A Landscape Scale Valley Confinement Algorithm .
A Landscape Scale Valley Confinement Algorithm:Delineating Unconfined Valley Bottoms for Geomorphic,Aquatic, and Riparian ApplicationsDavid E. Nagel, John M. Buffington, Sharon L. Parkes, Seth Wenger, and Jaime R. GoodeUnited States Department of Agriculture / Forest ServiceRocky Mountain Research StationGeneral Technical Report RMRS-GTR-321June 2014
Nagel, David E.; Buffington, John M.; Parkes, Sharon L.; Wenger, Seth; Goode, Jaime R.2014. A landscape scale valley confinement algorithm: Delineating unconfined valleybottoms for geomorphic, aquatic, and riparian applications. Gen. Tech. Rep. RMRSGTR-321. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky MountainResearch Station. 42 p.AbstractValley confinement is an important landscape characteristic linked to aquatic habitat, ripariandiversity, and geomorphic processes. This report describes a GIS program called the ValleyConfinement Algorithm (VCA), which identifies unconfined valleys in montane landscapes.The algorithm uses nationally available digital elevation models (DEMs) at 10-30 m resolution to generate results at subbasin scales (8 digit hydrologic unit). User-defined parametersallow results to be tailored to specific applications and landscapes. Field data were sampledto verify geomorphic characteristics of valley types identified by the program, and a detailedaccuracy assessment was conducted to quantify the reliability of the algorithm output.Keywords: valley confinement, valley bottom, stream channel morphology, fish habitat,riparian habitatAuthorsDavid E. Nagel is a Spatial Analyst with the Rocky MountainResearch Station, Boise Aquatic Sciences Laboratory in Boise,Idaho. He holds a B.S. degree from Michigan State Universityand an M.S. degree from the University of Wisconsin-Madison.He has worked for private, state, and Federal agencies formore than 25 years in the fields of GIS and remote sensing.He is currently involved with developing spatial analysis toolsfor watershed and aquatic applications.John M. Buffington is a Research Geomorphologist with theRocky Mountain Research Station, Boise Aquatic SciencesLaboratory in Boise, Idaho. He holds a B.A. degree in geologyfrom the University of California, Berkeley, with M.S. and Ph.D.degrees in geomorphology from the University of Washington.He was a National Research Council Fellow from 1998 to 2000and a professor in the Center for Ecohydraulics Research at theUniversity of Idaho from 2000 to 2004. His research focuses onfluvial geomorphology of mountain basins, biophysical interactions, and the effects of natural and anthropogenic disturbanceson salmonid habitat.Sharon L. Parkes is GIS Specialist with the Rocky MountainResearch Station, Boise Aquatic Sciences Laboratory in Boise,Idaho. She holds a B.S. degree from Lincoln University andgraduated Summa Cum Laude as an 1890 USDA Land-grantScholar. She conducts GIS analyses and web program development.Seth Wenger is an Assistant Professor at the University ofGeorgia, Odum School of Ecology. He holds an undergraduate degree from Lebanon Valley College, with M.S. and Ph.D.degrees from the University of Georgia. He studies potentialeffects of climate change on native and invasive trout in theWestern United States.Jaime R. Goode is a Lecturer at the University of Aberdeen,Scotland. She holds a B.S. degree from Connecticut Collegewith M.S. and Ph.D. degrees from Colorado State University.Her interests include interactions among ecologic and geomorphic processes in mountain environments, specifically rivers.You may order additional copies of this publication by sending your mailing information in label form through one of the following media.Please specify the publication title and number.Publishing ServicesTelephone (970) 498-1392FAXWeb siteMailing Address(970) 498-1122http://www.fs.fed.us/rmrsPublications DistributionRocky Mountain Research Station240 West Prospect RoadFort Collins, CO 80526
AcknowledgmentsBruce Rieman and Jason Dunham provided the initial impetus and guidancefor developing a GIS based valley confinement algorithm for use in fisheriesapplications. David Theobald and Kurt Fesenmyer provided valuable reviewsof this report and their time and insight are greatly appreciated. Thank you toLeslie Jones and Joel Murray who provided useful feedback by testing the VCAfor their respective study sites.Disclaimer of Non-endorsement—Reference herein to any specific commercial products, process,or service by trade name, trademark, manufacturer, or otherwise, does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government. Theviews and opinions of authors expressed herein do not necessarily state or reflect those of theUnited States Government, and shall not be used for advertising or product endorsement purposes.ArcGIS, ArcMap, and ArcCatalog are registered trademarks of ESRI, Inc., 380 New York Street, Redlands,CA 92373The Python Programming Language and Python are registered trademarks of the Python Software Foundation, http://www.python.org/psf/.
Executive SummaryValley confinement describes the degree to whichbounding topographic features, such as hillslopes, alluvialfans, glacial moraines, and river terraces, limit the lateralextent of the valley floor and the floodplain along a river.Valleys can be broadly classified as confined or unconfined, with corresponding differences in their appearance,vegetation, ground water exchange rates, topographicgradient, and stream characteristics. Unconfined valleys are generally less extensive than confined valleysin montane environments, but host a diverse array ofterrestrial and aquatic organisms and provide disproportionately important ecosystem functions. Consequently,identifying the location and abundance of each valleytype is increasingly recognized as an important aspectof ecosystem management. In this report, we describea GIS program called the Valley Confinement Algorithm(VCA) that maps the extent and shape of unconfinedvalley bottoms using readily available spatial data asinput.The VCA is designed to operate using ESRI ArcGISsoftware with 1:100,000 scale stream lines from the National Hydrography Dataset (NHDPlusV1) and 10-30 mdigital elevation models (DEMs). The algorithm focuseson fluvial applications and therefore only considers channeled valleys. The smallest unconfined valley that can beresolved by the VCA depends on the resolution of the DEM;the VCA is unable to resolve unconfined valleys that arenarrower than about two to three times the DEM cell size(i.e., valleys that are 60-90 m in width for a 30 m DEM or20-30 m for a 10 m DEM). In addition, as bankfull widthapproaches two times the DEM cell size, the VCA maymisinterpret the channel as a narrow unconfined valley.Consequently, care should be exercised in interpretingresults in such locations.We conducted field work in central Idaho to documentchannel characteristics in confined and unconfined valleysmapped by the algorithm. Results showed that channelconfinement measured in the field (ratio of valley widthto bankfull width) agreed with valley confinement predicted by the algorithm 79% of the time and that channelcharacteristics were similar to those documented in otherstudies of confinement. In particular, confined channelstypically exhibited steep-gradient step-pool and planebed morphologies composed of coarse-grained bedmaterial, with a median channel confinement of about2 bankfull widths. In contrast, unconfined channels wereprimarily low-gradient pool-riffle and plane-bed streamscomposed of finer substrate, with a median channelconfinement of about 10 bankfull widths.We further assessed the accuracy of the algorithm bygenerating a stratified random sample of points equallypartitioned between confined and unconfined valleysas identified by the VCA. Predicted valley types werecompared with those observed from digital photos andquadrangle maps. Results showed that the algorithmcould differentiate between the two valley types with89-91% accuracy.
ContentsIntroduction. 1Part I—Review. 6Morphogenesis of Unconfined Valleys. 6Application and Significance of Valley Confinement. 7Previous Algorithms and Comparison to the VCA Approach. 9Part II—VCA Software.11Software Requirements and Overview.11Scale Considerations.11Input and Ancillary Data Overview. 14Input and Ancillary GIS Data Download Instructions. 15Input and Ancillary GIS Data Pre-processing Instructions. 16Substituting Higher Resolution Input Data. 17Program Inputs, Parameters, and Output. 18Algorithm Sequence. 19Output Shapefiles. 22Part III—Field Assessment. 23Approach. 23Findings and Discussion. 25Part IV—Statistical Validation. 30Methods. 30Results . 31Part V—Online Database. 33Part VI—Summary. 35References. 35Appendix A. Field Collected Data. 40Appendix B: Examples of Channel Types. 41Appendix C: Examples of Substrate Types. 42
A Landscape Scale Valley Confinement Algorithm:Delineating Unconfined Valley Bottoms forGeomorphic, Aquatic, and Riparian ApplicationsDavid E. Nagel, John M. Buffington, Sharon L. Parkes,Seth Wenger, and Jaime R. GoodeIntroductionLooking across a mountainous landscape, an observer will immediately perceive thepeaks, ridges, and valleys that comprise the terrain. Our attention is often drawn to thepeaks, but it is the valleys that carry surface water, harbor fish, provide riparian habitat,and impart critical resources to the montane ecosystem. The morphology, or shape ofthe valley, is an important predictor of the types of services that the valley can providefor the ecosystem. One of the most fundamental characteristics of a valley is its degreeof lateral confinement by topographic features, such as hillslopes, alluvial fans, glacialmoraines, and relict river terraces.Confined valleys in mountain basins are typically narrow and v-shaped, with littlealluvial fill (figure 1). These valleys have relatively steep, erosive gradients, and containcoarse-grained, high-energy streams with little to no floodplain (e.g., Montgomery andBuffington’s (1997) transport reaches [cascade and step-pool channels] or Rosgen’s(1994, 1996) A, B, and G channel types) (figure 2).Figure 1—Graphic of a typical confined valley illustrating shallow alluvial deposits.USDA Forest Service Gen. Tech. Rep. RMRS-GTR-321. 20141
Figure 2—Typical confined valleys in the project study area, described in Part III.2USDA Forest Service Gen. Tech. Rep. RMRS-GTR-321. 2014
In contrast, unconfined valleys are wider depositional areas, with extensive alluvialfill and broad floodplains that allow active channel migration and the development ofchannel sinuosity or braiding (figure 3). Unconfined valleys typically have relativelylower gradients and finer-grained sediment (e.g., Montgomery and Buffington’s (1997)response reaches [pool-riffle and dune-ripple channels] or Rosgen’s (1994, 1996) C,E, and F channel types) (figure 4), except where coarse-grained braided rivers occurbelow alpine glaciers.Both confined and unconfined valleys are associated with different process domainsand ecosystems (e.g., Brierley and Fryirs 2005; Buffington and Tonina 2009; Montgomery 1999; Paustian and others 1992; Wohl and others 2013). Knowing the locationand abundance of each valley type can be a key component for addressing a variety ofmanagement issues related to aquatic species and terrestrial riparian animals.To help address management and research endeavors in fluvial systems where valleyconfinement is of interest, a GIS-based software program called the Valley Confinement Algorithm (VCA) was developed that identifies unconfined valleys using readilyavailable, nationwide spatial data. The program uses stream line data from the NationalHydrography Dataset (NHDPlusV1) and digital elevation models (DEMs) with 10-30 mresolution as input. Unconfined valley bottom polygons are delineated by the algorithmand output in ArcGIS shapefile format. All areas within these polygons are consideredunconfined valleys, while other areas along streams but outside of the polygons areconsidered confined valleys (figure 5). The output is generated at landscape scalescomposed of subbasins defined by 8-digit (4th code) hydrologic units (Seaber and others 1987). Valley confinement can be identified along stream reaches as small as 100m in length. The algorithm optionally produces a second output that computes networkdistance along the stream channel to the nearest unconfined valley bottom polygon(figure 6), which was developed for fisheries applications (Wenger and others 2011).In addition to the VCA, this report describes an online database of valley confinementdata that have been processed for a substantial portion of the western United States.Figure 3—Graphic of a typical unconfined valley illustrating relatively deep alluvial deposits.USDA Forest Service Gen. Tech. Rep. RMRS-GTR-321. 20143
Figure 4—Typical unconfined valleys in the project study area, described in Part III.4USDA Forest Service Gen. Tech. Rep. RMRS-GTR-321. 2014
Figure 5—Example output from the VCA, where unconfined valleys aredelineated as polygons and all other valleys outside of the polygon andalong stream channels are considered confined.Figure 6—Distance from unconfined valleys as measured along thestream network.USDA Forest Service Gen. Tech. Rep. RMRS-GTR-321. 20145
Part I of this document reviews the formation of unconfined valleys, the applicationand significance of valley confinement, and prior automated routines for identifyingunconfined valleys. Part II describes the VCA software and its technical implementation, including details for downloading and preprocessing the input GIS data and anoverview of the algorithm methods. Part III presents field data documenting channelcharacteristics in confined and unconfined valleys mapped by the VCA for central Idaho,and qualitatively assesses the results of the algorithm. Part IV describes a statisticalassessment of the VCA output to examine classification accuracy. Part V describes anonline database of valley confinement data for the Intermountain Region of the westernUnited States, and Part VI summarizes the report.The VCA program described herein may be accessed from the Rocky MountainResearch Station valley confinement s/valley confinement.shtmlPart I—ReviewMorphogenesis of Unconfined ValleysIn the broadest sense, an unconfined valley is a landscape feature that is low lying andrelatively flat compared to its surroundings (Gallant and Dowling 2003). Unconfinedvalleys may be formed by a variety of geologic processes in mountainous environments.Some unconfined valleys may be structural features, such as fault-bound grabens, likethose of the basin and range physiography of the western United States. Others may beself-formed depositional features that occur where the long-term sediment supply exceedsthe channel transport capacity (typically lower-sloped portions of the stream network).In these self-formed cases, floodplain initiation and the development of an unconfinedvalley may be related to downstream gradients in stream power (Jain and others 2008),while absolute values of stream power affect the type of floodplain environment thatoccurs (Nanson and Crooke 1992).In northerly and high elevation systems, Pleistocene alpine glaciers are one of theprimary agents that have influenced valley form. Where glaciers have scoured bedrockto form U-shaped valleys, valley width is generally greater than in fluvially formedenvironments (Amerson and others 2008; Montgomery 2002). In addition, glaciers canhave indirect effects on valley form by delivering large sediment supplies to valleys(e.g., Wohl 2000). When glacial sediment cannot be transported because of inadequatestream power or because it is blocked by a downstream obstruction, such as a moraineor bedrock constriction, a wide valley may be formed with deep alluvial deposits.Valleys may also fill with alluvium from more recent geomorphic activity, such asdebris flows and landslides. Again, if a valley obstruction or inadequate stream powerreduces sediment transport, a wide valley bottom will often form. Valleys may becomewider still if side slopes are composed of low-strength material. These side slopes maybecome over-steepened by lateral erosion, causing slope failure and facilitating additionalsediment input (Lifton and others 2009). Valley width has also been linked to the occurrence of deep-seated landslides that are controlled by lithology and geologic structureand that, in turn, influence habitat availability for salmonids (May and others 2013).Riverine animals and riparian vegetation can also modulate fluvial processes andaffect valley form. For example, beaver dams alter channel slope, transport capacity,and the frequency of overbank flooding, promoting deposition and the developmentor expansion of unconfined valleys, particularly in smaller channels (e.g., Butler andMalanson 1995; 2005; Pollock and others 2007; Persico and Meyer 2009; Polvi and6USDA Forest Service Gen. Tech. Rep. RMRS-GTR-321. 2014
Wohl 2012). Similarly, riparian vegetation creates roughness that increases floodplainsedimentation and stability (Allmendinger and others 2005; Smith 2004) that over timemay lead to expansion of unconfined valleys.Application and Significance of Valley ConfinementValley confinement mapping has been used for a variety of geomorphic, aquatic, andriparian applications. Some applications pertain to physical modeling, such as debrisflow routing, while others are concerned with in-stream biological habitat, botanicalpredictions, or wildlife management.Valley confinement in mountain basins is widely used for classifying process domainsand stream reach morphology due to the strong effect of confinement and associatedvalley slope on fluvial processes and hillslope–channel coupling (e.g., Bengeyfield1999; Brierley and Fryirs 2005; Montgomery 1999; Montgomery and Buffington 1997
Valley confinement is an important landscape characteristic linked to aquatic habitat, riparian diversity, and geomorphic processes. This report describes a GIS program called the Valley Confinement Algorithm (VCA), w
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