Data Measures for Water Quality & Quantity

303(d): Impaired Watershed Area

RESTORE Goal: Water Quality and Quantity – Priority Attribute: Water Quality Impairment

DEFINITION A percent attribute that stands for the proportion of impaired watershed within each hexagon. The watershed data are analyzed based on the 12-digit hydrologic unit code (HUC-12) level. Any HUC-12 watershed that contains an Environmental Protection Agency (EPA) 303(d) listed impaired waterbody would be considered impaired (EPA 1972).

Data Summary

• Data Source: EPA 303(d) list (EPA 1972); NHDPlusV2 (McKay, Bondelid, and Dewald 2019)

• Unit: Percentage (%)

• Default Utility Function: The lower proportion of impaired watershed (lower score), the better for conservation

• Area of Interest Aggregation: The score for the area of interest is the summed score from the hexagons inside the area of interest

• Threshold: Continuous utility value ranging from 0 to 1

Workflow:

1. Clip the impaired watershed boundary layer with hexagon boundaries.

2. Perform spatial join to calculate the proportion of each hexagon that contains an impaired watershed.

Hydrologic Response to Land-Use Change

RESTORE Goal: Water Quality and Quantity – Priority Attribute: Flow

DEFINITION The magnitude of change in peak flow due to Land-Use/Land-Cover change from 1996 to 2016, analyzed at the HUC-12 watershed scale (Shamaskin, dissertation, in press). The magnitude of peak flow change is categorized in the following way under the default value system: 0, Very Significant (10-50% increase); 0.25, Significant (5-10% increase); 0.5, Moderate (1-5% increase); 0.75, Minimal (0-1% increase); 1, No Change or Decrease (0% or lower). Watersheds comprised of 90% or more of open water were excluded from analysis.

Data Summary

• Data Source: NLCD 2016 (Yang et al. 2018); SSURGO (USDA 2018); NHDPlusV2 (McKay, Bondelid, and Dewald 2019)

• Unit: Percentage (%)

• Default Utility Function: The less of an impact on hydrology (higher score), the better for conservation

• Area of Interest Aggregation: Maximum score from the hexagons inside the area of interest

• Threshold: Discrete utility value ranging from 0 to 1

  • 0, Very Significant (10-50% increase); 0.25, Significant (5-10% increase); 0.5, Moderate (1-5% increase); 0.75, Minimal (0-1% increase); 1, No Change or Decrease (0% or lower)

Workflow:

1. Perform spatial join of the vector data with hexagon boundaries.

2. Compute mean of percent change in peak flow values within each hexagon.

Lateral Connectivity of Floodplain

RESTORE Goal: Water Quality and Quantity – Priority Attribute: Floodplain and Streambank Integrity

DEFINITION The proportion of floodplain within the area of interest that is connected (or disconnected if using negative utility function), using the Environmental Protection Agency’s (EPA) 100-year floodplain and a measure of relative floodplain inundation frequency derived from Landsat imagery (Allen 2016).

Data Summary

• Data Source: Measure of relative floodplain inundation frequency (Allen 2016); EPA 100-year floodplain

• Unit: Percentage (%)

• Default Utility Function: A higher proportion of floodplain connectivity (higher score) is better for conservation

• Area of Interest Aggregation: Average of all hexagons that have floodplain (hexagons with no floodplain have “No Floodplain” as the column value)

• Threshold: Continuous utility value ranging from 0 to 1

Workflow:

1. Take floodplain inundation frequency layer (IF) and apply urban mask to indicate urban areas are not connected to the floodplain.

2. Intersect IF layer with EPA 100-year floodplain layer.

3. Reclassify the resulting layer into 0, 1, or 2. A value of 2 indicates the IF and EPA layers overlap (connected floodplain). A value of 1 indicates the EPA layer is present, but not the IF layer (disconnected floodplain). A value of 0 indicates the EPA layer is present (no floodplain).

4. Merge reclassified layer with hexagon grid.

5. Calculate relative area of the floodplain that is connected within each hexagon (%). Hexagons without any floodplain area are classified as “NA”.

Percent Irrigated Agriculture

RESTORE Goal: Water Quality and Quantity – Priority Attribute: Water Availability

DEFINITION The proportion (%) of the area of interest that is covered by irrigated agriculture, according to the 2017 version of the Moderate Resolution Imaging Spectroradiometer (MODIS) Irrigated Agriculture Dataset for the United States (Pervez and Brown 2010).

Data Summary

• Data Source: Irrigated Agriculture Dataset for the United States (Pervez and Brown 2010)

• Unit: Percentage (%)

• Default Utility Function: The lower the proportion of irrigated agriculture (lower score), the better for conservation

• Area of Interest Aggregation: Average of all hexagons in the area of interest

• Threshold: Continuous utility value ranging from 0 to 1

Workflow:

1. Take 250-meter raster and convert to polygon.

2. Select polygons with attribute value 1, indicating irrigated agriculture.

3. Intersect irrigated agriculture polygons with hexagons, creating polygons that fit completely within hexagons.

4. Calculate area of each irrigated agriculture polygon (square meters).

5. Add the areas of each irrigated agriculture polygon that belong to the same hexagon (noted by ObjectID).

Composition of Riparian Zone Lands

RESTORE Goal: Water Quality and Quantity – Priority Attribute: Floodplain and Streambank Integrity

DEFINITION An average index value of the composition of lands within a 100-meter buffer of streams. The index score was calculated by first organizing the Land-Use/Land-Cover (LULC) classes from NLCD 2016 into three tiers: 1) Developed, 2) Agricultural, and 3) Natural (Table 9). Then, after aggregating the combined area of the LULC classes within each tier, the index score in each hexagon was calculated using Equation 8 below. Conversely, if the desired utility is to value more disturbed riparian area, then the index score is calculated using Equation 9 below.

Note: this measure only evaluates an area of interest based on the quality of the riparian zone, not on the amount of riparian zone.

Data Summary

• Data Source: Land-Use/Land-Cover classes from National Land Cover Dataset (NLCD) (Yang et al. 2018)

• Unit: Index

  • See equation 8 below (default utility function; the more natural riparian zone, the better)

  • See equation 9 below (negative utility function: more disturbed riparian zone, the better)

• Default Utility Function: The more natural riparian zone (higher score), the better for conservation

• Area of Interest Aggregation: Average of all hexagons in the area of interest

• Threshold: Continuous utility value ranging from 0 to 1

Workflow:

1. Reclassify NLCD 2016 layer into three tiers as specified in Table 9.

2. Clip reclassified NLCD 2016 layer to the EPA Riparian Zone layer.

3. Compute spatial join between clipped layer and hexagon grid.

4. Calculate composition value for each hexagon using equation 8 below.

Equation 8 (default utility function):

$$Score = Developed*0 +Agricultural*0.5 +Natural*1$$

Equation 9 (negative utility function):

$$Score = Developed*1+Agricultural*0.5+Natural*0$$

Table 9. Land-Use/Land-Cover (LULC) classes from NLCD 2016.

Tier	NLCD Attribute
1) Developed	21 Developed, Open Space 22 Developed, Low Intensity 23 Developed, Medium Intensity 24 Developed, High Intensity
2) Agriculture	81 Pasture/Hay 82 Cultivated Crops
3) Nature	31 Barren Land 41 Deciduous Forest 42 Evergreen Forest 43 Mixed Forest 52 Shrub/Scrub 71 Grassland/Herbaceous 90 Woody Wetlands 95 Emergent Herbaceous Wetlands

Presence of Impoundments

RESTORE Goal: Water Quality and Quantity – Priority Attribute: Hydromodification

DEFINITION This measure describes whether or not an area is impacted by hydromodification. The Southeast Aquatic Resources Partnership (SARP) Barrier Inventory data takes into account modifications to hydrology by impoundments and dams only. It does not factor in levees or culverts. This measure is not volume-based - it does not distinguish between impoundments that hold back large volumes of water versus those that hold back small volumes of water.

Note: This measure was added after the initial measure vetting process by the SCA Data Working Group. Therefore, the data included in this measure did not undergo the same amount of stakeholder input as the initial 22 data measures included in the tool.

Data Summary

• Data Source: Southeast Aquatic Barrier Prioritization Tool (Version 2.3.1)

• Unit: Binary

• Default Utility Function: Areas of interest with no impoundments (score = 0) are better for conservation

• Area of Interest Aggregation: Maximum score from the hexagons inside the area of interest

• Threshold: Binary utility value (0 and 1)

Workflow:

1. Perform spatial join of the point SARP data with the hexagon boundaries

2. Obtain counts within each hexagon

References

Allen, Y. 2016. Landscape Scale Assessment of Floodplain Inundation Frequency Using Landsat Imagery: Floodplain Inundation Frequency. River Research and Applications 32:1609–1620.

EPA. 1972. “Clean Water Act.” Washington, DC, USA: EPA.

McKay, L, T Bondelid, and T Dewald. 2019. “NHDPlus Version 2: User Guide 2012.” EPA. https://nctc.fws.gov/courses/references/tutorials/geospatial/CSP7306/Readings/NHDPlusV2_User_Guide.pdf.

Pervez, M. S., and J. F. Brown. 2010. Mapping Irrigated Lands at 250-m Scale by Merging MODIS Data and National Agricultural Statistics. Remote Sensing 2:2388–2412.

USDA. 2018. “Soil Survey Staff Web Soil Survey.” Natural Resources Conservation Service. Washington, DC, USA: USDA.

Yang, L.; Jin, S.; Danielson, P.; Homer, C.; Gass, L.; Bender, S.M.; Case, A.; Costello, C.; Dewitz, J.; Fry, J.; et al. A new generation of the United States National Land Cover Database: Requirements, research priorities, design, and implementation strategies. ISPRS J. Photogramm. Remote. Sens. 2018, 146, 108–123.