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Baltimore Stream Restoration: Assessments of Environmental, Willingness to Pay, and Social Suitability
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| Type: | Resource | |
| Storage: | The size of this resource is 11.7 MB | |
| Created: | Mar 11, 2026 at 4:51 p.m. (UTC) | |
| Last updated: | Mar 12, 2026 at 10:17 p.m. (UTC) | |
| Citation: | See how to cite this resource | |
| Content types: | CSV Content |
| Sharing Status: | Public |
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| Views: | 96 |
| Downloads: | 7 |
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Abstract
Reducing nitrogen delivery to coastal waters is a “wicked problem” involving tradeoffs in environmental, economic and social need domains. Because these tradeoffs arise from spatial and temporal complexities in sources and sinks of this element, we hypothesized that a transdisciplinary focus on disproportionality could allow for the identification of “hot” or “sweet” spots where multiple factors converge to create opportunities to control nitrogen flux. We applied this approach to the Baltimore, MD USA region by mapping stream reaches with high nitrogen concentrations, hydrologic conditions amenable to stream restoration, high willingness to pay for restoration projects, and high social need for restoration, and subsequently identifying locations where these factors converge to create sweet spots. Our analysis suggests that sweet spots that optimize environmental, economic, and social need components of sustainability may be rare. The desire to bundle multiple benefits in the budgeting for environmental interventions such as stream restoration may create a sub-optimal distribution of these interventions in a sustainability context.
The repository:
The repository includes data stream-level nitrogen reduction post-stream restoration, willingness to pay (WTP) from households within 1 mile of stream midpoints, and associated census factors within the 1-mi buffer. Estimates of stream nitrogen concentrations from the SPARROW model (https://sparrow.wim.usgs.gov/sparrow-northeast-2012) within our study area are also included. A Jupyter Notebook contains code for processing and generating figures of the study. Check "README.docx" file for details.
Subject Keywords
Coverage
Spatial
Content
README.md
The repository contains python code (FigurePlotting_DataProcessing.ipynb) and data that Groffman et al. (2026) used.
Code
FigurePlotting_DataProcessing.ipynb:
- This Jupyter Notebook detailed how figures were created using the data from SPARROW TN concentration, willingness to pay (WTP) from stream restoration with forest and boulder landscape, and social need index derived from census data.
- Comments/notes within the notebook explained how each variable is calculated and classified.
- Geospatial visualizations were produced using the Contextily library. The basemap utilizes the CartoDB Positron style, which incorporates data from OpenStreetMap contributors and is distributed under the Creative Commons Attribution 3.0 (CC BY 3.0) license.
Tabular Data (./Data)
WTP_stream_seg.csv
Total WTP for design and per lb of N reduction from all households with 1-mi buffer from stream segments (see shapefiles/Stream_seg.json) delineated in Baltimore.
| Name | Description |
|---|---|
| fid | Identifier for stream reaches |
| FREQUENCY | Number of households inside 1-mi buffer |
| SUM_pub_WTP_FB | Total WTP for forest and boulder on public land |
| SUM_pri_WTP_FB | Total WTP for forest and boulder on private land |
| SUM_pub_WTP_GB | Total WTP for grass and boulder on public land |
| SUM_pri_WTP_GB | Total WTP for grass and boulder on private land |
| SUM_pub_WTP_N_red | WTP for per lb of N reduction on public land |
| SUM_pri_WTP_N_red | WTP for per lb of N reduction on private land |
Social_Need_Index.csv
Social need index derived by area-averaging census information (population density, vegetation cover, median household income, and median property value) within the 1-mi buffer from midpoint of each stream segment.
| Name | Description |
|---|---|
| fid_1 | Identifier for stream reaches |
| SUM_Weighted_Index | Sum of individual social index |
Shapefiles
Stream_seg.json (n = 4,596)
Delineated stream segments (~1000 ft) using 10-m DEM data (https://www.sciencebase.gov/catalog/item/681c128bd4be0260c2c465b4) from USGS. Stream network is delineated using r.watershed (https://grass.osgeo.org/grass-stable/manuals/r.watershed.html) tool in GRASS GIS.
| Name | Description |
|---|---|
| stream_fid | Identifier for stream reaches |
| strahler_order | Strahler stream order |
| pct_public_buffer | % public land within 100-m of stream reach |
| household_count | Number of households within 1-m of stream midpoint |
| f75 | Stream flashiness (Shields et al. (2008)) |
Sparrow_NE_BAL.json (n = 609)
SPARROW total nitrogen concentration (from USGS’s 2012 Northeast dataset, https://sparrow.wim.usgs.gov/sparrow-northeast-2012).
| Name | Description |
|---|---|
| COMID | Identifier of NHDPlus stream |
| GNIS_NAME | Name of stream |
| ne_sparrow | Total nitrogen concentration (mg/L) |
| quintiles | Quintile group labels |
Administrative Boundaries and Spatial Data
- BALT_City.shp: Baltimore City boundary (https://data.imap.maryland.gov/datasets/2315ef0b071a4ec59420e3d342dbcfe2_0).
- BALT_County.shp : Baltimore County boundary (https://data.imap.maryland.gov/datasets/2315ef0b071a4ec59420e3d342dbcfe2_0).
- URDL.shp : Urban-Rural Demarcation Line (https://opendata.baltimorecountymd.gov/datasets/BC-GIS::urban-rural-demarcation-line).
- MergedWatersheds.gpkg: Three major watersheds, Gwynns Falls, Jones Falls, and Herring Run, in Baltimore, delineated from USGS 10-m DEM using GRASS GIS's r.watershed.
References
Shields, C. A., Band, L. E., Law, N., Groffman, P. M., Kaushal, S. S., Savvas, K., Fisher, G. T., & Belt, K. T. (2008). Streamflow distribution of non–point source nitrogen export from urban‐rural catchments in the Chesapeake Bay watershed. Water Resources Research, 44(9). https://doi.org/10.1029/2007wr006360
Related Resources
| This resource is described by | Rosenberg, A. B., Newburn, D. A., & Towe, C. A. (2022). Household willingness to pay for stream restoration on private and public land: Evidence from the Baltimore metropolitan region. JAWRA Journal of the American Water Resources Association, 59(2), 376–395. https://doi.org/10.1111/1752-1688.13089 |
| This resource is described by | Zhang, R., Newburn, D., Rosenberg, A., Lin, L., Groffman, P., Duncan, J., & Band, L. (2022). Spatial Asynchrony in environmental and economic benefits of stream restoration. Environmental Research Letters, 17(5), 054004. https://doi.org/10.1088/1748-9326/ac61c6 |
| This resource is described by | Shields, C. A., Band, L. E., Law, N., Groffman, P. M., Kaushal, S. S., Savvas, K., Fisher, G. T., & Belt, K. T. (2008). Streamflow distribution of non–point source nitrogen export from urban‐rural catchments in the Chesapeake Bay watershed. Water Resources Research, 44(9). https://doi.org/10.1029/2007wr006360 |
| The content of this resource is derived from | Zhang, R. (2026). Baltimore Stream Restoration: Assessments of Environmental, Willingness to Pay, and Social Suitability, HydroShare, http://www.hydroshare.org/resource/2eb09e65cde84162a9a5fdeb580b7623, accessed on: 03/11/2026 |
Credits
Funding Agencies
This resource was created using funding from the following sources:
| Agency Name | Award Title | Award Number |
|---|---|---|
| U.S. National Science Foundation | Coastal Science, Engineering and Education for Sustainability | EAR-1426819 |
| U.S. National Science Foundation | Long Term Ecological Research | DEB-1855277 |
| U.S. National Science Foundation | Long Term Research in Environmental Biology | DEB-2123318 |
| United States Department of Agriculture | None | None |
Contributors
People or Organizations that contributed technically, materially, financially, or provided general support for the creation of the resource's content but are not considered authors.
| Name | Organization | Address | Phone | Author Identifiers |
|---|---|---|---|---|
| Lawrence Band | University of Virginia | Virginia, US | ||
| David A. Newburn | University of Maryland | |||
| J. Morgan Grove | USDA Forest Service | |||
| Andrew Miller | University of Maryland, Baltimore County | |||
| Andrew Rosenberg | USDA Economic Research Service | |||
| Charles Towe | University of Connecticut | |||
| Dexter Locke | USDA Forest Service | |||
| Ruoyu Zhang | University of Virginia | Virginia, US | ||
| Alexander Reisinger | University of Florida | |||
| Jon Duncan | Penn State University | PA, US | ||
| Peter Groffman | City University of New York;Cary Institute of Ecosystem Studies | New York, US |
How to Cite
This resource is shared under the Creative Commons Attribution CC BY.
http://creativecommons.org/licenses/by/4.0/
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