDLE FORK WHITEWATER RIVER NR ST. CHARLES, MN 50 4/91-8/91 6 PSD 1988-92 5376500 SOUTH FORK WHITEWATER RIVER NEAR ALTURA, MN 1 Add. SS ('91) 1939-71 5376800 WHITEWATER RIVER NEAR BEAVER, MN 43 7/75-7/91 2283 PSD 1975-85,91-99 5378230 STOCKTON VALLEY CREEK AT STOCKTON, MN 30 2/82-7/85 640 Turb, PSD 1982-85 5378235 GARVIN BROOK NEAR MINNESOTA CITY, MN 32 3/82-7/85 632 Turb, PSD 1982-91 5384000 ROOT RIVER NEAR LANESBORO, MN 3 12/67-9/71 82 PSD 1940-85,87-90 5384120 SOUTH BRANCH ROOT RIVER AT LANESBORO, MN 5384500 RUSH CREEK NEAR RUSHFORD, MN 1 5385000 ROOT RIVER NEAR HOUSTON, MN 27 12/67-9/81 2959 PSD 1929-83,91-00 5385500 SOUTH FORK ROOT RIVER NEAR HOUSTON, MN 14 7/75-9/81 2263 PSD 1953-83 5457000 CEDAR RIVER NEAR AUSTIN, MN 34 3/71-9/81 355 PSD 1909-03

NOTES: SS = Suspended Sediment, Turb = Turbidity, PSD = Particle Size Distribution Limited period of record for bankfull flow frequency determination.

P:\23\62\880\Final Report\Phase I Report.doc 1-3 scores, where available, or otherwise used the raw data to calculate and enter each score into the overall spreadsheet.

Bill Thompson compiled spreadsheets with the available data on the dates and locations of DNR Fisheries Surveys in southeast Minnesota, as well as the locations of surveys done for the Brown Trout database. Barr transformed the data and used the kittle number and stream mile section data in the spreadsheet to match the monitored locations with the DNR’s 24K Stream Coverage and map the stream sections in GIS.

The Minnesota Pollution Control Agency’s Biological Monitoring Program was in the process of collecting extensive biological data in southeast Minnesota while this study was in progress. The MPCA sampling procedures for wadeable streams are modeled after Wisconsin’s warmwater stream guidance (Lyons 1992a). The MPCA sampling procedures for large unwadeable reaches follow U. S. Geological Survey (USGS) National Water-Quality Assessment (NAWQA) guidance (Meador et al, 1993).

Watershed Basin and Physical Stream Characteristics Wilson (2003) presented the large range in observed sediment yields throughout the Lower Mississippi and Cedar River basins under various flow conditions. This can be attributed to the variability of the geology, topography, land use and climatology of each ecoregion. There are portions of three EPA Level III ecoregions that cover this study area. The Western Corn Belt Plains ecoregion, occupying most of the southern portion of the state, is predominantly agricultural lands with variable topography, clayey and loess soils, and higher precipitation from west to east. The Northern Central Hardwood Forests ecoregion, located in the headwaters/lake region of the Cannon River watershed, has mixed landuse, and consists of variable topography, with sand and clay soils, and higher annual precipitation. The Driftless Area ecoregion, located in the extreme southeast portion of the state, has mixed landuse, and consists of hilly topography with highly erodible loess and rock or sandy soils, and high annual precipitation. Tornes (1986) notes that tillage of the loessial soils, combined with high runoff from the steep topography, result in average suspended solids concentrations above 50 mg/L, and maximum concentrations exceeding 5,000 mg/L at several monitoring stations.

Gowda and Mulla (2004) compiled existing sources of watershed and landscape characteristics for the Lower Mississippi River Basin in GIS, previously developed by the University of Minnesota, Department of Soil, Water, and Climate and Mulla et al. (2004). The watershed and landscape characteristics include the following:

P:\23\62\880\Final Report\Phase I Report.doc 1-1 • Area of minor watershed (ha) • Soil internal drainage percentage (percentage of well drained soils) • Water erosion potential (tons/ac) • Rainfall factor used in the USLE • Average watershed slope (percent) • Cropland area within 100 meter proximity of surface waters (in ha and percentage) • Total cropland area (in ha and percentage) • Total urban land area (in ha and percentage) • P-index • Geomorphology • Agroecoregions • Karst features • Land area proximity to various surface water types

William Thorn, Minnesota Department of Natural Resources (DNR), provided us with a spreadsheet containing the following DNR stream survey and classification data, as described in Thorn and Anderson (1999):

• Watershed • Instream Flow Region • Ecoregion • % POOL • % RIFFLE • % RUN • Ave. Width • Ave. Depth • W:D Ratio • Flow • Gradient • Sinuosity • % Fines • Cover • Bank Erosion Severity • Shade • Ecological Classification

The DNR stream survey data was available for a significant portion of the streams in the Lower Mississippi River basin. Barr utilized the kittle number and stream mile section data in the spreadsheet to match the monitored locations with the DNR’s 24K Stream Coverage and map the stream sections in GIS.

P:\23\62\880\Final Report\Phase I Report.doc 1-2 The Minnesota Department of Natural Resources and Minnesota Pollution Control Agency (2001) completed a draft stream geomorphology and physical stream classification report that contained bankfull flow and Rosgen stream classification data for various stream sites in southeast Minnesota. Corey Hanson, MDNR, and Bill Thompson, MPCA, provided us with the data from this study which also developed regional bankfull flow relationships from the data. Barr provided locations for each of the fifteen stream sites in GIS.

Assessment of Monitoring Methodology for Compiled Data This section provides an assessment and interpretation of the various monitoring protocols or methodology that was used to collect the data discussed in the previous section. Most of the groups collecting data in the Lower Mississippi River basin provided Barr with monitoring protocols that describe their methodology for sampling and quality assurance/quality control. The remaining groups cited methodologies that were consistent with those used by the Citizen Stream Monitoring Program (MPCA, 2002) or other published protocols for the collection and assessment of biological and physical stream data.

The following summarizes some of instructions provided to CSMP volunteers:

• Select one location on your stream, and monitor at that site throughout the season. Ideally, you want to choose a location that is typical of the stream. Choose a spot that is somewhat deep and flowing. Avoid shallow, fast running rocky areas (“riffles”) and stagnant deep areas (“pools”).

• Try to visit your stream at the same time of day every time you monitor. There are two times when you should monitor your stream: once a week during the stream-monitoring season, and as needed, in response to significant rainfall events. Measurements should be taken at least once a week, especially during the months of April through September. We encourage you to monitor more frequently than once a week at first, to help us determine how often measurements should be taken. Additional measurements taken earlier or later in the year are welcome. In addition to your weekly stream monitoring, measurements should be taken daily for 2-3 days (or longer) after a significant rain event, if possible. You may want to adjust the length of your daily measurement period (e.g. 4-5 days), depending on how quickly rainwater travels from the land to the stream channel and past your sampling location. Once you have monitored a few rainfalls, use your best judgment to determine when a rainfall is significant, and how long stream conditions change in response to a rain event. Then take enough daily measurements to capture that change. You may find that daily measurements are not frequent

P:\23\62\880\Final Report\Phase I Report.doc 1-3 enough to capture rapid changes, and decide to take readings more frequently. As a general rule of thumb, a rainfall of approximately 1/2-inch in a relatively short period of time can result in a significant runoff event.

• HOW TO TAKE STREAM TRANSPARENCY READINGS: Collect your water sample in a clean bucket or bottle at mid-stream & depth. If a sample from mid-stream and depth is not possible, avoid stagnant water and sample as far from the shoreline as is safe. Try not to stir up the bottom and face upstream as you fill your bucket. Avoid collecting sediment from the stream bottom and materials floating on the water surface. Take your tube readings in open conditions. Avoid direct sunlight by turning your back to the sun if necessary. Swirl the water in your sampling bucket or bottle so that materials do not settle on the bottom and pour the water into the tube until the symbol on the bottom is not visible. While looking down into your tube, open the valve at the bottom and slowly release water until you can JUST begin to make out the symbol on the bottom. Note this depth. Release a bit more water until the symbol is visible. When you can see the screw in the middle of the black and white symbol, it is “visible.” Note this depth. Record the average of the two depths taken in the previous steps to the nearest centimeter. If the symbol is visible when your tube is full, indicate this on the data sheet (e.g. > 60 cm).

The USGS (and LTRMP) water quality sampling is typically occurring at the mouth or at bridge crossings near the downstream portion of larger river systems. The stream flow velocity and water quality concentrations may experience significant gradients, both horizontally and vertically, depending on the stream stage, discharge, bed form, and channel alignment at many of these monitoring locations. As a result, the USGS has developed monitoring protocols and training that are significantly more rigorous, especially for sampling suspended sediment.

The USGS determines the sediment concentration of the flow by collecting depth-integrated suspended sediment samples that define the mean discharge-weighted concentration in the sample vertical and collecting sufficient verticals to define the mean discharge-weighted concentration in the cross section. This practice is repeated a sufficient number of times to evaluate the relationship between the mean discharge-weighted concentrations in the cross section and the mean discharge- weighted concentrations from one of the vertical locations (or fixed station) under varying flows and over time. Dividing the concentration in the cross section by the concentration from the fixed station (or box) produces the cross-section coefficient. An analysis of this coefficient may be used to re- evaluate the sampling methods and location of the fixed station until a coefficient that is nearly equal to 1.0 will exist for all flow conditions. If this occurs, the USGS may even utilize volunteers to

P:\23\62\880\Final Report\Phase I Report.doc 1-4 collect routine mean discharge-weighted concentrations from the fixed station and then supplement that with occasional mean discharge-weighted concentrations in the cross section as a check.

Another technical memorandum will be prepared for Task 6 of this study which will further discuss the alternatives and make recommendations for the various types of monitoring that should be completed in the basin to implement TMDL projects and assess their effectiveness over a 25-year period.

P:\23\62\880\Final Report\Phase I Report.doc 1-5 Task 2 – Review and Analyze the Existing Monitoring Data and Background Information

The purpose of this section is to discuss our review, analysis, and interpretation of the existing monitoring data and the background technical information collected in Task 1. Based on the availability of data, this task is intended to include the following analyses:

• Characterize the streams in the basin by type, gradient, and basic stream geomorphology criteria.

• Define the extent of relevant data in the basin, by stream type, stream size, and watershed location.

• Integrate stream sediment, physical, and biological variables, where possible, for similar types and /or sizes of streams.

• Develop dimensionless sediment transport curves.

• Calculate flow-weighted mean concentrations by season at sites where adequate flow and concentration data is available.

• Investigate the relationship between % fines, stream embeddedness, particle size data sets, and aquatic habitat quality, where all are available for a given stream reach.

• Develop relationships and sediment “translators” for sediment-related variables where existing data sets are adequate to allow valid statistical analyses.

• Investigate potential relationships between the sediment-related variables and land cover, runoff, agroecoregion characteristics and contributing drainage areas above each stream monitoring site or stream reach.

• Assess relationships between bio-indicators and pertinent sediment data sets.

• For streams in the karst areas, assess groundwater influences as related to stream sediment pollution.

• Assess the Citizen’s Stream Monitoring Program (CSMP) data set in the LMB for recreational suitability and stream appearance ratings made by volunteer citizen monitors. Also utilize the volunteer transparency and river stage data sets.

P:\23\62\880\Final Report\Phase I Report.doc 2-1 Characterize the Streams in the Basin The Lower Mississippi River (LMR) basin, including the Cedar River basin, is located in all or part of 17 counties and has 12 major watersheds covering about 4,650,100 acres. Bluffs, springs, caves and numerous trout streams exist in the eastern portion of the basin, where steep topography and erosive soils increase the potential for pollutant runoff and sedimentation of streams. Sinkholes and disappearing streams highlight the close connection between surface water and groundwater in this part of the basin. Average annual runoff ranges from 5.5 to about 8 inches, increasing from west to east. The abundant moisture greatly benefits crops but aggravates problems associated with soil erosion and sediment transport to surface water.

In the southwestern portion of the LMR basin, Mississippi tributaries emerge as small streams out of a prairie landscape once rich in wetlands. The headwaters areas are now extensively drained to support productive agriculture. Further to the north of the basin, in the western Cannon River Watershed, remnants of the Big Woods hardwood forest intermingle with mixed crop and livestock farming in a rolling terrain interspersed with lakes and wetlands. Smaller streams in the eastern karst region of the basin often originate from groundwater discharge points such as springs or seeps. Table 2-1 describes the major river systems, their tributaries, and watersheds, located in the LMR basin.

Table 2-1 Summary of the LMR Watershed Characteristics

Stream/River & Drainage Area (square miles at mouth- Number of Listed Reaches for Watershed unless noted otherwise) Turbidity – 2004 List Root River 1660 3 Zumbro River 1414 1 Cannon River 1340 (at Welch) 1 Straight River 442 (at Faribault) 3 Cedar River 399 (at Austin) 2 Whitewater River 321 6

P:\23\62\880\Final Report\Phase I Report.doc 2-2 Stream/River & Drainage Area (square miles at mouth- Number of Listed Reaches for Watershed unless noted otherwise) Turbidity – 2004 List Vermillion River 195 (at Hastings) 1 Shell Rock River 190 (near Gordonsville) 1 Garvin Brook 46 1 Gilmore Creek 9 -

A summary of the number of reaches listed in each watershed based on the draft 2004 list is given in Table 2-1. The river reaches for the 2004 Impaired Waters List include nine (9) new turbidity impairments, seven of which are in the Cannon River watershed and two are in the Root River watershed. A broad overview of turbidity values shows that the water quality standard is exceeded for about 23% of samples taken in the Zumbro, from 47 to 75 percent of samples for Garvin Brook, and between 20 - 40% of samples in the Mississippi River downstream of the Root River confluence. The State of Minnesota currently uses turbidity as a numerical water quality standard under Minn. Rules Chapter 7050. The numerical water quality standard for turbidity is 10 Nephelometric Turbidity Units (NTU) for Class 2A waters (cold water fishery, all recreation) and 25 NTU for cool and warm water fishery, all recreation.

P:\23\62\880\Final Report\Phase I Report.doc 2-3 floodplains, making farming of the rich soil possible, at the cost of increased sedimentation of the Mississippi and the degrading of a rich ecosystem.

William Thorn, from the Minnesota Department of Natural Resources (DNR), provided the following DNR stream survey and classification data, as described in Thorn and Anderson (1999):

• Watershed • Instream Flow Region • Ecoregion • % POOL • % RIFFLE • %RUN • Ave. Width • Ave. Depth • W:D Ratio • Flow • Gradient • Sinuosity • %Fines • Cover • Bank Erosion Severity • Shade • Alkalinity • Ecological Classification

This DNR stream survey data was available for a significant portion of the streams in the Lower Mississippi River basin. The kittle number and stream mile section data from the survey was used to match the monitored locations with the DNR’s 24K Stream Coverage and provided a way for the water quality monitoring locations and associated data to be linked with the stream sections in GIS.

Figure 2-1 shows the extent of the five major geomorphology classifications in relation to the MnDNR’s major and minor watershed boundaries within the basin. The Harmony-Plainview Uplands consist of silty soils in gently rolling terrain, while the Kenyon-Taopi Plain is undulating. The Moraines area consists of irregular, rolling silty-loamy-clayey soils. The Red Wing-LaCresent Uplands consist of the steepest topography.

P:\23\62\880\Final Report\Phase I Report.doc 2-4 Figure 2-1 Lower Mississippi River basin watershed boundaries and geomorphology classifications

Major watershed boundary Minor watershed boundary Geomorphology Classification Harmony-Plainview Uplands Kenyon-Taopi Plain Moraines RedWing-LaCreesentUplands Rochester Drift Plain

P:\23\62\880\Final Report\Phase I Report.doc 2-5 recreational opportunities, and decreased economic activity which result from activities such as fishing, canoeing, and tubing. Assessing the complex nature of sediment pollution within the LMB basin requires an extensive network of monitoring locations with long-term sediment, physical, biological data.

Extent of Relevant Data in the Basin and Integration of Sediment, Physical, and Biological Variables for Similar Streams This section describes the extent of relevant data in the basin and integration of sediment, physical and biological variables for similar streams. The following data were compiled for this study:

• Stream sediment, flow, turbidity and sediment-related variables

• Stream biological data

• Watershed landscape and physical stream characteristics

Wherever possible, stream monitoring locations were obtained in a GIS format to facilitate mapping and integration of the data for similar streams. All of the compiled data represented approximately 41,000 monitoring events for the period of record from all of the monitoring locations in the basin. Figure 1-1 shows all of the monitoring station locations, for each data source, within the Lower Mississippi River basin. Figure 1-1 shows that most of the larger watersheds have a significant number of monitoring locations (greater than 90). The CSMP sites are concentrated in the Cannon River, Mississippi River-Winona, Root River and Zumbro River major watersheds. There are approximately 1,000 monitoring locations throughout the basin.

Our evaluation of the relationships between the various sediment and biological variables was completed with the raw data pairs from the compiled (overall) database. While sediment and biological data has been collected from several monitoring locations throughout the basin, some DNR major and minor watershed areas have a significantly greater density of active and past locations with both sediment and biological data, and some major and several minor watersheds have very limited datasets or do not have both water quality and biological data. Also, while the DNR has completed stream surveys for more than 1,000 warmwater and coldwater stream segments, some areas have not been surveyed, including areas that have water quality or biological data. Smaller or minor watershed areas that have more than one monitoring location may not necessarily possess a full compliment of the water quality and biological variables of interest for this study. As a result, GIS was used to associate the water quality and biological monitoring locations with the DNR’s stream survey locations and all of the sediment, physical and biological monitoring locations were

P:\23\62\880\Final Report\Phase I Report.doc 2-6 intersected with the major and minor watershed divides to facilitate the integration of the available data with the watershed characteristics of the contributing drainage areas above each stream monitoring site or reach. The dataset median for each sediment, physical and biological variable was associated with the watershed characteristics for each of the minor watersheds. The resulting (integrated) dataset was used to evaluate the relationships between sediment and biological variables and the physical stream and watershed characteristics.

Dimensionless Sediment Transport Curves One goal of this study was to develop dimensionless sediment transport curves by completing a regression analysis on the available pairs of suspended sediment concentration and instantaneous discharge data for as many of the USGS sites as possible. Our initial evaluation of the available data showed that only six gage sites had more than 30 pairs of suspended sediment concentrations and instantaneous discharge readings in the basin. After meeting with the USGS staff, we determined that we could obtain enough of this data from their archives and the USGS web sites to develop sediment transport curves for the following six gage sites:

• NORTH FORK WHITEWATER RIVER NEAR ELBA, MN

• WHITEWATER RIVER NEAR BEAVER, MN

• GARVIN BROOK NEAR MINNESOTA CITY, MN

• ROOT RIVER NEAR HOUSTON, MN

• SOUTH FORK ROOT RIVER NEAR HOUSTON, MN

• CEDAR RIVER NEAR AUSTIN, MN

The remaining USGS gage sites did not have adequate suspended sediment data or lacked a sufficient period of record for determining the expected bankfull flow discharge. The methodology for development of the sediment transport curves followed that of Troendle et al. (2002). Our methodology for development of the sediment transport curves involved the following steps:

1. Compile all of the available pairs of suspended sediment concentrations and discharge readings for each gage site 2. Plot the suspended sediment concentration data versus the corresponding discharge rates for each station and develop a regression line using a power function. Figure 2-3 provides an example of this plot for the Cedar River near Austin.

P:\23\62\880\Final Report\Phase I Report.doc 2-7 3. Compile the discharge monitoring data from each site to develop flow frequency distributions for the period of flow and sediment monitoring records 4. Estimate the bankfull flow discharge (rate during channel-forming flows) from each flow frequency curve (summarized in Table 2-2), assuming that 1.5-year return period is representative of the bankfull discharge rate for each gage site.

5. Estimate the suspended sediment concentration at the bankfull flow discharge rate using the power function regression from the plot of suspended sediment versus discharge for each station 6. Calculate dimensionless suspended sediment by dividing each suspended sediment concentration by the concentration at the bankfull discharge rate and calculate dimensionless discharge by dividing each discharge reading by the bankfull flow discharge rate.

Figure 2-2 Example Plot of USGS Suspended Sediment versus Discharge

P:\23\62\880\Final Report\Phase I Report.doc 2-8 Table 2-2 Estimated Bankfull Discharge Rates from Flow Frequency Analysis

Plotting the dimensionless suspended sediment versus the dimensionless discharge, along with the power function regression line, results in the sediment transport curve for each station. Figures 2-3 through 2-8 show the dimensionless sediment transport curves for each of the six USGS stations.

Figure 2-3 Dimensionless Suspended Sediment Transport Curve for Cedar River

P:\23\62\880\Final Report\Phase I Report.doc 2-9 Figure 2-4 Dimensionless Suspended Sediment Transport Curve for Garvin Brook

Figure 2-5 North Fork Whitewater R. Dimensionless Suspended Sediment Transport Curve

P:\23\62\880\Final Report\Phase I Report.doc 2-10 Figure 2-6 Root River Dimensionless Suspended Sediment Transport Curve

Figure 2-7 South Fork Root R. Dimensionless Suspended Sediment Transport Curve

P:\23\62\880\Final Report\Phase I Report.doc 2-11 Figure 2-8 Whitewater River Dimensionless Suspended Sediment Transport Curve

Since each of the sediment transport curves are dimensionless, they can be plotted together and superimposed to compare the rates of suspended sediment transport per unit change in discharge (slope of the power function regressions shown in Figure 2-9). In addition, the 95 percent confidence intervals were determined for each of the power function regressions to evaluate the significant differences between the slopes of the curves for each station. Comparing the 95 percent confidence intervals developed for the slope of each of the curves shown in Figure 2-9 results in the following conclusions:

• The rate of suspended sediment transport per unit discharge is significantly less for the Cedar River than for the South Fork Root, North Fork Whitewater and Root Rivers

• The rate of suspended sediment transport per unit discharge is significantly less for Garvin Brook than for the South Fork Root and North Fork Whitewater Rivers

• The rate of suspended sediment transport per unit discharge for the Whitewater River near Beaver is not statistically different than any of the other stations

P:\23\62\880\Final Report\Phase I Report.doc 2-12 Figure 2-9 Superimposed Suspended Sediment Transport Curves for All USGS Sites

The Whitewater River near Beaver, North Fork Whitewater and South Fork Root River sites have been classified with Rosgen stream types of C, B and F, respectively (Hanson and Thompson, 2001). Troendle et al. (2002) did not show significant differences in dimensionless sediment transport were attributable to Rosgen stream type, but they demonstrated that reference sediment transport functions for suspended sediment and bedload appear to function well for stable streams and indicate that departure can be demonstrated for unstable streams. As a result, Pfankuch (1975) stability ratings and Rosgen stream classifications would need to be developed for each of the six USGS gage sites to determine whether one of more of the sites represents a “reference” condition that can be used to assess the relative transport and stability of the remaining USGS sites.

Flow-Weighted Mean Concentrations by Season This section is intended to discuss calculated flow-weighted mean concentrations of sediment data, by season, at sites where adequate flow and water quality data are available. A review of the USGS suspended sediment loading data revealed that four gage locations had enough long-term data to evaluate the seasonal concentrations. The loading calculations are based on the individual daily flow and concentration data and are not based on long-term statistical evaluation methodology, such as

P:\23\62\880\Final Report\Phase I Report.doc 2-13 that used by MPCA, MCES and the LTRMP. Both MPCA and MCES typically use the FLUX program to estimate constituent loadings from long-term flow and concentration data. LTRMP has collected and compiled long-term flow and total suspended solids (TSS) concentration data from several of the major Mississippi River tributary monitoring sites and used that data to calculate monthly TSS loadings using LOADEST2 (Crawford, 1998).

The LTRMP monthly flow and TSS loading data were downloaded for the period of record from all of their monitoring locations, with the exception of the Vermillion River at the mouth of the Mississippi River which is heavily influenced by the River itself. The monthly flow and TSS loading data was manipulated to determine the long-term average flow-weighted mean concentrations (FWMCs), by season, based on the following assumptions applied to each month of data for each site:

• Early spring, March and April • Late spring, May and June • Summer, July through September • Fall, October and November • Winter, December through February

Table 2-3 shows the results of the LTRMP TSS monitoring for each of the monitoring locations in the basin. The results indicate that:

• The FWMCs are consistently lower in the winter and fall than the other three seasons for all of the monitoring locations

P:\23\62\880\Final Report\Phase I Report.doc 2-14 Table 2-3 Results of LTRMP Total Suspended Solids Monitoring for Period of Record in Lower Mississippi River Basin

P:\23\62\880\Final Report\Phase I Report.doc 2-15 Relationship Between Stream Embeddedness, Particle Size Data and Aquatic Habitat Quality The relationship between stream embeddedness, sediment size data and aquatic habitat quality was investigated and is discussed in this section. For this analysis, stream embeddedness is characterized by the percentage of fines data obtained from Thorn and Anderson (1999). Aquatic habitat quality is based on the HBI, ICI and fish IBI scores compiled from the available data throughout the basin. Sediment particle size data has only been collected by the USGS within the basin. The following types of bed sediment data and range in particle sizes determined were compiled for this analysis:

• Bed sediment, fall % <0.004 mm to % <1 mm • Bed sediment, sieve % <0.063 mm to % <32 mm

The paired embeddedness, particle size and aquatic habitat quality data are summarized in Table 2-4. Since the USGS has not collected significant amounts of bed sediment data in the basin, it greatly reduced the amount of paired data available for this analysis. Four USGS gage sites, all located within the Miss. R-Winona watershed, had paired data for the parameters of interest. Of the four sites, Garvin Brook near Minnesota City had the lowest percentage of fines (84%) and HBI score (3.9), combined with the highest coldwater fish IBI score (92.5). The biological metrics for Garvin Brook indicate that it has significantly better aquatic quality than the other three sites, but the percentage of fines and the particle size distribution data for the bed sediment is not significantly different than the Whitewater River and Stockton Valley Creek.

Additional particle size distribution data should be collected for bed sediment to further evaluate the relationship between stream embeddedness and aquatic habitat quality in the basin.

P:\23\62\880\Final Report\Phase I Report.doc 2-16 Table 2-4 Relationship Between Stream Embeddedness, Particle Size Data and Aquatic Habitat Quality

P:\23\62\880\Final Report\Phase I Report.doc 2-17 Relationships and Sediment “Translators” for Sediment-Related Variables As previously described, there are several groups collecting water quality data within the Lower Mississippi River basin and many of them have data on stream sediment, flow, turbidity and other related variables. All of the available data for the following sediment and sediment-related variables were collected and compiled from each agency:

The USGS occasionally collected turbidity, TSS and instantaneous flow readings from the monitoring sites that they had used to collect suspended sediment data. Turbidity data was occasionally collected for five of the USGS sites, of which, only three sites had suspended sediment data. TSS data was not collected simultaneously with any of the suspended sediment data at the

P:\23\62\880\Final Report\Phase I Report.doc 2-18 USGS sites. The USGS no longer collects suspended sediment data from any of the sites and currently only collects flow data from three sites in the basin.

Ganske (2004) completed flow and concentration duration analyses based on 1993-2002 daily streamflow measurements from six USGS gaging stations and turbidity and TSS data for the same time period obtained from six USGS Long-Term Resource Monitoring Program (LTRMP) sites. Results of the analyses include:

• Despite large differences in watershed size, the flow duration curves for six USGS gage sites exhibit a generally similar form. Watershed size alone does not appear to be the major factor defining flow dynamics for these rivers. The curves for the Vermillion (129 square miles) and Root (1250 square miles) are similar to each other, as are the curves for the South Fork Zumbro (303 square miles) and Cannon (1340 square miles). For the Root River, the relatively high base flow would be consistent with the karst nature of the watershed, which includes substantial groundwater inputs from sources such as springs. On a relative basis, the Straight River is the most flood-prone, and at the same time the most likely to experience very low flow conditions. These characteristics could be consistent with the high intensity of agricultural drainage in the Straight River watershed, compared to other portions of the basin.

• A high degree of correlation between turbidity and total suspended solids for the six rivers with LTRMP monitoring data was confirmed. The relationship between flow percentile, and turbidity and TSS, varies by river, although all show a clear relationship of higher turbidity and TSS at higher flows. R-squared values for the Zumbro and Root rivers are greater than 0.5, and between 0.2 and 0.5 for the Vermillion (regressed on Vermillion flow percentile), Cannon, Whitewater, and Wells Creek. The r-squared values for Vermillion River turbidity and TSS regressed on Mississippi River flow were less than 0.2. For the three rivers with the most reliable flow percentile values, the 25 NTU (Class 2B water quality) standard corresponds with roughly the 40th percentile for the Zumbro and Root rivers, and with the 20th percentile for the Cannon River. The Cannon appears to exhibit somewhat lower overall turbidity and TSS concentrations, and the turbidity standard appears to be violated about half as frequently, compared to the Zumbro and Root rivers.

• Based on hydrograph separation, those TSS and turbidity observations associated with greater than 50% of the flow consisting of surface-runoff stormflow (versus base-flow) were identified. Most of the > 50% stormflow observations fall above the respective TSS and turbidity regression lines. This supports the importance of surface- runoff processes, in

P:\23\62\880\Final Report\Phase I Report.doc 2-19 addition to channel or in-stream processes (e.g. streambank erosion), contributing to TSS and turbidity.

Figure 2-10 shows the relationships between several of the sediment-related variables using all of the available paired data collected from the water quality monitoring stations in the LMR basin. The best-fit linear regression and confidence intervals are included for each plot. The results show that TSS, turbidity and VSS are each significantly correlated with each other and VSS is also significantly correlated with chlorophyll-a. Chlorophyll-a does not significantly influence turbidity readings and TSS concentrations, based on the overall dataset. Stepwise multiple linear regression analyses were done and showed that TSS explained 92% of the variance associated with the turbidity readings. The addition of VSS to the regression produces a relationship that was statistically significant and explains 93% of the total variance.

Figure 2-10 Scatterplot Matrix of Sediment-Related Variables

P:\23\62\880\Final Report\Phase I Report.doc 2-20 Correlation analyses were also completed for all of the remaining sediment-related variables to test the statistical significance of the relationships using all of the paired water quality data collected in the basin. The results of these analyses indicate the following:

• TSS and turbidity are significantly correlated with several of the residue parameters

• Transparency tube readings are significantly correlated with TSS, turbidity, and VSS

• TSS, VSS, turbidity, transparency tube readings and SSC are significantly correlated with instantaneous and average daily flow readings and inversely correlated with alkalinity

• Turbidity and transparency tube readings are significantly correlated with total organic carbon and transparency is inversely correlated with chlorophyll-a

• Transparency is significantly correlated with stream physical appearance ratings and transparency, TSS and turbidity are significantly correlated with the recreational suitability ratings

Turbidity readings varied significantly throughout the dataset compiled for this study. Maximum turbidity readings approached 4,000 NTUs in some cases. Figure 2-11 shows a notched box plot of all of the turbidity readings below 200 NTUs for each of the major watersheds by the five seasonal categories (previously described). The notches represent the confidence interval and the upper and lower edges of the box represent the quartiles for each plot. Datasets are considered to be significantly (statistically, at the specified confidence level) different when the lower notch in one box plot is higher than the higher notch of another box plot. Figure2-11 shows that the fall and winter turbidity values are significantly lower than the other seasons for some of the major watersheds. In general, the turbidity readings for the Upper Iowa, Cannon, Cedar and Miss. R.-Lake Pepin watersheds are less variable and significantly lower than the remaining watersheds. The readings for the Zumbro and Root River watersheds are significantly higher in the early spring and the readings in the Shell Rock River watershed are significantly higher than most of the remaining watersheds in the summer.

P:\23\62\880\Final Report\Phase I Report.doc 2-21 Figure 2-11 Box Plot of Turbidity Readings by Major Watershed and Season

The overall dataset was used to evaluate the relationships between turbidity and stream class, by season. Figure 2-12 shows that the turbidity readings for the coldwater streams were significantly lower than the warmwater streams for each season. For the coldwater streams, the turbidity readings were significantly higher in the early spring compared to the remaining seasons. For the warmwater streams, the summer, early and late spring readings are not significantly different than each other, but are significantly higher than the fall and winter readings.

P:\23\62\880\Final Report\Phase I Report.doc 2-22 Figure 2-12 Box Plot of Turbidity Readings by Stream Class and Season

Figure 2-13 compares the turbidity readings with the percentage of fines in the stream bed, as determined by the DNR stream surveys. The box plots show that there are not any significant differences in turbidity readings for the varying levels of fines contained in the stream beds.

The minor watershed areas that are currently listed as impaired for turbidity by the MPCA were entered into the integrated dataset to compare the various water quality variables for the impaired watersheds and the minor watersheds that are not listed. The results can be used to assess whether or not the sediment problem is generally more widespread than the watersheds that are currently listed. Figure 2-14 compares the turbidity readings for the impaired watersheds to the remaining minor watersheds. The results show that there is a statistically significant difference between the impaired and non-listed watersheds for turbidity. The results also show that almost all of the median turbidity measurements for each minor watershed area is below the turbidity standard for warmwater streams.

Figure 2-15 shows that the transparency tube readings are not significantly different when comparing the minor watershed impaired for turbidity with the watersheds that are not listed.

P:\23\62\880\Final Report\Phase I Report.doc 2-23 Figure 2-13 Box Plot of Turbidity Readings versus Percentage of Fines in Stream Bed

P:\23\62\880\Final Report\Phase I Report.doc 2-24 Figure 2-14 Box Plot of Turbidity Readings from Impaired and Non-Listed Watersheds

Figure 2-15 Box Plot of Transparency Tube Readings from Impaired and Non-Listed Watersheds

P:\23\62\880\Final Report\Phase I Report.doc 2-25 Relationships Between Sediment-Related Variables and Watershed Characteristics Gowda and Mulla (2004) compiled existing sources of watershed and landscape characteristics for the Lower Mississippi River Basin in GIS, previously developed by the University of Minnesota, Department of Soil, Water, and Climate and Mulla et al. (2004). The watershed and landscape characteristics include the following:

• Area of minor watershed (ha) • Soil internal drainage percentage (percentage of well drained soils) • Water erosion potential (tons/ac) • Rainfall factor used in the USLE • Average watershed slope (percent) • Cropland area within 100 meter proximity of surface waters (in ha and percentage) • Total cropland area (in ha and percentage) • Total urban land area (in ha and percentage) • P-index • Geomorphology • Agroecoregions • Karst features • Land area proximity to various surface water types

Figure 2-16 shows the coverage of the eight agroecoregions and the minor watersheds within the basin.

The integrated dataset developed for this study was used to evaluate the relationship between sediment-related variables and watershed characteristics. Figures 2-17 and 2-18 show that there was no significant difference between the median suspended sediment concentrations and turbidity readings for the various minor watershed areas in the basin.

Figure 2-20 shows a comparison of the ecoregion areas listed in the DNR stream survey database and the turbidity readings throughout the basin. The North Central Hardwood Forest ecoregion (3) appears to have significantly lower turbidity readings than the Western Corn Belt Plains ecoregion (5), which has significantly lower readings than the Driftless Area ecoregion (4).

P:\23\62\880\Final Report\Phase I Report.doc 2-26 Figure 2-16 Lower Mississippi River Basin Agroecoregions and Minor Watersheds

Minor Watershed Boundary Agriecoregions Alluvium & Outwash Blufflands Level Plains Rochester Plateau Rolling Moraine Steep Wetter Moraine Steeper Alluvium Undulating Plains

Figure 2-17 Box Plot of Median Suspended Sediment Concentrations versus Watershed Area

P:\23\62\880\Final Report\Phase I Report.doc 2-27 Figure 2-18 Box Plot of Median Turbidity Readings versus Watershed Area

Figure 2-19 Box Plot of Median Turbidity Readings for Each Level III Ecoregion

P:\23\62\880\Final Report\Phase I Report.doc 2-28 Multiple linear regressions were evaluated to predict turbidity readings from watershed characteristics. The results showed that a significant relationship existed with the average watershed slope (r2 = 0.485). None of the other watershed or physical stream characteristics improved the predictive model for this dataset.

Relationship Between Bio-Indicators and Sediment Data Barr compiled biological data from five different sources (WSU, MCES, Lakeville/Farmington, CRWP, and the EDA Biological data). The WSU data consisted of hard copies of field data sheets for both invertebrate and fisheries sampling. Barr staff entered the raw data into an Access database and subsequently calculated HBI and ICI scores, consistent with the methodology contained in Hilsenhoff (1987) and DeShon (1995), respectively. The published IBI scores taken from Mundahl (2001) were also compiled, along with the EDA Biological database data collected by Schmidt and Talmage (2001). The other three sources of biological data consisted of invertebrate sampling, only. For these data sources, the ICI and HBI scores were calculated and compiled.

Figure 2-20 shows a scatterplot matrix of the relationships between the median watershed turbidity readings and the various biological indices. The results show that the small amount of variability in the turbidity data does not result in significant relationships with any of the biological indices.

Figure 2-20 Scatterplot Matrix of Median Turbidity Readings and Biological Indices

P:\23\62\880\Final Report\Phase I Report.doc 2-29 Figures 2-21 and 2-22 show that the HBI scores may be more significantly impacted in the watersheds that are currently listed for turbidity, while the ICI scores are not significantly different when comparing watersheds that are listed for turbidity with those that are not listed.

Figure 2-21 Box Plot of HBI Ratings for Impaired Watersheds and Watersheds Not Listed for Turbidity

Figure 2-22 Box Plot of ICI Ratings for Impaired Watersheds and Watersheds Not Listed for Turbidity

Thorn and Anderson (1999) classified all of the rivers in Minnesota based on their associated fish communities. Ten of the nineteen classes of streams are present within the LMR basin. Figure 2-23

P:\23\62\880\Final Report\Phase I Report.doc 2-30 shows how the turbidity readings varied for each of the DNR stream survey classes. The turbidity readings for stream classes 6, 7 and 9 are significantly lower than they are for classes 13, 15, 16 and 17. The primary difference between these two sets of stream classes is that classes 6, 7 and 9 are coldwater streams and classes 13, 15, 16 and 17 are warmwater streams. Stream classes 1 and 2 represent small coldwater streams.

Figure 2-23 Box Plot of ICI Ratings for Impaired Watersheds and Watersheds Not Listed for Turbidity

Multiple linear regressions were completed to evaluate the relationships between the biological indices and the stream and watershed characteristics. The overall dataset was used to evaluate the influence of the physical stream characteristics, alone. The results showed that a significant relationship existed for the HBI scores with the average stream depth and the amount of shade (r2 = 0.499). None of the other physical stream characteristics improved the predictive model for this dataset. There were no significant relationships between the physical stream characteristics and the

P:\23\62\880\Final Report\Phase I Report.doc 2-31 ICI scores or warmwater fish IBI scores. A significant relationship existed between the coldwater fish IBI scores and the average stream width (positive correlation), sinuosity (inversely correlated), and the severity of bank erosion (inversely correlated). However, these three variables explained only explained 20 percent of the variance.

The integrated dataset was used to incorporate the watershed characteristics into the multiple linear regression analysis to predict the median biological indices at the minor watershed scale. The results showed that a significant relationship existed for the HBI scores with the stream gradient (r2 =0.359). None of the other physical stream or watershed characteristics improved the predictive model for this dataset. There was a significant relationship between the ICI scores and the watershed water erosion potential (inversely correlated), urban land use percentage (positively correlated), and the landlocked watershed percentage (inversely correlated) which explained 82 percent of the variance. There were no significant relationships with the warmwater fish IBI scores. A significant relationship existed between the coldwater fish IBI scores and the stream run percentage (inversely correlated). This variable explained approximately 72 percent of the variance in the coldwater fish IBI scores at the minor watershed scale.

Assess Groundwater Influences Related to Stream Sediment Data Figure 2-24 shows the distribution and quantity of the various karst features throughout the basin. The largest concentration of sinkhole and spring features exist within the South Branch Root River watershed. Fillmore County (2002) completed springshed mapping and dye tracing in 1995 to better define groundwater flow patterns in the watershed. The boundaries between many of the basins are still not totally defined. More tracing would need to be done to accomplish this and further evaluate the flow conditions under varying hydrologic conditions. Sediment sampling was not specifically done as part of this effort (Fillmore County, 2002), but TSS samples collected throughout the watershed indicated that the areas downstream of the karst features had lower median concentrations and higher maximum concentrations than the remainder of the watershed. The integrated dataset compiled for this study indicates that the median sediment-related variable measurements are consistent with the surrounding minor watersheds that are not influenced by karst features.

P:\23\62\880\Final Report\Phase I Report.doc 2-32 Figure 2-24 Map of Karst Features and Minor Watershed Boundaries

Minor watershed boundary Karst Feature Sinkhole Spring Stream sink/sieve

Assess Citizen Stream Monitoring Program (CSMP) Data Set This section describes our assessment of how well the CSMP dataset corresponds to the other sediment-related variables and evaluates how other variables might be influencing the volunteer’s perceptions of stream appearance and recreational suitability. Figure 2-25 shows a scatterplot matrix of the sediment-related and CSMP variables from the overall dataset. The figure shows that slight increases in TSS, VSS and/or turbidity result in significant decreases in transparency. There appears to be significant variability in the stream appearance and recreational suitability ratings for the corresponding transparency readings.

P:\23\62\880\Final Report\Phase I Report.doc 2-33 Figure 2-25 Scatterplot Matrix of Sediment-Related and CSMP Variables from Overall Dataset

Figures 2-26 and 2-27 show the relationships between turbidity and stream appearance, as well as turbidity and recreational suitability. Both figures show that, with the exception of the highest rating for each metric, the turbidity readings were not significantly different for stream appearance and recreational suitability ratings of 2 through 5. The turbidity readings were significantly lower for stream appearance and recreational suitability ratings of 1. Multiple linear regressions were completed to evaluate significant relationships with stream appearance and recreational suitability. The results indicated that a significant inverse relationships exist between stream appearance and the transparency tube readings (r2 = 0.548), as well as between recreational suitability and the transparency tube readings (r2 = 0.322). As previously discussed, there is a significant amount of variability associated with each of the CSMP ratings that likely is the result of the subjectivity of the volunteers. This should explain why the transparency tube relationships only explain 32 and 55 percent of the variability associated with recreational suitability and stream appearance, respectively.

P:\23\62\880\Final Report\Phase I Report.doc 2-34 Figure 2-26 Box Plot of Turbidity versus Stream Appearance

Figure 2-27 Box Plot of Turbidity versus Recreational Suitability

P:\23\62\880\Final Report\Phase I Report.doc 2-35 Task 3 – Propose Alternative Expressions of the Sediment Variables

The purpose of this section is to provide recommendations for specific endpoints and alternative alternative expressions of sediment variables. This analysis includes:

• Types of indicators to be considered • Alternate methods to address variability • Temporal averaging considerations • Stream classification • Recommendations for monitoring

Types of Indicators to be Considered The problem of stream sediment pollution in the basin is multifaceted. While agricultural land uses dominate major expanses of the basin, the percentage of cultivated lands responsible for much of the soil erosion is rather small (USDA, 1997 and 2002). Of those cultivated lands, the vast majority are in the corn-soybean rotation, with soybeans becoming the dominant economic crop of necessity for many landowners. Sediment delivery from upland sources varies with soil types, slopes, and management factors. In addition to sediment pollution originating from agricultural lands, channels downstream from urbanizing or suburbanizing watersheds face increased flow and sediment loads, often causing stream channel instability, an effect of which is excessive streambank erosion. While some watershed scale monitoring programs have been initiated in the last 15 years, a comprehensive and sustainable stream monitoring and evaluation system does not currently exist. Stream pollution due to sediment inputs and altered hydrology results in degraded stream channels, a loss of recreational opportunities, and decreased economic activity which result from activities such as fishing, canoeing, and tubing.

The State of Minnesota currently uses water column turbidity as a numerical water quality standard under Minn. Rules Chapter 7050. Turbidity is mainly a function of inorganic particulates, and to a lesser degree, organic particulate matter, in the water column. The turbidity standard is for the protection of aquatic life. The numerical water quality standard for turbidity is 10 Nephelometric Turbidity Units (NTU) for Class 2A waters (cold water fishery, all recreation) and 25 NTU for cool and warm water fishery, all recreation. Waters are considered impaired for turbidity when more than ten percent of the samples exceed the applicable water quality standard. There are currently no ambient stream water quality standards associated with other sediment-related water quality variables such as total suspended

P:\23\62\880\Final Report\Phase I Report.doc 3-1 solids or suspended sediment concentration. In addition, there currently are no recreational water quality standards associated with sediment-related variables. Current recreational water quality standards are only tied to measures of eutrophication.

The damage to aquatic habitats by heavier sediment particles, due to sedimentation and embeddedness, cannot be accounted for by measuring turbidity or total suspended solids (TSS). Pool depth decreases as heavier particles settle out in the stream channel. In addition, the quality of aquatic habitat is also dependent, to some degree, on factors such as stream stability, cover and shade.

Total Maximum Daily Loads (TMDLs) are intended to assess sources of pollutants that are causing an impairment and allocate reductions from the sources so that a water quality standard can be achieved in the stream. A variety of factors can affect the selection of the appropriate TMDL indicators, including scientific and technical validity as well as practical management decisions (EPA, 1999). Indicators should be logically related to the applicable numeric and narrative water quality standards. Practical considerations include choosing indicators that can be suitably monitored using cost-effective means and selecting indicators that are consistent with data that is already available and for which information concerning reference and natural background conditions can be utilized. Other than turbidity, the following indicators also warrant consideration for the LMR basin:

P:\23\62\880\Final Report\Phase I Report.doc 3-2 o Percentage of pools o Shade o Cover • Biological indicators o Benthic invertebrate indices o Fish • Riparian/hillslope indicators o Riparian buffer width and vegetation character • Recreational indicators o Stream appearance o Recreational suitability

Several of these possible TMDL indicators, that can be used with water column turbidity, were evaluated and described in the memorandum prepared as part of the second task of this project. The relevant sections of that task are further described here.

Figure 3-1 shows the relationships between several of the sediment-related variables using all of the available paired data collected from the water quality monitoring stations in the LMR basin. The best-fit linear regression and confidence intervals are included for each plot. The results show that TSS, turbidity and VSS are each significantly correlated with each other and VSS is also significantly correlated with chlorophyll-a. Chlorophyll-a does not significantly influence turbidity readings and TSS concentrations, based on the overall dataset. Stepwise multiple linear regression analyses were done and showed that TSS explained 92% of the variance associated with the turbidity readings.

P:\23\62\880\Final Report\Phase I Report.doc 3-3 Figure 3-1 Scatterplot Matrix of Sediment-Related Variables

Correlation analyses were also completed for all of the remaining sediment-related variables to test the statistical significance of the relationships using all of the paired water quality data collected in the basin. The results of these analyses indicate the following:

• TSS and turbidity are significantly correlated with several of the residue parameters

• Transparency tube readings are significantly correlated with TSS, turbidity, and VSS

• TSS, VSS, turbidity, transparency tube readings and SSC are significantly correlated with instantaneous and average daily flow readings and inversely correlated with alkalinity

• Turbidity and transparency tube readings are significantly correlated with total organic carbon and transparency is inversely correlated with chlorophyll-a

P:\23\62\880\Final Report\Phase I Report.doc 3-4 • Transparency is significantly correlated with stream physical appearance ratings and transparency, TSS and turbidity are significantly correlated with the recreational suitability ratings

Turbidity readings varied significantly throughout the dataset compiled for this study. Maximum turbidity readings approached 4,000 NTUs in some cases. The fall and winter turbidity values are significantly lower than the other seasons for some of the major watersheds. In general, the turbidity readings for the Upper Iowa, Cannon, Cedar and Miss. R.-Lake Pepin watersheds are less variable and significantly lower than the remaining watersheds. The readings for the Zumbro and Root River watersheds are significantly higher in the early spring and the readings in the Shell Rock River watershed are significantly higher than most of the remaining watersheds in the summer. Multiple linear regressions were evaluated to predict turbidity readings from watershed characteristics. The results showed that a significant relationship existed with the average watershed slope (r2 =0.485). None of the other watershed or physical stream characteristics improved the predictive model for this dataset.

Our assessment also evaluated how well the CSMP dataset corresponds to the other sediment-related variables and evaluates how other variables might be influencing the volunteer’s perceptions of stream appearance and recreational suitability. Slight increases in TSS, VSS and/or turbidity result in significant decreases in transparency. There appears to be significant variability in the stream appearance and recreational suitability ratings for the corresponding transparency readings. Multiple linear regressions indicated that significant inverse relationships exist between stream appearance and the transparency tube readings (r2 = 0.548), as well as between recreational suitability and the transparency tube readings (r2 = 0.322). As previously discussed, there is a significant amount of variability associated with each of the CSMP ratings that likely is the result of the subjectivity of the volunteers. This should explain why the transparency tube relationships only explain 32 and 55 percent of the variability associated with recreational suitability and stream appearance, respectively.

The following DNR stream survey and classification data was included in our analysis, as described in Thorn and Anderson (1999):

• Watershed • Instream Flow Region • Ecoregion • % POOL • % RIFFLE

P:\23\62\880\Final Report\Phase I Report.doc 3-5 • %RUN • Ave. Width • Ave. Depth • W:D Ratio • Flow • Gradient • Sinuosity • %Fines • Cover • Bank Erosion Severity • Shade • Alkalinity • Ecological Classification

The results of multiple linear regression analyses to predict the median biological indices at the minor watershed scale indicated that a significant relationship existed for the HBI scores and stream gradient (r2 = 0.359). None of the other physical stream or watershed characteristics improved the predictive model for this dataset. There was a significant relationship between the ICI scores and the watershed water erosion potential (inversely correlated), urban land use percentage (positively correlated), and the landlocked watershed percentage (inversely correlated) which explained 82 percent of the variance. There were no significant relationships with the warmwater fish IBI scores. A significant relationship existed between the coldwater fish IBI scores and the stream run percentage (inversely correlated). This variable explained approximately 72 percent of the variance in the coldwater fish IBI scores at the minor watershed scale.

Our analysis also determined that additional particle size distribution data should be collected for bed sediment to further evaluate the relationship between stream embeddedness and aquatic habitat quality in the basin. There was not enough existing data to thoroughly evaluate these relationships.

One goal of this study was to develop dimensionless sediment transport curves by completing a regression analysis on the available pairs of suspended sediment concentration and instantaneous discharge data for as many of the USGS sites as possible. Our evaluation of the available data showed that the following six gage sites had more than 30 pairs of suspended sediment concentrations and instantaneous discharge readings in the basin:

• NORTH FORK WHITEWATER RIVER NEAR ELBA, MN

P:\23\62\880\Final Report\Phase I Report.doc 3-6 • WHITEWATER RIVER NEAR BEAVER, MN • GARVIN BROOK NEAR MINNESOTA CITY, MN • ROOT RIVER NEAR HOUSTON, MN • SOUTH FORK ROOT RIVER NEAR HOUSTON, MN • CEDAR RIVER NEAR AUSTIN, MN

Figure 3-2 provides an example plot of suspended sediment concentration versus discharge used to determine the concentration at the apparent bankfull flow capacity of each stream. Dividing all of the suspended sediment concentrations by this concentration will make this parameter dimensionless. Dividing each of the corresponding discharge measurements by the bankfull flow will make discharge dimensionless. Plotting the dimensionless suspended sediment versus the dimensionless discharge, along with the power function regression line, results in the sediment transport curve for each station (see Figure 3-3 for an example).

Since each of the sediment transport curves are dimensionless, they can be plotted together and superimposed to compare the rates of suspended sediment transport per unit change in discharge. In addition, the 95 percent confidence intervals were determined for each of the power function regressions to evaluate the significant differences between the slopes of the curves for each station. Comparing the 95 percent confidence intervals developed for the slope of each of the curves can used be used as a way of comparing stable (reference) streams with stream reaches that may be unstable or in transition. Troendle et al. (2002) did not show significant differences in dimensionless sediment transport were attributable to Rosgen stream type, but they demonstrated that reference sediment transport functions for suspended sediment and bedload appear to function well for stable streams and indicate that departure can be demonstrated for unstable streams. As a result, Pfankuch (1975) stability ratings and Rosgen stream classifications would need to be developed for each of the six USGS gage sites to determine whether one of more of the sites represents a “reference” condition that can be used to assess the relative transport and stability of the remaining USGS sites.

P:\23\62\880\Final Report\Phase I Report.doc 3-7 Figure 3-2 Example Plot of USGS Suspended Sediment versus Discharge

Figure 3-3 Dimensionless Suspended Sediment Transport Curve for Cedar River

P:\23\62\880\Final Report\Phase I Report.doc 3-8 Alternative Methods to Address Variability This section is intended to evaluate a range of methods that can be considered to address variability in the data. Attachment 1 presents the statistics for all of the sediment-related and biological data that have been integrated to the minor watershed areas. Based on a review of the range of values, the skewness, and comparison of the median to the mean, the table indicates that many times the data is skewed, with a few extremely high values compared to the remaining dataset for each sediment- related variable. The table also shows the range of the 95 percent confidence intervals for each dataset, which typically is quite significant for the sediment-related variables in most of the watersheds.

If stable or “reference” stream segments with significant amounts of data can be identified within the basin, then the data could be used as a baseline of what should be expected with the statistics presented in Attachment 1. Use of the geometric mean should also be considered as a way of comparison with reference conditions for each of the indicators discussed here.

Temporal Averaging Considerations This section is intended to discuss temporal averaging considerations by evaluating calculated flow- weighted mean concentrations of sediment data, by season, at sites where adequate flow and water quality data are available and by looking at concentrations at the channel forming flow on a seasonal basis for various sites.

LTRMP has collected and compiled long-term flow and total suspended solids (TSS) concentration data from several of the major Mississippi River tributary monitoring sites and used that data to calculate monthly TSS loadings using LOADEST2 (Crawford, 1998). The monthly flow and TSS loading data was manipulated to determine the long-term average flow-weighted mean concentrations (FWMCs), by season, based on the following assumptions applied to each month of data for each site:

• Early spring, March and April • Late spring, May and June • Summer, July through September • Fall, October and November • Winter, December through February

Table 3-1 shows the results of the LTRMP TSS monitoring for each of the monitoring locations in the basin. The results indicate that:

P:\23\62\880\Final Report\Phase I Report.doc 3-9 Table 3-1 Results of LTRMP Total Suspended Solids Monitoring for Period of Record in Lower Mississippi River Basin

P:\23\62\880\Final Report\Phase I Report.doc 3-10 • The FWMCs are consistently lower in the winter and fall than the other three seasons for all of the monitoring locations

The suspended sediment concentrations were further evaluated, on a seasonal basis, for the same six USGS sites that had been used to develop dimensionless sediment transport curves (see Figures 3-2 and 3-3). Figure 3-4 provides a notched box plot comparison of the dimensionless suspended sediment concentrations between the data for each gage, by season. The suspended sediment concentrations for each gage were made dimensionless by dividing through by the suspended sediment concentration at the bankfull flow rate obtained from the regression of suspended sediment versus discharge (see Figure 3-2). Figure 3-4 shows how the suspended sediment concentrations typically exceed the concentration expected for bankfull flows (1.0 in the dimensionless scale) in the early spring at Garvin Brook near Minnesota City (#05378235) and they are significantly higher than the other seasonal concentrations for all six sites. Figure 3-4 shows that the concentrations at Garvin Brook drop significantly as you proceed from early spring to late spring and summer. The fall and winter concentrations are both significantly lower than the other seasons. The early spring concentrations in the Cedar River at Austin (#05457000) are also quite high relative to the expected bankfull flow concentration and are significantly higher than the other seasons. The late spring concentrations in the Whitewater River near Beaver (#05376800) are significantly higher than the early spring concentrations and the summer concentrations are also high. The other stations do not show much in the way of significant seasonal differences, but Figure 3-4 shows that many of the observed concentrations are considerably lower than the concentration expected under bankfull flow conditions. Figure 3-4 does show that temporal variation should be considered in application of

P:\23\62\880\Final Report\Phase I Report.doc 3-11 water quality standards depending on the state of each of the watershed areas depicted. As previously recommended, these watersheds should be further assessed for stability and their state relative to “reference” conditions before it can be determined that temporal variation should be important.

Figure 3-4 Box Plot of Dimensionless Suspended Sediment versus USGS Gage Site by Season

Stream Classification The overall dataset was used to evaluate the relationships between turbidity and stream class, by season. Figure 3-5 shows that the turbidity readings for the coldwater streams were significantly lower than the warmwater streams for each season. For the coldwater streams, the turbidity readings

P:\23\62\880\Final Report\Phase I Report.doc 3-12 were significantly higher in the early spring compared to the remaining seasons. For the warmwater streams, the summer, early and late spring readings are not significantly different than each other, but are significantly higher than the fall and winter readings.

Figure 3-5 Box Plot of Turbidity Readings by Stream Class and Season

Figure 3-6 shows a comparison of the ecoregion areas listed in the DNR stream survey database and the turbidity readings throughout the basin. The North Central Hardwood Forest ecoregion (3) appears to have significantly lower turbidity readings than the Western Corn Belt Plains ecoregion (5), which has significantly lower readings than the Driftless Area ecoregion (4).

Figures 3-5 and 3-6 show that stream class and location are also likely to play an important role in determining the best attainable conditions for each stream. As a result, “reference” stream reaches will need to be identified for each stream class in each ecoregion, at a minimum. Consideration should also be given to identifying reference reaches within each agroecoregion, as well.

P:\23\62\880\Final Report\Phase I Report.doc 3-13 Figure 3-6 Box Plot of Median Turbidity Readings for Each Level III Ecoregion

Recommendations for Monitoring

P:\23\62\880\Final Report\Phase I Report.doc 3-14 will provide a logical way to select reference conditions that are scientifically defensible and indicative of the best-attainable environment.

P:\23\62\880\Final Report\Phase I Report.doc 3-15 Task 6 – Propose Additional Monitoring Data Collection at the Basin Scale

The purpose of this section is to discuss recommendations for the types of monitoring (including locations, frequencies, etc.) that should be completed in the Lower Mississippi and Cedar River basins to implement TMDL projects and assess their effectiveness over a 25-year period. These recommendations include:

• The appropriate sediment-related variables, as well as the physical and biological stream variables to be monitored

• A preliminary list of stream reaches and sites across the basin that may represent “minimally impacted” or “best-attainable” conditions

• A discussion about a recommended basin-wide monitoring program including:

- Approximate costs for the recommended monitoring program on an annual basis, assuming a 25-year time frame

- The cost-benefit implications of allocating monitoring resources on a basin scale versus smaller scale studies

Water Quality Monitoring in the Lower Mississippi River Basin A considerable number of federal, state, regional, and local governmental agencies have historically conducted a wide variety of water quality monitoring activities throughout the Lower Mississippi River Basin. As is shown in Table 4-1, most monitoring programs have at least some overlap with others, in terms of parameters measured. Distribution of monitoring sites, by subwatershed locations, is shown in Table 4-2. Data from these monitoring programs are all valuable and potentially useful to TMDL study efforts, either for diagnosing problem sources or for demonstrating the effectiveness of remedial measures. Unfortunately, however, many of these monitoring programs are now inactive because of funding cuts. Additionally, the fact these monitoring programs often measure different parameters, according to different protocols, limits their utility when basin-wide assessments are being made.

P:\23\62\880\Final Report\Phase I Report.doc 4-1 Table 4-1 Summary of Available Monitoring Data for Sediment-Related Variables/Lower Mississippi Basin Monitoring Sites by Monitoring Program/Agency

Physiochemical Variables Physical Variables Biological Variables Number of Physical Estimated Total Sediment Monitoring Watershed Suspended Appearance/ Physical Annual Agency Suspended Particle Program Monitoring Sediment Turbidity Residue Recreational Transparency Stream Discharge Invertebrates Fish Cost Per Solids Size Sites (SSC) Suitability Characteristics Site (TSS) Distribution Ratings MPCA Milestone (A*) 10 E E O $3,600 CSMP (A) 133 O E E O $265 Other (A,I) 670 E E,C OE,C Suspended $20K – USGS 17 E O E O O E,C Sediment (I) $65K Water Quality (I) 51 E O EO O E,C Daily Flow (I) 18 C USGS/DNR LTRMP (A) 9 E E $10K - MCES Water Quality (A) 2 E E C $15K Biological (I) 16 E CRWP Water Quality (A) 16 E E E E $2,000 Invertebrates (I) 23 O $2,000

WSU Biology (I) 107 E E $200 Stream Surveys MDNR 548 OEE (A) Dakota Water Quality (A) 15 E E C $3,000 County Fillmore Water Quality (A) 25 E County Lakeville/ Trout Stream (I) 5 E E O E,C O O $6,000 Farmington

NOTE: A—Active, I—Inactive, A*—Milestone monitoring on an approximately four-year rotation. E—Episodic, C—Continuous, O—Occasional

P:\23\62\880\Final Report\Phase I Report.doc 4-2 Table 4-2 Summary of Monitored Sites within the Lower Mississippi River Basin, by Major Watershed (1967-present)

Number of Sites Fillmore Dakota Dakota East CRWP CRWP SWCD Lakeville/ RIVER/ BIOLOGICAL CSMP SWCD/ SWCD/ Side LAKE LTRMP MCES USGS WSU Invertebrates WQ /Root STREAM Major Basin NCRWMO Vermillion Lake Farmington TOTAL River

TOTAL 20 23 99 144 2 4 8 27 62 11 5 2 420 70 108 1018

P:\23\62\880\Final Report\Phase I Report.doc 4-3 Sediment-Related Water Quality Variables Of the 11 different sediment-related water quality variables shown in Table 4-1, three physiochemical parameters (Suspended Sediment Concentration [SSC], Total Suspended Solids [TSS], and Turbidity) along with the physical measures of suspended particle size distribution, and stream discharge at the time samples are collected, are perhaps the most important. If a valid stream sediment flux estimate is to be made, these parameter measurements are essential. The remaining physical and biological measures are also important and serve to gage the adverse impacts of the transported sediment on aquatic biota and the suitability of their stream habitat.

Suspended sediment loads (or yields) are commonly estimated from stream discharge records using a streamflow regression model (i.e., sediment transport curves. Such a model relates sediment flux to stream discharge on some temporal basis. The USGS recently concluded (Christensen et al., 2002) that such models are most properly based on sediment flux estimates calculated from suspended sediment concentration (SSC) data, not total suspended solids (TSS) data. This conclusion stems from the fact that the TSS method, which was originally developed for analyses of wastewater samples, is fundamentally unreliable for analyses of natural-water samples. Because TSS data are produced by analyzing subsamples of a collected natural-water sample obtained by pipette, or by pouring from an open container, a sand-deficient subsample results (Glysson and Grey, 2002). The [SSC] of a sample always equals, and generally exceeds its [TSS], especially at high stream flows. Therefore, [SSC] and [TSS] data collected from natural waters are not comparable and should not be used interchangeably, the USGS has concluded. Previously constructed sediment transport curves based on [TSS] values will underestimate actual sediment yields, therefore.

Currently, none of the state, regional, or local governmental water quality monitoring efforts include measurements of [SSC]. Even the USGS, which did previously collect such data at major sites in the Lower Mississippi River Basin, has discontinued this expensive, labor-intensive monitoring activity (last measured in 1991). Gaging [SSC]s involves the use of highly specialized equipment to conduct that is termed ‘Isokinetic, Depth-Integrated’ sampling (see Figure 4-1; Wilde et al, 1999). Use of this rather sophisticated sampling method may be limited to rather large, higher order streams, and not useful at small stream sites. Fortunately, however, the USGS has also determined that a suitable surrogate for [SSC] exists, and that surrogate is Turbidity, which is the reduction in the transparency of water due to suspended and dissolved particles. Fortuitously, turbidity is probably the easiest sediment-related water quality parameter to measure with reasonable precision (Anderson and Davic, 2004) and it is almost universally measured by monitoring groups in the Lower Mississippi River Basin. It is also the basis for the MPCA water quality standard.

P:\23\62\880\Final Report\Phase I Report.doc 4-4 Figure 4-1 Equal-width-increment method for collection of water samples (modified from Edwards and Glysson, 1998) Recognizing that it will probably never be financially feasible to measure [SSC] at most sites, it seems prudent to advocate resumed [SSC] monitoring at major gaging stations (usually higher order streams) in order to develop streamflow regression models based on [SSC] correlated to turbidity, that can be extended (by inference, with best professional judgment) to upstream gaging sites. Such model development will require concurrent monitoring of [SSC], suspended sediment particle size distribution, and turbidity for an extended period of time to establish correlative relationships valid over the expected range of stream discharge rates at gaging sites. It must also be followed by periodic repeat monitoring to verify the continued validity and applicability of these correlations. Such monitoring will require continuous flow gaging, as well as ‘isokinetic, depth-integrated’

P:\23\62\880\Final Report\Phase I Report.doc 4-5 sampling conducted (preferably) on a turbidity-threshold activated basis. Continuous turbidity recording may also be desirable, especially if such methods are likely to be employed at the other gaging sites to which the regression models may be extended for estimation of sediment yields.

Finally, suspended sediment particle size distribution measurements are mandatory. For a sediment transport curve developed at one monitoring station, based on turbidity data, to be transferable to another station, suspended particle size distributions must be similar. Otherwise, similar turbidities at the different sites may correspond to disparate suspended sediment concentrations. These disparities could relate to either differences in watershed soil types or differing streambed composition, or both. They could also relate to the presence of algae in stream reaches below impoundments, a fact which suggests that the volatile fraction of suspended sediment should also be quantified.

Other Pertinent Water Quality Parameters Water quality monitoring programs should be robust in terms of their scope, and anticipate the need for analyses of other parameters of general interest. Certainly, in southeastern Minnesota, a highly agricultural area, nutrient export from watersheds should be gaged in addition to sediment yields.

Total nitrogen and total phosphorus, plus their soluble components (i.e., NH4-N, NO3+NO2-N, and SRP or OP), which fuel algal growth in lakes and streams, should be monitored, at a minimum. Depending on local conditions and watershed land use, additional water quality variables may warrant inclusion in a monitoring program that focuses primarily on turbidity and sediment transport (e.g., heavy metals and oil & grease in urbanized areas, dissolved oxygen downstream from wastewater treatment facilities).

Physical and Biological Stream Variables The adverse impacts of increased watershed sediment yields generally fall on aquatic biota, and may result in significant biotic impairments. These impacts on stream dwelling organisms may be either direct (e.g., smothering by gill fouling, or interference with sight-feeding activities) or indirect through habitat destruction. Transported sediments may originate from upland erosion, or from stream channel down-cutting and widening as a result of increased frequencies of bankfull or greater discharges. In order to relate aquatic biota (numbers and diversity) and stream habitat quality to observed turbidities and sediment transport rates, a concomitant program of physical and biological stream monitoring is desirable. Historically, only the Minnesota Department of Natural Resources and Winona State University staff have attempted any type of stream fish surveys. (A one-time trout survey was also conducted by the Cities of Lakeville and Farmington on South Creek in 1995.)

P:\23\62\880\Final Report\Phase I Report.doc 4-6 Benthic macroinvertebrate monitoring for both abundance and diversity of taxa) is conducted by a somewhat larger number of stream monitoring groups (MCES, CRWP, WSU and MDNR), but sampling protocols and periodicity vary widely. And, until recently, only the MDNR has previously attempted any sort of physical or ecological stream classification. The MPCA now conducts a stream monitoring program, similar to the MDNR stream survey for fish, that includes both physical and biological data collection. MPCA field staff monitored selected streams in the Lower Mississippi River Basin for the first time this year (2004), but those data were not yet available for consideration in this memorandum. Both the MPCA and MDNR stream surveys employ methods that are similar, and are summarized in the following paragraphs.

Physical Classification of Streams The purpose of a physical classification of stream type is to provide evidence of how the stream has been affected by changing land use, how the stream will behave under existing conditions, and to indicate how restoration may be approached if a portion of the stream is different or becomes different from its normal or expected condition.

Methodology. TheclassificationsystemusedisthatdevelopedbyDavidL.Rosgen(Rosgen,1996). Rosgen’s classification system describes a stream on a reach by reach basis. A single stream can have several different stream types over its length. The system defines a stream type according to the shape, pattern, and profile of the reach. In particular, the following parameters are used to classify a stream type: the degree of entrenchment of the channel, the ratio of width to depth, degree of channel meandering or sinuosity, channel material, and the water surface slope. Some of these parameters are illustrated on Figure 4-2.

The Rosgen classification system has seven stream types, ranging from A to G as shown on Figure 4-3. Each type has six subclasses corresponding to the predominant bed material present in the reach. These subclasses are numbered from 1 to 6: 1 is bedrock, 2 is boulder, 3 is cobble, 4 is gravel, 5 is sand, and 6 is silt. This allows for 42 combinations of stream type. A description of these stream types is given in Table 4-3. This table gives a range of values of the criteria used for stream classification. These ranges are those most commonly observed. The actual observed values can lie outside of these ranges by a certain extent as a function of the continuum concept. This concept recognizes that as the stream type changes, the criteria will adjust accordingly.

P:\23\62\880\Final Report\Phase I Report.doc 4-7 Figure 4-2 Channel Parameters Defined (from Rosgen, 1996)

P:\23\62\880\Final Report\Phase I Report.doc 4-8 Figure 4-3 Delineation of Major Stream Types showing Profile, Cross-Sectional and Plan View Morphology (from Rosgen, 1996)

P:\23\62\880\Final Report\Phase I Report.doc 4-9 Table 4-3 Summary of Criteria for Physical Classification of Streams (from Rosgen, 1996)

Stream Entrenchment W/D General Description Sinuosity Slope Landform/Soils/Features Type Ratio Ratio A Steep, entrenched, debris transport < 1.4 < 12 1.0 to 1.2 0.04 to 0.10 High relief, mountainous environments; entrenched streams and confined streams with cascading reaches; frequent deep pools. B Moderately entrenched, moderate 1.4 to 2.2 > 12 > 12 0.02 to 0.039 Moderate relief, colluvial deposition and/or residual gradient, riffle dominated channel soils. Moderate entrenchment and W/D ratio. Narrow, with infrequent pools. Very stable. gently sloping valleys. Rapids with occasional pools. C Low gradient, meandering alluvial >2.2 >12 >1.4 <0.02 Broad valleys with terraces, associated with channels with broad, well defined floodplains, alluvial soils. Slightly entrenched with floodplains. well-defined meandering channel. Riffle-pool bed morphology. D Braided channel; very wide channel n/a > 40 n/a < 0.04 Broad valleys with alluvial and colluvial fans. with eroding banks. Abundant sediment supply. E Low gradient, meandering stream > 2.2 < 12 > 1.5 < 0.02 Broad valley/meadows. Alluvial materials with with low width/depth ratio and little floodplain. Highly sinuous with stable, well vegetated deposition. Very efficient and banks. Riffle-pool morphology with very low stable. width/depth ratio. F Entrenched meandering riffle/pool <1.4 >12 >1.4 <0.02 Entrenched in highly weathered material. Gentle channel on low gradients with high gradients with high W/D ratio. Meandering, laterally width/depth ratio. unstable with high bank-erosion rates. Riffle-pool morphology. G Entrenched Gully step/pool with low <1.4 <12 >1.2 0.02to0.039 Gully, step-pool morphology with moderate slopes and width/depth ratio on moderate low W/D ratio. Narrow valleys, or deeply incised in gradients alluvial or colluvial materials. Unstable, with grade control problems and high bank erosion rates.

P:\23\62\880\Final Report\Phase I Report.doc 4-10 The entrenchment ratio is defined as the ratio of the width of the flood-prone area to the bankfull surface width of the channel. The flood-prone area is defined as the width measured at an elevation which is determined at twice the maximum bankfull depth. Field observation shows this elevation to be a frequent flood (50-year) or less, rather than a rare flood elevation. The entrenchment ratio describes the interrelationship of the river to its valley and landform features. This interrelationship determines whether the river is deeply incised or entrenched in the valley floor or deposit feature. The entrenchment ratio indicates whether the flat area adjacent to the channel is a frequent floodplain, a terrace (abandoned floodplain), or is outside the flood-prone area.

The width/depth ratio is the ratio of bankfull channel width to bankfull mean depth; it is used to describe the dimension and shape of the channel. Bankfull discharge occurs at approximately the 1.6-year recurrence interval and is referenced to as the dominant discharge for the stream. Hydraulic geometry and sediment transport relations rely heavily on the frequency and magnitude of bankfull discharge.

Sinuosity is the ratio of stream length to valley length. It can also be described as the ratio of valley slope to channel slope. Sinuosity can often be determined from aerial photographs, and interpretations can then be made of slope, channel materials, and entrenchment. Values of sinuosity appear to be modified by bedrock control, roads, channel confinement, and vegetation types, among other factors. Generally, as gradient and particle size decrease, there is a corresponding increase in sinuosity. Meander geometry characteristics are directly related to sinuosity following minimum expenditure of energy concepts. Based on these relations and ease of determination, sinuosity is one of the delineative criteria for stream classification.

Channel materials refer to bed and bank materials of the stream. Channel material is critical for sediment transport and hydraulic influences, and also modifies the form, plan, and profile of the stream. Interpretations of biological function and stability also require this information. The channel materials can often be predicted from soils maps and geologic information. They can also be determined in the field, and at the detailed level the materials are measured and the size plotted on percent distribution paper.

The water surface slope is of major importance to the morphological character of the channel and its sediment, hydraulic, and biological function. It is determined by measuring the difference in water surface elevation per unit stream length. It is typically measured through at least 20 channel widths or two meander wavelengths (Rosgen). In broad level delineations, slope can be estimated by measuring sinuosity from aerial photos and measuring valley slope from topographic maps.

P:\23\62\880\Final Report\Phase I Report.doc 4-11 Sensitivity to Disturbance by Stream Type. Different types of streams have differing sensitivities to disturbance and varying recovery potential. Sensitivity and recovery potential are interrelated to sediment supply in the stream, bank erosion potential, and the influence of vegetation on controlling bank erosion. These differences are itemized by stream type in Table 4-4.

The information in Table 4-4 is best applied when a stream's behavior can be predicted by appearance and by extrapolating information from similar stream types. Knowing the sensitivity of each stream type allows for better management of the stream systems, potential impact assessment, and risk analysis.

Ecological Use Classification of Streams A stream is an ecosystem made up of climate, watershed, banks, bed, water volume, water quality, and biota (i.e., fish, macroinvertebrates, etc.). A stream’s use is dependent upon the natural characteristics of the entire ecosystem, and on the cultural alterations or impacts which have occurred or are occurring. Present stream uses are always affected by both natural characteristics and cultural impacts. Potential uses are always affected by natural characteristics, and may be affected by cultural impacts. The management goal of a stream generally focuses on the control of cultural impacts affecting stream use. Ecological use classification of streams is a management tool enabling stream management decisions to be based upon realistic uses of streams. The ecological use classification is based on a stream’s potential to support a given use in the absence of controllable impacts, and is not based on the present state of the biological community. The potential use of a stream represents the maximum attainable use of the stream under existing habitat conditions.

Methodology. Procedures for classifying streams have been developed by the Minnesota Department of Natural Resources (Thorn and Anderson, 1999) to provide a scientific method for designating uses according to a stream's natural ability to support a certain warmwater or coldwater fish community. The objective of the classification system is to provide a basis for making and supporting recreational fisheries management decisions. The need for classifying surface waters is based on the recognition that all surface waters will not support the same fish communities, and that different stream classes may require different levels of water quality to support their fisheries.

P:\23\62\880\Final Report\Phase I Report.doc 4-12 Table 4-4 Management Interpretations of various stream types (from Rosgen, 1996)

Streambank Vegetation Sensitivity to Recovery Sediment Erosion Controlling Stream Type Disturbancea Potentialb Supplyc Potential Influenced A1 Very low Excellent Very low Very low Negligible A2 Very low Excellent Very low Very low Negligible A3 Very high Very poor Very high Very high Negligible A4 Extreme Very poor Very high Very high Negligible A5 Extreme Very poor Very high Very high Negligible A6 High Poor High High Negligible

B1 Very low Excellent Very low Very low Negligible B2 Very low Excellent Very low Very low Negligible B3 Low Excellent Low Low Moderate B4 Moderate Excellent Moderate Low Moderate B5 Moderate Excellent Moderate Moderate Moderate B6 Moderate Excellent Moderate Low Moderate

C1 Low Very good Very low Low Moderate C2 Low Very good Low Low Moderate C3 Moderate Good Moderate Moderate Very high C4 Very high Good High Very high Very high C5 Very high Fair Very high Very high Very high C6 Very high Good High High Very high

D3 Very high Poor Very high Very high Moderate D4 Very high Poor Very high Very high Moderate D5 Very high Poor Very high Very high Moderate D6 High Poor High High moderate

Da4 Moderate Good Very low Low Very high DA5 Moderate Good Low Low Very high DA6 Moderate Good Very low Very low Very high

E3 High Good Low Moderate Very high E4 Very high Good Moderate High Very high E5 Very high Good Moderate High Very high E6 Very high Good Low Moderate Very high

F1 Low Fair Low Moderate Low F2 Low Fair Moderate Moderate Low F3 Moderate Poor Very high Very high Moderate F4 Extreme Poor Very high Very high Moderate F5 Very high Poor Very high Very high Moderate F6 Very high Fair High Very high Moderate

G1 Low Good Low Low Low G2 Moderate Fair Moderate Moderate Low G3 Very high Poor Very high Very high High G4 Extreme Very poor Very high Very high High G5 Extreme Very poor Very high Very high High G6 Very high Poor High High High a Includes increases in streamflow magnitude and timing and/or sediment increases. b Assumes natural recovery once cause of instability is corrected. c Includes suspended and bedload from channel derived sources and/or from stream adjacent slopes. d Vegetation that influences width/depth ratio-stability.

P:\23\62\880\Final Report\Phase I Report.doc 4-13 The Provisional Classification System for Minnesota Rivers with Associated Fish Communities considers both physical and chemical variables recorded in stream surveys. These variables are listed below, in Table 4-5:

Table 4-5 Variables from stream surveys used to classify Minnesota rivers and streams

Variable Abbreviation % pool Pool %riffle Riffle %run Run Width (feet) AveW Depth (feet) AveD Width:Depth a WD Flow (cubic feet/second) Flow Gradient (feet/mile) Grad Sinuosity Sinu % fines b Fines Bank erosion c Ero Shade d Shade Cover e Cover Alkalinity (ppm) Alk f Ecological classification CW, WW a Mean width/mean depth (wetted width and depth under low flow conditions) b Sum of sand, silt, clay, and muck c 1 = light, 2 = moderate, 3 = severe d 1 = light = 0-25% shaded, 2 = moderate = 26-75% shaded, 3 = heavy = >75% shaded e Sum of ratings (1 = scarce, 2 = occasional, 3 = frequent) for each type of cover (log jams, overhanging vegetation, undercut banks, instream vegetation, boulders) f CW = coldwater, WW = warmwater

This classification system results in Minnesota river and stream reaches being distributed into 19 distinct classes. These classes are summarized in Table 4-6. Stream reaches evaluated by this methodology may be further evaluated to determine attainable habitat improvements by predicting habitat score improvements achievable from the implementation of remedial measures. Currently, a similar protocol is being followed by the MPCA in their “Milestone” monitoring program; a copy of which is appended to this Technical Memorandum.

P:\23\62\880\Final Report\Phase I Report.doc 4-14 Table 4-6 Minnesota river and stream classes with associated fish communities

Stream Class 1 Streams of this soft-water, coldwater class were small (width <10 ft) to medium sized (width 10-20 ft), had moderate gradient (500-100 ft/mi), and little apparent degradation (1:1 pool/riffle morphology, very good cover, heavy shade, little bank erosion, and few fine substrates). Seventy percent of the stream reaches in this class were in the forested Lake Superior watershed, and all but one were upstream from the natural fish barriers near their mouths in Lake Superior. Only five species were common, including introduced brook trout and steelhead. Stream Class 2 This soft-water, coldwater class includes small streams (width <10 ft) with riffle morphology, light bank erosion, high gradient (>100 ft/mi), moderate cover, and low sinuosity. Of the 79% of the streams in this class that were in the Lake Superior watershed, 89% are direct tributaries to Lake Superior, and most were found downstream of the natural fish barrier. Rainbow trout was the only common fish species, and brook trout were moderately common. The mean score for PC2 showed poor suitability for cyprinids. Stream Class 3 The soft-water streams in this class were large for coldwater streams (width >20 ft), and had riffle morphology, moderate gradients, light bank erosion, a high WD, and moderate cover. A majority of the stream reaches were in the Lake Superior watershed. Seven fish species were common, including brook trout. Stream Class 4 This widely distributed class was present in 15 different watersheds, and included soft-water and hard-water streams. The medium sized streams (width 10-20 ft) in this coldwater class had 9:1 pool/riffle morphology, a low mean WD, moderate- good cover, and light bank erosion. Although this class included many of the streams within the native brook trout range of east-central Minnesota, trout were not common – only found 37% of the streams – and the mean score for PC6 was negative. This is the most suitable class for finescale dace and pearl dace (PC3). Stream Class 5 The hard-water streams in this coldwater class were small (<10 ft) to medium sized (width 10-20 ft) with light bank erosion, low WD and sinuosity, poor cover, and abundant fine substrates. Most streams were north-central Minnesota, and were outside the native brook trout range. Only four nongame fish species were common. Introduced brook trout and brown trout were present in 30% of the streams of this class. Stream Class 6 Streams in this coldwater class were small (<10 ft) to medium sized (width 10-20 ft), >50% fine substrates, good fish cover, and high sinuosity. Most streams were in southeast and north-central Minnesota, and were managed for trout. Ten species were common, including brook trout, brown trout, and cyprinids. Stream Class 7 The hard-water streams of this class were small (<10 ft), >50% fine substrates, light bank erosion, moderate cover, and low WD. This class was found throughout Minnesota, but was most common in southeast and central Minnesota. Only five species of fish were common, including brook trout. The streams in this class were most suitable for the blackside darter (PC4).

P:\23\62\880\Final Report\Phase I Report.doc 4-15 Table 4-6 Minnesota river and stream classes with associated fish communities

Stream Class 8 Streams in this hard-water, coldwater class were small (<10 ft) to medium sized (width 10-20 ft), and had 2:1 pool/riffle morphology, severe bank erosion (erosion=3), moderate cover, and <50% fine substrates. Most streams were in southeast Minnesota. The 10 common fish species included cyprinids, brook trout, and brown trout. Stream Class 9 The large (width >20 ft) hard-water streams in this coldwater class were described by 3:1 pool/riffle morphology, <50% fine substrates, good cover, and high sinuosity. This class includes most of the larger trout streams of southeast Minnesota, and most stream reaches in the Root River watershed of southeast Minnesota. Ten fish species were common, including brook trout, brown trout, and cyprinids. This is the only stream class were slimy sculpin were common and there was a high mean score for PC10. Stream Class 10 Streams in this hard-water, coldwater class were intermediate in size (width 10-20 ft), and had a pool/riffle morphology of 4:1, >75% fine substrates, and very low abundance of fish cover. Most streams were in southeast Minnesota, and seven fish species, including brown trout, were common. Stream Class 11 This class of large, warmwater streams (width >40 ft) was described by pool/riffle/run morphology, few fine substrates, light bank erosion, and little shade. These streams were most frequent in the northern one-half of the state. Eight species, including northern pike, were common. The mean score for PC1 shows moderate suitability for the smallmouth bass component, however, smallmouth bass were present in only 24% of the streams in this class. The mean score for PC8 shows moderate suitability for the walleye component, but they were present in only 12% of the streams in the class. Stream Class 12 This class of large, warmwater streams (>40 ft) had run morphology and light bank erosion. Most were in the Upper Mississippi River watershed of central and north-central Minnesota. Only five fish species were common, and the low score for PC2 showed low suitability for cyprinids. Stream Class 13 This class of medium sized, warmwater streams (width 15-50 ft) was characterized by a 1:1 pool/riffle morphology, <50% fine substrates, and light bank erosion. The class was distributed throughout east-central, south-east, and north-central Minnesota. Seven fish species were common and did not include game fish. Stream Class 14 The medium sized streams (width 15-40 ft) in this warmwater class had 9:1 pool/riffle morphology, good cover, and light bank erosion and shade. This class was found in the upper Mississippi River drainage and east-central Minnesota. Five fish species, including northern pike, were common in streams of this class. Stream Class 15 The large streams in this warmwater class (width >40 ft) had 9:1 pool/riffle morphology, poor cover, and light bank erosion and shade. Most streams were in southern and east-central Minnesota. Twelve fish species, including walleye, were common, and the high score for PC8 showed this class to be most suitable for walleye. The mean score for PC1 shows moderate suitability for the smallmouth bass component and smallmouth bass were moderately common (in 36% of the streams).

P:\23\62\880\Final Report\Phase I Report.doc 4-16 Table 4-6 Minnesota river and stream classes with associated fish communities

Stream Class 16 The medium sized warmwater streams (width 15-40 ft) of this class had 4:1 pool/riffle morphology, high sinuosity, and severe bank erosion. This class was found in agricultural southeast, south-central, and west-central Minnesota. More fish species were common in the class (20) than in any other class, and the mean score for PC1 identifies this class as the most suitable for the smallmouth bass component. Smallmouth bass were moderately common (in 31% of the streams). The mean score for PC8 indicates moderate suitability for the walleye component, but walleye were present only in 24% of the streams in this class. Stream Class 17 The small streams of this warmwater class (width <15 ft) were distinguished by 4:1 pool/riffle morphology and poor fish cover. Seventy-five percent of the reaches were in agricultural southeast and south-central Minnesota. Seven of the nine fish species that were common were cyprinids. Stream Class 18 Streams of this warmwater class were small (width <15 ft) with a low WD ratio, poor fish cover, and light bank erosion. This class was widely distributed in agricultural Minnesota, and the seven common fish species did not include game fish. Stream Class 19 This class of large warmwater streams (>40 ft) had run-dominated morphology and good fish cover. Most stream reaches were found in agricultural Minnesota. Eleven species were common, and the mean score for PC8 indicates this class is suitable for the walleye component. The mean score for PC7 identifies this class as most suitable for the Iowa darter.

P:\23\62\880\Final Report\Phase I Report.doc 4-17 “Minimally Impacted-” or “Best Attainable-”Reference Stream Reaches Without conducting an extensive evaluation of the physical and ecological use classifications of streams in the Lower Mississippi River Basin, it is impossible to identify all stream reaches that might serve as “Minimally Impacted-” or “Best Attainable- reference reaches for goal setting purposes. Little, if any, of these classifications have been completed to date. The very best indicators of stream quality that are currently available reside in benthic macroinvertebrate data collected by staff and students from Winona State University. (Fewer similar data have also been collected less extensively by the Metropolitan Council Environmental Services and the Cannon River Watershed Partnership.) As relatively immobile organisms attached to the streambed, benthic invertebrates are exposed to the varying conditions of streamflow and water quality. Consequently, they integrate the effects of temporal variations in these parameters into their population statistics, both abundance and diversity.

All available benthic microinvertebrate data inventoried for this project were subjected to analyses according to the Hilsenhoff Biotic Index methodology (Hilsenhoff, 1987) and an HBI score was calculatedforeachmonitoringsite,ona0to10scale.

Biotic Index* Water Quality Degree of Pollution 0.00 – 3.50 Excellent No apparent pollution 3.51 – 4.50 Very Good Possible slight pollution 4.51 – 5.50 Good Some pollution 5.51 – 6.50 Fair Fairly significant pollution 6.51 – 7.50 Fairly Poor Significant pollution 7.51 – 8.50 Poor Very significant pollution 8.51 – 10.0 Very Poor Severe pollution

* Based on abundance-weighted pollution tolerance levels of aquatic benthos.

Sites receiving an “Excellent” rating (i.e., 0.0 < HBI < 3.50) are considered to be candidate reference sites that are indicative of “Minimally Impacted-” or “Best Attainable-” reference conditions, pending later field verification. These candidate sites number only five, and include those listed in Table 4-7, with average HBI scores shown. All sites receiving “Excellent” scores are in either the “Mississippi River-Winona” (Whitewater-Garvin Brook) or “Root River” (South Branch) major watersheds (Figure 4-4).

P:\23\62\880\Final Report\Phase I Report.doc 4-18 Table 4-7 Hilsenhoff Biotic Index (HBI) values for stream monitoring sites within the Lower Mississippi River Basin that rated either “Excellent” or “Very Good,” plus highest HBI scores reported for sites within other major watersheds that had ratings of “Good,” or lower

Condition Sampling Station Rating Major Watershed [Name (ID Code)] Data Source HBI Score Excellent Miss R-Winona E. Indian Cr. (EIC-2) WSU 3.30 Miss R-Winona S. Fork Whitewater R. (SBWW-3) WSU 3.41 Miss R-Winona Crow Spring (MBWW-K-1) WSU 3.44 Root River South Branch Root River (SBRR-13) WSU 2.55 Root River South Branch Root River (SBRR-14) WSU 2.92 Very Good Cannon River Cannon River (LCH-1) CRWP 3.94 Cannon River Cannon River (LCR-12) CRWP 4.33 Cannon River Prairie Creek (PCR-8) CRWP 4.39 Cannon River Straight Rive (SRF-30) CRWP 4.42 Miss R-Winona Trout Creek (TVC-3) WSU 3.52 Miss R-Winona Rollingstone Creek (RC-K-1) WSU 3.56 Miss R-Winona Garvin Brook (GB-Lower) WSU 3.58 Miss R-Winona Crow Spring (UMBWW-1) WSU 3.62 Miss R-Winona Trout Creek (TVC-1) WSU 3.63 Miss R-Winona Trout Creek (TVC-Mid) WSU 3.66 Miss R-Winona Whitewater River (MWR-6) WSU 3.69 Miss R-Winona Garvin Brook (GB-1) WSU 3.73 Miss R-Winona South Fork Whitewater River (SBWW-2) WSU 3.74 Miss R-Winona Whitewater River (MWR-4) WSU 3.82 Miss R-Winona E Indian Creek (EIC-1) WSU 3.83 Miss R-Winona Whitewater River (MWR-5) WSU 3.87 Miss R-Winona S Fork Whitewater River (SBWW-4) WSU 3.91 Miss R-Winona Beaver Creek (BC-2) WSU 3.92 Miss R-Winona S Fork Whitewater River (SBWW-2) WSU 3.94 Miss R-Winona S Fork Whitewater River (SBWW-5) WSU 3.96 Miss R-Winona S Fork Whitewater River (LSBWW-1) WSU 3.97 Miss R-Winona Unknown Watershed Name (SWT-1) WSU 3.98 Miss R-Winona Unknown Watershed Name (SWT-3) WSU 3.99 Miss R-Winona Beaver Creek (BC-1) WSU 4.03 Miss R-Winona Garvin Brook (DGB) WSU 4.06 Miss R-Winona N Fork Whitewater River (NWR-1) WSU 4.10 Miss R-Winona Whitewater River (MWR-3) WSU 4.12 Miss R-Winona Crow Spring (MWR-7) WSU 4.13 Miss R-Winona Garvin Brook (SGB-K-1) WSU 4.17 Miss R-Winona S Fork Whitewater River (SWR-1) WSU 4.20 Miss R-Winona Logan Brook (ULC-K-1) WSU 4.26 Miss R-Winona Trout Run (UTR-1) WSU 4.28 Miss R-Winona N Fork Whitewater River (NWR-9) WSU 4.34 Miss R-Winona N Fork Whitewater River (NWR-2) WSU 4.40 Miss R-Winona N Fork Whitewater River (NWR-8) WSU 4.44 Miss R-Winona Trout Run (TR-2) WSU 4.46 Miss R-Winona N Fork Whitewater River (NWR-3) WSU 4.47 Root River South Branch Root River (SBRR-11) WSU 3.54 Root River South Branch Root River (SBRR-4) WSU 3.81 Root River South Branch Root River (SBRR-5) WSU 3.99 Root River South Branch Root River (SBRR-6) WSU 4.12 Root River South Branch Root River (SBRR-8) WSU 4.12 Root River South Branch Root River (SBRR-1) WSU 4.14 Root River South Branch Root River (SBRR-7) WSU 4.34 Root River South Branch Root River (SBRR-10) WSU 4.41 Good Miss R & L Pepin Vermillion River (#9) Lakeville 4.74 No Data Cedar River ND Miss R-LaCrescent ND Miss River-Reno ND Shell Rock River ND Wapsipinican River ND Winnebago River ND Zumbro River ND

P:\23\62\880\Final Report\Phase I Report.doc 4-19 I MISS R & L PEPIN

52.5 0 5 10 15

Miles (!G Project Area Monitoring Site (!VG HBI Rating MISS R & L PEPIN (!VG (!E Excellent (!VG !(X CANNON RIVER (!VG Very Good (!G Good ZUMBRO RIVER (!X High Quality Based on Anecdotal Information (!VG VG (!E !(X (! (!VG MISS R-Winona VG (!VG VG (! (!VG (! VG (!VG(!VG(! MISS R-La Crescent !(X (!VG VG (!VG (!VG (!VG (!VG(! (!VG (!VG (!VG (!VG VG!VGVG VG (!VG(!VG(!(!E(! (! (!VG (!VG(!VG (!VG (!VG(!E(!VG

SHELL ROCK RIVER ROOT RIVER

(!VGX X (!VG !((!VG !((!E (!VG VG (!VG E (!VG (! (!X (!VG !( Figure 4-4 Locations of Preliminarily Recommended Reference Sites, Based on HBI Scores WINNEBAGO RIVER CEDAR RIVER WAPSIPINICAN RIVER UPPER IOWA RIVER UPPER IOWA RIVER MISS R-Reno ("E" and "VG" sites only) Barr Footer: Date: 12/16/2004 12:15:38 PM File: User: I:\Projects\23\62\880\Gis\Maps\ArcMap\Excellent_VeryGood_Good_HBIs.mxd SAS Numerous other monitoring sites, some within the Cannon River watershed, and the remainder within either the Whitewater-Garvin Brook portion of the Mississippi River-Winona watershed or the South Branch portion of the Root River watershed, averaged “Very Good” HBI ratings. These and the best scoring site in each of other major watersheds, along with their HBI scores, also appear in Table 4-7, and may be more indicative of “Best Attainable” conditions, given current watershed land use practices. No benthic macroinvertebrate or HBI data were available from six of the lower Mississippi River basin’s ten major watersheds, or from the Cedar River watershed.

Fish surveys conducted between 1994 and 1999, by Winona State University, have also shown excellent Index of Biotic Integrity (IBI, a fish community statistic) ratings for Beaver Creek, a tributary to the Lower Whitewater River, and East Indian Creek, a direct tributary to the Mississippi River. These coldwater streams could potentially be added to the preliminary list of “Minimally Impacted-” or “Best Attainable-” reference reaches. Similarly, four other stream reaches have also been suggested by MPCA staff as candidate reference sites, based on anecdotal evidence. They include:

Upper South Branch Root River near Warmwater stream with stable banks, connected to the Mower-Fillmore Line floodplain, decent perennial vegetation in wider riparian zone. Canfield Creek and Forestville Creek Higher quality trout streams, the lower segments of which are contained within Forestville SP. Maple Creek Tributary to the Straight River near Owatonna. High quality riparian zone with numerous wetlands. Waterville Creek Stable flows, lower sediment loads (observed, not measured), larger intact Hans Marsh in watershed.

The relatively small number of monitoring sites within the lower Mississippi River basin that rate either “Excellent” or “Very Good,” and the total lack of benthic invertebrate data from the Cedar River watershed and six of the Lower Mississippi River Basin’s ten major watersheds points out the need for additional data collection. Future monitoring should include concurrent physical, chemical, and biological sampling, and should be coordinated by the MPCA to ensure uniformity in monitoring protocols, and relatively uniform distribution of monitoring sites (initially, at least). This type of program will allow resource managers to assess current conditions, basin-wide, at first, and to home in on apparent problem areas, late, wherever they are suspected or known to exist.

Initial distribution of monitoring sites should (access permitting) cover stream reaches of all numerical orders to ensure that the complete gradient of water quality and benthic habitat conditions

P:\23\62\880\Final Report\Phase I Report.doc 4-21 are described in the collected data sets. In general, it is better to collect a comprehensive set of data from all reach orders on a relatively few representative streams within each watershed than it would be to dilute the monitoring effort over many streams. Results from such a monitoring plan will then provide data upon which relationships between cause and effect variables can be developed. These relationships can then be transferred to other similar streams through the application of computer simulation modeling techniques. Model predictions can later be validated by monitoring that is refocused on the initially unmonitored streams, if necessary.

Recommended Basin-Wide Monitoring Program Future water quality monitoring of sediment-related variables in streams within the Lower Mississippi River Basin should be approached on a systematic basis, with one agency (presumably the MPCA) coordinating the sampling efforts of other state, regional, and local groups. The goals of the future monitoring should be, initially, to determine:

1. Watershed sediment yields estimated from sediment transport relationships developed from collected data 2. Physical Stream Classifications, by stream reach 3. Ecological Use Classifications, by stream reach 4. Abundance and diversity of aquatic biota 5. Interrelationships between monitored parameters 6. Impaired stream reaches, actual or suspected, to be confirmed by later, refocused monitoring

Accomplishment of these initial goals will require continued cooperation from resource management agencies involved in previous monitoring efforts. In addition to spreading cost and workload more broadly, their continued involvement also promotes increased public awareness of water quality problems and stakeholder involvement in TMDL projects to resolve those problems.

Scope The general purpose of water quality monitoring at all sampling sites should be to characterize the quantity and quality of watershed runoff in relation to watershed land use practices. The best way of characterizing watershed land use is probably through the use of agroecoregion data (Hatch et al., 2001; see Figure 4-5), which groups land into areas with common physiography, soil types, and agricultural cropping practices, principal among other attributes. As is shown on Figure 4-5 and Table 4-8, each of the major watersheds within the Lower Mississippi River Basin is comprised of areas that fall into several different agroecoregions. In some watersheds, a single agroecoregion

P:\23\62\880\Final Report\Phase I Report.doc 4-22 I MISS R & L PEPIN 502.5

Miles Project Area Major Watersheds MISS R & L PEPIN Agroecoregions

CANNON RIVER Alluvium & Outwash Blufflands ZUMBRO RIVER Level Plains Rochester Plateau Rolling Moraine Steep Wetter Moraine MISS R-Winona Steeper Alluvium

MISS R-La Crescent Undulating Plains

SHELL ROCK RIVER ROOT RIVER

Figure 4-5 Agroecoregions Within the Lower Mississippi River Basin Area of WINNEBAGO RIVER CEDAR RIVER WAPSIPINICAN RIVER UPPER IOWA RIVER UPPER IOWA RIVER MISS R-Reno Minnesota Barr Footer: Date: 12/16/2004 4:25:27 PM File: User: I:\Projects\23\62\880\Gis\Maps\ArcMap\Agriecoregions_LowerMinnesota.mxd tja Table 4-8 Distribution of Agroecoregion Types within Major Watersheds of the Lower Mississippi River Basin

Area (acres) Steep Alluvium & Level Rochester Rolling Wetter Steeper Undulating Watershed Name Outwash Blufflands Plains Plateau Moraine Moraine Alluvium Plains TOTAL CANNON RIVER 141,997 67,745 1,938 56,451 641,087 427 10,927 20,410 940,984 CEDAR RIVER 87,476 0 145,466 0 120,000 0 0 98,721 451,662 MISS R & L PEPIN 178,695 105,704 0 17,544 70,003 6,489 4,787 321 383,544 MISS R-La Crescent 5,775 45,067 0 0 0 0 3,015 0 53,857 MISS R-Reno 14,880 82,433 0 13,312 0 0 5,812 0 116,437 MISS R-Winona 56,649 206,569 0 132,600 0 0 5,963 15,085 416,865 ROOT RIVER 35,965 481,434 15,858 271,739 0 0 34,136 222,456 1,061,587 SHELL ROCK RIVER 18,156 0 0 0 137,953 0 0 0 156,109 UPPER IOWA RIVER 1,885 22,139 0 38,055 0 0 0 75,337 137,417 WAPSIPINICAN RIVER 0 0 0 0 0 0 0 7,538 7,538 WINNEBAGO RIVER 14,305 0 0 0 30,617 0 0 0 44,921 ZUMBRO RIVER 61,275 174,889 122,615 311,699 30,443 0 19,433 189,995 910,349 TOTAL 617,059 1,185,980 285,877 841,401 1,030,103 6,916 84,072 629,863 4,681,270

P:\23\62\880\Final Report\Phase I Report.doc 4-24 predominates, and, in other cases, as many as three or four are significant. It is recommended that long-term flow gaging and water quality monitoring stations be established at locations on streams that drain areas comprised of a single agroecoregion. This would evidence unambiguous relationships between data that are not confounded by the effects of runoff from dissimilar watershed areas. Monitoring at these sampling sites should include:

• Continuous discharge gaging

• Water quality monitoring of:

- Suspended sediment concentration ([SSC], total and volatile)

- Particle size distribution

- Turbidity (continuous recorder, best; turbidity tube, acceptable)

- Total and volatile suspended solids ([TSS] and [VSS])

- - + - Nutrients ([TN], [NO2 +NO3 -N], [NH4 -N], [TP], and [SRP] or [OP])

• Surveys of adjacent stream reaches for:

- Physical classification

- Ecological use classification

- Benthic macroinvertebrates

- Fish populations

It may be possible to monitor a site in one watershed and extrapolate its data to areas of like agroecoregion classification in another, but caution should be exercised when doing so. At a minimum, stream monitoring sites gaging runoff from the ten agroecoregions present in the Lower Mississippi River Basin should be sampled, concurrently, for a period of approximately five years, we recommend. Thereafter, suspended sediment concentration monitoring may be discontinued, temporarily, provided sufficient data have been collected and watershed land use is unchanged. Resumed suspended sediment concentration monitoring, every fifth year, will be necessary to revalidate sediment transport relationships. Continued, longer-term suspended sediment concentration monitoring may be warranted at a limited subset of the intensively monitored sties to account for climatic variability, to assess effectiveness of BMP implementation, and to assist in the quantification of bedload movement, where it is significant. During the five-year period of intensive monitoring, other sites distributed throughout each watershed should also be monitored for as many

P:\23\62\880\Final Report\Phase I Report.doc 4-25 of the parameters on the preceding list as possible. This is unlikely to include suspended sediment concentrations and continuous flow gaging because of cost considerations. Instead, “Volunteer-” level monitoring of the other parameters will likely occur, episodically.

The number of stream sites monitored will undoubtedly be limited by funds available to collect data, so their placement should be strategic. First priority should be given to additional sites on the streams where suspended sediment concentration data are being collected, in order to characterize conditions over all stream reach orders. Second priority should be given to similar stream order- related progressions of sites on other streams where suspended sediment concentration data are not being collected, but where known or suspected improvements exist. Lowest priority should be given to isolated monitoring sites that do not coordinate well with the other more intensively monitored sites. The actual number of monitoring sites established per major watershed will depend on the complexity of each watershed’s drainage network and its total stream miles.

Costs and Cost-Benefit Implications To estimate costs of future recommended stream monitoring in the Lower Mississippi River Basin, four different sampling programs are assumed to operate over the next 25 years (see Table 4-9). It is further assumed that “Intensive” level monitoring of stream sites at agroecoregion boundaries will be conducted by the MPCA, and the estimated per station annual cost ($50,000) of monitoring is based on the USGS cost estimate presented in Table 4-1. “Volunteer” level monitoring, it is assumed, will be done by citizen volunteers with oversight and data processing performed by MPCA staff, or by technical personnel from local or regional governmental agencies. The “Volunteer+” or “Intermediate” level monitoring is assumed to be done by a more highly trained and better equipped subset of citizen volunteers with increased involvement of MPCA staff and other professionals (e.g., biologists from Winona State University). Cost estimates for these monitoring activities were estimated jointly by Barr and MPCA staff. Annual cost totals shown in Table 4-9 are all calculated according to present-day unit costs. No attempt has been made to adjust them upward to account for inflation.

P:\23\62\880\Final Report\Phase I Report.doc 4-26 Table 4-9 Ongoing and Recommended Monitoring in the Lower Mississippi River Basin to Support Sediment TMDLs

Total Cost Annual Years ($1,000) Total Cost Number Cost per Monitoring Program of Sites Site 1 2 3 4 5 6 7 8 9 10111213141516171819202122232425 "Intensive" level monitoring at agroecoregion boundaries (base flow & storm event basis), including: 25 $50,000 X X X X X X X X X $11,250 $11,250,000 - Continuous Flow Gaging - Suspended Sediment Concentration - Turbidity - Suspended Particle Size Distribution - Nutrients (N & P) - Suspended Solids (TSS & VSS) - Benthic Macroinvertebrate Surveys "Volunteer" level monitoring (i.e., Citizens' Starting Stream Monitoring Program, CSMP) at with 133 distributed sites, including:sites and $800 X X X X X X X X X X X X X X X X X X X X X X X X X $3,732 $3,732,000 increasing - Stream Stage Measurement to 200 - Turbidity sites by Year 10 -Precipitation "Intermediate" or "Volunteer +" level monitoring at distributed sites, including: $4,000 X X X X X X X X X X X X X X X X X X X X X X X X X $2,460 $2,460,000 Starting - Continuous Flow Gaging with 3 - Turbidity sites and increasing - Suspended Particle Size Distribution to 30 - Nutrients (N & P) sites by Year 10 - Suspended Solids (TSS & VSS) - Benthic Macroinvertebrate Surveys Fish Surveys, including 25 $6,500 X X X X X X X $1,138 $1,137,500 - Physical Stream Classification - Ecological Use Classification

Total Cost ($1,000) $1,531 $1,386 $1,404 $1,422 $1,603 $208 $226 $244 $425 $1,530 $280 $280 $443 $280 $1,530 $280 $443 $280 $280 $1,530 $443 $280 $280 $280 $1,693 $18,580 $18,579,500

P:\23\62\880\Final Report\Phase I Report.doc 4-27 Costs of the recommended stream monitoring are highest during the initial five-year period (ca., $1.5 million, annually) when intensive monitoring of suspended sediment concentrations at agroecoregion boundaries is being done to develop sediment transport curves. Costs range between approximately $200,000 and $425,000 for the following four years, depending on whether or not fish surveys are being collected. Annual cost rises back to about $1.5 million in the tenth year when suspended sediment concentration monitoring resumes to revalidate sediment transport curves developed from data collected during years one through five. This spending pattern is recurrent, thereafter, through Year 25.

Most all the costs shown in Table 4-9 will be MPCA costs. Agency costs could be reduced somewhat if local and/or regional governmental agencies can be persuaded to conduct a portion of the recommended monitoring at their own cost. Also, the MDNR may be able to perform some of the fish surveys to complement similar MPCA surveys. These fish surveys may be performed on a staggered schedule to avoid a glut of work that would otherwise have to be completed each fourth year. This would also help to even-out annual costs, somewhat.

Allocation of sampling sites amongst the watersheds comprising the Lower Mississippi River Basin should be made proportional to watershed areas or aggregate stream mileage. Within each watershed, these allocated sampling stations should then be distributed according to stream order, again on a relative drainage area basis. These allocation processes should be conducted with the best professional judgment of MPCA staff who are familiar with the basin. Until such a process is completed, the exact locations of monitoring sites should probably not be prescribed. However, the stream order and drainage area information presented on Figure 4-6 and Table 4-10 does provide the basis for allocating the 200 recommended sampling stations amongst the 10 watersheds that comprise the basin. A preliminary distribution of sites, allocated to watersheds according to aggregate stream mileage, and to stream orders within watersheds according to drainage areas is also shown in Table 4-10.

P:\23\62\880\Final Report\Phase I Report.doc 4-28 I MISS R & L PEPIN

52.5 0 5 10 15

Miles

Major Watersheds MISS R & L PEPIN Project Area Stream Order

CANNON RIVER 1 2 ZUMBRO RIVER 3 4 5 Catchment Stream Order 1 MISS R-Winona 2 MISS R-La Crescent 3 4 5

SHELL ROCK RIVER ROOT RIVER

Figure 4-6 Lower Mississippi River Basin Stream Orders WINNEBAGO RIVER CEDAR RIVER WAPSIPINICAN RIVER UPPER IOWA RIVER UPPER IOWA RIVER MISS R-Reno (Based on 250K DEM) Barr Footer: Date: 12/15/2004 3:33:37 PM File: User: I:\Projects\23\62\880\Gis\Maps\ArcMap\Watersheds_StreamOrder.mxd SAS Table 4-10 Allocation of Stream Monitoring Sites amongst Major Watersheds within the Lower Mississippi River Basin based on Aggregate Stream Mileage and Catchment Areas, according to Stream Order

A. Initial Allocation based on Aggregate Stream Mileage Total River Number of Sites Watershed Miles per Watershed CANNON RIVER 749 42 CEDAR RIVER 340 19 MISS R & L PEPIN 303 17 MISS R-La Crescent 30 2 MISS R-Reno 71 4 MISS R-Winona 298 16 ROOT RIVER 856 47 SHELL ROCK RIVER 110 6 UPPER IOWA RIVER 79 4 WAPSIPINICAN RIVER 3 0 WINNEBAGO RIVER 35 2 ZUMBRO RIVER 733 41 TOTAL 3607 200

B. Suballocation based on Catchment Areas, according to Stream Order Catchment Stream Order Area (acres) Watershed Name 1st Order 2nd Order 3rd Order 4th Order 5th Order Total CANNON RIVER 565,931 152,552 140,107 66,943 0 925,532 CEDAR RIVER 295,050 90,586 30,787 22,869 9,729 449,021 MISS R & L PEPIN 223,709 72,407 20,238 30,376 0 346,730 MISS R-La Crescent 26,04017,03700043,077 MISS R-Reno 67,772 14,949 13,676 0 0 96,396 MISS R-Winona 244,710 67,713 45,400 26,985 0 384,808 ROOT RIVER 642,653 225,896 105,767 38,507 49,852 1,062,674 SHELL ROCK RIVER 105,422 23,079 10,171 16,030 0 154,703 UPPER IOWA RIVER 101,974 21,410 4,202 0 0 127,586 WAPSIPINICAN RIVER 6,296 00006,296 WINNEBAGO RIVER 31,396 7,955 2,288 0 0 41,639 ZUMBRO RIVER 558,646 163,645 113,129 21,661 48,907 905,989 TOTAL 2,869,599 857,229 485,764 223,371 108,488 4,544,452

Number of Monitoring Sites per Stream Order Watershed Name 1st Order 2nd Order 3rd Order 4th Order 5th Order Total CANNONRIVER 26 763042 CEDARRIVER 13 411019 MISSR&LPEPIN 11 411017 MISSR-LaCrescent 1 10002 MISSR-Reno 2 11004 MISS R-Winona 10 321016 ROOTRIVER 281052247 SHELLROCKRIVER 4 10106 UPPER IOWA RIVER 3 10004 WAPSIPINICAN RIVER 0 00000 WINNEBAGO RIVER 2 00002 ZUMBRORIVER 25 851241 TOTAL 125 40 21 10 4 200

P:\23\62\880\Final Report\Phase I Report.doc 4-30 References

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P:\23\62\880\Final Report\Phase I Report.doc REF-4 Minnesota Pollution Control Agency. 2003a. 2002 Report on the Water Quality of Minnesota Streams. Citizen Stream-Monitoring Program. Environmental Outcomes Division. Minnesota Pollution Control Agency. 2003b. Personal communication, Dave Morrison, MPCA Regional Office, Rochester, Minnesota. Minnesota Pollution Control Agency. 2004. Guidance Manual For Assessing the Quality of Minnesota Surface Waters for the Determination of Impairment. 305(b) Report and 303(d) List. Environmental Outcomes Division. Mower County and the City of Austin. 1992. East Side Lake Water Quality Improvement Project. Phase 1 Clean Water Partnership diagnostic study. Report completed by Bonestroo, Rosene, Anderlik & Associates. (Section 2 and Appendix B contains sediment data and load estimations). Mower County. 2001. Water quality study of the Cedar River and tributaries in Mower County. Carol Mostrom (author). [TSS and transparency at 15 sites] Mulla, D.J., P.H. Gowda, G.J. Wilson and H.M. Runke. 2004. Estimating Phosphorus Losses from Agricultural Lands for MPCA’s Detailed Assessment of Phosphorus Sources to Minnesota Watersheds. Mundahl, N.D. 1999. Whitewater Watershed Project: 1998 Fish, Benthic Macroinvertebrate, and Habitat Assessments. Final Report. Winona State University. Mundahl, N.D. 2001. Whitewater Watershed Project: Analysis of Instream and Riparian Habitat Assessments and Fish and Aquatic Invertebrate Biomonitoring, 1994-2000. Final Report. Winona State University. Mundahl, N.D. 1994. Whitewater Sampling and Analysis Project: Physical and Biotic Assessments of Stream Sites Within and Near the Whitewater River Watershed. Final Report. Winona State University. Mundahl, N.D. 1995. Whitewater Watershed Project: 1995 Fish, Benthic Macroinvertebrate, and Habitat Assessments. Final Report. Winona State University. Mundahl, N.D., B.A. Nerbonne and B. Vondracek. 1996. Whitewater Watershed Project: 1996 Fish, Benthic Macroinvertebrate, and Habitat Assessments. Interim Report. Mundahl, N.D., B.A. Nerbonne and B. Vondracek. 1997. Whitewater Watershed Project: 1997 Fish, Benthic Macroinvertebrate, and Habitat Assessments. Interim Report. Natural Resources Conservation Service, U.S. Forest Service and Minnesota Pollution Control Agency. 1996. Watershed Plan and Environmental Assessment. Whitewater River Watershed Project. Nerbonne, B.A. 1999. Effects of Land Use and Sediment on the Distribution of Benthic Invertebrates and Fish in the Whitewater River Watershed of Minnesota. M.S. Thesis. University of Minnesota. Newcombe, C.P. and Jensen, J.O.T. 1996. Channel suspended sediment and fisheries: A synthesis for quantitative assessment of risk and impact. North American Journal of Fisheries Management: 16(4):693 –727. Olmsted County Land Use Plan Annual Reports. Rochester-Olmsted Planning Dept.

P:\23\62\880\Final Report\Phase I Report.doc REF-5 Payne, G. 2001. Suspended-Sediment Transport Curves for Selected Streams in the Minnesota River Basin. Pfannkuch. 1975. Stream Reach Inventory and Channel Stability Evaluation. A Watershed Management Procedure. U.S. Department of Agriculture and Forest Service/Northern Region. Porterfield, G. 1972. Computation of fluvial-sediment discharge. U.S. Geological Survey. Techniques of Water-Resources Investigations, Book 3, Chapter C3. Potter, K.W. 1991. Hydrological impacts of changing land management practices in a moderate- sized agricultural catchment. Water Resources Research 27(5): 845-855. Pruitt, B. 2002. Use of Turbidity by State Agencies. Proceedings of the Seventh Federal Interagency Sedimentation Conference, Reno, NV. March 25-29, 2001. Radtke, D.B. 1997. Bottom-Material Samples. U.S. Geological Survey. Techniques of Water- Resources Investigations, Book 9, Chapter A8. Rice County Comprehensive Plan, 2002. Rice County, Minnesota. (www.co.rice.mn.us)See Planning and Zoning Department. Rippley, Richard J. 1991. Stream Survey, Whitewater Watershed Project. (Stream bank erosion field survey). Rochester Public Works Department. 2003. Stormwater Management. www.rochestermn.gov/stormwater . Rosgen, D.L. A Stream Channel Stability Assessment Methodology. Rosgen, D. 1996. Applied River Morphology. Wildland Hydrology. ISBN 0-9653289-0-2. Rubin, D.M. and D.J. Topping. 2001. What regulates suspended-sediment transport in a given setting? Grain size of bed sediment or flow? Proceedings of the Seventh Federal Interagency Sedimentation Conference, Reno, NV. March 25-29, 2001. Schmidt, K. and P. Talmage. 2001. Fish Community Surveys of Twin Cities Metropolitan Area Streams. Minnesota Department of Natural Resources. Special Publication 156. Schottler, S. 2002. Identification of Sediment Sources in an Agricultural Watershed.FinalReport to the Legislative Commission on Minnesota’s Resources. St. Croix Watershed Research Station. Science Museum of Minnesota. Sekely, A.C., Mulla, D.J. and D.W. Bauer. 2002. Streambank slumping and its contribution to the phosphorus and suspended sediment loads of the Blue Earth River, Minnesota.JournalofSoil and Water Conservation. 57(5):243-250. Simon, A. 1989. The discharge of sediment in channelized alluvial streams. Water Resources Bulletin. 25(6): 1177-1188. Simon, A. 1994. Gradation Processes and Channel Evolution in Modified West Tennessee Streams: Process, Response, and Form. U.S. Geological Survey Professional Paper 1470. Simon, A., Dickerson, W., and A. Heins. 2003. Suspended-sediment transport rates at the 1.5-year recurrence interval for ecoregions of the United States: transport conditions at the bankfull and effective discharge? Geomorphology: Article in Press.

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P:\23\62\880\Final Report\Phase I Report.doc REF-7 Thorn, W.C. and Anderson, C.S. 2001. Evaluating habitat quality from stream survey variables. Minnesota Department of Natural Resources, Fish Management Report 35. Thorn, W.C. and Anderson, C.S, Lorenzen, W.E., Hendrickson, D.L., and Wagner, J.W. 1997. A review of trout management in Southeast Minnesota streams. North American J. of Fisheries Management 17:860-872. (Investigational Report 466). Tornes, L.H. 1986. Suspended sediment in Minnesota streams. U.S. Geological Survey. Water- Resources Investigations Report 85-4312. St. Paul, MN. Trimble, S.W. and Lund, S.W. 1982. Soil conservation and the reduction of erosion and sedimentation in the Coon Creek Basin, Wisconsin. Geological Survey Professional Paper 1234. Trimble, S.W. and Knox, J.C. 1984. Comment on “Erosion, Redeposition, and Delivery of Sediment to Midwestern Streams” by D.C. Wilkin and S.J. Hebel. Water Resources Research 20(9): 1317- 1318. Trimble, S.W. 1993. The distributed sediment budget model and watershed management in the paleozoic plateau of the Upper Midwestern United States. Physical Geography 14(3): 285-303. Troendle, C.A., , Rosgen, D.L., Ryan, S.E., Porth, L.S., Nankervis, J.M. 2002. Developing a Reference sediment transport relationship. www.wildlandhydrology.com/assets/FINAL_sed2000paper.pdf Turcios, L.M. and J.R. Gray. 2001. U.S.Geological Survey sediment and ancillary data on the world wide web. Seventh Federal Interagency Sedimentation Conference. Reno, NV. University of Minnesota. 2002. Tillage best management practices for water quality protection in Southeastern Minnesota. College of Agricultural, Food and Environmental Sciences and Extension Service. Authors: Randall, Gyles, Wagar, T.L., Senjem, N.B., Busman, L.M., and Moncrief, J.F. Upper Mississippi River Basin Association. 2004. Upper Mississippi River Water Quality: The State’s Approaches to Clean Water Act Monitoring, Assessment, and Impairment Decisions. Upper North Branch Root River Diagnostic Study, Lake Florence Restoration Feasibility Study, and Watershed Plan – Environmental Assessment. 1992. USDA, 1996. Sediment budget Whitewater River Watershed. P.L. 566 project report. USDA, 1997. National Resources Inventory. USDA, 2002. National Resources Inventory (NRI) data. Data cited are tentative, subject to pending corrections by NRCS. Changes are not expected to be major. USDA, Minnesota Agricultural Statistics Service. County reports and annual bulletins. U.S. Department of Agriculture, Soil Conservation Service, Economics, Statistics, and Cooperatives Service, and Forest Service. 1980. Southeast Minnesota Tributaries Basin Report. In cooperation with the Southern Minnesota Rivers Basin Board. U.S. Environmental Protection Agency. 1999. Protocol for Developing Sediment TMDLs. First Edition. Watershed Branch, Assessment and Watershed Protection Division, Office of Water. EPA 841-B-99-004.

P:\23\62\880\Final Report\Phase I Report.doc REF-8 U.S. Geological Survey. 2000. USGS Policy on Collection and Use of Total Suspended Solids Data. Office of Water Quality Technical Memorandum No. 2001.03. Wall, D.B., S.A. McGuire and J.A. Magner. 1989. Water Quality Monitoring and Assessment in the Garvin Brook Rural Clean Water Project Area. Minnesota Pollution Control Agency. Division of Water Quality. Wang, L., Lyons, J. and Kanehl, P. 2002. Effects of watershed best management practices on habitat and fish in Wisconsin streams. J. American Water Resources Assoc. 38(3):663-680. Wang, L., Lyons, J., Kanehl, P. and R. Gatti. 1997. Influences of watershed land use on habitat quality and biotic integrity in Wisconsin streams. Fisheries. 22(6):6-12. Waters, T. 1997. The streams and rivers of Minnesota. University of Minnesota Press. Waters,T.F.,ed.1995.Sediment in Streams: Sources, Biological Effects, and Control. American Fisheries Society. 251 pp. Watkins, J. 2002. How to use your transparency tube and the internet to compute a phosphorus load for the Straight River. Cannon River Watershed Partnership. Wilde, F.D., D.B. Radtke, J. Gibs and R.T. Iwatsubo. 1999. Collection of Water Samples. U.S. Geological Survey. Techniques of Water-Resources Investigations, Book 9, Chapter A4. Wilson, G.J. 2003. Final Streambank Erosion Technical Memorandum. Detailed Assessment of Phosphorus Sources to Minnesota Watersheds. Wren, D.G. 2002. Surrogate techniques for suspended sediment measurement. Turbidity and Other Sediment Surrogates Workshop. Reno, NV. Wolman,M.G.andJ.P.Miller.1960. Magnitude and frequency of forces in geomorphic processes. Journal of Geology. 68(1):54-74. Wotzka, Paul J. 2001. Why, What, Where and How of Water Quality Monitoring in Southeastern Minnesota. Presentation to the Watershed Workshop, Water Quality in the Lower Mississippi River Basin, March 1, 2001, Rochester, Minnesota. Ziegler, A.H. 2002. Issues related to use of turbidity measurements as a surrogate for suspended sediment. Turbidity and Other Sediment Surrogates Workshop. Reno, NV. Zischke, J., G. Schnobrich, C. Robbins, J. Arthur, M. Vlasek and M. McGrath. 1996. Assessment of Water Quality in Streams of the Cannon River Watershed Basin. Cannon River Watershed Partnership.

Data Sources Barr Engineering Company. Biological and water quality monitoring data collected for Cities of Lakeville and Farmington. Biological and water quality monitoring data collected for Cannon River Watershed Partnership. Bonestroo and Associates. Water quality monitoring data collected for East Side Lake Improvement Project.

P:\23\62\880\Final Report\Phase I Report.doc REF-9 Dakota County Soil and Water Conservation District. Water quality monitoring data collected for Vermillion River and North Cannon River Water Management Organizations. Fillmore County Soil and Water Conservation District. Water quality monitoring data collected for Root River watershed. Gowda, P.H. and D.J. Mulla. 2004. Lower Mississippi River Basin GIS Watershed Characteristics. University of Minnesota. Department of Soil, Water, and Climate. Long Term Resource Monitoring Program. Water quality monitoring data at the mouth of major Mississippi River tributaries. MDNR Brown Trout database data. MDNR Fisheries Survey data. MDNR Stream Survey data. Described in Thorn and Anderson, 1999. Metropolitan Council biological and water quality monitoring data. MPCA Citizen Stream Monitoring Program Reports (1999, 2000, 2001 and 2002) with data tables for the Lower Mississippi River Basin. MPCA Environmental Data Access (EDA) database downloads for biological, Modern and Legacy STORET data and database station locations in GIS shapefile. MPCA Summary of Historical Monitoring Data by Watershed – Lower Mississippi River Basin in Minnesota –includes data from various sources for TSS, TSVS, SSC, SFS, FD, and bedload. Turbidity and TSS box plots by MPCA monitoring site. U.S. Army Corps of Engineers. Locations of dams within the State of Minnesota derived from USACE NID data. Later combined with Kittle Numbers in MDNR’s 24K GIS stream coverage. U.S. Geological Survey. Suspended sediment, flow, stage and water quality monitoring data collected from various stations for the Lower Mississippi River Basin. Winona State University biological monitoring data.

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P:\23\62\880\Final Report\Phase I Report.doc REF-11

Major Watershed Minor Watershed Statistic Susp. Sediment Turbidity Appearance Rec. Suitability TSS Transp. Tube HBI ICI WWFISHIBI CWFISHIBI Zumbro River Zumbro R N of cases 23.0 441.0 473.0 479.0 254.0 580.0 0.00 0.0 0.0 0.0 Zumbro River Zumbro R Minimum 31.0 1.0 1.0 1.0 1.6 2.0 Zumbro River Zumbro R Maximum 8550.0 1192.0 5.0 5.0 1682.0 60.0 Zumbro River Zumbro R Median 372.0 10.0 2.0 3.0 19.6 32.0 Zumbro River Zumbro R Mean 1051.3 33.4 3.2 3.3 70.5 33.8 Zumbro River Zumbro R 95% CI Upper 1895.3 42.9 3.4 3.4 91.1 35.3 0.00 0.0 0.0 0.0 Zumbro River Zumbro R 95% CI Lower 207.4 23.8 3.1 3.2 49.9 32.4 0.00 0.0 0.0 0.0 Zumbro River Zumbro R Standard Dev 1951.6 102.0 1.6 0.9 166.8 18.1 Zumbro River Zumbro R C.V. 1.9 3.1 0.5 0.3 2.4 0.5 Zumbro River Zumbro R Skewness(G1) 3.0 7.0 0.0 -0.4 5.5 0.1 Cannon River Wolf Cr N of cases 0.0 26.0 188.0 188.0 5.0 188.0 0.00 3.0 0.0 0.0 Cannon River Wolf Cr Minimum 0.7 1.0 1.0 33.0 1.5 22.0 Cannon River Wolf Cr Maximum 32.0 5.0 5.0 55.0 60.0 38.0 Cannon River Wolf Cr Median 5.5 4.5 4.0 42.0 16.0 30.0 Cannon River Wolf Cr Mean 7.5 4.0 3.4 44.8 22.8 30.0 Cannon River Wolf Cr 95% CI Upper 0.0 10.4 4.2 3.5 56.1 25.2 0.00 49.9 0.0 0.0 Cannon River Wolf Cr 95% CI Lower 0.0 4.5 3.7 3.2 33.5 20.3 0.00 10.1 0.0 0.0 Cannon River Wolf Cr Standard Dev 7.3 1.5 1.2 9.1 17.0 8.0 Cannon River Wolf Cr C.V. 1.0 0.4 0.4 0.2 0.7 0.3 Cannon River Wolf Cr Skewness(G1) 1.9 -1.3 -0.8 -0.1 1.2 Miss R & L P Wells Cr N of cases 0.0 60.0 155.0 163.0 60.0 243.0 0.00 0.0 0.0 0.0 Miss R & L P Wells Cr Minimum 2.0 1.0 1.0 1.9 0.0 Miss R & L P Wells Cr Maximum 400.0 5.0 5.0 290.6 60.0 Miss R & L P Wells Cr Median 6.0 2.0 2.0 9.0 60.0 Miss R & L P Wells Cr Mean 19.0 2.2 2.2 19.8 49.4 Miss R & L P Wells Cr 95% CI Upper 0.0 33.8 2.5 2.4 31.0 51.4 0.00 0.0 0.0 0.0 Miss R & L P Wells Cr 95% CI Lower 0.0 4.1 2.0 2.0 8.5 47.5 0.00 0.0 0.0 0.0 Miss R & L P Wells Cr Standard Dev 57.6 1.5 1.3 43.5 15.6 Miss R & L P Wells Cr C.V. 3.0 0.7 0.6 2.2 0.3 Miss R & L P Wells Cr Skewness(G1) 5.8 0.9 0.9 5.1 -1.6 Miss R & L P Vermillion R N of cases 1.0 1039.0 71.0 74.0 1931.0 108.0 9.00 7.0 0.0 0.0 Miss R & L P Vermillion R Minimum 32.0 0.5 1.0 1.0 0.0 5.0 4.10 42.3 Miss R & L P Vermillion R Maximum 32.0 1740.0 5.0 4.0 1889.0 60.0 6.02 44.1 Miss R & L P Vermillion R Median 32.0 6.5 2.0 3.0 10.0 60.0 4.95 43.6 Miss R & L P Vermillion R Mean 32.0 17.2 2.5 2.7 23.5 48.8 4.97 43.5 Miss R & L P Vermillion R 95% CI Upper 32.0 21.4 2.8 3.0 26.4 51.9 5.50 44.0 0.0 0.0 Miss R & L P Vermillion R 95% CI Lower 32.0 13.0 2.1 2.4 20.7 45.8 4.45 43.0 0.0 0.0 Miss R & L P Vermillion R Standard Dev 68.4 1.4 1.2 64.1 15.8 0.69 0.6 Miss R & L P Vermillion R C.V. 1.0 4.0 0.6 0.4 2.7 0.3 0.14 0.0 Miss R & L P Vermillion R Skewness(G1) 19.0 0.7 -0.2 16.9 -1.2 0.24 -1.7 Miss R-Winon Trout Run N of cases 0.0 0.0 53.0 53.0 0.0 52.0 61.00 61.0 0.0 5.0 Miss R-Winon Trout Run Minimum 1.0 2.0 1.0 2.88 20.9 30.0 Miss R-Winon Trout Run Maximum 5.0 5.0 60.0 5.81 44.3 95.0 Miss R-Winon Trout Run Median 5.0 4.0 44.0 4.39 37.6 95.0 Miss R-Winon Trout Run Mean 3.9 3.7 41.6 4.45 36.7 69.0 Miss R-Winon Trout Run 95% CI Upper 0.0 0.0 4.3 4.0 0.0 46.7 4.60 38.2 0.0 113.2 Miss R-Winon Trout Run 95% CI Lower 0.0 0.0 3.5 3.4 0.0 36.6 4.30 35.2 0.0 24.8 Miss R-Winon Trout Run Standard Dev 1.5 1.1 18.0 0.59 5.9 35.6 Miss R-Winon Trout Run C.V. 0.4 0.3 0.4 0.13 0.2 0.5 Miss R-Winon Trout Run Skewness(G1) -0.8 -0.3 -0.5 0.12 -1.0 -0.6 Miss R-Winon S Fork White N of cases 19.0 35.0 191.0 191.0 19.0 175.0 91.00 91.0 5.0 5.0 Miss R-Winon S Fork White Minimum 38.0 0.2 1.0 1.0 1.2 0.0 1.57 12.6 19.0 10.0 Miss R-Winon S Fork White Maximum 6740.0 180.0 5.0 5.0 100.0 60.0 9.27 44.1 32.0 36.0 Miss R-Winon S Fork White Median 1880.0 7.0 2.0 3.0 5.6 51.0 4.21 41.6 24.0 30.0 Miss R-Winon S Fork White Mean 2495.6 15.4 2.7 3.0 12.2 40.1 4.22 39.4 24.8 27.6 Miss R-Winon S Fork White 95% CI Upper 3555.0 25.9 3.0 3.2 22.8 43.4 4.45 40.6 31.0 40.9 Miss R-Winon S Fork White 95% CI Lower 1436.1 4.9 2.5 2.8 1.6 36.8 4.00 38.3 18.6 14.3 Miss R-Winon S Fork White Standard Dev 2198.1 30.5 1.7 1.2 22.0 22.0 1.06 5.7 5.0 10.7 Miss R-Winon S Fork White C.V. 0.9 2.0 0.6 0.4 1.8 0.5 0.25 0.1 0.2 0.4 Miss R-Winon S Fork White Skewness(G1) 0.6 4.9 0.5 -0.2 3.9 -0.5 0.67 -2.7 0.6 -1.4 Miss R-Winon Crow Spring N of cases 0.0 0.0 0.0 0.0 0.0 0.0 41.00 41.0 0.0 4.0 Miss R-Winon Crow Spring Minimum 1.97 20.4 36.0 Miss R-Winon Crow Spring Maximum 5.35 43.7 90.0 Miss R-Winon Crow Spring Median 3.52 37.3 50.5 Miss R-Winon Crow Spring Mean 3.63 36.3 56.8 Miss R-Winon Crow Spring 95% CI Upper 0.0 0.0 0.0 0.0 0.0 0.0 3.92 38.0 0.0 98.2 Miss R-Winon Crow Spring 95% CI Lower 0.0 0.0 0.0 0.0 0.0 0.0 3.34 34.5 0.0 15.3 Miss R-Winon Crow Spring Standard Dev 0.91 5.6 26.0 Miss R-Winon Crow Spring C.V. 0.25 0.2 0.5 Miss R-Winon Crow Spring Skewness(G1) 0.12 -1.3 0.7 Miss R-Winon Logan Br N of cases 0.0 0.0 4.0 4.0 0.0 4.0 15.00 15.0 0.0 0.0 Miss R-Winon Logan Br Minimum 1.0 2.0 9.0 3.63 22.7 Miss R-Winon Logan Br Maximum 5.0 4.0 59.0 5.01 40.4 Miss R-Winon Logan Br Median 3.5 2.5 36.5 4.55 34.8 Miss R-Winon Logan Br Mean 3.3 2.8 35.3 4.50 31.2 Miss R-Winon Logan Br 95% CI Upper 0.0 0.0 6.5 4.3 0.0 72.2 4.73 35.1 0.0 0.0 Miss R-Winon Logan Br 95% CI Lower 0.0 0.0 0.0 1.2 0.0 -1.7 4.28 27.4 0.0 0.0 Miss R-Winon Logan Br Standard Dev 2.1 1.0 23.2 0.40 6.9 Miss R-Winon Logan Br C.V. 0.6 0.3 0.7 0.09 0.2 Miss R-Winon Logan Br Skewness(G1) -0.2 0.9 -0.2 -0.59 -0.1 Cannon River Cannon R N of cases 4.0 464.0 995.0 998.0 478.0 961.0 0.00 14.0 0.0 0.0 Cannon River Cannon R Minimum 29.0 0.9 1.0 1.0 0.5 1.8 19.0 Cannon River Cannon R Maximum 346.0 2000.0 7.0 5.0 1470.0 122.0 42.0 Cannon River Cannon R Median 94.5 11.0 5.0 4.0 17.0 33.0 29.0 Cannon River Cannon R Mean 141.0 32.1 4.5 3.6 48.6 34.4 29.4 Cannon River Cannon R 95% CI Upper 371.3 43.6 4.6 3.6 59.5 35.6 0.00 33.4 0.0 0.0 Cannon River Cannon R 95% CI Lower -89.3 20.5 4.5 3.5 37.8 33.2 0.00 25.3 0.0 0.0 Cannon River Cannon R Standard Dev 144.7 126.5 1.4 1.1 120.8 19.1 7.0 Cannon River Cannon R C.V. 1.0 3.9 0.3 0.3 2.5 0.6 0.2 Cannon River Cannon R Skewness(G1) 1.4 12.0 -1.2 -0.5 7.0 0.5 0.2 Miss R-Winon Garvin Bk N of cases 64.0 262.0 221.0 223.0 21.0 208.0 107.00 107.0 0.0 12.0 Miss R-Winon Garvin Bk Minimum 110.0 0.5 1.0 1.0 4.8 1.0 1.42 16.2 34.0 Miss R-Winon Garvin Bk Maximum 7350.0 2800.0 5.0 5.0 45.0 60.0 6.46 43.9 100.0 Miss R-Winon Garvin Bk Median 1750.0 12.0 1.0 1.0 21.0 60.0 3.94 36.4 92.5 Miss R-Winon Garvin Bk Mean 2490.6 133.4 2.0 2.1 22.2 54.5 3.92 34.9 74.3 Miss R-Winon Garvin Bk 95% CI Upper 3031.8 184.1 2.1 2.3 28.2 56.2 4.15 36.3 0.0 92.7 Miss R-Winon Garvin Bk 95% CI Lower 1949.4 82.6 1.8 2.0 16.2 52.8 3.69 33.5 0.0 56.0 Miss R-Winon Garvin Bk Standard Dev 2166.6 417.0 1.5 1.4 13.2 12.7 1.20 7.3 28.9 Miss R-Winon Garvin Bk C.V. 0.9 3.1 0.8 0.6 0.6 0.2 0.31 0.2 0.4 Miss R-Winon Garvin Bk Skewness(G1) 1.0 4.1 1.4 0.6 0.4 -2.6 -0.14 -0.9 -0.8 Miss R-Winon Trout Cr N of cases 0.0 0.0 0.0 0.0 0.0 0.0 42.00 42.0 0.0 7.0 Miss R-Winon Trout Cr Minimum 2.37 15.8 30.0 Miss R-Winon Trout Cr Maximum 5.02 41.9 100.0 Miss R-Winon Trout Cr Median 3.60 30.9 70.0 Miss R-Winon Trout Cr Mean 3.59 30.9 62.1 Miss R-Winon Trout Cr 95% CI Upper 0.0 0.0 0.0 0.0 0.0 0.0 3.79 33.0 0.0 88.7 Miss R-Winon Trout Cr 95% CI Lower 0.0 0.0 0.0 0.0 0.0 0.0 3.39 28.8 0.0 35.6 Miss R-Winon Trout Cr Standard Dev 0.63 6.7 28.7 Miss R-Winon Trout Cr C.V. 0.18 0.2 0.5 Miss R-Winon Trout Cr Skewness(G1) 0.11 -0.2 0.1 Cannon River Turtle Cr N of cases 0.0 16.0 15.0 15.0 16.0 16.0 0.00 6.0 0.0 0.0 Cannon River Turtle Cr Minimum 1.5 1.0 1.0 2.8 10.9 27.0 Cannon River Turtle Cr Maximum 37.0 5.0 5.0 124.0 60.0 34.0 Cannon River Turtle Cr Median 8.0 4.0 4.0 16.5 52.5 30.5 Cannon River Turtle Cr Mean 11.2 3.5 3.3 31.1 42.9 30.7 Cannon River Turtle Cr 95% CI Upper 0.0 16.6 4.4 4.2 48.3 53.5 0.00 33.4 0.0 0.0 Cannon River Turtle Cr 95% CI Lower 0.0 5.8 2.5 2.5 13.9 32.3 0.00 28.0 0.0 0.0 Cannon River Turtle Cr Standard Dev 10.1 1.7 1.5 32.4 19.9 2.6 Cannon River Turtle Cr C.V. 0.9 0.5 0.4 1.0 0.5 0.1 Cannon River Turtle Cr Skewness(G1) 1.3 -0.6 -0.7 1.7 -0.7 -0.1 Miss R-Winon Whitewater R N of cases 136.0 203.0 345.0 345.0 192.0 394.0 77.00 77.0 3.0 5.0 Miss R-Winon Whitewater R Minimum 17.0 2.0 1.0 1.0 4.5 0.0 2.27 12.7 25.0 36.0 Miss R-Winon Whitewater R Maximum 30600.0 1012.0 5.0 5.0 827.6 60.0 9.76 44.2 32.0 100.0 Miss R-Winon Whitewater R Median 1200.0 8.0 2.0 3.0 15.7 37.0 4.52 40.9 29.0 95.0 Miss R-Winon Whitewater R Mean 2672.2 33.2 3.0 3.2 45.2 36.8 4.58 38.8 28.7 72.4 Miss R-Winon Whitewater R 95% CI Upper 3397.5 47.1 3.1 3.3 58.4 38.9 4.79 40.3 37.4 113.7 Miss R-Winon Whitewater R 95% CI Lower 1946.9 19.3 2.8 3.0 32.0 34.8 4.37 37.3 19.9 31.1 Miss R-Winon Whitewater R Standard Dev 4277.1 100.4 1.5 1.2 92.6 20.5 0.91 6.6 3.5 33.3 Miss R-Winon Whitewater R C.V. 1.6 3.0 0.5 0.4 2.1 0.6 0.20 0.2 0.1 0.5 Miss R-Winon Whitewater R Skewness(G1) 3.9 6.5 0.3 -0.2 5.5 -0.3 2.23 -2.4 -0.6 Cannon River Trout Bk N of cases 0.0 62.0 59.0 59.0 31.0 59.0 0.00 0.0 0.0 0.0 Cannon River Trout Bk Minimum 0.3 1.0 1.0 1.0 0.0 Cannon River Trout Bk Maximum 2000.0 5.0 5.0 5860.0 122.0 Cannon River Trout Bk Median 2.1 1.0 1.0 30.0 60.0 Cannon River Trout Bk Mean 123.3 2.6 2.6 814.1 48.9 Cannon River Trout Bk 95% CI Upper 0.0 206.6 3.1 3.1 1340.7 58.6 0.00 0.0 0.0 0.0 Cannon River Trout Bk 95% CI Lower 0.0 39.9 2.1 2.1 287.6 39.2 0.00 0.0 0.0 0.0 Cannon River Trout Bk Standard Dev 328.2 1.9 1.9 1435.6 37.2 Cannon River Trout Bk C.V. 2.7 0.7 0.7 1.8 0.8 Cannon River Trout Bk Skewness(G1) 4.0 0.4 0.4 2.4 0.4 Cannon River Unknown Wate N of cases 0.0 59.0 172.0 128.0 33.0 193.0 0.00 0.0 0.0 0.0 Cannon River Unknown Wate Minimum 0.3 1.0 1.0 0.5 2.0 Cannon River Unknown Wate Maximum 1400.0 5.0 5.0 3270.0 115.0 Cannon River Unknown Wate Median 7.0 5.0 3.0 26.0 43.0 Cannon River Unknown Wate Mean 59.8 3.3 3.4 313.4 41.9 Cannon River Unknown Wate 95% CI Upper 0.0 113.7 3.6 3.7 590.0 44.9 0.00 0.0 0.0 0.0 Cannon River Unknown Wate 95% CI Lower 0.0 5.8 3.0 3.2 36.8 38.9 0.00 0.0 0.0 0.0 Cannon River Unknown Wate Standard Dev 206.9 1.8 1.5 780.0 21.0 Cannon River Unknown Wate C.V. 3.5 0.5 0.4 2.5 0.5 Cannon River Unknown Wate Skewness(G1) 5.3 -0.2 -0.5 3.2 0.2 Miss R-Winon Unknown Wate N of cases 0.0 0.0 0.0 0.0 0.0 0.0 6.00 6.0 0.0 3.0 Miss R-Winon Unknown Wate Minimum 3.30 39.7 55.0 Miss R-Winon Unknown Wate Maximum 5.28 44.1 80.0 Miss R-Winon Unknown Wate Median 3.91 40.3 65.0 Miss R-Winon Unknown Wate Mean 4.18 41.0 66.7 Miss R-Winon Unknown Wate 95% CI Upper 0.0 0.0 0.0 0.0 0.0 0.0 4.95 42.8 0.0 97.9 Miss R-Winon Unknown Wate 95% CI Lower 0.0 0.0 0.0 0.0 0.0 0.0 3.40 39.2 0.0 35.4 Miss R-Winon Unknown Wate Standard Dev 0.74 1.7 12.6 Miss R-Winon Unknown Wate C.V. 0.18 0.0 0.2 Miss R-Winon Unknown Wate Skewness(G1) 0.65 1.5 Miss R-Winon Stockton Val N of cases 30.0 36.0 62.0 62.0 0.0 62.0 9.00 9.0 0.0 0.0 Miss R-Winon Stockton Val Minimum 12.0 0.6 1.0 1.0 1.0 4.62 31.6 Miss R-Winon Stockton Val Maximum 26700.0 2000.0 5.0 5.0 60.0 5.48 41.1 Miss R-Winon Stockton Val Median 2035.0 21.0 2.0 2.0 46.0 4.92 39.9 Miss R-Winon Stockton Val Mean 4183.4 208.4 2.4 2.2 44.9 5.02 38.9 Miss R-Winon Stockton Val 95% CI Upper 6700.7 362.7 2.7 2.5 0.0 48.9 5.27 41.2 0.0 0.0 Miss R-Winon Stockton Val 95% CI Lower 1666.2 54.1 2.0 2.0 0.0 40.8 4.78 36.6 0.0 0.0 Miss R-Winon Stockton Val Standard Dev 6741.3 456.1 1.4 1.0 15.8 0.31 3.0 Miss R-Winon Stockton Val C.V. 1.6 2.2 0.6 0.4 0.4 0.06 0.1 Miss R-Winon Stockton Val Skewness(G1) 2.7 2.8 1.1 0.3 -0.8 0.26 -2.2 Cannon River Straight R N of cases 2.0 215.0 346.0 334.0 115.0 356.0 0.00 10.0 0.0 0.0 Cannon River Straight R Minimum 78.0 0.4 1.0 1.0 1.2 1.5 20.0 Cannon River Straight R Maximum 203.0 1100.0 6.0 5.0 1500.0 122.0 36.0 Cannon River Straight R Median 140.5 12.0 4.5 3.0 22.4 37.8 30.0 Cannon River Straight R Mean 140.5 23.9 3.6 3.2 52.8 38.3 29.4 Cannon River Straight R 95% CI Upper 934.6 34.9 3.8 3.3 80.3 40.5 0.00 32.7 0.0 0.0 Cannon River Straight R 95% CI Lower -653.6 12.9 3.4 3.1 25.3 36.0 0.00 26.1 0.0 0.0 Cannon River Straight R Standard Dev 88.4 82.0 1.7 1.1 149.0 21.6 4.6 Cannon River Straight R C.V. 0.6 3.4 0.5 0.4 2.8 0.6 0.2 Cannon River Straight R Skewness(G1) 11.4 -0.5 -0.4 8.5 0.2 -0.6 Root River Etna Cr N of cases 0.0 11.0 3.0 3.0 11.0 3.0 2.00 0.0 0.0 4.0 Root River Etna Cr Minimum 1.6 2.0 2.0 2.4 60.0 4.12 35.0 Root River Etna Cr Maximum 120.0 2.0 2.0 140.0 60.0 4.79 40.0 Root River Etna Cr Median 3.6 2.0 2.0 5.2 60.0 4.46 35.0 Root River Etna Cr Mean 24.0 2.0 2.0 24.9 60.0 4.46 36.3 Root River Etna Cr 95% CI Upper 0.0 54.3 2.0 2.0 55.0 60.0 8.71 0.0 0.0 40.2 Root River Etna Cr 95% CI Lower 0.0 -6.2 2.0 2.0 -5.2 60.0 0.20 0.0 0.0 32.3 Root River Etna Cr Standard Dev 45.1 0.0 0.0 44.8 0.0 0.47 2.5 Root River Etna Cr C.V. 1.9 0.0 0.0 1.8 0.0 0.11 0.1 Root River Etna Cr Skewness(G1) 1.9 2.3 2.0 Root River S Br Root R N of cases 0.0 85.0 907.0 788.0 92.0 1109.0 7.00 0.0 10.0 4.0 Root River S Br Root R Minimum 0.7 1.0 1.0 1.2 0.0 3.54 42.0 30.0 Root River S Br Root R Maximum 1500.0 5.0 5.0 1400.0 60.0 4.41 65.0 40.0 Root River S Br Root R Median 4.7 2.0 3.0 8.4 52.0 4.12 50.0 32.5 Root River S Br Root R Mean 74.8 2.9 3.0 75.7 42.0 4.05 50.3 33.8 Root River S Br Root R 95% CI Upper 0.0 130.7 3.1 3.1 119.6 43.2 4.33 0.0 54.8 41.4 Root River S Br Root R 95% CI Lower 0.0 18.8 2.8 2.9 31.7 40.8 3.77 0.0 45.8 26.1 Root River S Br Root R Standard Dev 259.3 1.7 1.5 212.3 20.3 0.30 6.3 4.8 Root River S Br Root R C.V. 3.5 0.6 0.5 2.8 0.5 0.07 0.1 0.1 Root River S Br Root R Skewness(G1) 4.5 0.0 0.1 4.3 -0.7 -0.63 1.4 0.9 Root River Jud Ditch #1 N of cases 0.0 0.0 0.0 0.0 0.0 0.0 1.00 0.0 2.0 0.0 Root River Jud Ditch #1 Minimum 5.15 57.0 Root River Jud Ditch #1 Maximum 5.15 57.0 Root River Jud Ditch #1 Median 5.15 57.0 Root River Jud Ditch #1 Mean 5.15 57.0 Root River Jud Ditch #1 95% CI Upper 0.0 0.0 0.0 0.0 0.0 0.0 5.15 0.0 57.0 0.0 Root River Jud Ditch #1 95% CI Lower 0.0 0.0 0.0 0.0 0.0 0.0 5.15 0.0 57.0 0.0 Root River Jud Ditch #1 Standard Dev 0.0 Root River Jud Ditch #1 C.V. 1.00 0.0 Root River Jud Ditch #1 Skewness(G1) Root River Forestville N of cases 0.0 14.0 92.0 92.0 13.0 101.0 1.00 0.0 0.0 2.0 Root River Forestville Minimum 0.5 1.0 1.0 1.2 10.0 2.92 65.0 Root River Forestville Maximum 3400.0 5.0 5.0 2900.0 60.0 2.92 95.0 Root River Forestville Median 2.7 2.0 1.0 6.0 60.0 2.92 80.0 Root River Forestville Mean 351.1 2.4 2.2 363.6 48.2 2.92 80.0 Root River Forestville 95% CI Upper 0.0 901.3 2.7 2.6 894.9 51.7 2.92 0.0 0.0 270.6 Root River Forestville 95% CI Lower 0.0 -199.0 2.0 1.9 -167.8 44.7 2.92 0.0 0.0 -110.6 Root River Forestville Standard Dev 952.8 1.6 1.7 879.3 17.6 21.2 Root River Forestville C.V. 2.7 0.7 0.8 2.4 0.4 1.00 0.3 Root River Forestville Skewness(G1) 3.0 0.8 0.8 2.6 -1.2 Root River Canfield Cr N of cases 0.0 12.0 92.0 92.0 11.0 104.0 1.00 0.0 0.0 2.0 Root River Canfield Cr Minimum 0.5 1.0 1.0 1.2 0.0 2.55 85.0 Root River Canfield Cr Maximum 140.0 5.0 5.0 130.0 60.0 2.55 95.0 Root River Canfield Cr Median 1.8 2.0 1.0 3.2 60.0 2.55 90.0 Root River Canfield Cr Mean 14.1 2.3 2.1 20.2 48.4 2.55 90.0 Root River Canfield Cr 95% CI Upper 0.0 39.4 2.7 2.5 47.2 51.8 2.55 0.0 0.0 153.5 Root River Canfield Cr 95% CI Lower 0.0 -11.1 2.0 1.8 -6.9 45.0 2.55 0.0 0.0 26.5 Root River Canfield Cr Standard Dev 39.8 1.6 1.7 40.3 17.5 7.1 Root River Canfield Cr C.V. 2.8 0.7 0.8 2.0 0.4 1.00 0.1 Root River Canfield Cr Skewness(G1) 3.4 0.8 0.9 2.5 -1.3 Cedar River Unknown Wate N of cases 0.0 27.0 0.0 0.0 54.0 42.0 0.00 0.0 0.0 0.0 Cedar River Unknown Wate Minimum 0.5 1.6 18.0 Cedar River Unknown Wate Maximum 380.0 2450.0 60.0 Cedar River Unknown Wate Median 4.0 6.7 60.0 Cedar River Unknown Wate Mean 36.9 67.6 57.8 Cedar River Unknown Wate 95% CI Upper 0.0 75.0 0.0 0.0 159.2 60.6 0.00 0.0 0.0 0.0 Cedar River Unknown Wate 95% CI Lower 0.0 -1.2 0.0 0.0 -24.0 55.0 0.00 0.0 0.0 0.0 Cedar River Unknown Wate Standard Dev 96.3 335.6 9.0 Cedar River Unknown Wate C.V. 2.6 5.0 0.2 Cedar River Unknown Wate Skewness(G1) 3.0 7.0 -4.2 Cedar River Cedar R N of cases 101.0 542.0 102.0 120.0 170.0 219.0 0.00 0.0 0.0 0.0 Cedar River Cedar R Minimum 3.0 0.5 1.0 2.0 1.2 3.0 Cedar River Cedar R Maximum 1470.0 500.0 5.0 5.0 328.0 60.0 Cedar River Cedar R Median 34.0 11.0 4.5 4.0 16.2 40.0 Cedar River Cedar R Mean 137.7 22.8 3.6 3.6 22.9 40.2 Cedar River Cedar R 95% CI Upper 187.6 26.2 3.9 3.7 27.5 42.7 0.00 0.0 0.0 0.0 Cedar River Cedar R 95% CI Lower 87.8 19.4 3.3 3.4 18.3 37.7 0.00 0.0 0.0 0.0 Cedar River Cedar R Standard Dev 252.8 40.4 1.5 0.8 30.4 18.6 Cedar River Cedar R C.V. 1.8 1.8 0.4 0.2 1.3 0.5 Cedar River Cedar R Skewness(G1) 3.1 6.0 -0.4 -0.8 6.6 -0.2 Cedar River Otter Cr N of cases 0.0 0.0 10.0 10.0 26.0 31.0 0.00 0.0 0.0 0.0 Cedar River Otter Cr Minimum 1.0 1.0 2.8 43.0 Cedar River Otter Cr Maximum 2.0 2.0 19.8 60.0 Cedar River Otter Cr Median 1.0 1.0 7.4 60.0 Cedar River Otter Cr Mean 1.4 1.1 8.8 57.4 Cedar River Otter Cr 95% CI Upper 0.0 0.0 1.8 1.3 10.8 59.4 0.00 0.0 0.0 0.0 Cedar River Otter Cr 95% CI Lower 0.0 0.0 1.0 0.9 6.7 55.4 0.00 0.0 0.0 0.0 Cedar River Otter Cr Standard Dev 0.5 0.3 5.0 5.5 Cedar River Otter Cr C.V. 0.4 0.3 0.6 0.1 Cedar River Otter Cr Skewness(G1) 0.5 3.2 0.7 -1.9 Cedar River Orchard Cr N of cases 0.0 0.0 10.0 10.0 26.0 31.0 0.00 0.0 0.0 0.0 Cedar River Orchard Cr Minimum 1.0 3.0 3.9 6.0 Cedar River Orchard Cr Maximum 5.0 4.0 260.0 60.0 Cedar River Orchard Cr Median 1.0 3.0 10.4 60.0 Cedar River Orchard Cr Mean 2.2 3.3 23.4 52.5 Cedar River Orchard Cr 95% CI Upper 0.0 0.0 3.6 3.6 43.4 58.0 0.00 0.0 0.0 0.0 Cedar River Orchard Cr 95% CI Lower 0.0 0.0 0.8 3.0 3.4 47.0 0.00 0.0 0.0 0.0 Cedar River Orchard Cr Standard Dev 1.9 0.5 49.4 15.1 Cedar River Orchard Cr C.V. 0.9 0.1 2.1 0.3 Cedar River Orchard Cr Skewness(G1) 1.0 1.0 4.7 -1.9 Cedar River Dobbins Cr N of cases 0.0 81.0 10.0 10.0 111.0 31.0 0.00 0.0 0.0 0.0 Cedar River Dobbins Cr Minimum 0.5 1.0 3.0 0.7 13.0 Cedar River Dobbins Cr Maximum 600.0 5.0 4.0 7870.0 60.0 Cedar River Dobbins Cr Median 6.5 2.0 3.0 20.0 38.0 Cedar River Dobbins Cr Mean 40.1 2.7 3.3 193.3 40.7 Cedar River Dobbins Cr 95% CI Upper 0.0 63.8 3.9 3.6 365.8 46.7 0.00 0.0 0.0 0.0 Cedar River Dobbins Cr 95% CI Lower 0.0 16.4 1.5 3.0 20.7 34.7 0.00 0.0 0.0 0.0 Cedar River Dobbins Cr Standard Dev 107.1 1.6 0.5 917.3 16.4 Cedar River Dobbins Cr C.V. 2.7 0.6 0.1 4.7 0.4 Cedar River Dobbins Cr Skewness(G1) 3.7 0.8 1.0 7.1 -0.2 Cedar River Wolf Cr N of cases 0.0 0.0 10.0 10.0 26.0 31.0 0.00 0.0 0.0 0.0 Cedar River Wolf Cr Minimum 3.0 3.0 2.1 12.0 Cedar River Wolf Cr Maximum 4.5 5.0 48.0 60.0 Cedar River Wolf Cr Median 4.5 3.0 4.5 60.0 Cedar River Wolf Cr Mean 4.3 3.6 9.7 54.3 Cedar River Wolf Cr 95% CI Upper 0.0 0.0 4.6 4.3 14.0 58.8 0.00 0.0 0.0 0.0 Cedar River Wolf Cr 95% CI Lower 0.0 0.0 4.0 2.9 5.5 49.7 0.00 0.0 0.0 0.0 Cedar River Wolf Cr Standard Dev 0.5 1.0 10.5 12.4 Cedar River Wolf Cr C.V. 0.1 0.3 1.1 0.2 Cedar River Wolf Cr Skewness(G1) -2.7 1.0 2.3 -2.3 Cannon River Maple Cr N of cases 0.0 16.0 16.0 16.0 16.0 16.0 0.00 0.0 0.0 0.0 Cannon River Maple Cr Minimum 1.2 1.0 1.0 0.8 9.0 Cannon River Maple Cr Maximum 36.0 5.0 4.0 114.0 60.0 Cannon River Maple Cr Median 5.0 2.0 2.0 12.9 60.0 Cannon River Maple Cr Mean 9.3 2.6 2.4 25.4 47.1 Cannon River Maple Cr 95% CI Upper 0.0 15.0 3.5 3.0 42.2 57.0 0.00 0.0 0.0 0.0 Cannon River Maple Cr 95% CI Lower 0.0 3.6 1.7 1.8 8.7 37.2 0.00 0.0 0.0 0.0 Cannon River Maple Cr Standard Dev 10.8 1.7 1.1 31.4 18.6 Cannon River Maple Cr C.V. 1.2 0.7 0.5 1.2 0.4 Cannon River Maple Cr Skewness(G1) 1.9 0.4 0.2 2.1 -1.0 Cannon River Crane Cr N of cases 0.0 19.0 15.0 15.0 16.0 16.0 0.00 3.0 0.0 0.0 Cannon River Crane Cr Minimum 2.4 1.0 1.0 3.8 19.9 27.0 Cannon River Crane Cr Maximum 17.0 5.0 4.0 52.0 60.0 31.0 Cannon River Crane Cr Median 9.9 3.0 3.0 27.9 55.5 29.0 Cannon River Crane Cr Mean 9.4 2.7 3.0 28.1 45.7 29.0 Cannon River Crane Cr 95% CI Upper 0.0 11.8 3.7 3.7 36.9 54.4 0.00 34.0 0.0 0.0 Cannon River Crane Cr 95% CI Lower 0.0 7.0 1.8 2.3 19.2 37.1 0.00 24.0 0.0 0.0 Cannon River Crane Cr Standard Dev 5.0 1.7 1.2 16.6 16.2 2.0 Cannon River Crane Cr C.V. 0.5 0.6 0.4 0.6 0.4 0.1 Cannon River Crane Cr Skewness(G1) 0.1 0.2 -0.9 0.1 -0.4 Miss R-Winon N Fork White N of cases 209.0 81.0 123.0 124.0 202.0 123.0 118.00 118.0 4.0 14.0 Miss R-Winon N Fork White Minimum 0.5 0.3 1.0 1.0 1.0 1.0 2.52 33.8 10.0 10.0 Miss R-Winon N Fork White Maximum 5190.0 290.0 5.0 5.0 5190.0 60.0 6.50 44.3 12.0 50.0 Miss R-Winon N Fork White Median 42.0 2.4 2.0 3.0 38.5 49.0 4.57 42.2 10.0 27.5 Miss R-Winon N Fork White Mean 246.3 10.3 2.8 2.8 226.3 40.0 4.48 41.7 10.5 28.6 Miss R-Winon N Fork White 95% CI Upper 343.8 17.6 3.1 3.1 320.0 43.8 4.64 42.0 12.1 34.9 Miss R-Winon N Fork White 95% CI Lower 148.9 3.0 2.5 2.6 132.6 36.1 4.33 41.4 8.9 22.2 Miss R-Winon N Fork White Standard Dev 714.6 32.9 1.6 1.4 675.4 21.6 0.84 1.7 1.0 11.0 Miss R-Winon N Fork White C.V. 2.9 3.2 0.6 0.5 3.0 0.5 0.19 0.0 0.1 0.4 Miss R-Winon N Fork White Skewness(G1) 4.8 7.9 0.4 0.3 4.8 -0.6 -0.09 -1.7 2.0 0.3 Cannon River Heath Cr N of cases 0.0 19.0 24.0 24.0 1.0 68.0 0.00 3.0 0.0 0.0 Cannon River Heath Cr Minimum 6.6 1.0 1.0 73.0 9.0 24.0 Cannon River Heath Cr Maximum 42.5 5.0 3.0 73.0 70.0 32.0 Cannon River Heath Cr Median 12.5 2.0 2.0 73.0 46.0 26.0 Cannon River Heath Cr Mean 16.2 3.1 2.0 73.0 45.0 27.3 Cannon River Heath Cr 95% CI Upper 0.0 20.6 3.7 2.3 73.0 48.6 0.00 37.7 0.0 0.0 Cannon River Heath Cr 95% CI Lower 0.0 11.7 2.5 1.7 73.0 41.4 0.00 17.0 0.0 0.0 Cannon River Heath Cr Standard Dev 9.2 1.3 0.7 14.7 4.2 Cannon River Heath Cr C.V. 0.6 0.4 0.3 1.0 0.3 0.2 Cannon River Heath Cr Skewness(G1) 1.6 0.3 0.0 -0.5 Zumbro River Middle Br Zu N of cases 0.0 9.0 13.0 13.0 18.0 12.0 0.00 0.0 0.0 0.0 Zumbro River Middle Br Zu Minimum 10.0 4.5 3.0 6.4 5.0 Zumbro River Middle Br Zu Maximum 71.8 5.0 5.0 330.0 44.0 Zumbro River Middle Br Zu Median 19.8 4.5 4.0 25.5 26.5 Zumbro River Middle Br Zu Mean 28.3 4.7 4.0 45.7 25.2 Zumbro River Middle Br Zu 95% CI Upper 0.0 42.9 4.9 4.3 82.1 31.9 0.00 0.0 0.0 0.0 Zumbro River Middle Br Zu 95% CI Lower 0.0 13.8 4.6 3.7 9.4 18.5 0.00 0.0 0.0 0.0 Zumbro River Middle Br Zu Standard Dev 18.9 0.3 0.6 73.1 10.5 Zumbro River Middle Br Zu C.V. 0.7 0.1 0.1 1.6 0.4 Zumbro River Middle Br Zu Skewness(G1) 1.7 0.2 0.0 3.9 -0.1 Zumbro River S Br Middle N of cases 0.0 40.0 675.0 640.0 45.0 859.0 0.00 0.0 0.0 0.0 Zumbro River S Br Middle Minimum 4.0 1.0 1.0 5.0 0.0 Zumbro River S Br Middle Maximum 1795.0 5.0 5.0 876.0 60.0 Zumbro River S Br Middle Median 85.5 5.0 3.0 77.0 30.0 Zumbro River S Br Middle Mean 225.6 3.4 3.2 164.6 33.7 Zumbro River S Br Middle 95% CI Upper 0.0 352.0 3.6 3.3 221.7 35.0 0.00 0.0 0.0 0.0 Zumbro River S Br Middle 95% CI Lower 0.0 99.2 3.3 3.1 107.4 32.3 0.00 0.0 0.0 0.0 Zumbro River S Br Middle Standard Dev 395.2 1.8 1.3 190.2 20.5 Zumbro River S Br Middle C.V. 1.8 0.5 0.4 1.2 0.6 Zumbro River S Br Middle Skewness(G1) 2.8 -0.4 -0.2 2.0 0.1 Root River Gribben Cr N of cases 0.0 0.0 34.0 34.0 0.0 37.0 0.00 0.0 0.0 0.0 Root River Gribben Cr Minimum 1.0 1.0 6.0 Root River Gribben Cr Maximum 5.0 3.0 60.0 Root River Gribben Cr Median 1.0 1.5 60.0 Root River Gribben Cr Mean 1.2 1.5 56.4 Root River Gribben Cr 95% CI Upper 0.0 0.0 1.4 1.7 0.0 60.6 0.00 0.0 0.0 0.0 Root River Gribben Cr 95% CI Lower 0.0 0.0 0.9 1.3 0.0 52.1 0.00 0.0 0.0 0.0 Root River Gribben Cr Standard Dev 0.7 0.6 12.7 Root River Gribben Cr C.V. 0.6 0.4 0.2 Root River Gribben Cr Skewness(G1) 5.0 0.4 -3.5 Miss R-Winon Rollingstone N of cases 0.0 1.0 26.0 27.0 0.0 28.0 3.00 3.0 0.0 0.0 Miss R-Winon Rollingstone Minimum 18.0 1.0 1.0 9.0 3.34 18.0 Miss R-Winon Rollingstone Maximum 18.0 5.0 4.0 60.0 3.75 19.8 Miss R-Winon Rollingstone Median 18.0 2.0 2.0 60.0 3.58 19.7 Miss R-Winon Rollingstone Mean 18.0 2.8 2.4 49.1 3.56 19.2 Miss R-Winon Rollingstone 95% CI Upper 0.0 18.0 3.4 2.8 0.0 55.0 4.07 21.8 0.0 0.0 Miss R-Winon Rollingstone 95% CI Lower 0.0 18.0 2.1 2.1 0.0 43.1 3.04 16.6 0.0 0.0 Miss R-Winon Rollingstone Standard Dev 1.7 1.0 15.4 0.21 1.0 Miss R-Winon Rollingstone C.V. 1.0 0.6 0.4 0.3 0.06 0.1 Miss R-Winon Rollingstone Skewness(G1) 0.4 0.0 -1.3 Miss R-Winon Speltz Cr N of cases 0.0 0.0 14.0 14.0 0.0 14.0 0.00 0.0 0.0 0.0 Miss R-Winon Speltz Cr Minimum 1.0 1.0 11.0 Miss R-Winon Speltz Cr Maximum 4.0 4.0 60.0 Miss R-Winon Speltz Cr Median 3.0 2.5 29.5 Miss R-Winon Speltz Cr Mean 2.4 2.5 36.0 Miss R-Winon Speltz Cr 95% CI Upper 0.0 0.0 3.2 3.0 0.0 48.2 0.00 0.0 0.0 0.0 Miss R-Winon Speltz Cr 95% CI Lower 0.0 0.0 1.7 2.0 0.0 23.8 0.00 0.0 0.0 0.0 Miss R-Winon Speltz Cr Standard Dev 1.3 0.9 21.1 Miss R-Winon Speltz Cr C.V. 0.6 0.4 0.6 Miss R-Winon Speltz Cr Skewness(G1) 0.0 0.0 0.2 Cannon River Pine Cr N of cases 0.0 91.0 26.0 26.0 40.0 26.0 0.00 3.0 0.0 0.0 Cannon River Pine Cr Minimum 0.3 1.0 1.0 1.0 12.0 20.0 Cannon River Pine Cr Maximum 190.0 5.0 5.0 585.0 122.0 24.0 Cannon River Pine Cr Median 2.2 1.0 1.0 15.0 55.0 23.0 Cannon River Pine Cr Mean 11.4 2.2 2.0 39.6 66.1 22.3 Cannon River Pine Cr 95% CI Upper 0.0 17.0 2.8 2.5 69.4 81.9 0.00 27.5 0.0 0.0 Cannon River Pine Cr 95% CI Lower 0.0 5.8 1.5 1.5 9.8 50.3 0.00 17.2 0.0 0.0 Cannon River Pine Cr Standard Dev 26.9 1.6 1.2 93.2 39.2 2.1 Cannon River Pine Cr C.V. 2.4 0.7 0.6 2.4 0.6 0.1 Cannon River Pine Cr Skewness(G1) 4.4 0.9 1.1 5.4 0.5 Cannon River Little Canno N of cases 0.0 9.0 158.0 158.0 0.0 153.0 0.00 9.0 0.0 0.0 Cannon River Little Canno Minimum 6.0 1.0 1.0 1.0 19.0 Cannon River Little Canno Maximum 75.0 5.0 5.0 60.0 34.0 Cannon River Little Canno Median 15.0 4.0 3.0 30.0 30.0 Cannon River Little Canno Mean 19.9 3.2 2.8 31.4 28.8 Cannon River Little Canno 95% CI Upper 0.0 36.1 3.4 3.0 0.0 34.8 0.00 32.2 0.0 0.0 Cannon River Little Canno 95% CI Lower 0.0 3.7 2.9 2.6 0.0 28.0 0.00 25.4 0.0 0.0 Cannon River Little Canno Standard Dev 21.1 1.7 1.3 21.3 4.4 Cannon River Little Canno C.V. 1.1 0.5 0.5 0.7 0.2 Cannon River Little Canno Skewness(G1) 2.8 -0.1 0.1 0.1 -1.4 Zumbro River Dodge Center N of cases 0.0 12.0 320.0 320.0 13.0 340.0 0.00 0.0 0.0 0.0 Zumbro River Dodge Center Minimum 27.0 1.0 1.0 23.0 0.0 Zumbro River Dodge Center Maximum 1314.0 5.0 5.0 364.0 60.0 Zumbro River Dodge Center Median 110.5 2.0 4.0 168.0 35.0 Zumbro River Dodge Center Mean 256.5 2.9 3.3 179.8 34.4 Zumbro River Dodge Center 95% CI Upper 0.0 485.9 3.1 3.4 236.8 36.7 0.00 0.0 0.0 0.0 Zumbro River Dodge Center 95% CI Lower 0.0 27.1 2.8 3.2 122.9 32.1 0.00 0.0 0.0 0.0 Zumbro River Dodge Center Standard Dev 361.1 1.8 1.2 94.2 21.4 Zumbro River Dodge Center C.V. 1.4 0.6 0.4 0.5 0.6 Zumbro River Dodge Center Skewness(G1) 2.6 0.2 -0.6 0.3 -0.1 Root River Money Cr N of cases 0.0 0.0 111.0 109.0 0.0 115.0 0.00 0.0 0.0 0.0 Root River Money Cr Minimum 1.0 1.0 1.0 Root River Money Cr Maximum 5.0 5.0 60.0 Root River Money Cr Median 2.0 2.0 41.0 Root River Money Cr Mean 2.0 2.1 40.3 Root River Money Cr 95% CI Upper 0.0 0.0 2.3 2.3 0.0 43.4 0.00 0.0 0.0 0.0 Root River Money Cr 95% CI Lower 0.0 0.0 1.8 2.0 0.0 37.2 0.00 0.0 0.0 0.0 Root River Money Cr Standard Dev 1.2 1.0 17.0 Root River Money Cr C.V. 0.6 0.5 0.4 Root River Money Cr Skewness(G1) 1.5 1.1 -0.5 Zumbro River Milliken Cr N of cases 0.0 0.0 0.0 0.0 0.0 40.0 0.00 0.0 0.0 0.0 Zumbro River Milliken Cr Minimum 2.0 Zumbro River Milliken Cr Maximum 60.0 Zumbro River Milliken Cr Median 41.0 Zumbro River Milliken Cr Mean 37.7 Zumbro River Milliken Cr 95% CI Upper 0.0 0.0 0.0 0.0 0.0 43.9 0.00 0.0 0.0 0.0 Zumbro River Milliken Cr 95% CI Lower 0.0 0.0 0.0 0.0 0.0 31.5 0.00 0.0 0.0 0.0 Zumbro River Milliken Cr Standard Dev 19.4 Zumbro River Milliken Cr C.V. 0.5 Zumbro River Milliken Cr Skewness(G1) -0.3 Miss R-Winon Beaver Cr N of cases 0.0 0.0 59.0 60.0 0.0 60.0 52.00 52.0 0.0 8.0 Miss R-Winon Beaver Cr Minimum 1.0 1.0 1.0 1.94 24.5 32.0 Miss R-Winon Beaver Cr Maximum 5.0 5.0 60.0 5.63 44.5 105.0 Miss R-Winon Beaver Cr Median 2.0 2.0 60.0 3.97 42.1 95.0 Miss R-Winon Beaver Cr Mean 2.1 2.3 53.3 3.96 41.4 80.8 Miss R-Winon Beaver Cr 95% CI Upper 0.0 0.0 2.4 2.6 0.0 57.4 4.21 42.3 0.0 106.0 Miss R-Winon Beaver Cr 95% CI Lower 0.0 0.0 1.8 2.0 0.0 49.2 3.70 40.4 0.0 55.5 Miss R-Winon Beaver Cr Standard Dev 1.1 1.1 15.9 0.92 3.6 30.2 Miss R-Winon Beaver Cr C.V. 0.5 0.5 0.3 0.23 0.1 0.4 Miss R-Winon Beaver Cr Skewness(G1) 1.6 0.9 -2.4 -0.46 -3.1 -1.3 Miss R-Winon Burns Valley N of cases 0.0 0.0 51.0 51.0 0.0 51.0 0.00 0.0 0.0 0.0 Miss R-Winon Burns Valley Minimum 1.0 1.0 5.0 Miss R-Winon Burns Valley Maximum 3.0 3.0 60.0 Miss R-Winon Burns Valley Median 1.0 1.0 60.0 Miss R-Winon Burns Valley Mean 1.1 1.1 57.7 Miss R-Winon Burns Valley 95% CI Upper 0.0 0.0 1.2 1.2 0.0 60.1 0.00 0.0 0.0 0.0 Miss R-Winon Burns Valley 95% CI Lower 0.0 0.0 1.0 1.0 0.0 55.3 0.00 0.0 0.0 0.0 Miss R-Winon Burns Valley Standard Dev 0.4 0.4 8.7 Miss R-Winon Burns Valley C.V. 0.3 0.4 0.2 Miss R-Winon Burns Valley Skewness(G1) 4.0 4.3 -5.0 Zumbro River Willow Cr N of cases 0.0 0.0 121.0 119.0 0.0 144.0 0.00 0.0 0.0 0.0 Zumbro River Willow Cr Minimum 1.0 1.0 0.0 Zumbro River Willow Cr Maximum 5.0 5.0 60.0 Zumbro River Willow Cr Median 4.5 3.0 32.5 Zumbro River Willow Cr Mean 3.5 3.0 33.1 Zumbro River Willow Cr 95% CI Upper 0.0 0.0 3.8 3.2 0.0 36.1 0.00 0.0 0.0 0.0 Zumbro River Willow Cr 95% CI Lower 0.0 0.0 3.1 2.7 0.0 30.2 0.00 0.0 0.0 0.0 Zumbro River Willow Cr Standard Dev 1.7 1.3 18.0 Zumbro River Willow Cr C.V. 0.5 0.5 0.5 Zumbro River Willow Cr Skewness(G1) -0.5 -0.1 0.0 Miss R-Winon Gorman Cr N of cases 0.0 0.0 25.0 25.0 0.0 25.0 0.00 0.0 0.0 0.0 Miss R-Winon Gorman Cr Minimum 1.0 1.0 3.0 Miss R-Winon Gorman Cr Maximum 5.0 5.0 60.0 Miss R-Winon Gorman Cr Median 2.0 4.0 35.0 Miss R-Winon Gorman Cr Mean 2.8 3.2 32.5 Miss R-Winon Gorman Cr 95% CI Upper 0.0 0.0 3.4 3.8 0.0 40.8 0.00 0.0 0.0 0.0 Miss R-Winon Gorman Cr 95% CI Lower 0.0 0.0 2.1 2.5 0.0 24.2 0.00 0.0 0.0 0.0 Miss R-Winon Gorman Cr Standard Dev 1.6 1.5 20.0 Miss R-Winon Gorman Cr C.V. 0.6 0.5 0.6 Miss R-Winon Gorman Cr Skewness(G1) 0.5 -0.3 -0.1 Root River Rush Cr N of cases 0.0 0.0 54.0 54.0 0.0 54.0 0.00 0.0 0.0 0.0 Root River Rush Cr Minimum 1.0 1.0 2.0 Root River Rush Cr Maximum 5.0 5.0 60.0 Root River Rush Cr Median 1.0 1.0 60.0 Root River Rush Cr Mean 1.5 1.5 49.8 Root River Rush Cr 95% CI Upper 0.0 0.0 1.8 1.8 0.0 54.3 0.00 0.0 0.0 0.0 Root River Rush Cr 95% CI Lower 0.0 0.0 1.2 1.2 0.0 45.3 0.00 0.0 0.0 0.0 Root River Rush Cr Standard Dev 1.1 1.1 16.4 Root River Rush Cr C.V. 0.7 0.7 0.3 Root River Rush Cr Skewness(G1) 2.7 2.4 -1.3 Zumbro River Bear Cr N of cases 2.0 0.0 55.0 55.0 0.0 85.0 0.00 0.0 0.0 0.0 Zumbro River Bear Cr Minimum 392.0 1.0 1.0 1.0 Zumbro River Bear Cr Maximum 802.0 5.0 5.0 60.0 Zumbro River Bear Cr Median 597.0 1.0 2.0 53.0 Zumbro River Bear Cr Mean 597.0 2.3 2.3 46.5 Zumbro River Bear Cr 95% CI Upper 3201.8 0.0 2.7 2.7 0.0 50.0 0.00 0.0 0.0 0.0 Zumbro River Bear Cr 95% CI Lower -2007.8 0.0 1.8 1.9 0.0 43.0 0.00 0.0 0.0 0.0 Zumbro River Bear Cr Standard Dev 289.9 1.7 1.5 16.2 Zumbro River Bear Cr C.V. 0.5 0.8 0.6 0.3 Zumbro River Bear Cr Skewness(G1) 0.9 0.7 -1.4 Cedar River Roberts Cr N of cases 0.0 20.0 45.0 45.0 26.0 62.0 0.00 0.0 0.0 0.0 Cedar River Roberts Cr Minimum 2.3 1.0 1.0 3.0 5.0 Cedar River Roberts Cr Maximum 16.0 5.0 5.0 126.3 60.0 Cedar River Roberts Cr Median 5.3 4.0 3.0 7.3 60.0 Cedar River Roberts Cr Mean 6.7 4.0 3.3 17.6 48.6 Cedar River Roberts Cr 95% CI Upper 0.0 8.6 4.4 3.6 27.7 52.7 0.00 0.0 0.0 0.0 Cedar River Roberts Cr 95% CI Lower 0.0 4.8 3.6 2.9 7.4 44.5 0.00 0.0 0.0 0.0 Cedar River Roberts Cr Standard Dev 4.0 1.4 1.1 25.1 16.1 Cedar River Roberts Cr C.V. 0.6 0.3 0.3 1.4 0.3 Cedar River Roberts Cr Skewness(G1) 1.3 -1.3 -0.2 3.5 -1.1 Cannon River N Br Of Chub N of cases 0.0 42.0 0.0 0.0 42.0 36.0 0.00 0.0 0.0 0.0 Cannon River N Br Of Chub Minimum 1.4 2.0 9.8 Cannon River N Br Of Chub Maximum 38.0 234.0 60.0 Cannon River N Br Of Chub Median 3.2 13.0 50.0 Cannon River N Br Of Chub Mean 7.6 35.2 48.9 Cannon River N Br Of Chub 95% CI Upper 0.0 10.4 0.0 0.0 51.6 53.6 0.00 0.0 0.0 0.0 Cannon River N Br Of Chub 95% CI Lower 0.0 4.7 0.0 0.0 18.9 44.1 0.00 0.0 0.0 0.0 Cannon River N Br Of Chub Standard Dev 9.1 52.5 13.9 Cannon River N Br Of Chub C.V. 1.2 1.5 0.3 Cannon River N Br Of Chub Skewness(G1) 2.1 2.8 -1.5 Cannon River Chub Cr N of cases 0.0 171.0 81.0 81.0 166.0 143.0 0.00 3.0 0.0 0.0 Cannon River Chub Cr Minimum 1.7 1.0 1.0 1.6 9.0 24.0 Cannon River Chub Cr Maximum 64.0 5.0 5.0 145.0 100.0 36.0 Cannon River Chub Cr Median 5.9 4.0 3.0 18.0 39.0 35.0 Cannon River Chub Cr Mean 9.5 3.3 3.0 28.9 40.5 31.7 Cannon River Chub Cr 95% CI Upper 0.0 11.0 3.7 3.2 33.8 43.0 0.00 48.2 0.0 0.0 Cannon River Chub Cr 95% CI Lower 0.0 8.1 3.0 2.7 24.0 38.0 0.00 15.1 0.0 0.0 Cannon River Chub Cr Standard Dev 9.6 1.5 0.9 32.0 15.2 6.7 Cannon River Chub Cr C.V. 1.0 0.4 0.3 1.1 0.4 0.2 Cannon River Chub Cr Skewness(G1) 2.6 -0.2 -0.2 2.0 0.3 Cedar River Turtle Cr N of cases 0.0 2.0 104.0 104.0 26.0 125.0 0.00 0.0 0.0 0.0 Cedar River Turtle Cr Minimum 25.0 2.0 3.0 30.0 2.0 Cedar River Turtle Cr Maximum 33.0 5.0 5.0 140.0 42.0 Cedar River Turtle Cr Median 29.0 5.0 4.0 61.9 15.0 Cedar River Turtle Cr Mean 29.0 4.8 4.1 71.8 15.1 Cedar River Turtle Cr 95% CI Upper 0.0 79.8 4.9 4.2 84.1 16.3 0.00 0.0 0.0 0.0 Cedar River Turtle Cr 95% CI Lower 0.0 -21.8 4.7 4.0 59.5 14.0 0.00 0.0 0.0 0.0 Cedar River Turtle Cr Standard Dev 5.7 0.7 0.6 30.5 6.6 Cedar River Turtle Cr C.V. 0.2 0.1 0.1 0.4 0.4 Cedar River Turtle Cr Skewness(G1) -3.6 0.0 0.9 0.9 Zumbro River Silver Cr N of cases 1.0 0.0 58.0 58.0 0.0 66.0 0.00 0.0 0.0 0.0 Zumbro River Silver Cr Minimum 1200.0 1.0 1.0 2.0 Zumbro River Silver Cr Maximum 1200.0 5.0 5.0 60.0 Zumbro River Silver Cr Median 1200.0 3.0 4.0 18.5 Zumbro River Silver Cr Mean 1200.0 3.3 3.4 23.3 Zumbro River Silver Cr 95% CI Upper 1200.0 0.0 3.7 3.7 0.0 27.1 0.00 0.0 0.0 0.0 Zumbro River Silver Cr 95% CI Lower 1200.0 0.0 2.9 3.2 0.0 19.5 0.00 0.0 0.0 0.0 Zumbro River Silver Cr Standard Dev 1.5 1.1 15.6 Zumbro River Silver Cr C.V. 1.0 0.5 0.3 0.7 Zumbro River Silver Cr Skewness(G1) 0.0 -0.6 1.0 Root River S Br Of Root N of cases 0.0 0.0 14.0 1.0 0.0 21.0 0.00 0.0 0.0 0.0 Root River S Br Of Root Minimum 2.0 4.0 0.0 Root River S Br Of Root Maximum 5.0 4.0 60.0 Root River S Br Of Root Median 4.5 4.0 44.0 Root River S Br Of Root Mean 4.0 4.0 36.3 Root River S Br Of Root 95% CI Upper 0.0 0.0 4.8 4.0 0.0 47.2 0.00 0.0 0.0 0.0 Root River S Br Of Root 95% CI Lower 0.0 0.0 3.2 4.0 0.0 25.4 0.00 0.0 0.0 0.0 Root River S Br Of Root Standard Dev 1.3 24.0 Root River S Br Of Root C.V. 0.3 1.0 0.7 Root River S Br Of Root Skewness(G1) -1.0 -0.5 Miss R & L P Gilbert Cr N of cases 0.0 0.0 9.0 9.0 0.0 28.0 0.00 0.0 0.0 0.0 Miss R & L P Gilbert Cr Minimum 3.0 3.0 0.0 Miss R & L P Gilbert Cr Maximum 5.0 5.0 60.0 Miss R & L P Gilbert Cr Median 5.0 5.0 8.9 Miss R & L P Gilbert Cr Mean 4.6 4.6 14.1 Miss R & L P Gilbert Cr 95% CI Upper 0.0 0.0 5.1 5.1 0.0 20.4 0.00 0.0 0.0 0.0 Miss R & L P Gilbert Cr 95% CI Lower 0.0 0.0 4.0 4.0 0.0 7.8 0.00 0.0 0.0 0.0 Miss R & L P Gilbert Cr Standard Dev 0.7 0.7 16.2 Miss R & L P Gilbert Cr C.V. 0.2 0.2 1.1 Miss R & L P Gilbert Cr Skewness(G1) -1.5 -1.5 1.4 Cannon River Rush Cr N of cases 0.0 1.0 65.0 65.0 0.0 65.0 0.00 0.0 0.0 0.0 Cannon River Rush Cr Minimum 2.7 1.0 2.0 1.0 Cannon River Rush Cr Maximum 2.7 5.0 5.0 60.0 Cannon River Rush Cr Median 2.7 1.0 2.0 60.0 Cannon River Rush Cr Mean 2.7 2.4 3.1 41.9 Cannon River Rush Cr 95% CI Upper 0.0 2.7 2.9 3.4 0.0 47.6 0.00 0.0 0.0 0.0 Cannon River Rush Cr 95% CI Lower 0.0 2.7 2.0 2.7 0.0 36.1 0.00 0.0 0.0 0.0 Cannon River Rush Cr Standard Dev 1.9 1.4 23.2 Cannon River Rush Cr C.V. 1.0 0.8 0.4 0.6 Cannon River Rush Cr Skewness(G1) 0.6 0.6 -0.7 Miss R & L P Hay Cr N of cases 0.0 5.0 86.0 86.0 0.0 86.0 0.00 0.0 0.0 0.0 Miss R & L P Hay Cr Minimum 8.9 1.0 1.0 0.0 Miss R & L P Hay Cr Maximum 16.0 5.0 5.0 60.0 Miss R & L P Hay Cr Median 16.0 4.0 4.0 43.0 Miss R & L P Hay Cr Mean 13.8 3.7 3.4 40.2 Miss R & L P Hay Cr 95% CI Upper 0.0 17.8 4.0 3.7 0.0 44.3 0.00 0.0 0.0 0.0 Miss R & L P Hay Cr 95% CI Lower 0.0 9.8 3.3 3.1 0.0 36.2 0.00 0.0 0.0 0.0 Miss R & L P Hay Cr Standard Dev 3.2 1.6 1.4 18.8 Miss R & L P Hay Cr C.V. 0.2 0.4 0.4 0.5 Miss R & L P Hay Cr Skewness(G1) -1.1 -0.7 -0.6 -0.6 Zumbro River Cascade Cr N of cases 2.0 0.0 253.0 256.0 0.0 257.0 0.00 0.0 0.0 0.0 Zumbro River Cascade Cr Minimum 1060.0 1.0 1.0 2.0 Zumbro River Cascade Cr Maximum 2040.0 5.0 5.0 60.0 Zumbro River Cascade Cr Median 1550.0 1.0 2.0 60.0 Zumbro River Cascade Cr Mean 1550.0 1.9 2.2 48.3 Zumbro River Cascade Cr 95% CI Upper 7776.0 0.0 2.1 2.3 0.0 50.4 0.00 0.0 0.0 0.0 Zumbro River Cascade Cr 95% CI Lower -4676.0 0.0 1.8 2.0 0.0 46.2 0.00 0.0 0.0 0.0 Zumbro River Cascade Cr Standard Dev 693.0 1.5 1.2 16.9 Zumbro River Cascade Cr C.V. 0.4 0.8 0.5 0.3 Zumbro River Cascade Cr Skewness(G1) 1.3 0.6 -1.4 Cannon River Prairie Cr N of cases 0.0 46.0 176.0 147.0 18.0 193.0 0.00 8.0 0.0 0.0 Cannon River Prairie Cr Minimum 0.4 1.0 1.0 3.2 2.0 18.0 Cannon River Prairie Cr Maximum 325.0 5.0 5.0 240.0 120.0 40.0 Cannon River Prairie Cr Median 8.5 3.0 4.0 30.0 35.0 30.5 Cannon River Prairie Cr Mean 30.0 3.0 3.5 59.5 38.0 29.3 Cannon River Prairie Cr 95% CI Upper 0.0 46.8 3.2 3.7 94.7 41.0 0.00 35.5 0.0 0.0 Cannon River Prairie Cr 95% CI Lower 0.0 13.2 2.7 3.4 24.3 35.1 0.00 23.0 0.0 0.0 Cannon River Prairie Cr Standard Dev 56.6 1.6 0.8 70.8 20.6 7.4 Cannon River Prairie Cr C.V. 1.9 0.6 0.2 1.2 0.5 0.3 Cannon River Prairie Cr Skewness(G1) 3.9 0.1 -0.6 1.9 0.1 -0.2 Root River Bear Cr N of cases 0.0 0.0 0.0 0.0 0.0 22.0 0.00 0.0 0.0 0.0 Root River Bear Cr Minimum 3.0 Root River Bear Cr Maximum 60.0 Root River Bear Cr Median 39.0 Root River Bear Cr Mean 37.4 Root River Bear Cr 95% CI Upper 0.0 0.0 0.0 0.0 0.0 47.6 0.00 0.0 0.0 0.0 Root River Bear Cr 95% CI Lower 0.0 0.0 0.0 0.0 0.0 27.2 0.00 0.0 0.0 0.0 Root River Bear Cr Standard Dev 22.9 Root River Bear Cr C.V. 0.6 Root River Bear Cr Skewness(G1) -0.3 Zumbro River Masten Cr N of cases 0.0 0.0 595.0 595.0 0.0 623.0 0.00 0.0 0.0 0.0 Zumbro River Masten Cr Minimum 1.0 1.0 0.0 Zumbro River Masten Cr Maximum 5.0 5.0 60.0 Zumbro River Masten Cr Median 1.0 1.0 60.0 Zumbro River Masten Cr Mean 1.8 1.6 51.8 Zumbro River Masten Cr 95% CI Upper 0.0 0.0 1.9 1.7 0.0 53.1 0.00 0.0 0.0 0.0 Zumbro River Masten Cr 95% CI Lower 0.0 0.0 1.7 1.5 0.0 50.5 0.00 0.0 0.0 0.0 Zumbro River Masten Cr Standard Dev 1.5 1.2 16.3 Zumbro River Masten Cr C.V. 0.8 0.7 0.3 Zumbro River Masten Cr Skewness(G1) 1.6 1.7 -1.9 Zumbro River Middle Fork N of cases 0.0 0.0 18.0 18.0 0.0 18.0 0.00 0.0 0.0 0.0 Zumbro River Middle Fork Minimum 1.0 2.0 0.0 Zumbro River Middle Fork Maximum 5.0 5.0 60.0 Zumbro River Middle Fork Median 5.0 4.0 25.5 Zumbro River Middle Fork Mean 3.7 3.7 32.1 Zumbro River Middle Fork 95% CI Upper 0.0 0.0 4.7 4.3 0.0 42.0 0.00 0.0 0.0 0.0 Zumbro River Middle Fork 95% CI Lower 0.0 0.0 2.8 3.1 0.0 22.3 0.00 0.0 0.0 0.0 Zumbro River Middle Fork Standard Dev 1.9 1.2 19.8 Zumbro River Middle Fork C.V. 0.5 0.3 0.6 Zumbro River Middle Fork Skewness(G1) -0.8 -0.4 0.4 Miss R-Winon Snake Cr N of cases 0.0 0.0 65.0 65.0 0.0 58.0 0.00 0.0 0.0 0.0 Miss R-Winon Snake Cr Minimum 1.0 1.0 1.0 Miss R-Winon Snake Cr Maximum 5.0 5.0 60.0 Miss R-Winon Snake Cr Median 2.0 2.0 47.5 Miss R-Winon Snake Cr Mean 2.7 2.9 38.3 Miss R-Winon Snake Cr 95% CI Upper 0.0 0.0 3.2 3.2 0.0 44.4 0.00 0.0 0.0 0.0 Miss R-Winon Snake Cr 95% CI Lower 0.0 0.0 2.3 2.5 0.0 32.3 0.00 0.0 0.0 0.0 Miss R-Winon Snake Cr Standard Dev 1.7 1.4 22.9 Miss R-Winon Snake Cr C.V. 0.6 0.5 0.6 Miss R-Winon Snake Cr Skewness(G1) 0.3 0.3 -0.5 Upper Iowa R Upper Iowa R N of cases 0.0 26.0 22.0 18.0 0.0 29.0 0.00 0.0 0.0 0.0 Upper Iowa R Upper Iowa R Minimum 1.2 1.0 1.0 3.0 Upper Iowa R Upper Iowa R Maximum 79.0 5.0 4.0 60.0 Upper Iowa R Upper Iowa R Median 4.7 4.0 3.0 27.0 Upper Iowa R Upper Iowa R Mean 11.5 3.3 3.1 27.7 Upper Iowa R Upper Iowa R 95% CI Upper 0.0 18.4 3.9 3.5 0.0 34.6 0.00 0.0 0.0 0.0 Upper Iowa R Upper Iowa R 95% CI Lower 0.0 4.5 2.8 2.7 0.0 20.7 0.00 0.0 0.0 0.0 Upper Iowa R Upper Iowa R Standard Dev 17.3 1.2 0.8 18.4 Upper Iowa R Upper Iowa R C.V. 1.5 0.4 0.3 0.7 Upper Iowa R Upper Iowa R Skewness(G1) 3.0 -0.5 -0.9 0.3 Upper Iowa R Little Iowa N of cases 0.0 0.0 0.0 0.0 0.0 6.0 0.00 0.0 0.0 0.0 Upper Iowa R Little Iowa Minimum 4.0 Upper Iowa R Little Iowa Maximum 60.0 Upper Iowa R Little Iowa Median 53.0 Upper Iowa R Little Iowa Mean 39.2 Upper Iowa R Little Iowa 95% CI Upper 0.0 0.0 0.0 0.0 0.0 67.7 0.00 0.0 0.0 0.0 Upper Iowa R Little Iowa 95% CI Lower 0.0 0.0 0.0 0.0 0.0 10.7 0.00 0.0 0.0 0.0 Upper Iowa R Little Iowa Standard Dev 27.2 Upper Iowa R Little Iowa C.V. 0.7 Upper Iowa R Little Iowa Skewness(G1) -0.9 Root River S Fork Root N of cases 0.0 0.0 117.0 114.0 0.0 121.0 0.00 0.0 0.0 0.0 Root River S Fork Root Minimum 1.0 1.0 0.0 Root River S Fork Root Maximum 5.0 5.0 60.0 Root River S Fork Root Median 2.0 2.0 60.0 Root River S Fork Root Mean 2.4 2.3 44.2 Root River S Fork Root 95% CI Upper 0.0 0.0 2.7 2.6 0.0 48.1 0.00 0.0 0.0 0.0 Root River S Fork Root 95% CI Lower 0.0 0.0 2.1 2.0 0.0 40.4 0.00 0.0 0.0 0.0 Root River S Fork Root Standard Dev 1.7 1.5 21.4 Root River S Fork Root C.V. 0.7 0.6 0.5 Root River S Fork Root Skewness(G1) 0.8 0.6 -1.0 Cannon River Mud Cr N of cases 0.0 42.0 80.0 80.0 42.0 98.0 0.00 0.0 0.0 0.0 Cannon River Mud Cr Minimum 1.8 1.0 2.0 2.0 8.2 Cannon River Mud Cr Maximum 37.0 5.0 5.0 193.0 60.0 Cannon River Mud Cr Median 4.2 4.8 4.0 11.0 48.0 Cannon River Mud Cr Mean 6.6 4.2 3.9 23.3 46.3 Cannon River Mud Cr 95% CI Upper 0.0 9.0 4.4 4.2 36.2 48.9 0.00 0.0 0.0 0.0 Cannon River Mud Cr 95% CI Lower 0.0 4.3 3.9 3.7 10.5 43.8 0.00 0.0 0.0 0.0 Cannon River Mud Cr Standard Dev 7.5 1.2 1.1 41.1 12.7 Cannon River Mud Cr C.V. 1.1 0.3 0.3 1.8 0.3 Cannon River Mud Cr Skewness(G1) 3.3 -1.8 -0.5 3.6 -0.9 Root River N Br Root R N of cases 0.0 17.0 71.0 71.0 0.0 67.0 0.00 0.0 0.0 0.0 Root River N Br Root R Minimum 0.7 1.0 1.0 1.0 Root River N Br Root R Maximum 130.0 5.0 5.0 60.0 Root River N Br Root R Median 3.0 4.0 3.0 36.0 Root River N Br Root R Mean 14.0 3.2 2.8 35.0 Root River N Br Root R 95% CI Upper 0.0 30.0 3.6 3.1 0.0 40.8 0.00 0.0 0.0 0.0 Root River N Br Root R 95% CI Lower 0.0 -2.0 2.7 2.4 0.0 29.2 0.00 0.0 0.0 0.0 Root River N Br Root R Standard Dev 31.1 1.8 1.4 23.8 Root River N Br Root R C.V. 2.2 0.6 0.5 0.7 Root River N Br Root R Skewness(G1) 3.6 -0.1 0.0 -0.2 Cannon River Belle Cr N of cases 0.0 0.0 99.0 108.0 0.0 109.0 0.00 3.0 0.0 0.0 Cannon River Belle Cr Minimum 1.0 1.0 1.0 27.0 Cannon River Belle Cr Maximum 5.0 5.0 60.0 36.0 Cannon River Belle Cr Median 5.0 4.0 46.0 29.0 Cannon River Belle Cr Mean 3.4 3.3 37.3 30.7 Cannon River Belle Cr 95% CI Upper 0.0 0.0 3.8 3.5 0.0 41.7 0.00 42.4 0.0 0.0 Cannon River Belle Cr 95% CI Lower 0.0 0.0 3.1 3.2 0.0 32.9 0.00 18.9 0.0 0.0 Cannon River Belle Cr Standard Dev 1.8 0.9 23.1 4.7 Cannon River Belle Cr C.V. 0.5 0.3 0.6 0.2 Cannon River Belle Cr Skewness(G1) -0.4 -0.6 -0.3 Shell Rock R Shell Rock R N of cases 0.0 167.0 18.0 27.0 22.0 24.0 0.00 0.0 0.0 0.0 Shell Rock R Shell Rock R Minimum 0.4 2.0 2.0 3.8 10.0 Shell Rock R Shell Rock R Maximum 390.0 5.0 5.0 170.0 60.0 Shell Rock R Shell Rock R Median 22.0 4.5 4.0 34.5 25.0 Shell Rock R Shell Rock R Mean 31.2 4.6 4.0 48.9 27.3 Shell Rock R Shell Rock R 95% CI Upper 0.0 37.1 4.9 4.2 67.8 32.7 0.00 0.0 0.0 0.0 Shell Rock R Shell Rock R 95% CI Lower 0.0 25.3 4.2 3.8 30.0 21.9 0.00 0.0 0.0 0.0 Shell Rock R Shell Rock R Standard Dev 38.4 0.7 0.6 42.7 12.8 Shell Rock R Shell Rock R C.V. 1.2 0.2 0.1 0.9 0.5 Shell Rock R Shell Rock R Skewness(G1) 5.4 -3.3 -1.5 1.4 1.4 Root River Spring Valle N of cases 0.0 4.0 16.0 15.0 0.0 20.0 0.00 0.0 0.0 0.0 Root River Spring Valle Minimum 1.0 1.0 1.0 6.0 Root River Spring Valle Maximum 44.0 5.0 5.0 60.0 Root River Spring Valle Median 1.3 1.5 3.0 46.5 Root River Spring Valle Mean 11.9 2.1 2.9 39.2 Root River Spring Valle 95% CI Upper 0.0 46.0 2.9 3.8 0.0 49.8 0.00 0.0 0.0 0.0 Root River Spring Valle 95% CI Lower 0.0 -22.2 1.2 2.0 0.0 28.5 0.00 0.0 0.0 0.0 Root River Spring Valle Standard Dev 21.4 1.5 1.6 22.8 Root River Spring Valle C.V. 1.8 0.7 0.6 0.6 Root River Spring Valle Skewness(G1) 2.0 1.4 0.2 -0.5 Cedar River Woodbury Cr N of cases 0.0 1.0 10.0 10.0 26.0 31.0 0.00 0.0 0.0 0.0 Cedar River Woodbury Cr Minimum 2.5 1.0 2.0 5.5 17.0 Cedar River Woodbury Cr Maximum 2.5 5.0 3.0 55.0 60.0 Cedar River Woodbury Cr Median 2.5 2.0 3.0 12.3 47.0 Cedar River Woodbury Cr Mean 2.5 2.8 2.9 15.5 45.8 Cedar River Woodbury Cr 95% CI Upper 0.0 2.5 3.9 3.1 20.0 50.9 0.00 0.0 0.0 0.0 Cedar River Woodbury Cr 95% CI Lower 0.0 2.5 1.7 2.7 10.9 40.7 0.00 0.0 0.0 0.0 Cedar River Woodbury Cr Standard Dev 1.5 0.3 11.3 14.0 Cedar River Woodbury Cr C.V. 1.0 0.6 0.1 0.7 0.3 Cedar River Woodbury Cr Skewness(G1) 0.9 -3.2 1.9 -0.3 Cedar River Rose Cr N of cases 0.0 1.0 10.0 10.0 26.0 31.0 0.00 0.0 0.0 0.0 Cedar River Rose Cr Minimum 3.2 1.0 3.0 1.7 4.0 Cedar River Rose Cr Maximum 3.2 5.0 4.0 356.0 60.0 Cedar River Rose Cr Median 3.2 1.0 3.0 12.4 51.0 Cedar River Rose Cr Mean 3.2 2.2 3.3 33.6 43.2 Cedar River Rose Cr 95% CI Upper 0.0 3.2 3.6 3.6 61.4 50.3 0.00 0.0 0.0 0.0 Cedar River Rose Cr 95% CI Lower 0.0 3.2 0.8 3.0 5.7 36.0 0.00 0.0 0.0 0.0 Cedar River Rose Cr Standard Dev 1.9 0.5 69.0 19.4 Cedar River Rose Cr C.V. 1.0 0.9 0.1 2.1 0.5 Cedar River Rose Cr Skewness(G1) 1.0 1.0 4.4 -0.6 Root River Root R N of cases 92.0 703.0 23.0 25.0 541.0 25.0 0.00 0.0 0.0 0.0 Root River Root R Minimum 10.0 0.4 1.0 2.0 1.0 7.0 Root River Root R Maximum 17200.0 2132.0 5.0 4.0 4090.0 60.0 Root River Root R Median 215.5 16.0 2.0 4.0 45.0 50.0 Root River Root R Mean 1490.2 48.4 3.0 3.5 119.5 44.6 Root River Root R 95% CI Upper 2028.1 60.0 3.7 3.8 149.6 51.6 0.00 0.0 0.0 0.0 Root River Root R 95% CI Lower 952.2 36.8 2.4 3.3 89.3 37.6 0.00 0.0 0.0 0.0 Root River Root R Standard Dev 2597.7 156.9 1.5 0.6 357.0 17.0 Root River Root R C.V. 1.7 3.2 0.5 0.2 3.0 0.4 Root River Root R Skewness(G1) 3.4 9.5 0.4 -0.8 7.5 -0.8 Miss R-Winon N Br Whitewa N of cases 0.0 0.0 0.0 0.0 0.0 0.0 3.00 3.0 0.0 0.0 Miss R-Winon N Br Whitewa Minimum 5.30 41.9 Miss R-Winon N Br Whitewa Maximum 5.54 42.0 Miss R-Winon N Br Whitewa Median 5.54 42.0 Miss R-Winon N Br Whitewa Mean 5.46 42.0 Miss R-Winon N Br Whitewa 95% CI Upper 0.0 0.0 0.0 0.0 0.0 0.0 5.80 42.1 0.0 0.0 Miss R-Winon N Br Whitewa 95% CI Lower 0.0 0.0 0.0 0.0 0.0 0.0 5.12 41.8 0.0 0.0 Miss R-Winon N Br Whitewa Standard Dev 0.14 0.1 Miss R-Winon N Br Whitewa C.V. 0.03 0.0 Miss R-Winon N Br Whitewa Skewness(G1) Zumbro River Trout Brook N of cases 0.0 48.0 0.0 0.0 0.0 0.0 0.00 0.0 0.0 0.0 Zumbro River Trout Brook Minimum 2.0 Zumbro River Trout Brook Maximum 330.0 Zumbro River Trout Brook Median 13.0 Zumbro River Trout Brook Mean 29.3 Zumbro River Trout Brook 95% CI Upper 0.0 45.3 0.0 0.0 0.0 0.0 0.00 0.0 0.0 0.0 Zumbro River Trout Brook 95% CI Lower 0.0 13.2 0.0 0.0 0.0 0.0 0.00 0.0 0.0 0.0 Zumbro River Trout Brook Standard Dev 55.2 Zumbro River Trout Brook C.V. 1.9 Zumbro River Trout Brook Skewness(G1) 4.2 Zumbro River Zumbro Middl N of cases 0.0 48.0 0.0 0.0 0.0 0.0 0.00 0.0 0.0 0.0 Zumbro River Zumbro Middl Minimum 2.0 Zumbro River Zumbro Middl Maximum 330.0 Zumbro River Zumbro Middl Median 12.0 Zumbro River Zumbro Middl Mean 32.1 Zumbro River Zumbro Middl 95% CI Upper 0.0 50.3 0.0 0.0 0.0 0.0 0.00 0.0 0.0 0.0 Zumbro River Zumbro Middl 95% CI Lower 0.0 13.9 0.0 0.0 0.0 0.0 0.00 0.0 0.0 0.0 Zumbro River Zumbro Middl Standard Dev 62.6 Zumbro River Zumbro Middl C.V. 2.0 Zumbro River Zumbro Middl Skewness(G1) 3.9 Root River Riceford N of cases 0.0 7.0 0.0 0.0 0.0 0.0 0.00 0.0 0.0 0.0 Root River Riceford Minimum 10.0 Root River Riceford Maximum 30.0 Root River Riceford Median 17.0 Root River Riceford Mean 17.7 Root River Riceford 95% CI Upper 0.0 24.4 0.0 0.0 0.0 0.0 0.00 0.0 0.0 0.0 Root River Riceford 95% CI Lower 0.0 11.1 0.0 0.0 0.0 0.0 0.00 0.0 0.0 0.0 Root River Riceford Standard Dev 7.2 Root River Riceford C.V. 0.4 Root River Riceford Skewness(G1) 0.7 Miss R-Reno Crooked Cr N of cases 0.0 13.0 0.0 0.0 0.0 0.0 0.00 0.0 0.0 0.0 Miss R-Reno Crooked Cr Minimum 2.3 Miss R-Reno Crooked Cr Maximum 72.0 Miss R-Reno Crooked Cr Median 15.0 Miss R-Reno Crooked Cr Mean 20.0 Miss R-Reno Crooked Cr 95% CI Upper 0.0 30.9 0.0 0.0 0.0 0.0 0.00 0.0 0.0 0.0 Miss R-Reno Crooked Cr 95% CI Lower 0.0 9.2 0.0 0.0 0.0 0.0 0.00 0.0 0.0 0.0 Miss R-Reno Crooked Cr Standard Dev 17.9 Miss R-Reno Crooked Cr C.V. 0.9 Miss R-Reno Crooked Cr Skewness(G1) 2.3 Zumbro River Salem Cr N of cases 0.0 18.0 0.0 0.0 0.0 0.0 0.00 0.0 0.0 0.0 Zumbro River Salem Cr Minimum 0.7 Zumbro River Salem Cr Maximum 80.0 Zumbro River Salem Cr Median 1.9 Zumbro River Salem Cr Mean 8.4 Zumbro River Salem Cr 95% CI Upper 0.0 17.7 0.0 0.0 0.0 0.0 0.00 0.0 0.0 0.0 Zumbro River Salem Cr 95% CI Lower 0.0 -0.8 0.0 0.0 0.0 0.0 0.00 0.0 0.0 0.0 Zumbro River Salem Cr Standard Dev 18.6 Zumbro River Salem Cr C.V. 2.2 Zumbro River Salem Cr Skewness(G1) 3.7 Root River Robinson Cr N of cases 0.0 4.0 0.0 0.0 0.0 0.0 0.00 0.0 0.0 0.0 Root River Robinson Cr Minimum 2.3 Root River Robinson Cr Maximum 3.1 Root River Robinson Cr Median 2.9 Root River Robinson Cr Mean 2.8 Root River Robinson Cr 95% CI Upper 0.0 3.3 0.0 0.0 0.0 0.0 0.00 0.0 0.0 0.0 Root River Robinson Cr 95% CI Lower 0.0 2.2 0.0 0.0 0.0 0.0 0.00 0.0 0.0 0.0 Root River Robinson Cr Standard Dev 0.3 Root River Robinson Cr C.V. 0.1 Root River Robinson Cr Skewness(G1) -1.2 Root River Wisel Cr N of cases 0.0 4.0 0.0 0.0 0.0 3.0 0.00 0.0 0.0 0.0 Root River Wisel Cr Minimum 1.1 5.0 Root River Wisel Cr Maximum 6.3 60.0 Root River Wisel Cr Median 4.8 39.9 Root River Wisel Cr Mean 4.3 35.0 Root River Wisel Cr 95% CI Upper 0.0 8.2 0.0 0.0 0.0 104.1 0.00 0.0 0.0 0.0 Root River Wisel Cr 95% CI Lower 0.0 0.3 0.0 0.0 0.0 -34.2 0.00 0.0 0.0 0.0 Root River Wisel Cr Standard Dev 2.5 27.8 Root River Wisel Cr C.V. 0.6 0.8 Root River Wisel Cr Skewness(G1) -0.8 Root River Middle Br Of N of cases 0.0 7.0 0.0 0.0 0.0 3.0 0.00 0.0 0.0 0.0 Root River Middle Br Of Minimum 1.0 3.0 Root River Middle Br Of Maximum 180.0 52.5 Root River Middle Br Of Median 5.1 5.0 Root River Middle Br Of Mean 61.4 20.2 Root River Middle Br Of 95% CI Upper 0.0 131.9 0.0 0.0 0.0 89.8 0.00 0.0 0.0 0.0 Root River Middle Br Of 95% CI Lower 0.0 -9.1 0.0 0.0 0.0 -49.4 0.00 0.0 0.0 0.0 Root River Middle Br Of Standard Dev 76.2 28.0 Root River Middle Br Of C.V. 1.2 1.4 Root River Middle Br Of Skewness(G1) 0.7 Cannon River Medford Cr N of cases 0.0 1.0 0.0 0.0 0.0 0.0 0.00 0.0 0.0 0.0 Cannon River Medford Cr Minimum 6.1 Cannon River Medford Cr Maximum 6.1 Cannon River Medford Cr Median 6.1 Cannon River Medford Cr Mean 6.1 Cannon River Medford Cr 95% CI Upper 0.0 6.1 0.0 0.0 0.0 0.0 0.00 0.0 0.0 0.0 Cannon River Medford Cr 95% CI Lower 0.0 6.1 0.0 0.0 0.0 0.0 0.00 0.0 0.0 0.0 Cannon River Medford Cr Standard Dev Cannon River Medford Cr C.V. 1.0 Cannon River Medford Cr Skewness(G1) Root River Riceford Cr N of cases 0.0 5.0 0.0 0.0 0.0 3.0 0.00 0.0 0.0 0.0 Root River Riceford Cr Minimum 12.0 10.0 Root River Riceford Cr Maximum 30.0 60.0 Root River Riceford Cr Median 21.0 43.1 Root River Riceford Cr Mean 21.6 37.7 Root River Riceford Cr 95% CI Upper 0.0 30.5 0.0 0.0 0.0 100.9 0.00 0.0 0.0 0.0 Root River Riceford Cr 95% CI Lower 0.0 12.7 0.0 0.0 0.0 -25.5 0.00 0.0 0.0 0.0 Root River Riceford Cr Standard Dev 7.2 25.4 Root River Riceford Cr C.V. 0.3 0.7 Root River Riceford Cr Skewness(G1) -0.2 Miss R-Winon E Indian Cr N of cases 0.0 0.0 0.0 0.0 0.0 0.0 59.00 59.0 0.0 10.0 Miss R-Winon E Indian Cr Minimum 1.45 17.1 24.0 Miss R-Winon E Indian Cr Maximum 5.61 40.6 90.0 Miss R-Winon E Indian Cr Median 3.66 29.6 65.0 Miss R-Winon E Indian Cr Mean 3.60 29.8 57.2 Miss R-Winon E Indian Cr 95% CI Upper 0.0 0.0 0.0 0.0 0.0 0.0 3.85 31.5 0.0 77.6 Miss R-Winon E Indian Cr 95% CI Lower 0.0 0.0 0.0 0.0 0.0 0.0 3.34 28.1 0.0 36.8 Miss R-Winon E Indian Cr Standard Dev 0.98 6.6 28.6 Miss R-Winon E Indian Cr C.V. 0.27 0.2 0.5 Miss R-Winon E Indian Cr Skewness(G1) -0.03 0.0 -0.2 Shell Rock R Albert Lea L N of cases 0.0 158.0 0.0 0.0 0.0 0.0 0.00 0.0 0.0 0.0 Shell Rock R Albert Lea L Minimum 0.4 Shell Rock R Albert Lea L Maximum 126.0 Shell Rock R Albert Lea L Median 15.0 Shell Rock R Albert Lea L Mean 20.1 Shell Rock R Albert Lea L 95% CI Upper 0.0 23.1 0.0 0.0 0.0 0.0 0.00 0.0 0.0 0.0 Shell Rock R Albert Lea L 95% CI Lower 0.0 17.0 0.0 0.0 0.0 0.0 0.00 0.0 0.0 0.0 Shell Rock R Albert Lea L Standard Dev 19.4 Shell Rock R Albert Lea L C.V. 1.0 Shell Rock R Albert Lea L Skewness(G1) 2.5 Cedar River Little Cedar N of cases 0.0 10.0 0.0 0.0 0.0 0.0 0.00 0.0 0.0 0.0 Cedar River Little Cedar Minimum 1.7 Cedar River Little Cedar Maximum 64.0 Cedar River Little Cedar Median 12.5 Cedar River Little Cedar Mean 14.6 Cedar River Little Cedar 95% CI Upper 0.0 27.9 0.0 0.0 0.0 0.0 0.00 0.0 0.0 0.0 Cedar River Little Cedar 95% CI Lower 0.0 1.4 0.0 0.0 0.0 0.0 0.00 0.0 0.0 0.0 Cedar River Little Cedar Standard Dev 18.5 Cedar River Little Cedar C.V. 1.3 Cedar River Little Cedar Skewness(G1) 2.5 Cannon River Tetonka L N of cases 0.0 7.0 0.0 0.0 9.0 0.0 0.00 0.0 0.0 0.0 Cannon River Tetonka L Minimum 1.1 1.6 Cannon River Tetonka L Maximum 25.0 24.0 Cannon River Tetonka L Median 5.0 4.0 Cannon River Tetonka L Mean 8.1 7.1 Cannon River Tetonka L 95% CI Upper 0.0 16.0 0.0 0.0 12.6 0.0 0.00 0.0 0.0 0.0 Cannon River Tetonka L 95% CI Lower 0.0 0.2 0.0 0.0 1.6 0.0 0.00 0.0 0.0 0.0 Cannon River Tetonka L Standard Dev 8.5 7.1 Cannon River Tetonka L C.V. 1.0 1.0 Cannon River Tetonka L Skewness(G1) 1.6 2.0 Miss R-Winon Mississippi N of cases 0.0 8.0 0.0 0.0 0.0 0.0 0.00 0.0 0.0 0.0 Miss R-Winon Mississippi Minimum 1.2 Miss R-Winon Mississippi Maximum 8.9 Miss R-Winon Mississippi Median 5.9 Miss R-Winon Mississippi Mean 5.5 Miss R-Winon Mississippi 95% CI Upper 0.0 7.9 0.0 0.0 0.0 0.0 0.00 0.0 0.0 0.0 Miss R-Winon Mississippi 95% CI Lower 0.0 3.1 0.0 0.0 0.0 0.0 0.00 0.0 0.0 0.0 Miss R-Winon Mississippi Standard Dev 2.9 Miss R-Winon Mississippi C.V. 0.5 Miss R-Winon Mississippi Skewness(G1) -0.5 Cannon River Lower Sakata N of cases 0.0 1.0 0.0 0.0 12.0 0.0 0.00 0.0 0.0 0.0 Cannon River Lower Sakata Minimum 4.0 1.2 Cannon River Lower Sakata Maximum 4.0 17.0 Cannon River Lower Sakata Median 4.0 9.0 Cannon River Lower Sakata Mean 4.0 9.5 Cannon River Lower Sakata 95% CI Upper 0.0 4.0 0.0 0.0 12.5 0.0 0.00 0.0 0.0 0.0 Cannon River Lower Sakata 95% CI Lower 0.0 4.0 0.0 0.0 6.4 0.0 0.00 0.0 0.0 0.0 Cannon River Lower Sakata Standard Dev 4.8 Cannon River Lower Sakata C.V. 1.0 0.5 Cannon River Lower Sakata Skewness(G1) -0.1 Cannon River Cannon L N of cases 0.0 5.0 0.0 0.0 6.0 0.0 0.00 0.0 0.0 0.0 Cannon River Cannon L Minimum 3.0 4.4 Cannon River Cannon L Maximum 18.0 45.0 Cannon River Cannon L Median 6.0 23.0 Cannon River Cannon L Mean 8.7 22.7 Cannon River Cannon L 95% CI Upper 0.0 16.1 0.0 0.0 37.9 0.0 0.00 0.0 0.0 0.0 Cannon River Cannon L 95% CI Lower 0.0 1.4 0.0 0.0 7.6 0.0 0.00 0.0 0.0 0.0 Cannon River Cannon L Standard Dev 5.9 14.4 Cannon River Cannon L C.V. 0.7 0.6 Cannon River Cannon L Skewness(G1) 1.1 0.4 Root River S Fork Of Ro N of cases 67.0 0.0 0.0 0.0 0.0 0.0 0.00 0.0 0.0 0.0 Root River S Fork Of Ro Minimum 20.0 Root River S Fork Of Ro Maximum 13300.0 Root River S Fork Of Ro Median 120.0 Root River S Fork Of Ro Mean 1425.1 Root River S Fork Of Ro 95% CI Upper 2141.1 0.0 0.0 0.0 0.0 0.0 0.00 0.0 0.0 0.0 Root River S Fork Of Ro 95% CI Lower 709.2 0.0 0.0 0.0 0.0 0.0 0.00 0.0 0.0 0.0 Root River S Fork Of Ro Standard Dev 2935.3 Root River S Fork Of Ro C.V. 2.1 Root River S Fork Of Ro Skewness(G1) 2.5 Root River Rice Cr N of cases 0.0 0.0 0.0 0.0 0.0 3.0 0.00 0.0 0.0 0.0 Root River Rice Cr Minimum 5.0 Root River Rice Cr Maximum 60.0 Root River Rice Cr Median 14.0 Root River Rice Cr Mean 26.3 Root River Rice Cr 95% CI Upper 0.0 0.0 0.0 0.0 0.0 99.6 0.00 0.0 0.0 0.0 Root River Rice Cr 95% CI Lower 0.0 0.0 0.0 0.0 0.0 -47.0 0.00 0.0 0.0 0.0 Root River Rice Cr Standard Dev 29.5 Root River Rice Cr C.V. 1.1 Root River Rice Cr Skewness(G1) Root River Torkelson Cr N of cases 0.0 0.0 0.0 0.0 0.0 3.0 0.00 0.0 0.0 0.0 Root River Torkelson Cr Minimum 12.5 Root River Torkelson Cr Maximum 58.0 Root River Torkelson Cr Median 27.9 Root River Torkelson Cr Mean 32.8 Root River Torkelson Cr 95% CI Upper 0.0 0.0 0.0 0.0 0.0 90.3 0.00 0.0 0.0 0.0 Root River Torkelson Cr 95% CI Lower 0.0 0.0 0.0 0.0 0.0 -24.7 0.00 0.0 0.0 0.0 Root River Torkelson Cr Standard Dev 23.1 Root River Torkelson Cr C.V. 0.7 Root River Torkelson Cr Skewness(G1) Root River Diamond Cr N of cases 0.0 0.0 0.0 0.0 0.0 3.0 0.00 0.0 0.0 0.0 Root River Diamond Cr Minimum 5.0 Root River Diamond Cr Maximum 60.0 Root River Diamond Cr Median 58.0 Root River Diamond Cr Mean 41.0 Root River Diamond Cr 95% CI Upper 0.0 0.0 0.0 0.0 0.0 118.5 0.00 0.0 0.0 0.0 Root River Diamond Cr 95% CI Lower 0.0 0.0 0.0 0.0 0.0 -36.5 0.00 0.0 0.0 0.0 Root River Diamond Cr Standard Dev 31.2 Root River Diamond Cr C.V. 0.8 Root River Diamond Cr Skewness(G1) Root River Raaen Cr N of cases 0.0 0.0 0.0 0.0 0.0 3.0 0.00 0.0 0.0 0.0 Root River Raaen Cr Minimum 4.0 Root River Raaen Cr Maximum 51.0 Root River Raaen Cr Median 14.0 Root River Raaen Cr Mean 23.0 Root River Raaen Cr 95% CI Upper 0.0 0.0 0.0 0.0 0.0 84.5 0.00 0.0 0.0 0.0 Root River Raaen Cr 95% CI Lower 0.0 0.0 0.0 0.0 0.0 -38.5 0.00 0.0 0.0 0.0 Root River Raaen Cr Standard Dev 24.8 Root River Raaen Cr C.V. 1.1 Root River Raaen Cr Skewness(G1) Root River Big Springs N of cases 0.0 0.0 0.0 0.0 0.0 3.0 0.00 0.0 0.0 0.0 Root River Big Springs Minimum 3.0 Root River Big Springs Maximum 60.0 Root River Big Springs Median 15.0 Root River Big Springs Mean 26.0 Root River Big Springs 95% CI Upper 0.0 0.0 0.0 0.0 0.0 100.6 0.00 0.0 0.0 0.0 Root River Big Springs 95% CI Lower 0.0 0.0 0.0 0.0 0.0 -48.6 0.00 0.0 0.0 0.0 Root River Big Springs Standard Dev 30.0 Root River Big Springs C.V. 1.2 Root River Big Springs Skewness(G1) Root River Camp Hayward N of cases 0.0 0.0 0.0 0.0 0.0 3.0 0.00 0.0 0.0 0.0 Root River Camp Hayward Minimum 4.0 Root River Camp Hayward Maximum 60.0 Root River Camp Hayward Median 40.0 Root River Camp Hayward Mean 34.7 Root River Camp Hayward 95% CI Upper 0.0 0.0 0.0 0.0 0.0 105.2 0.00 0.0 0.0 0.0 Root River Camp Hayward 95% CI Lower 0.0 0.0 0.0 0.0 0.0 -35.8 0.00 0.0 0.0 0.0 Root River Camp Hayward Standard Dev 28.4 Root River Camp Hayward C.V. 0.8 Root River Camp Hayward Skewness(G1) Root River Shattuck Cr N of cases 0.0 0.0 0.0 0.0 0.0 3.0 0.00 0.0 0.0 0.0 Root River Shattuck Cr Minimum 12.5 Root River Shattuck Cr Maximum 60.0 Root River Shattuck Cr Median 42.8 Root River Shattuck Cr Mean 38.4 Root River Shattuck Cr 95% CI Upper 0.0 0.0 0.0 0.0 0.0 98.1 0.00 0.0 0.0 0.0 Root River Shattuck Cr 95% CI Lower 0.0 0.0 0.0 0.0 0.0 -21.3 0.00 0.0 0.0 0.0 Root River Shattuck Cr Standard Dev 24.0 Root River Shattuck Cr C.V. 0.6 Root River Shattuck Cr Skewness(G1) Root River Unknown Wate N of cases 0.0 0.0 0.0 0.0 0.0 3.0 0.00 0.0 0.0 0.0 Root River Unknown Wate Minimum 14.5 Root River Unknown Wate Maximum 60.0 Root River Unknown Wate Median 23.7 Root River Unknown Wate Mean 32.7 Root River Unknown Wate 95% CI Upper 0.0 0.0 0.0 0.0 0.0 92.5 0.00 0.0 0.0 0.0 Root River Unknown Wate 95% CI Lower 0.0 0.0 0.0 0.0 0.0 -27.0 0.00 0.0 0.0 0.0 Root River Unknown Wate Standard Dev 24.1 Root River Unknown Wate C.V. 0.7 Root River Unknown Wate Skewness(G1) Root River Duschee Cr N of cases 0.0 0.0 0.0 0.0 0.0 3.0 0.00 0.0 0.0 0.0 Root River Duschee Cr Minimum 4.0 Root River Duschee Cr Maximum 60.0 Root River Duschee Cr Median 43.5 Root River Duschee Cr Mean 35.8 Root River Duschee Cr 95% CI Upper 0.0 0.0 0.0 0.0 0.0 107.3 0.00 0.0 0.0 0.0 Root River Duschee Cr 95% CI Lower 0.0 0.0 0.0 0.0 0.0 -35.7 0.00 0.0 0.0 0.0 Root River Duschee Cr Standard Dev 28.8 Root River Duschee Cr C.V. 0.8 Root River Duschee Cr Skewness(G1) Root River Watson Cr N of cases 0.0 0.0 0.0 0.0 0.0 3.0 0.00 0.0 0.0 0.0 Root River Watson Cr Minimum 3.0 Root River Watson Cr Maximum 40.0 Root River Watson Cr Median 17.0 Root River Watson Cr Mean 20.0 Root River Watson Cr 95% CI Upper 0.0 0.0 0.0 0.0 0.0 66.4 0.00 0.0 0.0 0.0 Root River Watson Cr 95% CI Lower 0.0 0.0 0.0 0.0 0.0 -26.4 0.00 0.0 0.0 0.0 Root River Watson Cr Standard Dev 18.7 Root River Watson Cr C.V. 0.9 Root River Watson Cr Skewness(G1) Root River Willow Cr N of cases 0.0 0.0 0.0 0.0 0.0 3.0 0.00 0.0 0.0 0.0 Root River Willow Cr Minimum 4.0 Root River Willow Cr Maximum 60.0 Root River Willow Cr Median 52.0 Root River Willow Cr Mean 38.7 Root River Willow Cr 95% CI Upper 0.0 0.0 0.0 0.0 0.0 113.9 0.00 0.0 0.0 0.0 Root River Willow Cr 95% CI Lower 0.0 0.0 0.0 0.0 0.0 -36.6 0.00 0.0 0.0 0.0 Root River Willow Cr Standard Dev 30.3 Root River Willow Cr C.V. 0.8 Root River Willow Cr Skewness(G1)