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A survey of transverse drainages in the Susquehanna River basin, Pennsylvania
Geomorphology 186 (2013) 50–67
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A survey of transverse drainages in the Susquehanna River basin, Pennsylvania Jacqueline Lee a r t i c l e
i n f o
Article history: Received 26 March 2012 Received in revised form 20 December 2012 Accepted 21 December 2012 Available online 2 January 2013 Keywords: Transverse drainages Susquehanna River Pennsylvania Appalachians Basin evolution Remote sensing
a b s t r a c t Although large-scale transverse drainages (TDs) such as those of the Susquehanna River above Harrisburg, PA, have been recognized since the nineteenth century, only two systematic surveys have been published of TDs (Ver Steeg, 1930; Oberlander, 1965). A topographic and statistical analysis of TDs in the Susquehanna River basin using Google Earth® and associated overlays identified 653 TDs in the study area, 95% of which contain streams with discharges of b 10 m 3/s (cms). The TD depths ranged from a 23-m-deep water gap near Blain, PA, to the 539-m-deep gorge of the Juniata River through Jacks Mountain. Although TD depth tends to increase with stream size, significant exceptions were noted. Streams with discharges of b 10 cms make up the majority of TDs regardless of the lithology of the breached structure. Overall, TDs through sandstone-capped ridges are deeper than those topped by shales, and TDs in both lithologies display a lognormal depth distribution, which may be indicative of a preferred value. Stream flow direction was primarily perpendicular to local structural strike, with 47% of streams flowing NW and 53% flowing SE. Nineteen percent of the TDs are aligned with at least one other TD, with aligned segment lengths ranging from 0.5 to 14.8 km. The majority of TDs are in rocks of Paleozoic age. The techniques described here allow the frequency and distribution of TDs to be quantified to better integrate them into models of basin evolution. © 2012 Elsevier B.V. All rights reserved.
1. Introduction The discipline of geomorphology has deep roots in the linear ridges and valleys of the folded Appalachians of Pennsylvania, where William Morris Davis first developed his theories of landscape evolution (Davis, 1889; Pazzaglia, 2003). As Morisawa (1989) noted in her centennial review of Davis' contributions, the basic question that he sought to answer still forms the core of much geomorphic research: How can present drainage systems be explained in terms of the geologic history and structure of the area? Among the features investigated by Davis were transverse drainages (TDs), gorges cut through resistant rock ridges by streams, sometimes in alignment with other TDs or with wind gaps. Since then, TDs have been identified in every continent except Antarctica (see in particular the surveys in Twidale (2004) and Ollier and Pain (2000)), and as Morisawa noted, the answers to Davis' questions are still not totally clear. Why should a river cut across a resistant ridge? Why do transverse courses cross successive ridges in aligned water gaps? Four major mechanisms have been proposed to explain the formation of TDs: superimposition, antecedence, stream piracy (also known as stream capture), and overflow (Clark, 1989; Morisawa, 1989; Bishop, 1995; Burbank et al., 1996; Twidale, 2004; Douglass and Schmeeckle, 2007; Douglass et al., 2009). While the first two mechanisms both assume a preexisting stratigraphic covermass, superimposed streams are believed to have maintained their E-mail address: [email protected]. 0169-555X/$ – see front matter © 2012 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.geomorph.2012.12.022
original channel and direction of flow as they downcut through buried ridges, while antecedent streams preserved their original course during uplift of buried resistant layers. In stream piracy, streams erode headward or laterally through divides to capture the drainages of other streams, while overflow refers to the phenomenon of impounded water overtopping a barrier. Each mechanism implies a different erosional history, and only overflow remains uncontroversial. Strahler (1945) considered stream piracy to be contrary to all principles of sound stream behavior and could not conceive of a small stream being capable of eroding through a resistant ridge. Bishop (1995) questioned headward erosion as a mechanism for stream capture, and others doubt the ability of seepage erosion and groundwater sapping to erode bedrock valleys in resistant rocks (Lamb et al., 2006; Lamb, 2009). Antecedence suffers from some of the same conceptual difficulties as stream capture, as it requires a stream's erosional rate to match or overcome the rate of uplift of a buried highground, and is difficult to prove (Twidale and Bourne, 2010). Superimposition requires mass wasting and overland flow until the ridge-forming layers are exposed (Douglass and Schmeeckle, 2007) and implies the existence of a covermass, for which evidence is often lacking (Morisawa, 1989; Katkins and Delano, 1999). Further insight comes from the innovative experiments of Douglass and Schmeeckle (2007) who used stream tables, misters, and expandable bladders to simulate all four mechanisms of TD formation. Although their experiments were at a much reduced scale, Paola et al. (2009) pointed out the ‘unreasonable effectiveness’ of small-scale modeling, noting that civil engineers have successfully used small-scale models for over a century.
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Fig. 1. Location map of study area (within dotted lines). Image courtesy of Google®.
In their antecedence experiments, Douglass and Schmeeckle (2007) found that trunk streams were more likely to be successful than tributaries in incising rising highgrounds. Their superimposition experiments failed to run to completion, in part because the design allowed aggradation to build up below the stream outlet. They surmised that superimposition experiments would take longer to complete because of the large amount of erosion required to erode the covermass. Although some of their stream piracy experiments succeeded, they found that the conditions necessary for completion were restricted, supporting Bishop's (1995) caution against the routine invocation of stream piracy as a mechanism of TD formation. The results of their stream piracy experiments would also tend to support Horton's (1945) theory of a belt of nonerosion at headward reaches of catchments. Of the four mechanisms tested, only overflow proved to be an unequivocal success. Ultimately, Douglass and Schmeeckle (2007) concluded that the establishment of knickpoints appears to be the key to TD formation. Given the questions raised by the presence of TDs in a drainage basin, their frequency and distribution are important factors to consider in any theory of basin evolution. However, there have been only two systematic studies of TDs published, those of Ver Steeg (1930), who used longitudinal profiles to identify 34 TDs in eastern Pennsylvania, and of Oberlander (1965), who mapped over 300 TDs in the Zagros Mountains of Iran. One of the reasons for the dearth of such studies may be the lack of universal criteria for defining TDs, perhaps because traditional topographic tools such as elevation profiles cannot
distinguish TDs from normal stream segments. For example, Ver Steeg's (1930) profiles were able to identify gorges but could not distinguish between those produced by normal streams and those produced by transverse streams. Currently, TD identification systems tend to focus upon methods of TD formation rather than upon morphology (Burbank et al., 1996; Zelilidis, 2000; Douglass et al., 2009). With the advent of Google Earth®, the capability now exists to economically utilize remote sensing data in order to develop a set of criteria that can identify and quantify the unique topographic signature of TDs both in profile and planview. Two decades ago, Marston (1989) recognized the potential of remote sensing data for megageomorphic studies; and Clark (1989), in his review of southern and central Appalachian water gaps, recommended the use of quantitative analysis of precise gap elevations, threedimensional digitized profiles, and analysis of high resolution remote sensing imagery to help resolve the old questions of wind and water gap levels and ridge crest topography. The research methodology that follows demonstrates the use of Google Earth® to meet Clark's (1989) recommendations in the Susquehanna River basin of Pennsylvania. 2. Methodology The Susquehanna River drainage basin presents several advantages for an analysis of TD frequency and distribution. First, the region is the classic study area for TDs and has been integral to theories of
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(4) A filled contour interval could be constructed that showed constriction of the stream channel through the TD.
Table 1 EDNA stream size scale. Stream size
Discharge in m3/s
1 2 3 4 5 6 7
0–0.5 0.5–10 10–50 50–100 100–250 250–500 >500
their formation since the late 1800s (Katkins and Delano, 1999). Many large-scale TDs are known to exist in the basin, including the five classic water gaps of the Susquehanna River above Harrisburg. In addition, the linearity of the basin's topographic features and the rich Google Earth® content available for the region make it ideally suited for a survey of this kind. The Susquehanna basin extends over several geographic provinces, but TDs are confined to the region between the Allegheny Front and the Fall Line, an area of about 38,000 km2 that includes portions of the Valley and Ridge, Blue Ridge, and Piedmont provinces (Fig. 1). Within the study area, TDs were identified by a set of Google Earth® tools uniquely suited to the map analysis that has traditionally formed the heart of much geomorphologic research (Vitek et al., 1996). Google Earth's® elevation tool, for example, allows a profile to be generated from any line drawn on the earth's surface, regardless of shape, and can be used to distinguish the lower elevations of the downstream and upstream segments of a TD from the higher elevation of the breached structure, by means of an S-shaped line connecting three parallel traverses of the stream channel, upstream, across, and downstream of the topographic high (Fig. 2A). The elevation generated by this S-profile over a TD will display a characteristic M-shape, whereas normal stream segments produce a flatter or more irregular elevation (Fig. 2B). TDs can be identified in planview by the constriction of contour lines through the breached topographic high. This constriction can be illustrated graphically using Google Earth's® overlay tool, which overlays shapes on the earth's surface whose bounding coordinates and altitude are defined by the user. One consequence of these properties is that an overlay whose coordinates are set to 90° N–S and 180° E–W will cover the entire globe at the altitude to which it has been assigned. This has been used to simulate rising sea level (Zoltan, 2012) but can also be used to identify TDs by simulating filled-in contour lines that constrict as they enter the topographic high (Fig. 2; Appendix A). Once TDs are identified, other overlays can help to characterize them. Google Earth® overlays used in this study included the U.S. Geological Survey (USGS) state geological map of Pennsylvania, Elevation derivatives for national application (EDNA) watershed atlas overlays (used to determine stream size), and a terrain overlay, which drapes a layer similar to a topographic map over Google Earth's® three-dimensional surface (Appendix A). In the study area, TDs were identified by visual inspection, by the use of S-profiles, and by contour-simulating overlays. The final criteria for TD identification included the following: (1) The stream could be observed either on the EDNA watersheds layer or the terrain layer, or through visual inspection of GE. (2) Original continuity of structure could be demonstrated across the TD, usually by the continuation of the geologic formation across the breach on the USGS geologic map. (3) An S-profile across the feature produced the characteristic M-shaped elevation.
Based on these criteria, every stream in the watershed was inspected and placemarks and S-profiles were generated for each identified TD. For each TD, the elevations were gathered of the highest point on the breached ridge, the base of the TD valley, and the farthest upstream point on the S-profile. The data were input into a spreadsheet, and the elevation of the farthest upstream point of each TD's S-profile was rounded to the nearest 20 m (the smallest contour interval of the terrain overlay) and used to create a contour-simulating overlay (CSO). All the TDs were viewed again using the CSOs generated from their upstream elevation. If the CSO either constricted through the TD or the contour interval could be increased or decreased within a range of about 100 m to depict constriction through the TD, then the TD was considered valid. Often, the CSO would reveal new TDs in the vicinity of existing TDs, from which relevant data would then be gathered. The TD identification erred on the side of underreporting; for example, if the topography strongly indicated a TD but no stream was visible because of heavy vegetation, it was not counted. The following data were also gathered for each placemark: (1) The age, formation, and primary lithology of the highest point on the TD, based on the USGS online digital geology map of Pennsylvania, which lists the major rock types in each formation. Formation age helps constrain the age of the drainage system, while the lithology of the ridge-capping formation has implications for models of TD formation. Because antecedence and superimposition require a preexisting covermass, the ridge-capping formation would be the first encountered by an incising stream. For the stream capture scenario, streams would have to be able to generate enough shear stress to overcome the resistance of the rock type at the interfluve divide. For this study, only the most prevalent rock type was assigned, if more than one were present in a formation. Because of the nature of this study, that was considered sufficient. (2) The size of the transverse stream on the EDNA scale, which ranks streams from 1 to 7 based on their mean annual discharge in cubic meters/second, where 1 is ≤0.5 cms and 7 is >500 cms (Table 1). Discharge is directly related to the ability of a stream to erode and transport sediment (Burbank et al., 1996; Attal et al., 2008). (3) The flow direction and approximate length of the stream segment through the breached structure (the measured distance of the stream between its entrance and exit from the breached structure was considered to be its length). Drainage patterns can offer insight into regional structure (Twidale, 2004; Hodgkinson et al., 2007), especially when combined with other measures of paleostress. (4) The difference between the elevation of the highest point on the profile and the lowest point on the valley bottom along the strike of the breached topographic high, as a proxy for TD depth. Accordant ridge elevations in the study area have long been used to argue for at least one original peneplanation surface (Sevon, 1999), under which scenario TD depths would be related to the depth of incision. (5) The slope of the steepest side of the breaching valley, as a proxy for the maximum slope of the sides of the incised valley. Persistence of slopes in the incised gorges needs to be explained by any model of basin erosion. The accuracy of slope data depends on the resolution and accuracy of Google Earth® data but was considered accurate enough for this survey.
Fig. 2. Comparison of S-profiles and filled contours between normal and TD stream segments. (A) S-profile and filled contour level of TD on Little Buffalo Creek, east of Bloomfield, PA, showing M-shaped elevation generated from S-profile line and constriction of contours through TD. (B) S-profile line and filled contour level over normal stream channel, showing lack of constriction and irregular elevation generated from S-profile. Images courtesy of Google®.
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Fig. 3. Transverse drainage morphologies. (A) Head stream TD (in circle) near Martic Forge, PA, displaying the mushroom-shaped outline typical of many headstream TDs. Filled contours set at 100 m asl. (B) Arrow points to trunk stream TD on Jacks Mountain between Mapleton and Mt. Union, PA, demonstrating continuity of stream above the TD. Filled contours set at 240 m asl. Images courtesy of Google®.
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Fig. 4. Lineaments west of Susquehanna River near Millerstown, PA, filled contours at 180–160 m asl. Note the linearity of the valleys. Image courtesy of Google®.
The TDs were then classified into two groups based on their upstream morphology, because catchment area is related to erosive ability (Howard et al., 1994). (1) Head streams, whose upstream catchment areas consist primarily of first- and second-order streams (as measured on the Strahler stream-order scale) and are largely bounded by the constricting contour that defined the TD (Fig. 3A). (2) Trunk streams, whose upstream drainages continue in significant measure past the upstream leg of the S-profile (Fig. 3B). Some TDs are also classified as lineaments—low-relief, multiridge, cross-strike features that may be related to tectonic fractures (O'Leary et al., 1976; Nur, 1982; Twidale, 1996; Prince et al., 2010). For this study, TDs were classified as lineaments if their stream valleys were longer than 1.5 km and if they exhibited a linear morphology at a contour interval equal to or 20 m less than that of the CSO. The purpose of the classification was to distinguish TDs with an unusually persistent element of channel linearity, although identification was necessarily somewhat subjective. Depending upon the upstream morphology, lineaments were also classified as head stream lineaments or trunk stream lineaments (Fig. 4). Data from the Google Earth® analysis were analyzed using Excel and the Tableau Public statistical graphics program. Finally, an image was generated of every TD showing its associated S-profile and the filled-in contour that best demonstrated constriction of the stream channel through the high.1 3. Results Six hundred and fifty-three TDs were identified in the Susquehanna watershed (Fig. 5). Ninety-two percent are located in the Valley and Ridge province, with a density of about three TDs per 100 km2 in the 18,400 km2 of the province within the study area. The remaining TDs are in the Piedmont uplands and on South Mountain of the Blue Ridge province. The majority of TDs are cut through ridges topped by Paleozoic formations of sandstone (45%), shale (48%), metamorphic rocks (3%), 1
http://doi.pangaea.de/10.1594/PANGAEA.773968.
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and calcareous rocks (4%). Two are in Precambrian metamorphic rocks of South Mountain and six are in Mesozoic rocks of the Piedmont uplands. Ninety-five percent of the TDs are occupied by streams ranked sizes 1–2 on the EDNA stream scale (discharge≤10 cms). TD depths ranged from 23 to 539 m, with TDs in sandstone being deeper than those in shales and mudstones. While TD depth tended to increase with stream size, 31% of size 1 and 2 streams fell within the depth range of the TDs of the Susquehanna, the largest stream in the basin (>500 cms discharge); and nine size 1–2 streams occupied gorges whose depths matched or exceeded the deepest of the Susquehanna TDs (Fig. 6). On three ridges, the Susquehanna River flowed through gaps similar in depth to those in the same ridge occupied by much smaller streams (Fig. 7). The deepest TD in the study area was 539 m through Jacks Mountain, a gap of the size 4 Juniata River (50– 100 cms discharge) (Fig. 3B). Another notable finding was that the distribution of TD depths is highly lognormal, even when lithology is factored in (Fig. 8). Lognormal distributions are common in natural parameters because of their inability to fall below zero and may be indicative of a preferred value (Limpert et al., 2001). If a group of values is lognormally distributed, then the natural logs of those values should fall into a normal probability distribution. This was tested by creating a normal quantile plot, where the natural logs of the depth values were plotted against the rank-based Z-scores. For all rock types, highly linear trend lines were produced, indicating that the lognormal distribution of depths is statistically significant (Fig. 9; Appendix B). To find the preferred value suggested by the lognormal distributions, the averages of the natural logs were found for both rock types and stream sizes and converted back to meters (Fig. 10). The preferred TD depth in sandstone was found to be approximately twice that of other rock types for stream sizes 1–4. For size 5–7 streams, the differences in TD depths between different lithologies were much less pronounced. More precise field identification of lithologies atop the breached ridges is needed to confirm the apparent lognormal distribution of the major rock types of the Susquehanna basin. As would be expected, TD slopes, as measured by Google Earth® along strike on the steepest side of the breaching valley, were higher for sandstones than shales. Slopes tended to increase with increasing TD depth, although a low R 2 value indicates that the linear regression thus derived may not be statistically significant. Approximately 15% of the TDs were b 0.5 km in length, 49% were between 0.5 and 1 km, and 37% were >1 km long, the length of the stream being its measurement between its entrance and exit from the topographic high. The direction of stream flow through TDs was almost invariably orthogonal to local structural strike, with 47% flowing NW and 53% flowing SE. All stream flow through TDs of size 4 and larger streams was to the SE, except for one TD of the Susquehanna River near Nanticoke, PA (Fig. 11). Overall, 56% of TDs were characterized as head streams, the majority of which were in sandstones; and 44% were characterized as trunk streams, the majority of which were in shales. The depth distribution of head stream TDs was approximately equal to that of trunk stream TDs for all rock types (Fig. 12). As a consequence of their location on the drainage network, all head stream TDs contained size 1 and 2 streams, but size 1 and 2 streams also made up the majority of the trunk streams, reflecting the overall distribution of stream sizes. Seventeen percent of TDs were classified as lineaments and were distributed roughly equally between head streams and trunk streams. One hundred and twenty-three TDs (19% of total) were aligned with at least one other TD. The TDs were considered aligned if the stream segment connecting them was linear, with no significant offset, and orthogonal to structural strike (Fig. 13). Fifty-five aligned segments were identified, with lengths ranging from 0.5 to 14.8 km, for a total combined length of 189 km. Thirty-six percent of aligned segments contained NW-flowing streams, for a total segment length of 48 km; while 64% (141 km total segment length) contained SE-flowing streams. While
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Fig. 5. Area map of identified TDs in the Susquehanna River basin by rock type and TD depth.
TD base level naturally decreased downstream on the aligned segments, 22 segments had downstream TDs whose topographic highs exceeded the elevations of the upstream TD's topographic highs (Fig. 14). These
segments had a greater percentage of streams flowing toward the NW and were shorter on average than those whose upstream highs exceeded downstream highs.
Fig. 6. Graph of lithology (top axis) and stream size (bottom axis) by depth in meters, showing proportion of size 1–2 streams whose TD depths fall within the depth range of Susquehanna TDs.
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Fig. 7. Google Earth® profiles showing gorges of similar depth occupied by different sized streams. (A) Berry Mountain, (B) Mahantango Mountain, and (C) Blue Mountain. Images courtesy of Google®.
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Fig. 8. Lognormal distribution of TD depths by lithology.
4. Discussion 4.1. Drainage development in the Susquehanna River basin Current theories have most of the Atlantic-draining streams of the Pennsylvania Appalachians flowing during the Cenozoic in locations and directions comparable to their present positions (Katkins and Delano, 1999), although the origination of the Susquehanna River drainage system is held by some to extend back to the Mesozoic (MacLachlan, 1999). The form of the Cenozoic surface is not known but is presumed to be a subdued erosional surface ~3000 ft higher than that of the present, with local relief in the same general form as the present, and streams probably nowhere entrenched (MacLachlan, 1999; Sevon, 1999). Superimposition and stream piracy, with some
measure of structural control, are the main mechanisms used to account for the formation of TDs (Strahler, 1945; Thompson, 1949; Epstein, 1966; Alvarez, 1999; Katkins and Delano, 1999). However, the results presented here raise questions about the proposed mechanisms of TD formation, particularly in regard to the following features: (1) The large number of TDs and the small size of most of the streams flowing through them. How could so many small streams have been able to incise gorges to the same depth or even greater than those of streams several orders of magnitude larger, often through highly resistant rocks? The problem is even more acute on ridges where similarly sized gorges containing very different stream sizes are found in close longitudinal proximity.
Fig. 9. Linear regression of LN values of TD depths by lithology (top axis) and rank-based Z scores (bottom axis), indicating statistical significance of lognormal distribution of depths (TD in one igneous rock was not calculated because of single sample size).
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Fig. 10. Preferred depth (in parentheses) by lithology (top axis) and stream size (bottom axis), calculated from average of LN depth (each bar represents one LN depth value).
(2) Lognormal distribution of depths. If this is a valid inference, why should there be a preferred depth for TDs and why should the most resistant rocks have the deepest preferred depth? (3) The distribution of TD morphology. Why is the depth distribution of trunk stream TDs roughly equivalent to that of head stream
TDs, whose catchment areas are much smaller in comparison especially if catchment area is a proxy for discharge and therefore for erosive ability? (Howard et al., 1994) In addition, how could the mechanisms available for erosion of head stream catchments, including overland flow, rain splash, and spring sapping, be
Fig. 11. Areal distribution of flow direction of streams through TDs.
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Fig. 12. Depth distribution by lithology (top axis) and morphology (bottom axis), showing similar depth distribution for rock types regardless of TD morphologies (each bar represents a TD depth).
capable of creating enough shear stress to erode resistant rocks at the interfluve divides? (4) The existence of aligned segments, many of which are quite striking both in linearity and in the disparity of ridge heights traversed by the incising streams (Fig. 15). Additionally, what combination of erosion and structural control could account for the increase in downstream topographic highs in almost half of the aligned segments? In addition, as Twidale (2004) pointed out, the persistence of rivers incised in consolidated bedrock stands in marked contrast to the shifting location and character of rivers of alluvial plains. In the cases of antecedence and superimposition, however, there must have been a transition from alluvium to bedrock. Modeling experiments addressing this issue
have been conducted but only in unconsolidated stream table sediments (see the review in Douglass and Schmeeckle, 2007). However, the defeat of the small tributaries in the stream table sediments of Douglass and Schmeeckle's (2007) antecedence experiments suggest that small streams would not be able to incise buried resistant ridges. Thus, the vertical transfer of small streams by incision from unconsolidated alluvium into consolidated bedrock, required by antecedence and by superimposition, appears doubtful. Further modeling experiments may help resolve these questions, along with numerical modeling of shear stresses necessary to bridge the divide between alluvial and entrenched incision. In the end, these results appear to have raised more questions than they have answered, but as Twidale (2003) pointed out, at regional scales, complexity in drainage systems is the rule rather than the exception. However, one possible inference of the survey
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Fig. 13. Google Earth® image of 55 aligned TD segments (inset box is area pictured in Fig. 15).
Fig. 14. Elevation difference in meters between upstream and downstream TD highs on aligned segments.
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Fig. 15. Aligned TD segments breaching anticline snout near Lamar, PA. Dashed line marks profile, arrows indicate stream flow in TDs. Image courtesy of Google®.
results may be that the streams that originally formed the TDs were larger than the streams that currently inhabit them. Twidale (2004) noted the importance of brief but large magnitude events in shaping landscapes, and others have inferred that floods are the cause of much erosion in bedrock reaches (Eaton et al., 2003a,b). Kochel et al. (2009) reported evidence for the subglacial outburst floods known as jokulhlaups in some tributaries of the glaciated areas of the Susquehanna drainage system; but the ridgetops were never covered by the glacial lobes, and the icedammed lakes drained through preexisting gaps in the ridges. They also attributed some incision of the Susquehanna in the Piedmont region to the breakout flows of jokulhlaups, but indicated that the major erosion features within the lower gorge may have been formed earlier. Coupled with the fact that much of the basin was not glaciated, breakout flooding from ice dam failure may account for the deepening of some TDs in glaciated areas but does not appear to be a plausible explanation for their origin. 4.2. Applications to other areas Preliminary investigation suggests that the pattern found in the Susquehanna basin of numerous TDs populated mainly by very small streams is replicated in other East Coast watersheds and potentially in
other mountain ranges around the world. The techniques introduced here may be helpful in quantifying and integrating transverse drainage data into models of basin evolution, in the Appalachians and in other drainage basins worldwide. For example, in the Potomac River watershed, numerous small streams are found in TDs, while the larger trunk streams conform to regional structure by following the strike of the fold valleys (Fig. 16A). In the Ohio watershed, the size 5 New River and Little Creek, a size 1 stream, are located in gorges of similar depths, 12 km apart on the same ridge (Fig. 16B). The methodology described here can be applied to many folded mountain ranges. One example is the Flinders Range of Australia, an area of Appalachian-style ridge-and-valley topography resulting from lithologically controlled differential erosion (Twidale and Bourne, 2010). The region features multiple TDs through quartzite ridges, breached synclinal snouts, and in-and-out streams that breach and flow through a ridge from one valley to another multiple times and are similar to features found in the Susquehanna basin. Antecedence, superimposition, and stream piracy have all been hypothesized for the area, as well as inheritance, another form of superimposition defined by Twidale (2004) as the imposition of a drainage surface developed on a weathered land surface onto the unweathered bedrock beneath; and impression, the transmission of structural effects from below.
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In the Zagros Mountains of Iran, Oberlander (1965) postulated drainage superimposed onto buried resistant layers by erosion through erodible strata that initially covered the higher parts of anticlines. Later, as ongoing erosion reached previously buried resistant layers, anticlinal ridges stood out in relief and were breached by superposed transverse streams (Mayer et al., 2003). According to Oberlander, the Zagros Mountains are a remarkable parallel to the folded Appalachians, although much younger and at a larger scale. Investigation of these and other areas of ridge-and-valley topography using the methodology presented here can help to determine
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whether or not the Susquehanna pattern of numerous small streams inhabiting large gorges is essentially an Appalachian phenomenon. 4.3. Suggestions for further study The techniques and methodology presented here may also be useful for investigating traditional geomorphic problems: (1) Ridge slope retreat vs. gorge incision. As Twidale (2004) pointed out, TDs may indicate a comparatively slow rate of slope lowering
Fig. 16. Potential areas of Susquehanna-type TD distribution in East Coast watersheds. (A) Potomac watershed in NE West Virginia with filled contours set at 360 m asl. Circles indicate TDs. Note tendency of head streams (in circles) to form TDs and trunk streams to form along-strike channels in structural folds. (B) Ohio watershed NW of Blacksburg, VA, with filled contours set at 640 m asl. Arrow indicates flow direction of New River. Dashed line marks profile showing size 1 stream (A) cutting similar-sized gorge to size 5 New River (B). Circles indicate TDs of size 1 streams. Images courtesy of Google®.
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Fig. 17. Through-valleys in upstate New York crossing the divide between Great Lakes and upper Chesapeake Bay watersheds. Dark curved line is watershed divide, white paddle icons indicate through-valleys. Arrow points to barbed headstream indicating catchment rearrangement by divide migration. Image courtesy of Google®.
versus that of river incision. In addition to the slopes of the TD valleys, S-profiles display the slopes of the breached ridges (Fig. 2A), and thus offer a unique opportunity to compare slope retreat of the breached highlands with gorge incision by the transverse stream. Using measurements gained from Google Earth's® elevation tool, volumetric analysis can easily be done on both the TDs and on the valleys on either side. Presuming the existence of an original surface of higher elevation, the rate of valley lowering that has occurred can then be compared to the rate of gorge incision. (2) Topographic data collection. Mills et al. (1987) noted that the operation of fluvial systems through time in much of the Appalachians has been recorded in its geomorphic landforms and alluvial terrace sequences. Google Earth's® elevation tool provides an easy method of creating cross sections for determining elevations and geologic information about paired and unpaired river terraces in both bedrock and alluvium, although studies such as these would need to be corroborated by field work (Marston, 1989). Topographic profiles can also help to identify the Vshaped incision of rejuvenated streams through U-shaped glacial valleys. In addition, since Google Earth's® elevation tool gives the mean elevation of every measured line, large-scale transects can be used to easily determine mean elevation. (3) Channel width determinations. During the course of the study, measurement of the Susquehanna streams as determined by Google Earth's® measuring tool revealed a close correspondence to the stream size on the EDNA overlay, i.e., size 1 streams (0– 0.5 cms discharge) had widths of .5 m or less, size 2 streams (0.5–1 cms discharge) were between .5 and 10 m in width, etc. This very useful feature can allow Google Earth's® measuring tool to approximate stream width in areas where streams are
visible on Google Earth® but field data are not readily available or dimensions of active channel width are lower than digital elevation model (DEM) resolution (Attal et al., 2008). (4) Analysis of regional stress patterns. Another possible avenue of research would be to compare TD azimuth trends with paleostress trends derived from regional structural and mineralogical studies, such as calcite twinning, stylolitization, or joint sets studies (Srivastava and Engelder, 1990; Faill and Nickelsen, 1999; Ong et al., 2007; Engelder et al., 2009). (5) Identification of through-valleys and wind gaps. Through-valleys, depressions eroded across a divide by glacier ice or meltwater streams, can be easily identified in glacial areas by contoursimulating overlays. For example, on the divide between the Great Lakes and the upper Chesapeake Bay watersheds in upstate New York, contour-simulating overlays at 380 m and 420 m show several glacial valleys crossing the divide, in which are located headstreams flowing in opposite directions on either side of the divides (Fig. 17). Contour-simulating overlays can also be used to identify wind gaps, as at Walyunga National Park, in Western Australia (Gozzard, 2007). A contour-simulating overlay at 180 m clearly outlines a higher, and therefore older, channel of a formerly westward-flowing stream that was captured by the south-flowing Swan River, whose channel is outlined at 80 m. The result is a wind gap to the west of the Swan River's course (Fig. 18A). An S-profile over the wind gap results in a modified M-elevation, with the now-defunct channel inside the wind gap perched at a higher elevation than either side of the ridge (Fig. 18B). The combination of S-profiles with channel patterns revealed by contour-simulating overlays may be able to aid in confirming the existence of wind gaps.
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Fig. 18. (A) Wind gap at Walyunga National Park, Western Australia. (B) S-profile over wind gap at Walyunga National Park, Western Australia. Images courtesy of Google®.
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Excel data and images of identified Susquehanna TDs: http://doi. pangaea.de/10.1594/PANGAEA.773968
5. Conclusion Because every TD represents an instance of flowing water bypassing the path of least resistance, the frequency and distribution of TDs within a basin should be an important factor in any theory of basin evolution. However, there is a dearth of TD surveys in the literature, perhaps because of the lack of objective physical criteria for TD identification. An initial step toward establishing such criteria has been suggested, along with their application to the Susquehanna River basin. As Valla et al. (2010) noted, the relative efficiency of glacial, fluvial, and hillslope processes operating in orogens remains poorly constrained, and improved empirical as well as physically based models are needed. The virtual reality capabilities of Google Earth®, combined with its ability to quantify topographic features, can help researchers to gather quantitative data on TDs and make reasonable estimates of their frequency and distribution so that they may be fully integrated into models of drainage basin evolution. The techniques described here are easily adaptable for use within the Appalachian basins and in other basins worldwide and offer the opportunity to reinvigorate the study of unique geomorphic features such as transverse drainages. Appendix A USGS Digital geologic maps of the United States: http://tin.er.usgs. gov/geology/state/ EDNA Derived watershed atlas: http://edna.usgs.gov/watersheds/ The Google Maps® terrain layer for Google Earth®: http://gemap-overlays.appspot.com/openstreetmap/cycle-map Tableau Public statistical graphics software: http://www. tableausoftware.com/public GPS Visualizer was used to transform data between spreadsheet and kml formats (http://www.gpsvisualizer.com). Instructions for creating filled-in contour elevations: http://tinyurl. com/7lbz5sm
Appendix C. Supplementary data Supplementary data associated with this article can be found in the online version, at http://dx.doi.org/10.1016/j.geomorph.2012.12. 022. These data include Google maps of the most important areas described in this article.
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Appendix B Statistical analysis of data in Fig. 8, LN of TD depth by rank-based Z scores grouped by rock type, from Tableau Public statistical graphics program. Trend lines model A linear trend model is computed for LN depth given rank-based Z scores. The model may be significant at P ≤ 0.05. The factor rock type may be significant at P = 0.05. Rock type ∗ (Rank-based Z scores + intercept) 652 0 8 644 2.15132 0.0033406 0.990322 0.0577975 b0.0001
Model formula: Number of modeled observations: Number of filtered observations: Model degrees of freedom: Residual degrees of freedom (DF): SSE (sum squared error): MSE (mean squared error): R2: Standard error: P-value (significance): Analysis of variance: Field Rock type Individual trend lines: Panes Row Column LN depth Calcareous
DF 6
SSE 0.165594 Line P-value b0.0001
DF 22
LN depth
Metamorphic
b0.0001
16
LN depth
Sandstone
b0.0001
294
LN depth
Shales and mudstones
b0.0001
312
MSE 0.0275991 Coefficients Term Rank-based intercept Rank-based intercept Rank-based intercept Rank-based intercept
Z scores Z scores Z scores Z scores
F 8.26182
Value 0.538505 4.6243 0.600466 4.66828 0.569157 4.6837 0.571775 4.64613
StdErr 0.010306 0.0105017 0.0172018 0.0160074 0.0049301 0.0052831 0.0032739 0.0030372
P-value b0.0001
t-value 52.2517 440.337 34.9073 291.633 115.446 886.545 174.645 1529.73
P-value b0.0001 b0.0001 b0.0001 b0.0001 b0.0001 b0.0001 b0.0001 b0.0001
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Paola, C., Straub, K., Mohrig, D., Reinhardt, L., 2009. The unreasonable effectiveness of stratigraphic and geomorphic experiments. Earth-Science Reviews 97, 1–43. Pazzaglia, F.J., 2003. Landscape evolution models. Developments in Quaternary Sciences 1, 247–274. Prince, P.S., Spotila, J.A., Henika, W.S., 2010. New physical evidence of the role of stream capture in active retreat of the Blue Ridge escarpment, southern Appalachians. Geomorphology 123, 305–319. Sevon, W.D., 1999. Cenozoic history. In: Schultz, C.H. (Ed.), Geology of Pennsylvania. Pennsylvania Geological Survey, Harrisburg, PA, pp. 450–455. Srivastava, D.C., Engelder, T., 1990. Crack-propagation sequence and pore-fluid conditions during fault-bend folding in the Appalachian Valley and Ridge, central Pennsylvania. Bulletin of the Geological Society of America 102, 116–128. Strahler, A.N., 1945. Hypotheses of stream development in the folded Appalachians of Pennsylvania. Geological Society of America Bulletin 56, 45–87. Thompson, H.D., 1949. Drainage evolution in the Appalachians of Pennsylvania. Annals of the New York Academy of Sciences 52, 33–62. Twidale, C., 1996. Derivation and innovation in improper geology, aka Geomorphology. In: Rhoads, B.L., Thorn, C.E. (Eds.), The Scientific Nature of Geomorphology: Proceedings of the 27th Binghamton Symposium in Geomorphology, Held 27–29 September, 1996. John Wiley and Sons Ltd., Chichester, England, pp. 361–380. Twidale, C.R., 2003. ‘Canons’ revisited and reviewed: Lester King's views of landscape evolution considered 50 years later. Geological Society of America Bulletin 115, 1155–1172. Twidale, C.R., 2004. River patterns and their meaning. Earth-Science Reviews 67, 159–218. Twidale, C.R., Bourne, J.A., 2010. Drainage patterns in an Appalachian fold mountain belt: Flinders ranges, south Australia. Cuaternario y geomorfologia: Revista de la Sociedad Española de Geomorfologia y Asociación Española para el Estudio del Cuaternario 24 (1), 11–33. Valla, P., Van Der Beek, P.A., Lague, D., 2010. Fluvial incision into bedrock: insights from morphometric analysis and numerical modeling of gorges incising glacial hanging valleys (western Alps, France). Journal of Geophysical Research 115, F02010. Ver Steeg, K., 1930. Wind gaps and water gaps of the northern Appalachians, their characteristics and significance. Annals of the New York Academy of Sciences 32 (1), 87–220. Vitek, J.D., Giardino, J.R., Fitzgerald, J.W., 1996. Mapping geomorphology: a journey from paper maps, through computer mapping to GIS and virtual reality. Geomorphology 16, 233–249. Zelilidis, A., 2000. Drainage evolution in a rifted basin, Corinth graben, Greece. Geomorphology 35, 69–85. Zoltan, B., 2012. Google Earth® rising sea level animation (http://www.google.com/gadgets/ directory?synd=earth&hl=en&gl=en&preview=on&url=http://www.google.com/ mapfiles/mapplets/earthgallery/Rising_Sea_Level_Animation.xml, accessed December 16, 2012).
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Geomorphology journal homepage: www.elsevier.com/locate/geomorph
A survey of transverse drainages in the Susquehanna River basin, Pennsylvania Jacqueline Lee a r t i c l e
i n f o
Article history: Received 26 March 2012 Received in revised form 20 December 2012 Accepted 21 December 2012 Available online 2 January 2013 Keywords: Transverse drainages Susquehanna River Pennsylvania Appalachians Basin evolution Remote sensing
a b s t r a c t Although large-scale transverse drainages (TDs) such as those of the Susquehanna River above Harrisburg, PA, have been recognized since the nineteenth century, only two systematic surveys have been published of TDs (Ver Steeg, 1930; Oberlander, 1965). A topographic and statistical analysis of TDs in the Susquehanna River basin using Google Earth® and associated overlays identified 653 TDs in the study area, 95% of which contain streams with discharges of b 10 m 3/s (cms). The TD depths ranged from a 23-m-deep water gap near Blain, PA, to the 539-m-deep gorge of the Juniata River through Jacks Mountain. Although TD depth tends to increase with stream size, significant exceptions were noted. Streams with discharges of b 10 cms make up the majority of TDs regardless of the lithology of the breached structure. Overall, TDs through sandstone-capped ridges are deeper than those topped by shales, and TDs in both lithologies display a lognormal depth distribution, which may be indicative of a preferred value. Stream flow direction was primarily perpendicular to local structural strike, with 47% of streams flowing NW and 53% flowing SE. Nineteen percent of the TDs are aligned with at least one other TD, with aligned segment lengths ranging from 0.5 to 14.8 km. The majority of TDs are in rocks of Paleozoic age. The techniques described here allow the frequency and distribution of TDs to be quantified to better integrate them into models of basin evolution. © 2012 Elsevier B.V. All rights reserved.
1. Introduction The discipline of geomorphology has deep roots in the linear ridges and valleys of the folded Appalachians of Pennsylvania, where William Morris Davis first developed his theories of landscape evolution (Davis, 1889; Pazzaglia, 2003). As Morisawa (1989) noted in her centennial review of Davis' contributions, the basic question that he sought to answer still forms the core of much geomorphic research: How can present drainage systems be explained in terms of the geologic history and structure of the area? Among the features investigated by Davis were transverse drainages (TDs), gorges cut through resistant rock ridges by streams, sometimes in alignment with other TDs or with wind gaps. Since then, TDs have been identified in every continent except Antarctica (see in particular the surveys in Twidale (2004) and Ollier and Pain (2000)), and as Morisawa noted, the answers to Davis' questions are still not totally clear. Why should a river cut across a resistant ridge? Why do transverse courses cross successive ridges in aligned water gaps? Four major mechanisms have been proposed to explain the formation of TDs: superimposition, antecedence, stream piracy (also known as stream capture), and overflow (Clark, 1989; Morisawa, 1989; Bishop, 1995; Burbank et al., 1996; Twidale, 2004; Douglass and Schmeeckle, 2007; Douglass et al., 2009). While the first two mechanisms both assume a preexisting stratigraphic covermass, superimposed streams are believed to have maintained their E-mail address: [email protected]. 0169-555X/$ – see front matter © 2012 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.geomorph.2012.12.022
original channel and direction of flow as they downcut through buried ridges, while antecedent streams preserved their original course during uplift of buried resistant layers. In stream piracy, streams erode headward or laterally through divides to capture the drainages of other streams, while overflow refers to the phenomenon of impounded water overtopping a barrier. Each mechanism implies a different erosional history, and only overflow remains uncontroversial. Strahler (1945) considered stream piracy to be contrary to all principles of sound stream behavior and could not conceive of a small stream being capable of eroding through a resistant ridge. Bishop (1995) questioned headward erosion as a mechanism for stream capture, and others doubt the ability of seepage erosion and groundwater sapping to erode bedrock valleys in resistant rocks (Lamb et al., 2006; Lamb, 2009). Antecedence suffers from some of the same conceptual difficulties as stream capture, as it requires a stream's erosional rate to match or overcome the rate of uplift of a buried highground, and is difficult to prove (Twidale and Bourne, 2010). Superimposition requires mass wasting and overland flow until the ridge-forming layers are exposed (Douglass and Schmeeckle, 2007) and implies the existence of a covermass, for which evidence is often lacking (Morisawa, 1989; Katkins and Delano, 1999). Further insight comes from the innovative experiments of Douglass and Schmeeckle (2007) who used stream tables, misters, and expandable bladders to simulate all four mechanisms of TD formation. Although their experiments were at a much reduced scale, Paola et al. (2009) pointed out the ‘unreasonable effectiveness’ of small-scale modeling, noting that civil engineers have successfully used small-scale models for over a century.
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Fig. 1. Location map of study area (within dotted lines). Image courtesy of Google®.
In their antecedence experiments, Douglass and Schmeeckle (2007) found that trunk streams were more likely to be successful than tributaries in incising rising highgrounds. Their superimposition experiments failed to run to completion, in part because the design allowed aggradation to build up below the stream outlet. They surmised that superimposition experiments would take longer to complete because of the large amount of erosion required to erode the covermass. Although some of their stream piracy experiments succeeded, they found that the conditions necessary for completion were restricted, supporting Bishop's (1995) caution against the routine invocation of stream piracy as a mechanism of TD formation. The results of their stream piracy experiments would also tend to support Horton's (1945) theory of a belt of nonerosion at headward reaches of catchments. Of the four mechanisms tested, only overflow proved to be an unequivocal success. Ultimately, Douglass and Schmeeckle (2007) concluded that the establishment of knickpoints appears to be the key to TD formation. Given the questions raised by the presence of TDs in a drainage basin, their frequency and distribution are important factors to consider in any theory of basin evolution. However, there have been only two systematic studies of TDs published, those of Ver Steeg (1930), who used longitudinal profiles to identify 34 TDs in eastern Pennsylvania, and of Oberlander (1965), who mapped over 300 TDs in the Zagros Mountains of Iran. One of the reasons for the dearth of such studies may be the lack of universal criteria for defining TDs, perhaps because traditional topographic tools such as elevation profiles cannot
distinguish TDs from normal stream segments. For example, Ver Steeg's (1930) profiles were able to identify gorges but could not distinguish between those produced by normal streams and those produced by transverse streams. Currently, TD identification systems tend to focus upon methods of TD formation rather than upon morphology (Burbank et al., 1996; Zelilidis, 2000; Douglass et al., 2009). With the advent of Google Earth®, the capability now exists to economically utilize remote sensing data in order to develop a set of criteria that can identify and quantify the unique topographic signature of TDs both in profile and planview. Two decades ago, Marston (1989) recognized the potential of remote sensing data for megageomorphic studies; and Clark (1989), in his review of southern and central Appalachian water gaps, recommended the use of quantitative analysis of precise gap elevations, threedimensional digitized profiles, and analysis of high resolution remote sensing imagery to help resolve the old questions of wind and water gap levels and ridge crest topography. The research methodology that follows demonstrates the use of Google Earth® to meet Clark's (1989) recommendations in the Susquehanna River basin of Pennsylvania. 2. Methodology The Susquehanna River drainage basin presents several advantages for an analysis of TD frequency and distribution. First, the region is the classic study area for TDs and has been integral to theories of
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(4) A filled contour interval could be constructed that showed constriction of the stream channel through the TD.
Table 1 EDNA stream size scale. Stream size
Discharge in m3/s
1 2 3 4 5 6 7
0–0.5 0.5–10 10–50 50–100 100–250 250–500 >500
their formation since the late 1800s (Katkins and Delano, 1999). Many large-scale TDs are known to exist in the basin, including the five classic water gaps of the Susquehanna River above Harrisburg. In addition, the linearity of the basin's topographic features and the rich Google Earth® content available for the region make it ideally suited for a survey of this kind. The Susquehanna basin extends over several geographic provinces, but TDs are confined to the region between the Allegheny Front and the Fall Line, an area of about 38,000 km2 that includes portions of the Valley and Ridge, Blue Ridge, and Piedmont provinces (Fig. 1). Within the study area, TDs were identified by a set of Google Earth® tools uniquely suited to the map analysis that has traditionally formed the heart of much geomorphologic research (Vitek et al., 1996). Google Earth's® elevation tool, for example, allows a profile to be generated from any line drawn on the earth's surface, regardless of shape, and can be used to distinguish the lower elevations of the downstream and upstream segments of a TD from the higher elevation of the breached structure, by means of an S-shaped line connecting three parallel traverses of the stream channel, upstream, across, and downstream of the topographic high (Fig. 2A). The elevation generated by this S-profile over a TD will display a characteristic M-shape, whereas normal stream segments produce a flatter or more irregular elevation (Fig. 2B). TDs can be identified in planview by the constriction of contour lines through the breached topographic high. This constriction can be illustrated graphically using Google Earth's® overlay tool, which overlays shapes on the earth's surface whose bounding coordinates and altitude are defined by the user. One consequence of these properties is that an overlay whose coordinates are set to 90° N–S and 180° E–W will cover the entire globe at the altitude to which it has been assigned. This has been used to simulate rising sea level (Zoltan, 2012) but can also be used to identify TDs by simulating filled-in contour lines that constrict as they enter the topographic high (Fig. 2; Appendix A). Once TDs are identified, other overlays can help to characterize them. Google Earth® overlays used in this study included the U.S. Geological Survey (USGS) state geological map of Pennsylvania, Elevation derivatives for national application (EDNA) watershed atlas overlays (used to determine stream size), and a terrain overlay, which drapes a layer similar to a topographic map over Google Earth's® three-dimensional surface (Appendix A). In the study area, TDs were identified by visual inspection, by the use of S-profiles, and by contour-simulating overlays. The final criteria for TD identification included the following: (1) The stream could be observed either on the EDNA watersheds layer or the terrain layer, or through visual inspection of GE. (2) Original continuity of structure could be demonstrated across the TD, usually by the continuation of the geologic formation across the breach on the USGS geologic map. (3) An S-profile across the feature produced the characteristic M-shaped elevation.
Based on these criteria, every stream in the watershed was inspected and placemarks and S-profiles were generated for each identified TD. For each TD, the elevations were gathered of the highest point on the breached ridge, the base of the TD valley, and the farthest upstream point on the S-profile. The data were input into a spreadsheet, and the elevation of the farthest upstream point of each TD's S-profile was rounded to the nearest 20 m (the smallest contour interval of the terrain overlay) and used to create a contour-simulating overlay (CSO). All the TDs were viewed again using the CSOs generated from their upstream elevation. If the CSO either constricted through the TD or the contour interval could be increased or decreased within a range of about 100 m to depict constriction through the TD, then the TD was considered valid. Often, the CSO would reveal new TDs in the vicinity of existing TDs, from which relevant data would then be gathered. The TD identification erred on the side of underreporting; for example, if the topography strongly indicated a TD but no stream was visible because of heavy vegetation, it was not counted. The following data were also gathered for each placemark: (1) The age, formation, and primary lithology of the highest point on the TD, based on the USGS online digital geology map of Pennsylvania, which lists the major rock types in each formation. Formation age helps constrain the age of the drainage system, while the lithology of the ridge-capping formation has implications for models of TD formation. Because antecedence and superimposition require a preexisting covermass, the ridge-capping formation would be the first encountered by an incising stream. For the stream capture scenario, streams would have to be able to generate enough shear stress to overcome the resistance of the rock type at the interfluve divide. For this study, only the most prevalent rock type was assigned, if more than one were present in a formation. Because of the nature of this study, that was considered sufficient. (2) The size of the transverse stream on the EDNA scale, which ranks streams from 1 to 7 based on their mean annual discharge in cubic meters/second, where 1 is ≤0.5 cms and 7 is >500 cms (Table 1). Discharge is directly related to the ability of a stream to erode and transport sediment (Burbank et al., 1996; Attal et al., 2008). (3) The flow direction and approximate length of the stream segment through the breached structure (the measured distance of the stream between its entrance and exit from the breached structure was considered to be its length). Drainage patterns can offer insight into regional structure (Twidale, 2004; Hodgkinson et al., 2007), especially when combined with other measures of paleostress. (4) The difference between the elevation of the highest point on the profile and the lowest point on the valley bottom along the strike of the breached topographic high, as a proxy for TD depth. Accordant ridge elevations in the study area have long been used to argue for at least one original peneplanation surface (Sevon, 1999), under which scenario TD depths would be related to the depth of incision. (5) The slope of the steepest side of the breaching valley, as a proxy for the maximum slope of the sides of the incised valley. Persistence of slopes in the incised gorges needs to be explained by any model of basin erosion. The accuracy of slope data depends on the resolution and accuracy of Google Earth® data but was considered accurate enough for this survey.
Fig. 2. Comparison of S-profiles and filled contours between normal and TD stream segments. (A) S-profile and filled contour level of TD on Little Buffalo Creek, east of Bloomfield, PA, showing M-shaped elevation generated from S-profile line and constriction of contours through TD. (B) S-profile line and filled contour level over normal stream channel, showing lack of constriction and irregular elevation generated from S-profile. Images courtesy of Google®.
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Fig. 3. Transverse drainage morphologies. (A) Head stream TD (in circle) near Martic Forge, PA, displaying the mushroom-shaped outline typical of many headstream TDs. Filled contours set at 100 m asl. (B) Arrow points to trunk stream TD on Jacks Mountain between Mapleton and Mt. Union, PA, demonstrating continuity of stream above the TD. Filled contours set at 240 m asl. Images courtesy of Google®.
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Fig. 4. Lineaments west of Susquehanna River near Millerstown, PA, filled contours at 180–160 m asl. Note the linearity of the valleys. Image courtesy of Google®.
The TDs were then classified into two groups based on their upstream morphology, because catchment area is related to erosive ability (Howard et al., 1994). (1) Head streams, whose upstream catchment areas consist primarily of first- and second-order streams (as measured on the Strahler stream-order scale) and are largely bounded by the constricting contour that defined the TD (Fig. 3A). (2) Trunk streams, whose upstream drainages continue in significant measure past the upstream leg of the S-profile (Fig. 3B). Some TDs are also classified as lineaments—low-relief, multiridge, cross-strike features that may be related to tectonic fractures (O'Leary et al., 1976; Nur, 1982; Twidale, 1996; Prince et al., 2010). For this study, TDs were classified as lineaments if their stream valleys were longer than 1.5 km and if they exhibited a linear morphology at a contour interval equal to or 20 m less than that of the CSO. The purpose of the classification was to distinguish TDs with an unusually persistent element of channel linearity, although identification was necessarily somewhat subjective. Depending upon the upstream morphology, lineaments were also classified as head stream lineaments or trunk stream lineaments (Fig. 4). Data from the Google Earth® analysis were analyzed using Excel and the Tableau Public statistical graphics program. Finally, an image was generated of every TD showing its associated S-profile and the filled-in contour that best demonstrated constriction of the stream channel through the high.1 3. Results Six hundred and fifty-three TDs were identified in the Susquehanna watershed (Fig. 5). Ninety-two percent are located in the Valley and Ridge province, with a density of about three TDs per 100 km2 in the 18,400 km2 of the province within the study area. The remaining TDs are in the Piedmont uplands and on South Mountain of the Blue Ridge province. The majority of TDs are cut through ridges topped by Paleozoic formations of sandstone (45%), shale (48%), metamorphic rocks (3%), 1
http://doi.pangaea.de/10.1594/PANGAEA.773968.
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and calcareous rocks (4%). Two are in Precambrian metamorphic rocks of South Mountain and six are in Mesozoic rocks of the Piedmont uplands. Ninety-five percent of the TDs are occupied by streams ranked sizes 1–2 on the EDNA stream scale (discharge≤10 cms). TD depths ranged from 23 to 539 m, with TDs in sandstone being deeper than those in shales and mudstones. While TD depth tended to increase with stream size, 31% of size 1 and 2 streams fell within the depth range of the TDs of the Susquehanna, the largest stream in the basin (>500 cms discharge); and nine size 1–2 streams occupied gorges whose depths matched or exceeded the deepest of the Susquehanna TDs (Fig. 6). On three ridges, the Susquehanna River flowed through gaps similar in depth to those in the same ridge occupied by much smaller streams (Fig. 7). The deepest TD in the study area was 539 m through Jacks Mountain, a gap of the size 4 Juniata River (50– 100 cms discharge) (Fig. 3B). Another notable finding was that the distribution of TD depths is highly lognormal, even when lithology is factored in (Fig. 8). Lognormal distributions are common in natural parameters because of their inability to fall below zero and may be indicative of a preferred value (Limpert et al., 2001). If a group of values is lognormally distributed, then the natural logs of those values should fall into a normal probability distribution. This was tested by creating a normal quantile plot, where the natural logs of the depth values were plotted against the rank-based Z-scores. For all rock types, highly linear trend lines were produced, indicating that the lognormal distribution of depths is statistically significant (Fig. 9; Appendix B). To find the preferred value suggested by the lognormal distributions, the averages of the natural logs were found for both rock types and stream sizes and converted back to meters (Fig. 10). The preferred TD depth in sandstone was found to be approximately twice that of other rock types for stream sizes 1–4. For size 5–7 streams, the differences in TD depths between different lithologies were much less pronounced. More precise field identification of lithologies atop the breached ridges is needed to confirm the apparent lognormal distribution of the major rock types of the Susquehanna basin. As would be expected, TD slopes, as measured by Google Earth® along strike on the steepest side of the breaching valley, were higher for sandstones than shales. Slopes tended to increase with increasing TD depth, although a low R 2 value indicates that the linear regression thus derived may not be statistically significant. Approximately 15% of the TDs were b 0.5 km in length, 49% were between 0.5 and 1 km, and 37% were >1 km long, the length of the stream being its measurement between its entrance and exit from the topographic high. The direction of stream flow through TDs was almost invariably orthogonal to local structural strike, with 47% flowing NW and 53% flowing SE. All stream flow through TDs of size 4 and larger streams was to the SE, except for one TD of the Susquehanna River near Nanticoke, PA (Fig. 11). Overall, 56% of TDs were characterized as head streams, the majority of which were in sandstones; and 44% were characterized as trunk streams, the majority of which were in shales. The depth distribution of head stream TDs was approximately equal to that of trunk stream TDs for all rock types (Fig. 12). As a consequence of their location on the drainage network, all head stream TDs contained size 1 and 2 streams, but size 1 and 2 streams also made up the majority of the trunk streams, reflecting the overall distribution of stream sizes. Seventeen percent of TDs were classified as lineaments and were distributed roughly equally between head streams and trunk streams. One hundred and twenty-three TDs (19% of total) were aligned with at least one other TD. The TDs were considered aligned if the stream segment connecting them was linear, with no significant offset, and orthogonal to structural strike (Fig. 13). Fifty-five aligned segments were identified, with lengths ranging from 0.5 to 14.8 km, for a total combined length of 189 km. Thirty-six percent of aligned segments contained NW-flowing streams, for a total segment length of 48 km; while 64% (141 km total segment length) contained SE-flowing streams. While
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Fig. 5. Area map of identified TDs in the Susquehanna River basin by rock type and TD depth.
TD base level naturally decreased downstream on the aligned segments, 22 segments had downstream TDs whose topographic highs exceeded the elevations of the upstream TD's topographic highs (Fig. 14). These
segments had a greater percentage of streams flowing toward the NW and were shorter on average than those whose upstream highs exceeded downstream highs.
Fig. 6. Graph of lithology (top axis) and stream size (bottom axis) by depth in meters, showing proportion of size 1–2 streams whose TD depths fall within the depth range of Susquehanna TDs.
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Fig. 7. Google Earth® profiles showing gorges of similar depth occupied by different sized streams. (A) Berry Mountain, (B) Mahantango Mountain, and (C) Blue Mountain. Images courtesy of Google®.
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Fig. 8. Lognormal distribution of TD depths by lithology.
4. Discussion 4.1. Drainage development in the Susquehanna River basin Current theories have most of the Atlantic-draining streams of the Pennsylvania Appalachians flowing during the Cenozoic in locations and directions comparable to their present positions (Katkins and Delano, 1999), although the origination of the Susquehanna River drainage system is held by some to extend back to the Mesozoic (MacLachlan, 1999). The form of the Cenozoic surface is not known but is presumed to be a subdued erosional surface ~3000 ft higher than that of the present, with local relief in the same general form as the present, and streams probably nowhere entrenched (MacLachlan, 1999; Sevon, 1999). Superimposition and stream piracy, with some
measure of structural control, are the main mechanisms used to account for the formation of TDs (Strahler, 1945; Thompson, 1949; Epstein, 1966; Alvarez, 1999; Katkins and Delano, 1999). However, the results presented here raise questions about the proposed mechanisms of TD formation, particularly in regard to the following features: (1) The large number of TDs and the small size of most of the streams flowing through them. How could so many small streams have been able to incise gorges to the same depth or even greater than those of streams several orders of magnitude larger, often through highly resistant rocks? The problem is even more acute on ridges where similarly sized gorges containing very different stream sizes are found in close longitudinal proximity.
Fig. 9. Linear regression of LN values of TD depths by lithology (top axis) and rank-based Z scores (bottom axis), indicating statistical significance of lognormal distribution of depths (TD in one igneous rock was not calculated because of single sample size).
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Fig. 10. Preferred depth (in parentheses) by lithology (top axis) and stream size (bottom axis), calculated from average of LN depth (each bar represents one LN depth value).
(2) Lognormal distribution of depths. If this is a valid inference, why should there be a preferred depth for TDs and why should the most resistant rocks have the deepest preferred depth? (3) The distribution of TD morphology. Why is the depth distribution of trunk stream TDs roughly equivalent to that of head stream
TDs, whose catchment areas are much smaller in comparison especially if catchment area is a proxy for discharge and therefore for erosive ability? (Howard et al., 1994) In addition, how could the mechanisms available for erosion of head stream catchments, including overland flow, rain splash, and spring sapping, be
Fig. 11. Areal distribution of flow direction of streams through TDs.
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Fig. 12. Depth distribution by lithology (top axis) and morphology (bottom axis), showing similar depth distribution for rock types regardless of TD morphologies (each bar represents a TD depth).
capable of creating enough shear stress to erode resistant rocks at the interfluve divides? (4) The existence of aligned segments, many of which are quite striking both in linearity and in the disparity of ridge heights traversed by the incising streams (Fig. 15). Additionally, what combination of erosion and structural control could account for the increase in downstream topographic highs in almost half of the aligned segments? In addition, as Twidale (2004) pointed out, the persistence of rivers incised in consolidated bedrock stands in marked contrast to the shifting location and character of rivers of alluvial plains. In the cases of antecedence and superimposition, however, there must have been a transition from alluvium to bedrock. Modeling experiments addressing this issue
have been conducted but only in unconsolidated stream table sediments (see the review in Douglass and Schmeeckle, 2007). However, the defeat of the small tributaries in the stream table sediments of Douglass and Schmeeckle's (2007) antecedence experiments suggest that small streams would not be able to incise buried resistant ridges. Thus, the vertical transfer of small streams by incision from unconsolidated alluvium into consolidated bedrock, required by antecedence and by superimposition, appears doubtful. Further modeling experiments may help resolve these questions, along with numerical modeling of shear stresses necessary to bridge the divide between alluvial and entrenched incision. In the end, these results appear to have raised more questions than they have answered, but as Twidale (2003) pointed out, at regional scales, complexity in drainage systems is the rule rather than the exception. However, one possible inference of the survey
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Fig. 13. Google Earth® image of 55 aligned TD segments (inset box is area pictured in Fig. 15).
Fig. 14. Elevation difference in meters between upstream and downstream TD highs on aligned segments.
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Fig. 15. Aligned TD segments breaching anticline snout near Lamar, PA. Dashed line marks profile, arrows indicate stream flow in TDs. Image courtesy of Google®.
results may be that the streams that originally formed the TDs were larger than the streams that currently inhabit them. Twidale (2004) noted the importance of brief but large magnitude events in shaping landscapes, and others have inferred that floods are the cause of much erosion in bedrock reaches (Eaton et al., 2003a,b). Kochel et al. (2009) reported evidence for the subglacial outburst floods known as jokulhlaups in some tributaries of the glaciated areas of the Susquehanna drainage system; but the ridgetops were never covered by the glacial lobes, and the icedammed lakes drained through preexisting gaps in the ridges. They also attributed some incision of the Susquehanna in the Piedmont region to the breakout flows of jokulhlaups, but indicated that the major erosion features within the lower gorge may have been formed earlier. Coupled with the fact that much of the basin was not glaciated, breakout flooding from ice dam failure may account for the deepening of some TDs in glaciated areas but does not appear to be a plausible explanation for their origin. 4.2. Applications to other areas Preliminary investigation suggests that the pattern found in the Susquehanna basin of numerous TDs populated mainly by very small streams is replicated in other East Coast watersheds and potentially in
other mountain ranges around the world. The techniques introduced here may be helpful in quantifying and integrating transverse drainage data into models of basin evolution, in the Appalachians and in other drainage basins worldwide. For example, in the Potomac River watershed, numerous small streams are found in TDs, while the larger trunk streams conform to regional structure by following the strike of the fold valleys (Fig. 16A). In the Ohio watershed, the size 5 New River and Little Creek, a size 1 stream, are located in gorges of similar depths, 12 km apart on the same ridge (Fig. 16B). The methodology described here can be applied to many folded mountain ranges. One example is the Flinders Range of Australia, an area of Appalachian-style ridge-and-valley topography resulting from lithologically controlled differential erosion (Twidale and Bourne, 2010). The region features multiple TDs through quartzite ridges, breached synclinal snouts, and in-and-out streams that breach and flow through a ridge from one valley to another multiple times and are similar to features found in the Susquehanna basin. Antecedence, superimposition, and stream piracy have all been hypothesized for the area, as well as inheritance, another form of superimposition defined by Twidale (2004) as the imposition of a drainage surface developed on a weathered land surface onto the unweathered bedrock beneath; and impression, the transmission of structural effects from below.
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In the Zagros Mountains of Iran, Oberlander (1965) postulated drainage superimposed onto buried resistant layers by erosion through erodible strata that initially covered the higher parts of anticlines. Later, as ongoing erosion reached previously buried resistant layers, anticlinal ridges stood out in relief and were breached by superposed transverse streams (Mayer et al., 2003). According to Oberlander, the Zagros Mountains are a remarkable parallel to the folded Appalachians, although much younger and at a larger scale. Investigation of these and other areas of ridge-and-valley topography using the methodology presented here can help to determine
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whether or not the Susquehanna pattern of numerous small streams inhabiting large gorges is essentially an Appalachian phenomenon. 4.3. Suggestions for further study The techniques and methodology presented here may also be useful for investigating traditional geomorphic problems: (1) Ridge slope retreat vs. gorge incision. As Twidale (2004) pointed out, TDs may indicate a comparatively slow rate of slope lowering
Fig. 16. Potential areas of Susquehanna-type TD distribution in East Coast watersheds. (A) Potomac watershed in NE West Virginia with filled contours set at 360 m asl. Circles indicate TDs. Note tendency of head streams (in circles) to form TDs and trunk streams to form along-strike channels in structural folds. (B) Ohio watershed NW of Blacksburg, VA, with filled contours set at 640 m asl. Arrow indicates flow direction of New River. Dashed line marks profile showing size 1 stream (A) cutting similar-sized gorge to size 5 New River (B). Circles indicate TDs of size 1 streams. Images courtesy of Google®.
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Fig. 17. Through-valleys in upstate New York crossing the divide between Great Lakes and upper Chesapeake Bay watersheds. Dark curved line is watershed divide, white paddle icons indicate through-valleys. Arrow points to barbed headstream indicating catchment rearrangement by divide migration. Image courtesy of Google®.
versus that of river incision. In addition to the slopes of the TD valleys, S-profiles display the slopes of the breached ridges (Fig. 2A), and thus offer a unique opportunity to compare slope retreat of the breached highlands with gorge incision by the transverse stream. Using measurements gained from Google Earth's® elevation tool, volumetric analysis can easily be done on both the TDs and on the valleys on either side. Presuming the existence of an original surface of higher elevation, the rate of valley lowering that has occurred can then be compared to the rate of gorge incision. (2) Topographic data collection. Mills et al. (1987) noted that the operation of fluvial systems through time in much of the Appalachians has been recorded in its geomorphic landforms and alluvial terrace sequences. Google Earth's® elevation tool provides an easy method of creating cross sections for determining elevations and geologic information about paired and unpaired river terraces in both bedrock and alluvium, although studies such as these would need to be corroborated by field work (Marston, 1989). Topographic profiles can also help to identify the Vshaped incision of rejuvenated streams through U-shaped glacial valleys. In addition, since Google Earth's® elevation tool gives the mean elevation of every measured line, large-scale transects can be used to easily determine mean elevation. (3) Channel width determinations. During the course of the study, measurement of the Susquehanna streams as determined by Google Earth's® measuring tool revealed a close correspondence to the stream size on the EDNA overlay, i.e., size 1 streams (0– 0.5 cms discharge) had widths of .5 m or less, size 2 streams (0.5–1 cms discharge) were between .5 and 10 m in width, etc. This very useful feature can allow Google Earth's® measuring tool to approximate stream width in areas where streams are
visible on Google Earth® but field data are not readily available or dimensions of active channel width are lower than digital elevation model (DEM) resolution (Attal et al., 2008). (4) Analysis of regional stress patterns. Another possible avenue of research would be to compare TD azimuth trends with paleostress trends derived from regional structural and mineralogical studies, such as calcite twinning, stylolitization, or joint sets studies (Srivastava and Engelder, 1990; Faill and Nickelsen, 1999; Ong et al., 2007; Engelder et al., 2009). (5) Identification of through-valleys and wind gaps. Through-valleys, depressions eroded across a divide by glacier ice or meltwater streams, can be easily identified in glacial areas by contoursimulating overlays. For example, on the divide between the Great Lakes and the upper Chesapeake Bay watersheds in upstate New York, contour-simulating overlays at 380 m and 420 m show several glacial valleys crossing the divide, in which are located headstreams flowing in opposite directions on either side of the divides (Fig. 17). Contour-simulating overlays can also be used to identify wind gaps, as at Walyunga National Park, in Western Australia (Gozzard, 2007). A contour-simulating overlay at 180 m clearly outlines a higher, and therefore older, channel of a formerly westward-flowing stream that was captured by the south-flowing Swan River, whose channel is outlined at 80 m. The result is a wind gap to the west of the Swan River's course (Fig. 18A). An S-profile over the wind gap results in a modified M-elevation, with the now-defunct channel inside the wind gap perched at a higher elevation than either side of the ridge (Fig. 18B). The combination of S-profiles with channel patterns revealed by contour-simulating overlays may be able to aid in confirming the existence of wind gaps.
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Fig. 18. (A) Wind gap at Walyunga National Park, Western Australia. (B) S-profile over wind gap at Walyunga National Park, Western Australia. Images courtesy of Google®.
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Excel data and images of identified Susquehanna TDs: http://doi. pangaea.de/10.1594/PANGAEA.773968
5. Conclusion Because every TD represents an instance of flowing water bypassing the path of least resistance, the frequency and distribution of TDs within a basin should be an important factor in any theory of basin evolution. However, there is a dearth of TD surveys in the literature, perhaps because of the lack of objective physical criteria for TD identification. An initial step toward establishing such criteria has been suggested, along with their application to the Susquehanna River basin. As Valla et al. (2010) noted, the relative efficiency of glacial, fluvial, and hillslope processes operating in orogens remains poorly constrained, and improved empirical as well as physically based models are needed. The virtual reality capabilities of Google Earth®, combined with its ability to quantify topographic features, can help researchers to gather quantitative data on TDs and make reasonable estimates of their frequency and distribution so that they may be fully integrated into models of drainage basin evolution. The techniques described here are easily adaptable for use within the Appalachian basins and in other basins worldwide and offer the opportunity to reinvigorate the study of unique geomorphic features such as transverse drainages. Appendix A USGS Digital geologic maps of the United States: http://tin.er.usgs. gov/geology/state/ EDNA Derived watershed atlas: http://edna.usgs.gov/watersheds/ The Google Maps® terrain layer for Google Earth®: http://gemap-overlays.appspot.com/openstreetmap/cycle-map Tableau Public statistical graphics software: http://www. tableausoftware.com/public GPS Visualizer was used to transform data between spreadsheet and kml formats (http://www.gpsvisualizer.com). Instructions for creating filled-in contour elevations: http://tinyurl. com/7lbz5sm
Appendix C. Supplementary data Supplementary data associated with this article can be found in the online version, at http://dx.doi.org/10.1016/j.geomorph.2012.12. 022. These data include Google maps of the most important areas described in this article.
References Alvarez, W., 1999. Drainage on evolving fold-thrust belts: a study of transverse canyons in the Apennines. Basin Research 11, 267–284. Attal, M., Tucker, G., Whittaker, A., Cowie, P., Roberts, G., 2008. Modeling fluvial incision and transient landscape evolution: influence of dynamic channel adjustment. Journal of Geophysical Research 113, F03013. Bishop, P., 1995. Drainage rearrangement by river capture, beheading and diversion. Progress in Physical Geography 19, 449–473. Burbank, D., Meigs, A., Brozovi'c, N., 1996. Interactions of growing folds and coeval depositional systems. Basin Research 8, 199–223. Clark, G.M., 1989. Central and southern Appalachian water and wind gap origins: review and new data. Geomorphology 2, 209–232. Davis, W.M., 1889. The rivers and valleys of Pennsylvania. National Geographic Magazine 1, 183–253. Douglass, J., Schmeeckle, M., 2007. Analogue modeling of transverse drainage mechanisms. Geomorphology 84, 22–43. Douglass, J., Meek, N., Dorn, R.I., Schmeeckle, M.W., 2009. A criteria-based methodology for determining the mechanism of transverse drainage development, with application to the southwestern United States. Geological Society of America Bulletin 121, 586–598. Eaton, S.L., Morgan, B.A., Craig Kochel, R., Howard, A.D., 2003a. Quaternary deposits and landscape evolution of the central Blue Ridge of Virginia. Geomorphology 56, 139–154. Eaton, L.S., Morgan, B.A., Kochel, R.C., Howard, A.D., 2003b. Role of debris flows in long-term landscape denudation in the central Appalachians of Virginia. Geology 31, 339–342. Engelder, T., Lash, G.G., Uzcátegui, R.S., 2009. Joint sets that enhance production from middle and upper Devonian gas shales of the Appalachian basin. AAPG Bulletin 93, 857–889. Epstein, J.B., 1966. Structural control of wind gaps and water gaps and of stream capture in the Stroudsburg area, Pennsylvania and New Jersey. Washington, DC Geological Survey Professional Paper 550-B, 80–86.
Appendix B Statistical analysis of data in Fig. 8, LN of TD depth by rank-based Z scores grouped by rock type, from Tableau Public statistical graphics program. Trend lines model A linear trend model is computed for LN depth given rank-based Z scores. The model may be significant at P ≤ 0.05. The factor rock type may be significant at P = 0.05. Rock type ∗ (Rank-based Z scores + intercept) 652 0 8 644 2.15132 0.0033406 0.990322 0.0577975 b0.0001
Model formula: Number of modeled observations: Number of filtered observations: Model degrees of freedom: Residual degrees of freedom (DF): SSE (sum squared error): MSE (mean squared error): R2: Standard error: P-value (significance): Analysis of variance: Field Rock type Individual trend lines: Panes Row Column LN depth Calcareous
DF 6
SSE 0.165594 Line P-value b0.0001
DF 22
LN depth
Metamorphic
b0.0001
16
LN depth
Sandstone
b0.0001
294
LN depth
Shales and mudstones
b0.0001
312
MSE 0.0275991 Coefficients Term Rank-based intercept Rank-based intercept Rank-based intercept Rank-based intercept
Z scores Z scores Z scores Z scores
F 8.26182
Value 0.538505 4.6243 0.600466 4.66828 0.569157 4.6837 0.571775 4.64613
StdErr 0.010306 0.0105017 0.0172018 0.0160074 0.0049301 0.0052831 0.0032739 0.0030372
P-value b0.0001
t-value 52.2517 440.337 34.9073 291.633 115.446 886.545 174.645 1529.73
P-value b0.0001 b0.0001 b0.0001 b0.0001 b0.0001 b0.0001 b0.0001 b0.0001
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