(MGLP) Regional Assessment – Final GIS Data Layers
Midwest Glacial Lakes Partnership
MGLP REGIONAL ASSESSMENT: GIS LAYERS (Final)
Lyn Bergquist, MN DNR – 3/31/10
DRAFT ONLY – DATA PREP NOT YET COMPLETE
*Format type: Grid (G): i-integer grid, f-floating point grid; xxM-cell size in meters; Shapefile (S) – points, lines or polys
* Variable type: Code (C)- alpha or numeric, Number (N), Percentage (P)
#
1
2
3
4
5
Calculate by Catchment
% of each Land Use Type
N
P
Variables
Land Use types: Open Water, Developed,
Forest, Agriculture, etc.
Mean runoff inches/year
% Impervious
Gf-30M
Gf-30M
Gf-30M
N
C
N
Available Water Storage (AWC)
Hydrologic Soil Group (Hygrp)
Soil Permeability (Perm)
Mean AWC (inches/inch)
Mean HYGRP (1-4)
Mean PERM (inches/hour)
LITH_ MGLP8
Gi-1000M
C
% of each Lith type
b Texture
TEXTURE_MGLP8
Gi-1000M
C
c Topo Moisture Potential
TMP_ MGLP8
Gi-30M
C
7
Geology and Minerals
GEOL_ MGLP8
Gi-30M
C
8
Bedrock Depth
BDEP_ MGLP8
Gi-30M
C
Lith types: Carbonate, Glacial Till, Hydric,
etc.
Texture types: Fine, Coarse, Other
(reclassified Lith types)
Moisture types:
[1-4], wet to dry
Geology types: Igneous, metamorphic,
sedimentary, etc.
Depth to bedrock types:
[201-211], 0–1600 ft depth
9
Climate
ANNPPT_MGLP8
ANNMIN_MGLP8
ANNMAX_MGLP8
JANMIN_MGLP8
JANMAX_MGLP8
JULMIN_MGLP8
JULMAX_MGLP8
Gf-100
Gf-100
Gf-100
Gf-100
Gf-100
Gf-100
Gf-100
N
N
N
N
N
N
N
Annual sum precipitation in inches
Mean annual minimum temp (degrees F)
Mean annual maximum temp (degrees F)
Mean January minimum temp (degrees F)
Mean January maximum temp (degrees F)
Mean July minimum temp (degrees F)
Mean July maximum temp (degrees F)
Mean annual sum ppt
Mean mean annual min temp
Mean mean annual max temp
Mean mean January min temp
Mean mean January max temp
Mean mean July min temp
Mean mean July max temp
6
Layer Category
Land Use (2001)
Land Use (1992)
Run-off
Imperviousness
Soils
Layer Name
NLCD01_MGLP8
NLCD92_MGLP8
RUNOFF_ MGLP8
IMPV01_ MGLP8
Format
Gi-30M
Gi-30M
Gf-500M
Gi-30M
Type*
C
a
b
c
S_AWC_MGLP8
S_HYGRP_MGLP8
S_PERM_MGLP8
Surficial Geology
a Lithology
Page 1 of 3
Mean runoff inches/year
Mean % impervious surface
Sum % Lith types to get
% of each Texture type
% of each Moisture type or
weighted mean value
% of each Geology type
% of each Depth to Bedrock
type
Midwest Glacial Lakes Partnership
#
10
11
12
13
14
15
16
17
18
Layer Category
Hydrography
EPA Point Source NPDES
Sites
Population
Road Crossings
USDA Waste/Nutrient Mgt
Nutrient Model Outputs
Agriculture Census
Applications
Cattle
(MGLP) Regional Assessment – Final GIS Data Layers
Layer Name
Format
_MGLP8
11_EPA_Point_
S-points
Source_MGLP8.shp
_MGLP8
_MGLP8
Type* Variables
NUTRIMT_MGLP8
WASTE_MGLP8
Nitrogen
TNY_TOT_MGLP8
TNY_PTS_MGLP8
TNY_FER_MGLP8
TPY_LVW_MGLP8
TNY_ATM_MGLP8
TNY_NAG_MGLP8
Phosphorus
TPY_TOT_MGLP8
TPY_PTS_MGLP8
TPY_FER_MGLP8
TPY_LVW_MGLP8
NO LAYER
TPY_NAG_MGLP8
N
N
Gi-100M
Gi-100M
Gf-100M
Gf-100M
Gf-100M
Gf-100M
Gf-100M
Gf-100M
Gf-100M
Gf-100M
Gf-100M
Gf-100M
Gf-100M
APPS_MGLP8
CATTLE_MGLP8
Gf-100M
ELEV30_MGLP8
SLOPE_MGLP8
Gf-30M
Gf-30M
Lyn Bergquist, MN DNR – 3/31/10
By HUC8
Total acres nutrient mgt applied in HUC8
Total acres waste util applied in HUC8
By HUC8
Total Nitrogen Yield: total mean
Total Nitrogen Yield: point source
Total Nitrogen Yield: fertilizer
Total Nitrogen Yield: livestock waste
Total Nitrogen Yield: atmospheric
Total Nitrogen Yield: non-agriculture
Total Phosphorus Yield: total mean
Total Phosphorus Yield: point source
Total Phosphorus Yield: fertilizer
Total Phosphorus Yield: livestock waste
Total Phosphorus Yield: atmospheric
Total Phosphorus Yield: non-agriculture
By county
NASS-determine most imp variables
Mean number of cattle and calves per 100
acres of all farm lands in county (adjust by
county acres?)
Calculate by Catchment
Adjust by acre?
Adjust by acre?
*NO ATTRIBUTE FOR PHOS
Elevation (NED)
Elevation (m)
Slope (% change in elevation)
Groundwater
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Mean Elevation
Mean Slope (% change in
elevation)
(MGLP) Regional Assessment – Final GIS Data Layers
Midwest Glacial Lakes Partnership
#
Layer Category
a Baseflow
b Runoff x Baseflow
c Recharge
19
Air Pollution
20
Ownership
a Ownership type
b Stewardship
21
Dams
22
Mines and Mineral Plants
LAYERS in blue, yet to be assembled
Layer Name
GW_BFL_MGLP8
GW_RBFL_MGLP8
GW_RCHI_MGLP8
Format
Gi-1000M
Gf-1000M
Gi-1000M
Type* Variables
N
Percentage of total stream flow
N
N
Recharge in inches/year (also ml/year)
CADEP_MGLP8
CLDEP_MGLP8
HDEP_MGLP8
KDEP_MGLP8
MGDEP_MGLP8
NADEP_MGLP8
NH4DEP_MGLP8
NO3DEP_MGLP8
SO4DEP_MGLP8
TOTNDEP_MGLP8
HGDEP_MGLP8
Gf-2500M
Gf-2500M
Gf-2500M
Gf-2500M
Gf-2500M
Gf-2500M
Gf-2500M
Gf-2500M
Gf-2500M
Gf-2500M
Gf-2500M
N
N
N
N
N
N
N
N
N
N
N
Calcium deposition
Chlorine deposition
Hydrogen deposition
Potassium deposition
Magnesium deposition
Sodium deposition
Ammonia deposition
Nitrate deposition
Sulfate deposition
Total nitrogen deposition
Mercury deposition
OWNER_MGLP8
Gi-30M
C
STEWRD_MGLP8
DAMS_MGLP8
MINES_MGLP8
Gi-30M
S-point
S-point
C
C
C
Ownership Types: County, Federal,
Indian, Private, State
Stewardship Protection Types: [1-4]
Dams
Mines and Mineral Plants x type
ITEMs in yellow, yet to be defined
Lyn Bergquist, MN DNR – 3/31/10
Calculate by Catchment
Mean % baseflow
DELETE-DUPE
Mean recharge (inches/year)
% of each Ownership type
% of each Stewardship type
# dams upstream of lake
# plants upstream of lake
All blank table cells will be populated
Important note: All variables will be summarized by local catchment and by tributary (upstream) catchments corresponding to each lake >= 10 acres in
the 8-state study area. Note that some data is only available at a scale of HUC08 watershed (layers 14, 15) or county (layer 16). For these layers, all
catchments within the HUC08 boundary or county boundary will have the same value. For catchments that cross county boundaries (layer 16), we may
need to weight the county-summarized values by % of catchment area in each county. Interpretations for layers 14, 15, 16 should be used with
caution because a value summarized by HUC08 or county may not actually affect the catchment in question (e.g., high number of cattle observed in
county, but actually none are near/upstream of a given catchment and so don’t affect the waterbody; because data comes summarized by county, we
don’t know the actual locations/concentrations of the variables of interest in relation to the catchments/waterbody of interest.)
Page 3 of 3