Road runoff is understood to be a significant stressor in terrestrial and aquatic ecosystems, yet the effects of this stressor are poorly understood at large spatial scales. We developed an efficient method for estimating the spatial impact of road runoff on lands and waters over large geographic areas and then applied our methodology to the 2.4 million ha Adirondack Park in New York State. We used TauDEM hydrologic modeling and a series of ESRI GIS processes to delineate surface flow downslope of paved roads, illustrating the potential movement of pollutants originating from paved roads through the USGS 10 m DEM topography. We then estimated the land and surface water areas, number of water bodies, and total stream length potentially impacted by road runoff from paved roads. We found that as much as 11 % of land area, 77 % of surface water area, 1/3 of the water bodies, and 52 % of stream length in the Adirondack Park may be impacted by road runoff. The high degree of hydrologic association between paved roads and the lands and waters of this region strongly suggests that the environmental impacts of road runoff should be evaluated along with other regional stressors currently being studied. Being able to estimate the spatial impact of road runoff is important for designing monitoring programs that can explicitly monitor this stressor while also providing opportunities to understand the interaction of multiple environmental stressors.
This is a preview of subscription content, access via your institution.
Buy single article
Instant access to the full article PDF.
Tax calculation will be finalised during checkout.
Agha, R., Cires, S., Wörmer, L., Domínguez, J. A., & Quesada, A. (2012). Multi-scale strategies for the monitoring of freshwater cyanobacteria: reducing the sources of uncertainty. Water Research, 46, 3043–3053.
Allan, J. (2004). Landscapes and riverscapes: the influence of land use on stream ecosystems. Annual Review of Ecology, Evolution and Systematics, 35, 257–284.
Bernhardt-Roemermann, M., Kirchner, M., Kudernatsch, T., Jakobi, G., & Fischer, A. (2006). Changed vegetation composition in coniferous forests near to motorways in Southern Germany: the effects of traffic-born pollution. Environmental Pollution, 143, 572–581.
Betz, R., Hitt, N. P., Dymond, R. L., & Heatwole, C. D. (2010). A method for quantifying stream network topology over large geographic extents. Journal of Spatial Hydrology, 10, 15–29.
Collins, S. J., & Russell, R. W. (2009). Toxicity of road salt to Nova Scotia amphibians. Environmental Pollution, 157, 320–324.
Corsi, S. R., De Cicco, L. A., Lutz, M. A., & Hirsch, R. M. (2015). River chloride trends in snow-affected urban watersheds: increasing concentrations outpace urban growth rate and are common among all seasons. Science of the Total Environment, 508, 488–497.
Crooks, J. A., Chang, A. L., & Ruiz, G. M. (2011). Aquatic pollution increases the relative success of invasive species. Biological Invasions, 13, 165–176.
Daley, M. L., Potter, J. D., & McDowell, W. H. (2009). Salinization of urbanizing New Hampshire streams and groundwater: effects of road salt and hydrologic variability. Journal of the North American Benthological Society, 28, 929–940.
Dalinsky, S. A., Lolya, L. M., Maguder, J. L., Pierce, J. L. B., Kelting, D. L., Laxson, C. L., & Patrick, D. A. (2014). Comparing the effects of aquatic stressors on model temperate freshwater aquatic communities. Water, Air, & Soil Pollution, 225. doi: 10.1007/s11270-014-2007-9.
de Lima, J. L. M. P., & Singh, V. P. (2002). The influence of the pattern of moving rainstorms on overland flow. Advances in Water Resources, 25, 817–828.
de Silva, N. D. G., Cholewa, E., & Ryser, P. (2012). Effects of combined drought and heavy metal stresses on xylem structure and hydraulic conductivity in red maple (Acer rubrum L.). Journal of Experimental Botany, 63, 5957–5966.
Fan, Y., Weisberg, P. J., & Nowak, R. S. (2014). Spatio-temporal analysis of remotely-sensed forest mortality associated with road de-icing salts. Science of the Total Environment, 472, 929–938.
Fancy, S. G., Gross, J. E., & Carter, S. L. (2009). Monitoring the condition of natural resources in US national parks. Environmental Monitoring and Assessment, 151, 161–174.
Fay, L., & Shi, X. (2012). Environmental impacts of chemicals for snow and ice control: state of the knowledge. Water, Air, & Soil Pollution, 223, 2751–2770.
Ferreira, A. L., Loureiro, S., & Soares, A. M. (2008). Toxicity prediction of binary combinations of cadmium, carbendazim and low dissolved oxygen on Daphnia magna. Aquatic Toxicology, 89, 28–39.
Gałuszka, A., Migaszewski, Z. M., Podlaski, R., Dołęgowska, S., & Michalik, A. (2011). The influence of chloride deicers on mineral nutrition and the health status of roadside trees in the city of Kielce, Poland. Environmental Monitoring and Assessment, 176, 451–464.
Gesch, D., & Wilson, R. (2001). Development of a seamless multisource topographic/bathymetric elevation model of Tampa Bay. Marine Technology Society Journal, 35(4), 58–64.
Goddeeris, B. R., Vermeulen, A. C., De Geest, E., Jacobs, H., Baert, B., & Ollevier, F. (2001). Diapause induction in the third and fourth instar of Chironomus riparius (Diptera) from Belgian lowland brooks. Archiv für Hydrobiologie, 150, 307–327.
Hayhoe, K., Wake, C. P., Huntington, T. G., Luo, L., Schwartz, M. D., & Sheffield, J. (2007). Past and future changes in climate and hydrological indicators in the US Northeast. Climate Dynamics, 28, 381–407.
Hodkinson, I. D., & Jackson, J. K. (2005). Terrestrial and aquatic invertebrates as bioindicators for environmental monitoring, with particular reference to mountain ecosystems. Environmental Management, 35, 649–666.
Holmstrup, M., Bindesbøl, A. M., Oostingh, G. J., Duschl, A., Scheil, V., & Köhler, H. R. (2010). Interactions between effects of environmental chemicals and natural stressors: a review. Science of the Total Environment, 408, 3746–3762.
Hynes, H. B. N. (1975). The stream and its valley. Verhandlungen der Internationalischen Vereinigung für Theoretische und Angewandte Limnologie, 19, 1–15.
Ito, M., Mitchell, M. J., & Driscoll, C. T. (2002). Spatial patterns of precipitation quantity and chemistry and air temperature in the Adirondack region of New York. Atmospheric Environment, 36, 1051–1062.
Jackson, R. B., & Jobbagy, E. G. (2005). From icy roads to salty streams. Proceedings of the National Academy of Sciences, 102, 14487–14488.
Jenkins, J., & Keal, A. (2004). The Adirondack Atlas. Syracuse: Syracuse University Press.
Jensen, T. C., Meland, S., Schartau, A. K., & Walseng, B. (2014). Does road salting confound the recovery of the microcrustacean community in an acidified lake? Science of the Total Environment, 478, 36–47.
Jenson, S. K., & Domingue, J. O. (1988). Extracting topographic structure from digital elevation data for geographic information system analysis. Photogrammetric Engineering and Remote Sensing, 54, 1593–1600.
Johnston, F. M., & Johnston, S. W. (2004). Impacts of road disturbance on soil properties and on exotic plant occurrence in subalpine areas of the Australian Alps. Arctic, Antarctic, and Alpine Research, 36, 201–207.
Karraker, N. E., Gibbs, J. P., & Vonesh, J. R. (2008). Impacts of road deicing salt on the demography of vernal pool-breeding amphibians. Ecological Applications, 18, 724–734.
Kaspari, M., Chang, C., & Weaver, J. (2010). Salted roads and sodium limitation in a northern forest ant community. Ecological Entomology, 35, 543–548.
Kaushal, S. S., Groffman, P. M., Likens, G. E., Belt, K. T., Stack, W. P., Kelly, V. R., & Fisher, G. T. (2005). Increased salinization of fresh water in the northeastern United States. Proceedings of the National Academy of Sciences of the United States of America, 102, 13517–13520.
Ke, C., Li, Z., Liang, Y., Tao, W., & Du, M. (2013). Impacts of chloride de-icing salt on bulk soils, fungi, and bacterial populations surrounding the plant rhizosphere. Applied Soil Ecology, 72, 69–78.
Kelting, D. L., & Laxson, C. L. (2010). Review of effects and costs of road de-icing with recommendations for winter road management in the Adirondack Park. Adirondack Watershed Institute, Paul Smith’s College, Paul Smiths, NY, Adirondack Watershed Institute Report# AWI2010-01.
Kelting, D. L., Laxson, C. L., & Yerger, E. C. (2012). Regional analysis of the effect of paved roads on sodium and chloride in lakes. Water Research, 46, 2749–2758.
Kiesecker, J. M. (2002). Synergism between trematode infection and pesticide exposure: a link to amphibian limb deformities in nature? Proceedings of the National Academy of Sciences, 99, 9900–9904.
Kilgour, B. W., Gharabaghi, B., & Perera, N. (2014). Ecological benefit of the road salt code of practice. Water Quality Research Journal of Canada, 49, 43–52.
Kishbaugh, S. A. (1988). The New York citizens’ statewide lake assessment program. Lake and Reservoir Management, 4, 137–145.
Klimaszewska, K. K., Polkowska, Ż. Ż., & Namieśnik, J. J. (2007). Influence of mobile sources on pollution of runoff waters from roads with high traffic intensity. Polish Journal of Environmental Studies, 16, 889–897.
Labadia, C. F., & Buttle, J. M. (1996). Road salt accumulation in highway snow banks and transport through the unsaturated zone of the Oak Ridges Moraine, Southern Ontario. Hydrological Processes, 10, 1575–1589.
Larsen, D. P., Olsen, A. R., Lanigan, S. H., Moyer, C., Jones, K. K., & Kincaid, T. M. (2007). Sound survey designs can facilitate integrating stream monitoring data across multiple programs. Journal of the American Water Resources Association, 43, 384–397.
Laudon, H., Seibert, J., Köhler, S., & Bishop, K. (2004). Hydrological flow paths during snowmelt: congruence between hydrometric measurements and oxygen 18 in meltwater, soil water, and runoff. Water Resources Research, 40, doi:10.1029/2003WR002455.
McDonald, T. L. (2002). Review of environmental monitoring methods: survey designs. Environmental Monitoring and Assessment, 85, 277–292.
McEathron, K. M., Mitchell, M. J., & Zhang, L. (2013). Acid-base characteristics of the Grass Pond watershed in the Adirondack Mountains of New York State, USA: interactions among soil, vegetation and surface waters. Hydrology and Earth System Sciences, 17, 2557.
McMaster, K.J. (2002). Effects of digital elevation model resolution on derived stream network positions. Water Resources Research, 38, doi: 10.1029/2000WR000150.
Meriano, M., Eyles, N., & Howard, K. W. (2009). Hydrogeological impacts of road salt from Canada's busiest highway on a Lake Ontario watershed (Frenchman's Bay) and lagoon, City of Pickering. Journal of Contaminant Hydrology, 107, 66–81.
Meter, R., Swan, C., Leips, J., & Snodgrass, J. (2011). Road salt stress induces novel food web structure and interactions. Wetlands, 31, 843–851.
Neher, D. A., Asmussen, D., & Lovell, S. (2013). Roads in northern hardwood forests affect adjacent plant communities and soil chemistry in proportion to the maintained roadside area. Science of the Total Environment. doi:10.1016/j.scitotenv.2013.01.062.
New York DEC. (2009). New York State section 305(b) and 303(d) consolidated assessment and listing strategy. New York State Department of Environmental Conservation.
New York State Department of Transportation. (2006). Highway maintenance guidelines: snow and ice control.
Nimiroski, M.T., & Waldron, M.C. (2002). Sources of sodium and chloride in the Scituate Reservoir Drainage Basin, Rhode Island. U.S. Geological Survey Report WRIR 02-4149.
Norrström, A. C., & Bergstedt, E. E. (2001). The impact of road de-icing salts (NaCl) on colloid dispersion and base cation pools in roadside soils. Water, Air, & Soil Pollution, 127, 281–299.
Oberts, G. L. (1994). Influence of snowmelt dynamics on stormwater runoff quality. Watershed Protection Techniques, 1(2), 16–22.
Palmer, M. E., & Yan, N. D. (2013). Decadal‐scale regional changes in Canadian freshwater zooplankton: the likely consequence of complex interactions among multiple anthropogenic stressors. Freshwater Biology, 58, 1366–1378.
Perera, N., Gharabaghi, B., & Howard, K. (2012). Groundwater chloride response in the Highland Creek watershed due to road salt application: a re-assessment after 20 years. Journal of Hydrology, 479, 159–168.
Price, J. R., & Szymanski, D. W. (2013). The effects of road salt on stream water chemistry in two small forested watersheds, Catoctin Mountain, Maryland, USA. Aquatic Geochemistry. doi:10.1007/s10498-013-9193-8.
Qiang, J., Ren, H., Xu, P., He, J., & Li, R. (2012). Synergistic effects of water temperature and salinity on the growth and liver antioxidant enzyme activities of juvenile GIFT Oreochromis niloticus. Yingyong Shengtai Xuebao, 23, 255–263.
Rosfjord, C. H., Webster, K. E., Kahl, J. S., Norton, S. A., Fernandez, I. J., & Herlihy, A. T. (2007). Anthropogenically driven changes in chloride complicate interpretation of base cation trends in lakes recovering from acidic deposition. Environmental Science & Technology, 41, 7688–7693.
Schiedek, D., Sundelin, B., Readman, J. W., & Macdonald, R. W. (2007). Interactions between climate change and contaminants. Marine Pollution Bulletin, 54, 1845–1856.
Silver, P., Rupprecht, S. M., & Stauffer, M. F. (2009). Temperature-dependent effects of road deicing salt on chironomid larvae. Wetlands, 29, 942–951.
Sloman, K. A., Scott, G. R., Diao, Z., Rouleau, C., Wood, C. M., & McDonald, D. (2003). Cadmium affects the social behavior of rainbow trout, Oncorhynchus mykiss. Aquatic Toxicology, 65(2), 171–185. doi:10.1016/S0166-445X(03)00122-X.
Snell-Rood, E. C., Espeset, A., Boser, C. J., White, W. A., & Smykalski, R. (2014). Anthropogenic changes in sodium affect neural and muscle development in butterflies. Proceedings of the National Academy of Sciences. doi:10.5061/dryad.v2t58.
Soranno, P. A., Cheruvelil, K. S., Bissell, E. G., Bremigan, M. T., Downing, J. A., Fergus, C. E., & Webster, K. E. (2014). Cross-scale interactions: quantifying multi-scaled cause-effect relationships in macrosystems. Frontiers in Ecology and the Environment, 12, 65–73.
Stager, J., McNulty, S., Beier, C., & Chiarenzelli, J. (2009). Historical patterns and effects of changes in Adirondack climates since the early 20th century. Adirondack Journal of Environmental Studies, 15, 14–24.
Sullivan, T. J., Fernandez, I. J., Herlihy, A. T., Driscoll, C. T., McDonnell, T. C., Nowicki, N. A., Snyder, K. U., & Sutherland, J. W. (2006). Acid-base characteristics of soils in the Adirondack Mountains, New York. Soil Science Society of America Journal, 70, 141–152.
Tang, J. M., Aryal, R., Deletic, A., Gernjak, W., Glenn, E., McCarthy, D., & Escher, B. I. (2013). Toxicity characterization of urban stormwater with bioanalytical tools. Water Research, 47, 5594–5606.
Tarboton, D. G. (1997). A new method for the determination of flow directions and contributing areas in grid digital elevation models. Water Resources Research, 33, 309–319.
Tarboton, D. G., Schreuders, K. A. T., Watson, D. W., & Baker, M. E. (2009). Generalized terrain-based flow analysis of digital elevation models. In Proceedings of the 18th World IMACS Congress and MODSIM09 International Congress on Modelling and Simulation, Cairns, Australia (pp. 2000-2006).
Trombulak, S. C., & Frissell, C. A. (2000). Review of ecological effects of roads on terrestrial and aquatic communities. Conservation Biology, 14, 18–30.
Vannote, R. L., Minshall, G. W., Cummins, K. W., Sedell, J. R., & Cushing, C. E. (1980). The river continuum concept. Canadian Journal of Fisheries and Aquatic Sciences, 37, 130–137.
Waller, K., Driscoll, C., Lynch, J., Newcomb, D., & Roy, K. (2012). Long-term recovery of lakes in the Adirondack region of New York to decreases in acidic deposition. Atmospheric Environment, 46, 56–64.
Woods, R. (2006). Hydrologic concepts of variability and scale. In M. G. Anderson (Ed.), Encyclopedia of hydrological sciences, part 1. Theory, organization and scale. New York: Wiley.
Yang, J., & Chu, X. (2013). Effects of DEM resolution on surface depression properties and hydrologic connectivity. Journal of Hydrologic Engineering, 18, 1157–1169.
Yousef, Y. A., Wanielista, M. P., Harper, H. H., & Skene, E. T. (1983). Impact of bridging on floodplains. Transportation Research Record, 948, 26–30.
Zechmeister, H. G., Hohenwallner, D. D., Riss, A. A., & Hanus-Illnar, A. A. (2005). Estimation of element deposition derived from road traffic sources by using mosses. Environmental Pollution, 138, 238–249.
Zhang, W., & Montgomery, D. R. (1994). Digital elevation model grid size, landscape representation, and hydrologic simulations. Water Resources Research, 30, 1019–1028.
Support for this research was provided with a grant from the Northeastern States Research Cooperative (nsrcforest.org).
Below are detailed instructions that accompany each subsection in “Methods”.
Producing a hydrologically relevant surface
The DEMs were mosaicked into a single raster dataset using the ArcGIS data management tool “workspace to new raster dataset.” Missing cells within the mosaicked dataset were identified using the “Is Null” tool. Identified missing cells were then replaced with interpolated elevation values using a conditional statement in ArcGIS. A low pass filter was used to remove DEM artifacts and noise from the appended DEM (Gesch and Wilson 2001).
Producing road disturbance grids
The eight shapefiles (SF, C, L, and SFCL and 100 m SF, 100 m C, 100 mL, and 100 m SFCL) were converted into 10 m cell size raster datasets using the ArcGIS “polyline to new raster” tool and the “polygon to new raster” tool. The new rasters were reclassified so that roads were set to a value of 1 and non-road cells were set to a value of 0. Reclassification was necessary to create a disturbance grid input parameter for the accumulation tool. The final indicator grids were then converted to TIFF as the accumulation tool requires this file format. The disturbance grid indicates the zone of the area of substance supply (runoff) with 1 representing the zone and 0 representing the rest of the domain.
Producing input weights
The effective runoff and decay multiplier grids were created by reclassifying of one of the disturbance area grids to a constant value of 1.
Delineating overland flow grids
TauDEM’s “D-Infinity concentration limited accumulation” functionality applies to a situation where an unlimited supply of a substance is loaded at a constant concentration over the cells of a value of 1 in the disturbance grid. For this paper, road runoff was the substance, and roads were the cells with a value of 1 in the disturbance grid. All inputs were clipped to a standard size to fit the needs of the tool parameters. The outputs were eight overland flow grids representing downhill flow originating from SF, C, L, and SFCL roads. These eight outputs were clipped by the extent of the Adirondack Park boundary polygon (apa.ny.gov/gis) to retain park only overland flow.
Quantifying impacted land area
Multiplying the overland flow dataset by open water cells represented by NoData excluded the original values from the output, and multiplying by 1 retained the original values in the output. The park wide open water raster data was created by clipping a NYS hydrography shapefile of lakes and ponds (gis.ny.gov) to the Adirondack Park boundary shapefile used above and then converting the clipped shapefile into a raster dataset using the ArcGIS “polygon to new raster” tool. The new raster dataset was then reclassified so that open water was represented by NoData and land area represented by a value of 1. The cell counts in the eight no-open-water overland flow grids were found and then multiplied by the cell area (100 m2) to find the total terrestrial area impacted by road runoff. Values were reported in hectares.
Identifying impacted lakes and ponds
Total surface area (hectares) of these impacted water bodies was calculated using the calculate geometry function.
Calculating downstream length of impacted streams
Point shapefiles were created at their intersections by setting the output type in the “intersect” tool to point. The raster dataset was then reclassified so that cells represent intersection as a value of 1 and non-intersection cells as a value of 0. Input effective runoff and decay grids as well as the original D-Infinity flow direction grid were reused. The eight output flow grids were thinned using the ArcGIS “thin” tool, and flow cells over lakes and ponds were removed. Thinning accumulation rasters efficiently identifies stream channels over large geographic areas (Betz et al. 2010). This approach is aimed at sidestepping the process of using flow accumulation thresholds to identify stream channels across the entire park. We found the intersection of overland flow from roads and linear stream data was sufficient for identifying the presence of a stream. Total lengths (kilometers) of these impacted stream channels were calculated using the calculate geometry function.
Quantifying impacted land and waters in APA forest preserve lands
Forest preserve land is represented by 4 of the 15 land use types, wilderness, primitive, canoe, and wild forest. These four land use types were merged, and impacted surface waters and streams for each of the six disturbance categories within the preserve were calculated by ESRI’s Select by Location and calculate geometry functions.
Betz, R., Hitt, N. P., Dymond, R. L., & Heatwole, C. D. (2010). A method for quantifying stream network topology over large geographic extents. Journal of Spatial Hydrology, 10, 15-29.
Gesch, D., & Wilson, R. (2001). Development of a seamless multisource topographic/bathymetric elevation model of Tampa Bay. Marine Technology Society Journal, 35(4), 58-64.
About this article
Cite this article
Regalado, S.A., Kelting, D.L. Landscape level estimate of lands and waters impacted by road runoff in the Adirondack Park of New York State. Environ Monit Assess 187, 510 (2015). https://doi.org/10.1007/s10661-015-4730-0
- Road runoff
- Road salt
- Multiple environmental stressors
- Adirondack Park