sediment

Metadata:

Identification_Information:
Citation:
Citation_Information:
Originator: Institute of Water Research - Michigan State University
Publication_Date: 9/2013
Title: sediment
Geospatial_Data_Presentation_Form: raster digital data
Description:
Abstract:
This dataset represents the annual amount of sediment in tons/acre/year that is eroded from a given area and delivered to the stream network. It is the result of multiplying the amount of erosion (determined by the Revised Universal Soil Loss Equation [RUSLE]) and a delivery ratio (determined by the Spatially Explicit Delivery Model [SEDMOD]).
Purpose:
This dataset can help identify areas at high-risk for sediment loading.
Time_Period_of_Content:
Time_Period_Information:
Multiple_Dates/Times:
Single_Date/Time:
Calendar_Date: 2006 (Year of land cover)
Single_Date/Time:
Calendar_Date: 1971-2001 (dates for R-factor from PRISM)
Currentness_Reference: ground condition
Status:
Progress: Complete
Maintenance_and_Update_Frequency: Irregular
Spatial_Domain:
Bounding_Coordinates:
West_Bounding_Coordinate: -89.5
East_Bounding_Coordinate: -77.4
North_Bounding_Coordinate: 45.8
South_Bounding_Coordinate: 40.4
Keywords:
Theme:
Theme_Keyword: erosion
Theme_Keyword: SEDMOD
Theme_Keyword: sediment
Theme_Keyword: delivery ratio
Theme_Keyword: RUSLE
Place:
Place_Keyword: Great Lakes Basin
Access_Constraints: none
Use_Constraints:
Please acknowlege the Institute of Water Research - Michigan State University as the data source.
Point_of_Contact:
Contact_Information:
Contact_Person_Primary:
Contact_Person: Glenn O'Neil
Contact_Organization: Institute of Water Research - Michigan State University
Contact_Position: GIS Specialist
Contact_Address: Contact_Voice_Telephone: (609) 557-3017
Contact_Facsimile_Telephone:ress: 1405 South Harrison Road
Address: Suite 101A
City: East Lansing
State_or_Province: MI
Postal_Code: 48823
Country: USA
Contact_Voice_Telephone: (609) 557-3012
Contact_Facsimile_Telephone: (517) 353 - 1812
Contact_Electronic_Mail_Address: oneilg@msu.edu
Data_Set_Credit:
Institute of Water Research - Michigan State University; U.S. Army Corps of Engineers; USDA - NRCS.
Native_Data_Set_Environment:
Microsoft Windows 7 Version 6.1 (Build 7601) Service Pack 1; Esri ArcGIS 10.1.1.3143
Cross_Reference:
Citation_Information:
Originator:
Renard, K.G., G.R.Foster, G.A. Weesies, D.K. McCool, and D.C. Yoder: United States Department of Agriculture
Publication_Date: January 1997
Title:
Predicting Soil Erosion by Water: A Guide to Conservation Planning With the Revised Universal Soil Loss Equation (RUSLE)
Edition: Agricultural Handbook Number 703
Cross_Reference:
Citation_Information:
Originator: J. Grigar and S. Davis - Michigan NRCS
Publication_Date: January 1995
Title:
Water Erosion Prediction and Control. Technical Guide Section I-C
Cross_Reference:
Citation_Information:
Originator:
Georgia Departnment of Natural Resources; Environmental Protection Division; Atlanta, Georgia
Publication_Date: June 2003
Title:
Total Maximum Daily Load Evaluation for Eight Stream Segments in the Tennessee River Basin for Sediment
Other_Citation_Details: p. 32
Online_Linkage:
<http://www.ganet.org/dnr/environ/techguide_files/wpb/tenn_bio_tmdl.pdf>
Cross_Reference:
Citation_Information:
Originator: Purdue University Conservation Tillage Information Center
Title:
National Crop Residue Management Survey, Conservation Tillage Data
Online_Linkage: <http://www.ctic.purdue.edu/CTIC/CRM.html>
Cross_Reference:
Citation_Information:
Originator: Bob Hickey
Title: Information and code used to calculate RUSLE LS factor
Online_Linkage:
<http://www.onlinegeographer.com/slope/slope.html>
Cross_Reference:
Citation_Information:
Originator: Robert Hungerford Fraser
Publication_Date: May 1999
Title: SEDMOD: A GIS-Based Deliver Model for Diffuse Source Pollutants
Other_Citation_Details:
A Dissertation Presented to the Faculty of the Graduate School of Yale University in Candidacy for the Degree of Doctor of Philosophy Dissertation Director: Paul K. Barten
Cross_Reference:
Citation_Information:
Originator:
Dr. T. Brikowski, Geosciences Dept., University of Texas at Dallas
Publication_Date: Spring 2007
Title: Manning's Roughness Coefficient
Online_Linkage:
<http://www.utdallas.edu/~brikowi/Teaching/Applied_Modeling/SurfaceWater/LectureNotes/Manning_Roughness/manning_roughness.html>
Cross_Reference:
Citation_Information:
Originator: Da Ouyang, Jon Bartholic, James Selegean
Publication_Date: 2005
Title:
Assessing Sediment Loading from Agricultural Croplands in the Great Lakes Basin
Other_Citation_Details: The Journal of American Science, 1(2)
Online_Linkage:
<http://www.hydra.iwr.msu.edu/iwr/cv/proposals/publications/documents/Assessing%20Sediment%20Loading2005.pdf>
Data_Quality_Information:
Attribute_Accuracy:
Attribute_Accuracy_Report:
The accuracy of the quantified sediment loading estimates depends upon the inputs, and is subject to the inherent error of the inputs(R, K, LS, C, Delivery Ratio). When possible, estimates have been compared to monitoring or dredging data. Estimates have been within an order of magnitude, but RUSLE (the source of the erosion estimates) does not account for ephemeral gully, bank erosion, or wind erosion; so estimates tend to be low. SEDMOD's delivery ratio uses DEM-derived surface water flow, so its accuracy is limited by the fidelity of the DEM. DEMs have problems capturing flows in especially flat areas, so error would be greatest in these areas. Another input, prercent clay, was derived from SSURGO data. Clay values were aggregated by soil map components. Roughness values were tied to the landcover (NLCD) and Crop Data layers at a 30-meter resolution. The NLCD and CDL were error-checked in its creation, but not necessarily in this area.
Completeness_Report:
This dataset represents a calculation of the RUSLE equation, combined with a spatially explicit delivery ratio layer generated by SEDMOD. It is a Map Algebra product of the following rasters: R-factor, C-factor, K-factor, LS-factor, and Delivery Ratio. See the section on Process Steps for more detail. The R-factor was provided by the PRISM group at Oregon State University (<http://www.prism.oregonstate.edu/index.phtml>), and represent precipitation data for 1971-2000. The C-factor was derived from NLCD 2006, the 2009-2012 Cropland Data Layers, Michigan NRCS C-factor tables, and Purdue University's CTIC crop and tillage data.
Positional_Accuracy:
Horizontal_Positional_Accuracy:
Horizontal_Positional_Accuracy_Report:
Dependent upon the accuracy of the inputs. NLCD data comes at a 30-meter resolution in Albers projection. For this analysis it was re-projected to analysis projection, intrdocuing unmeasured projection error. The DEM used to derive the LS factor and Delivery Ratio was obtained from the National Elevation Dataset 1/3 arc-second product (<http://ned.usgs.gov>). The SSURGO soils data was created at a 1:24K scale, see SSURGO metadata for more details.See PRISM website for R-factor details.
Lineage:
Source_Information:
Source_Citation:
Citation_Information:
Originator: NRCS
Publication_Date: 1999 - present
Title: NRCS Watershed Boundary Dataset
Geospatial_Data_Presentation_Form: vector digital data
Online_Linkage: <http://www.ncgc.nrcs.usda.gov/products/datasets/watershed/>
Source_Scale_Denominator: 1:24,000
Type_of_Source_Media: online
Source_Citation_Abbreviation: 8-digit HUC
Source_Contribution: Boundary of the dataset.
Source_Information:
Source_Citation:
Citation_Information:
Originator: USGS
Publication_Date: Unknown
Title: 1/3 arc-second DEM (30-meters)
Geospatial_Data_Presentation_Form: raster digital data
Online_Linkage: <http://ned.usgs.gov>
Source_Scale_Denominator: 1:24,000
Type_of_Source_Media: online
Source_Citation_Abbreviation: DEM
Source_Contribution:
Used in calculating a RUSLE LS factor and determining surface water flow in SEDMOD.
Source_Information:
Source_Citation:
Citation_Information:
Originator: USDA-NRCS
Publication_Date: Unpublished Material
Title: SSURGO
Geospatial_Data_Presentation_Form: vector digital data
Online_Linkage: <http://soils.usda.gov/survey/geography/SSURGO/>
Source_Scale_Denominator: 1:24,000
Type_of_Source_Media: online
Source_Citation_Abbreviation: SSURGO Soils
Source_Contribution:
NRCS SSURGO Soil Surveys were analyzed to derive a K-factor layer for the RUSLE calculation and percent clay input for SEDMOD.
Source_Information:
Source_Citation:
Citation_Information:
Originator: MRLC
Publication_Date: 3/19/2007
Title: NLCD
Geospatial_Data_Presentation_Form: raster digital data
Online_Linkage: <http://www.mrlc.gov/>
Source_Citation_Abbreviation: Land cover
Source_Contribution:
Used to derive a C-factor grid for use in the RUSLE calculation and surface roughness for SEDMOD.
Source_Information:
Source_Citation:
Citation_Information:
Originator: USDA-NASS
Publication_Date: 3
Title: Cropland Data Layer (CDL)
Geospatial_Data_Presentation_Form: raster digital data
Online_Linkage: <http://www.nass.usda.gov/research/Cropland/SARS1a.htm>
Source_Citation_Abbreviation: CDL
Source_Contribution:
Used to derive a C-factor grid for use in the RUSLE calculation.
Source_Information:
Source_Citation:
Citation_Information:
Originator: PRISM Group
Publication_Date: Unknown
Title: PRISM R-factor
Geospatial_Data_Presentation_Form: raster digital data
Online_Linkage: <http://www.prism.oregonstate.edu/index.phtml>
Type_of_Source_Media: online
Source_Citation_Abbreviation: PRISM precipitation
Source_Contribution: Provides the R Factor for the RUSLE calculation.
Source_Information:
Source_Citation:
Citation_Information:
Originator: USGS
Publication_Date: Unknown
Title: NHD Streams (High-resolution)
Geospatial_Data_Presentation_Form: vector digital data
Online_Linkage: <http://nhd.usgs.gov/>
Source_Scale_Denominator: 1:24,000
Type_of_Source_Media: online
Source_Citation_Abbreviation: NHD Streams
Source_Contribution:
This stream layer was burned into the DEM layer used by SEDMOD. This forced SEDMOD to recognize the actual stream network, as opposed to a DEM's artificial network.
Process_Step:
Process_Description:
Watershed boundary was downloaded from the NRCS Watershed Boundary Dataset. The study-area watershed was selected out and re-projected to NAD_1983_Hotine_Oblique_Mercator_Azimuth_Natural_Origin from Geographic Lat./Lon. This boundary was utilized as the boundary of the intermediate and output rasters.
Source_Used_Citation_Abbreviation: 8-digit HUC
Process_Date: 2012-11-01T00:00:00
Process_Step:
Process_Description:
1/3 arc-second DEMs were downloaded from the USGS NED website (<http://ned.usgs.gov>) and clipped by the Watershed Boundary Dataset to a yield a study-area DEM (30-meter resolution).
Source_Used_Citation_Abbreviation: USGS 1/3 arc-second DEM
Process_Date: 2012-11-01T00:00:00
Process_Step:
Process_Description:
NRCS SSURGO soil surveys of each county that intersected the study area were downoladed from the USDA soil data mart (<http://soildatamart.nrcs.usda.gov/>). For this Sediment layer, 'Kffact' (rock-free K factor data) was extracted from the database and linked to the SSURGO layer. A buffered 8-digit HUC boundary was then used to clip the polygon SSURGO layer. The resulting watershed-scale K-factor polygon layer was conveted to a GRID dataset, and then clipped by a mask of the DEM layer. This ensured that the K-factor grid cells were coincedent with all other input grids. The resulting K-factor layer was used with other RUSLE layers to estimate annual erosion. This process was repeated for SSURGO's Percent Clay attribute, and the resulting Percent Clay grid was used as an input for SEDMOD's calculation of delivery ratio.
Source_Used_Citation_Abbreviation: SSURGO Soils
Process_Date: 2012-11-01T00:00:00
Process_Step:
Process_Description:
NHD HIGH resolution stream data was obtained from the USGS. Stream features of the study area were extracted, re-projected from Geographic Lat./Lon. to NAD_1983_Hotine_Oblique_Mercator_Azimuth_Natural_Origin and converted to a GRID layer. The stream grid was burned into the DEM used as a SEDMOD input. To force SEDMOD to recognize the actual drainage network (as opposed to a DEM derived artificial network) all DEM cells not coincident with the stream cells were raised by 10 meters. This grid was then filled to enforce a full drainage network.
Source_Used_Citation_Abbreviation: NHD Streams
Process_Date: 2012-11-01T00:00:00
Process_Step:
Process_Description:
Spatially explicit C-factor data was the most difficult to find. The method used here was to link C-factor data to the NLCD 2006. First, C-factor values for most of the NLCD classes were obtained from literature (&lt;http://www.ganet.org/dnr/environ/techguide_files/wpb/tenn_bio_tmdl.pdf&gt;). This covered all but the agricultural grid cells in the NLCD. Next, we developed a custom Python script that read in mutliple year layers from the CDL, observed the annual crop rotation for each pixel, referenced a Michigan NRCS document for C-factors for given annual rotations, and weighted these factors by estimates of county-level conservation tillage for the study area reported to CTIC for the the years (2000, 2002, and 2004 - the most recent available). The end result was a C-Factor value for each ag cell in the NLCD, with the value derived from discernible rotations in the CDL from the years 2009-2012, and weighted by the probability of each crop's tillage conservation as reported to CTIC. C-factors for non-ag cells were derived from literature as described above.
Source_Used_Citation_Abbreviation: Land cover
Process_Date: 2012-11-01T00:00:00
Process_Step:
Process_Description:
To calculate the RUSLE LS layer we employed the method described by Van Remortel et al. (2004) as a custom Python script. Van Remortel, R., R. Maichle, and R. Hickey, 2004, Computing the RUSLE LS Factor through Array- based Slope Length Processing of Digital Elevation Data Using a C++ Executable. Computers and Geosciences. V. 30, No. 9-10, pp. 1043-1053. Code and paper accessible at: http://www.onlinegeographer.com/slope/slope.html.
Source_Used_Citation_Abbreviation: USGS 1/3 arc-second DEM
Process_Date: 2012-11-01T00:00:00
Process_Step:
Process_Description:
Similar to the creation of the C-factor grid, the Surface Roughness grid was derived from the NLCD grid; but without the county-level and crop-level analysis and aggregation. Land cover classes were re-classified according to Manning R values from Dr. T. Brikowski at UT-Dallas. His work is online at <http://www.utdallas.edu/~brikowi/Teaching/Applied_Modeling/SurfaceWater/LectureNotes/Manning_Roughness/manning_roughness.html>.
Source_Used_Citation_Abbreviation: Land cover
Process_Date: 2012-11-01T00:00:00
Process_Step:
Process_Description:
The Percent Clay, Surface Roughness, and burned/filled DEM grids were then placed in a separate ArcINFO workspace. The SEDMOD alogrithm was employed within ArcGIS and produced the Delivery Ratio grid.
Process_Date: 2012-11-01T00:00:00
Process_Step:
Process_Description:
The 'K-factor,' 'C-factor,' 'LS-factor,' and 'R-factor' grids grids were then multiplied together in ArcMap's Raster Calculator to yield a grid representing total annual erosion in tons/acre. However, the individual grid cells roughly covered 100 square meters, not an acre. Therefore the grid had to be divided by 40.47 (1 acre = 4,047 square meters, divided by 100 square meters) to determine the total annual amount of erosion per cell. This grid was then multliplied by the SEDMOD Delivery Ratio grid, and divided by 100 to get total annual sediment loading to streams for each cell.
Process_Date: 2012-11-01T00:00:00
Spatial_Data_Organization_Information:
Direct_Spatial_Reference_Method: Raster
Raster_Object_Information:
Raster_Object_Type: Grid Cell
Row_Count: unknown
Column_Count: unknown
Vertical_Count: 1
Spatial_Reference_Information:
Horizontal_Coordinate_System_Definition:
Planar:
Planar_Coordinate_Information:
Planar_Coordinate_Encoding_Method: row and column
Coordinate_Representation:
Abscissa_Resolution: 30.000000
Ordinate_Resolution: 30.000000
Planar_Distance_Units: meters
Geodetic_Model:
Horizontal_Datum_Name: North American Datum of 1983
Ellipsoid_Name: Geodetic Reference System 80
Semi-major_Axis: 6378137.000000
Denominator_of_Flattening_Ratio: 298.257222
Distribution_Information:
Resource_Description: Downloadable Data
Distribution_Liability:
IWR-MSU provides these geographic data "as is." IWR-MSU makes no guarantee or warranty concerning the accuracy of information contained in the geographic data. IWR-MSU further makes no warranty either expressed or implied, regarding the condition of the product or its fitness for any particular purpose. The burden for determining fitness for use lies entirely with the user. Although these files have been processed successfully on computers at IWR-MSU, no warranty is made by IWR-MSU regarding the use of these data on any other system, nor does the fact of distribution constitute or imply any such warranty. (Distribution liability format courtesy of the Wyoming Geographic Information Science Center).
Standard_Order_Process:
Digital_Form:
Digital_Transfer_Information:
Format_Name: ARCG
Transfer_Size:
Metadata_Reference_Information:
Metadata_Date: 20130912
Metadata_Review_Date: 20130912
Metadata_Contact:
Contact_Information:
Contact_Person_Primary:
Contact_Person: Glenn O'Neil
Contact_Organization: Institute of Water Research - Michigan State University
Contact_Position: GIS Specialist
Contact_Address:
Address_Type: mailing and physical address
Address: 1405 South Harrison Road
Address: Suite 101A
City: East Lansing
State_or_Province: MI
Postal_Code: 48823
Country: USA
Contact_Voice_Telephone: (609) 557-3017
Contact_Facsimile_Telephone: (517) 353-1812
Contact_Electronic_Mail_Address: oneilg@msu.edu
Metadata_Standard_Name: FGDC Content Standards for Digital Geospatial Metadata
Metadata_Standard_Version: FGDC-STD-001-1998
Metadata_Time_Convention: local time
Generated by mp version 2.9.12 on Thu Sep 12 11:50:29 2013