Geomorphic Offsets Along the Creeping Laohu Shan Section of the Haiyuan Fault, Northern Tibetan Plateau GEOSPHERE, V

Research Paper

GEOSPHERE Geomorphic offsets along the creeping Laohu Shan section of the Haiyuan fault, northern Tibetan Plateau GEOSPHERE, v. 14, no. 3 Tao Chen1,2, Jing Liu-Zeng1, Yanxiu Shao1, Peizhen Zhang1,3, Michael E. Oskin4, Qiyun Lei1, and Zhanfei Li1 1State Key Laboratory of Earthquake Dynamics, Institute of Geology, China Earthquake Administration, Beijing, 100029, China doi:10.1130/GES01561.1 2Department of Science and Technology, China Earthquake Administration, Beijing, 100036, China 3School of Earth Science and Geological Engineering, Sun Yan-Sen University, Guangzhou, 510275, China 11 figures; 3 tables; 1 set of supplemental files 4Department of Earth and Planetary Sciences, University of California–Davis, Davis, California 95616, USA

CORRESPONDENCE: [email protected] ABSTRACT and varying over the seismic cycle (e.g., Peng and Gomberg, 2010; Barbot et al., 2012). It ranges from episodic offsets during earthquakes to continu-

CITATION: Chen, T., Liu-Zeng, J., Shao, Y.X., Zhang, High-resolution topographic or imagery data effectively reveal geomorphic ous aseismic slip, or other modes in between, such as slow-slip events and P.Z, Oskin, M.E., Lei, Q.Y., and Li, Z.F., 2018, Geo- morphic offsets along the creeping Laohu Shan sec- offsets along faults that can be used to deduce slip-per-event of recurrent rup- low-frequency earthquakes. These modes of slip ultimately determine the seis- tion of the Haiyuan fault, northern Tibetan Plateau: ture events. Documentation of patterns of geomorphic offsets is scarce on mic potential of individual faults. Evidence for past coseismic offsets may help Geosphere, v. 14, no. 3, p. 1165–1186, https://doi.org faults that undergo both creep and coseismic rupture. In this paper, we used to identify multimodal slip (e.g., Lienkaemper et al., 2006; Barbot et al., 2012), /10.1130/GES01561.1. newly acquired high-resolution light detection and ranging (LiDAR) data to improving our understanding of the spatial and temporal complexity of fault compile geomorphic offsets along the Laohu Shan section of the Haiyuan behavior, and contributing to the development of physics-based earthquake Science Editor: Raymond M. Russo Associate Editor: Colin Amos fault, in the northern Tibetan Plateau, where interferometric synthetic aperture hazard evaluation and forecasting techniques. radar (InSAR) data suggest creep presently occurs over a 35-km-long stretch Quantification of past fault slip events is usually based on reconstructing Received 22 May 2017 at a rate comparable to the long-term geological slip rate, despite evidence offset landforms along a fault trace, such as deflected stream channels, al- Revision received 14 January 2018 for past coseismic fault rupture. Numerous offset gullies identified using the luvial fans, and offset ridge lines (Sieh, 1978; McGill and Sieh, 1991). Recent Accepted 16 March 2018 Published online 17 April 2018 LiDAR data yield a range of offsets from less than 2 m up to 50 m. These offsets advances in remotely sensed high-resolution topography and optical imag- have well-separated probability density peaks at 2–3 m, ~7 m, and ~14 m, with ing have accelerated this approach. For example, light detection and ranging increments of 2–3 m, 4–6 m, and 5–7 m. The sequence of paleoseismic events (LiDAR) systems can acquire high-resolution (as high as centimeter-scale) along the Laohu Shan section indicates that the gullies with offsets of 2–3 m topographic data, enabling the detailed characterization of landforms and are likely related to surface rupture of the historical 1888 Jingtai earthquake, small displacements. Recent investigations have highlighted the scientific po- plus subsequent creep. Offset increments of 4–6 m and 5–7 m may represent tential of high-resolution topographic data sets for accurately documenting coseismic slip in past paleoseismic events plus creep during the interseismic past fault slip distribution, reconstructing slip history, and formulating earth- period. The creeping Laohu Shan section preserves numerous discrete cumu- quake recurrence models (Hudnut et al., 2002; Haugerud et al., 2003; Zielke et lative offsets, with an offset clustering pattern indistinguishable from that on al., 2010, 2012, 2015; Salisbury et al., 2012, 2015; Haddon et al., 2016). a locked fault with recurrent earthquake ruptures. Association of offset incre Airborne LiDAR topographic data were acquired in 2011 along 130 km of ments with known paleoseismic events yields a slip rate of 3–5 mm/yr during the Haiyuan fault on the northern Tibetan Plateau to illuminate offset land- the past 200 years, roughly similar to the ~5 mm/yr creep rate. If the ratio of forms (Liu et al., 2013). This survey included both sections that ruptured in the OLD G surface creep rate to the total fault slip rate has been continuous, then seismic 1920 M ~8 Haiyuan earthquake to the east of Jingtai, and sections within the moment release by brittle ruptures, and thus seismic hazard, would be much Tianzhu seismic gap to the west of Jingtai (Fig. 1; Gaudemer et al., 1995). The reduced on the Laohu Shan section of the Haiyuan fault. Alternatively, the cur- survey point cloud had an average shot density of 5 points/m2 after filtering rent high creep rate may be a transient phenomenon, perhaps after slip follow- and classification, which was used to generate 1-m-resolution digital eleva- OPEN ACCESS ing the 2000 Jingtai Mw 5.6 earthquake or in response to the adjacent 1920 tion models (DEMs). Based on the LiDAR-derived digital model of the section M ~8 Haiyuan earthquake rupture that terminated immediately to the east. of the fault that ruptured during the 1920 M ~8 earthquake, Ren et al. (2016) documented the clustering of offsets and discussed the implications of this clustering for slip repetition and fault segmentation. INTRODUCTION Here, we present LiDAR-derived slip measurements along the Laohu Shan section to the west of Jingtai. This 55 km stretch of the Haiyuan fault includes This paper is published under the terms of the Slip accumulation along faults can be achieved through different fault a 30-km-long section adjacent to the western termination of the 1920 rupture, CC‑BY-NC license. behavior modes, depending on the frictional properties of the fault plane, where Cavalié et al. (2008) and Jolivet et al. (2012, 2013) used interferometric

GEOSPHERE | Volume 14 | Number 3 Chen et al. | Geomorphic offsets along the Laohu Shan creeping fault 1165

Research Paper

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Figure 1. (A) Tectonic setting of the Haiyuan fault showing the location of major active faults and historical earthquakes (M >2) in adjacent regions. Surface ruptures associated with the 1920 and 1927 M ~8 earthquakes (EQs) are shown in orange, and the Tianzhu seismic gap is highlighted in red (after Gaudemer et al., 1995). (B) Distribution of active faults in and around the Tibetan Plateau.

GEOSPHERE | Volume 14 | Number 3 Chen et al. | Geomorphic offsets along the Laohu Shan creeping fault 1166 Research Paper

synthetic aperture radar (InSAR) to identify fault creep during 1995–1998 and ing fabric in trench exposures (Liu-Zeng et al., 2007). No significant surface during 2003–2009. The creeping behavior of the Haiyuan fault was unknown ruptures were reported for the 2000 Mw 5.6 earthquake (Rong et al., 2001). prior to its discovery via InSAR geodesy. The Tianzhu seismic gap is not associated with any large historical (M >7) Interrogation of airborne LiDAR-based DEMs generated 146 offset measure- earthquakes over the past few centuries, despite this area containing clear ments, among which 128 displacements were also identified and measured geomorphic evidence of Holocene seismicity (Gaudemer et al., 1995). Yuan et during field work in the same area. We used the resulting slip distribution data to al. (1994) excavated five trenches at several locations along the Laohu Shan reconstruct the most recent event, as well as earlier events, with timing from cor- fault (Fig. 3) and identified eight paleoearthquake events, suggesting recur- relations to previously published paleoseismic and historical records. Our offset rence interval of ~1000 yr, although the published trench logs are interpreta- measurements bear on the questions of (1) whether the present, rapid creep of tive sketches and are therefore difficult to evaluate. Excavations at a site west the Haiyuan fault is transient or persistent over the approximately thousand-year of that of Yuan et al. (1994) corroborated that the recurrence interval of large seismic scale, and (2) whether a partially creeping fault section can preserve cu- surface-rupturing events in this area is 800–1000 yr (Liu-Zeng et al., 2007). The mulative slip per earthquake in a fashion similar to that of locked fault sections. last major surface-rupturing event in this region was ~1000 yr ago and probably correlates with a historical earthquake in A.D. 1092. Liu-Zeng et al. (2007) found that smaller events were also preserved in the stratigraphy in the form SEISMOTECTONIC SETTING of cracks with no or nominal apparent vertical offsets. The Quaternary slip rate of the Maomao Shan–Laohu Shan segment is esti- The WNW-ESE–striking Haiyuan fault, together with the Altyn Tagh, Kunlun, mated to be 12 ± 4 mm/yr (Lasserre et al., 1999), which is higher than estimates and Xianshuihe faults, accommodates part of the eastward movement of Ti- of 5–8 mm/yr or less on the same section and those to the east of the Jingtai bet relative to the Gobi–Ala Shan platform to the north (e.g., Peltzer et al., 1988; step-over (Zhang et al., 1988; He and Lu, 1994; He et al., 1996; Yuan et al., 1997; Gaudemer et al., 1995; Daout et al., 2016). The ~1000-km-long, left-lateral Haiyuan Li et al., 2009; Chen et al., 2014). Estimates of modern strain accumulation rates fault is located on the northeastern margin of the Tibetan Plateau and extends across the Haiyuan fault using global positioning system (GPS) velocity or In- from the interior of the Qilian Shan mountains in the west to the N-S–striking Li- SAR data vary between 5 and 10 mm/yr, depending on subtle modeling differ- upan Shan thrust in the east (Fig. 1). The Haiyuan fault is a complex fault system ences (Gan et al., 2007; Meade, 2007; Loveless and Meade, 2011; Daout et al., segmented by pull-apart basins and step-overs. This includes the Jingtai Basin, 2016). The inconsistence of slip rates derived from different methods indicates a prominent 4-km-wide extensional step-over that marks the western termina- the challenges faced when attempting to understand fault behavior over vary- tion of the great 16 December 1920, M ~8 Haiyuan earthquake. This earthquake ing time scales. In addition, by stacking multiple years of Earth Resources Sat- generated an ~240-km-long surface rupture and a maximum left-lateral slip of ellite (ERS) and Envisat InSAR data, Cavalié et al. (2008) and Jolivet et al. (2012) ~10 m, reported from field investigations during the 1980s (Deng et al., 1986; identified a 35-km-long creeping section with an average creep rate of 4–8 mm/ Zhang et al., 1987). Note that Ren et al. (2016) questioned the 10 m offset and yr near the eastern end of the Laohu Shan fault segment. A similar rate of 5.6 ± suggested instead that this may represent offset from two or more earthquakes. 1.3 mm/yr value was obtained by the joint inversion of InSAR and GPS data with The 260-km-long section of the Haiyuan fault to the west of the Jingtai step- modeling accounting for fault geometry and slip partitioning (Daout et al., 2016). over has been termed the Tianzhu seismic gap (Gaudemer et al., 1995). This gap includes the Laohu Shan segment, which has a geomorphically well-ex- pressed rectilinear fault trace (Fig. 2). A local seismic monitoring network has DATA recorded a cluster of small- to moderate-magnitude (M >2) earthquakes along the Laohu Shan section over the past few decades, contrasting sharply with We used the 1-km-wide airborne LiDAR swath topography centered on the the low seismicity along the 1920 Haiyuan earthquake rupture (Fig. 1). These Haiyuan fault trace (Fig. 4). The LiDAR acquisition mission took ~8 d in Novem- small- to moderate-magnitude earthquakes include the 20 October 1990, Mw ber 2011. We used a Leica ALS-60 Airborne Laser Scanner and an integrated 60 5.8, and 6 June 2000, Mw 5.6, earthquakes. The elliptical isoseismic contours megapixel, medium-format, digital frame camera mounted on a fixed-wing air- of these two earthquakes, both of which have WNW-ESE–trending long axes, craft. The aircraft flew at ~1000 m above the ground. The elevation of scanned are generally parallel to the fault strike (Fig. 2A). Both earthquakes have high- region ranged from 1200 to 2500 m above sea level. To ensure position pre- est intensity values of VIII, with overlapping intensity VII isoseismal lines. The cision, we deployed six Trimble Net-R8 GPS receivers along the flight line at 1990 Mw 5.8 earthquake may have generated surface rupture, though this had a spacing of ~20 km to synergistically work with the high-frequency onboard not been directly reported. Liu-Zeng et al. (2007) made the inference, linking GPS. In total, >800 million laser returns were registered, with a point density meters-long fault-parallel, en echelon cracks observed on the fault (Gansu generally >4 points/m2 and locally as high as 10 points/m2. The postflight static Bureau of China Earthquake Administration, Lanzhou Institute of Seismology GPS observations indicated that the vertical mean square error (MSE) was less China Earthquake Administration, 1990) and up-to-surface cracks with shear- than 0.1 m, and the horizontal MSE was less than 0.2 m.

GEOSPHERE | Volume 14 | Number 3 Chen et al. | Geomorphic offsets along the Laohu Shan creeping fault 1167 Research Paper

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Isoseismal contours Surface rupture of the Inferred surface rupture Section of the fault with The 1990 Mw 5.8 EQ 1920 Haiyuan M~8 of the 1888 Jintai M~63/4 LiDAR scans shown in Fig. 4 The 2000 Mw 5.6 EQ EQ (Deng et al., 1986) EQ (Zhou et al., 1992)

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Figure 2. (A) Isoseismic maps of the 1990 Mw 5.8 Tianzhu and the 2000 Mw 5.6 Jingtai earthquakes (EQ), both with the highest seismic intensity reaching VIII degree on Chinese Seismic Intensity scale (NQTSA, 1999). The surface ruptures of the 1920 M ~8 Haiyuan earthquake and the 1888 Jingtai earthquake (inferred) are highlighted in red and orange shadings, respectively. Also shown are photographs of the fault trace within the intensity VII zone of (B) the 1990 Mw 5.8 Tianzhu earthquake and (C) the 2000 Mw 5.6 Jingtai earthquake, both looking to the west. The red triangles in B and C mark the position of the fault. LiDAR—light detection and ranging.

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Creeping section from InSAR data by Cavalié et al. (2008) and Jolivet et al. (2012) Trench sites Yuan et al. (1994) Q4 Holocene E Eocene S Silurian Liu-Zeng et al. (2007) Q3 Late Pleistocene T Triassic O Ordovician Q2 Middle Pleistocene Fault trace, dashed P Permian δ33 Late Caledonian Quartz diorite Q1 Early Pleistocene C Carboniferous u33 Late Caledonian metagabbro when inferred N Neogene

Figure 3. Geological map along the creeping section of the Laohu Shan fault. Also shown are locations of paleoseismic trenches (Yuan et al., 1994; Liu-Zeng et al., 2007). The extent of creeping section is delineated by a thick black line (after Cavalié et al., 2008; Jolivet et al., 2012). 0 km starts at the westernmost limit covered by the airborne light detection and ranging (LiDAR) data in this study. InSAR—interferometric synthetic aperture radar.

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Aluoquan 103°30′ E 103°40′ E

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Figure 4. Hillshade relief maps derived from the light detection and ranging (LiDAR) point cloud. Also shown are locations of measurements along the fault. The output files for computer-based offset measurements using the LaDiCaoz scripts (Zielke and Arrowsmith, 2012) and photos taken with field measurements are provided as electronic supplements (LiDAR.kmz and field.kmz; see text footnote 1). Limited by flight-line design, our airborne LiDAR survey includes a 2.4-km-long data gap, indicated by a dashed box in the upper panel.

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The scanned section is located in an arid to semiarid region with little veg- et al., 2014). Before field investigation, we translated all of the computer-based etation cover except low bushes. Artificial features and the vegetation were re- results, including 1-m-resolution DEMs, surface rupture locations, and mea- moved from the raw point cloud data using the manual recognition method in surement positions, to KMZ files. In the field, every recognizable offset fea- Terrasolid V10.00 software (MicroStation CONNECT Edition). The ultimate point ture was then independently measured by a three-person team equipped with cloud was classified into terrain and nonterrain point subsets, with more than Trimble Juno 3E handheld GPS receiver. The features on both sides of the 90% of all points being the former and therefore available for use in the gener- fault were projected onto the simplified fault trace, and two team members ation of a bare-earth model (Liu et al., 2013; Chen et al., 2014). The interpolation stood on the projected points to mark the crossing. The horizontal offset was of this point cloud was followed by the generation of 1-m-resolution DEMs. measured using a TruPulse 200 Laser Rangefinder, and the entire process was repeated three times for each feature. Finally, every later-added offset identified during field work was measured in LaDiCaoz again, including associated METHODS uncertainties (Fig. 5; Supplemental Table S11). 1 Supplemental Files. Two .kmz files, LiDAR.kmz and Generally speaking, the uncertainties in the measurements included two field.kmz, containing information of offset measures based on LiDAR DEM and optical images, and those Fault traces were mapped and offset features were identified in ArcMap components: quantitative range values and qualitative confidence values (e.g., made in the field. LiDAR.kmz file includes informa- V10.0 software and the 1-m-resolution LiDAR DEM and overlapping aerial Sieh, 1978; Weldon et al., 1996; Klinger et al., 2011; Zielke et al., 2015). The LaD- tion of offset measures based on LiDAR. When click- photos. Some features, such as small channel thalwegs, channel margins, iCaoz package of Zielke and Arrowsmith (2012) treats qualitative confidence by ing on the symbol, a pop-up window will displace additional information, coordinates (latitude, longi- and ridge crests, were labeled as candidates for displacement measurements subjectively assigning high, high–moderate, moderate, moderate–low, and low tude), distance along the fault relative to reference (Fig. 4). Epistemic and aleatory uncertainties in measurements were a signif- confidence values, similar to the rating schemes previously discussed (e.g., Sieh, starting point, best offset measurements, quality rat- icant challenge. To reduce epistemic error due to misinterpretation of offset 1978; Lienkaemper, 2001). We estimated quantitative range values during field ing, comments, and screen shots showing the con- features, three researchers independently identified candidate offset piercing work using an approach where each measurement was obtained three times, toured shaded relief map of the measurement site, and LaDiCaoz outputs and GOF (Goodness of Fit). features back-to-back and then cross-checked to ensure their applicability and with the quality rating of the measurement dependent on the preservation of The high-resolution DEMs derived from LiDAR data appropriateness. This approach cannot completely remove epistemic uncer- the offset landform and its geometric relationship to the fault. The factors that are also included. Field.kmz file includes information tainties, but it helps to reduce them as much as possible. affected this rating included the influence of degradation and aggradation, fault of offset measurements taken in the field. When click- ing on the symbol, a pop-up window will displace Horizontal offsets were measured using LaDiCaoz (Zielke and Arrowsmith, zone orientation and width, and the angle of intersection between the offset fea- additional information, coordinates (latitude, longi- 2012) by matching two cross-section profiles on either side of the fault (Fig. 5). ture and the fault, among others (Fig. 7). These factors are usually coupled in the tude), distance along the fault relative to reference The goodness of fit (GOF) was quantified to yield the optimal offset for each majority of cases and can be divided into fault- and feature-related categories. starting point, the values of three measurements, quality rating, and field photos. Please visithttp://doi .org offset marker. The GOF curve represents a weighted offset probability density Salisbury et al. (2015) presented a simplified bivariate rubric for feature qual- /10.1130 /GES01561 .S1 or the full-text article on www function for each offset measurement. Each reference feature was measured ity rating that compares the obliquity of an offset feature with fault zone width, .gsapubs.org to view the Supplemental Files. three to five times by a single researcher (Tao Chen), with a time interval of a which is used to assign the offset quality ranking. High-quality measurements few weeks to a few months between every two measurements. This measure- are generally obtained from clearly fault-normal piercing features that are off- ment process involved the revision of optimal offset and quality rating values. set by narrow and well-defined faults, whereas low-quality measurements are Field investigation further improved the data set by removing some falsely generally associated with less obvious, more ambiguous, poorly preserved, or identified landforms, and by adding new measurements unrecognizable in the highly oblique piercing lines that are offset by broad and poorly defined faults high-resolution DEMs. (e.g., Sieh, 1978; Lienkaemper, 2001). Here, we expanded on the bivariate rubric LiDAR data sets and imagery provide more than adequate context to mea- scheme of Salisbury et al. (2015) by developing a 3 × 3 matrix that semiquanti- sure large-magnitude (>20 m) offsets. On the other hand, limited by the imag- tatively described the measurement confidence values, with faults and features ery resolution, small-magnitude offsets (<2 m in this study) might be ambig- graded individually (Fig. 7). Instead of differentiating three quality rankings of uous or even invisible remotely, but they are identifiable in the field (i.e., site high (3), medium (2), and low (1), as in Salisbury et al. (2015), we assigned qual- s106 shown in Fig. 6A). In addition, man-made features (e.g., footpaths) with ity rating numbers from 1 and 9 from left to right and from top to bottom, each apparent curvature can be mistaken as left-lateral offset markers, even with of which assigned a unique value to the qualitative confidence rating. overlapping high-resolution optical imagery (Fig. 6B). Field investigation can help to remove these artificial features from the candidate landforms and to confirm the location and complexity of fault traces, both of which affect mea- RESULTS surements and associated uncertainties. This is why computer-based measurements should be reviewed in the field, if conditions permit. We obtained 146 offset measurements on 126 landforms based on LiDAR Field measurements are a vital step to understanding the origin and evo- imagery alone, and an additional 198 offset measurements on 167 landforms lution of the geomorphic feature identified remotely, which helps to reduce from field work (labeled with “s” or “c,” respectively, in Supplemental Table epistemic uncertainty and ensure the measurements are appropriate (Scharer S1 [footnote 1]). In total, 128 displacements were identified and measured by

GEOSPHERE | Volume 14 | Number 3 Chen et al. | Geomorphic offsets along the Laohu Shan creeping fault 1171 Research Paper a combination of confidence level of high quality in the fault zone element (HF) and median quality in landform element (MR) for the field measurement. See Figure 7 for detail. photo of offset channel by ~2.9 m. The table below shows the offset values as maximum, minimum, optimal, and confidence level of measurements. HF+MR ranking indicates and Arrowsmith, 2012), (C) reconstruction of topography by back-slipping 2.6 m, and (D) the overlap between two profiles on two sides of the fault after back-slipping, and (E) field 37.146104°N), in UTM 48N coordinate system, (B) with location of fault-parallel topographic profiles (red and blue) fault trace (turquoise) for LaDiCaoz offset analysis (Zielke Figure 5. Examples of light detection and ranging (LiDAR)–derived and field measurements of channel offset with uncertainties. (A) Current topography at site C631(103.449112°E, C361 No. C AB 20 m E 2.2m Min. Measurements based on LiDA 3.0m Max. 2.6m Opt. 20 m Rank High R Meas.1 D 20 m 3.1m Meas.2 Field measurements 2.7m Meas.3 2.9m HF+M R Ran k

GEOSPHERE | Volume 14 | Number 3 Chen et al. | Geomorphic offsets along the Laohu Shan creeping fault 1172 Research Paper

Offset channel

Upstream Fault Upstream Fault Downstream ?

Downstream

5 m

Offset crest？ Fault Fault Human footpath Offset crest？

5 m 5 m

Figure 6. Comparison of offset landform identification based on light detection and ranging (LiDAR) data and field measurements. (A) At site s106, the downstream part of the offset channel was not recognized with LiDAR data, but it was clearly identifiable in the field. (B) A feature initially interpreted as an offset ridge line in digital elevation models and optical images is, in fact, a man-made footpath.

GEOSPHERE | Volume 14 | Number 3 Chen et al. | Geomorphic offsets along the Laohu Shan creeping fault 1173 Research Paper

Landform element rank In general, the LiDAR-based measurements were comparable to those ob- High Median Low tained in the field (Fig. 8). In total, 128 displacements were measured repeat- edly by both methods. The measurements obtained by both methods have 9 8 6 a correlation coefficient of around 1.03, with the LiDAR-based measurements yielding values slightly higher than the field measurements (Fig. 8A). The qual-

High ity ratings assigned using the two methods can also be compared quantita- tively. The LaDiCaoz software quality ratings were translated to values of 1, 3, 5, 7, and 9, corresponding to low, medium–low, medium, medium–high, and 7 5 3 high ratings. In total, 101 of the paired LiDAR and field measurements showed differences in quality value less than 2, which we consider to be similar. There were only 27 features with rating differences more than 2, of which 18 features had higher-quality ratings for field measurements than LiDAR-based computer Median analysis (Fig. 8B).

Fault zone definition Figure 9A shows the distribution of all offset measurements obtained 4 2 1 from both methods along the fault. Distance along the fault was calculated, with the westernmost village (Aluoquan) covered by the LiDAR swath as the

Low start point (Figs. 2, 3, and 4). In general, measurements in the two data sets match quite well, especially for offsets less than 20 m (Fig. 9A). We analyzed these data further by combining them into a single data set, where (1) the Figure 7. Schematic diagram outlining the quantification of confi- measurement with the higher quality rating was preferred if a single feature dence in offset measurements as a function of the geometry of the was measured using both methods, and (2) the field measurements were fault trace and offset piercing lines using a nine-block-box approach, modified from Salisbury et al. (2015). Quality rating values were as- preferred if both methods had identical quality rating values. This yielded a signed from 1 and 9 from left to right, and from top to bottom. High combined data set that contained 216 measurements, including 162 field and value corresponds to well-preserved fault-normal piercing features 54 LiDAR-based measurements (Tables 1 and 2). Here, we focus on offsets that are offset by a well-defined and narrow fault zone, whereas a low value is associated with poorly preserved, highly oblique pierc- less than 20 m, as these values are most likely reliable and well-preserved ing lines that are offset by a broad and poorly defined fault. offsets that yield high-quality ratings. This yielded 187 measurements, among which 110 measurements had a quality rating of moderate or higher, and these were used in reconstructing the slip distribution of the most recent both approaches, representing 88% of the LiDAR-based measurements and earthquake events. 65% of the field measurements. It should be remarked that one measurement Plotting the offsets from the study area by summing individual normal- labeled “c” was identified, but failed to be measured in the high-resolution im- ized offset probability density plots yielded at least three offset peaks at 2–3 agery. Instead, it was obtained in the field (see Supplemental Table S1). Finally, m, 6–7 m, and 13–14 m (Fig. 9B). These cumulative offset probability density there were 128 repeat measurements with both methods. The computer-based (COPD) peak values roughly tend to decay exponentially with increasing off- measurements included three measurements with offsets less than 2 m, 114 set, as the larger peaks are less represented and more poorly defined due to measurements with offsets of 2–20 m, and 29 measurements with offsets more modification of features over time (Klinger et al., 2011). The resulting, clearly than 20 m, with the largest offset being ~60 m. In contrast, the field measure- separated offset groups suggest that offsets associated with surface-break- ments included 65 measurements with offsets less than 2 m, 123 measure- ing events are repeated in ~3 or ~6 m increments, which could include ac- ments with offsets between 2 and 20 m, and 10 measurements with offsets cumulated fault creep between surface-breaking events. We also calculated larger than 20 m, with the smallest offset being 0.6 m. The field-based data and normalized COPD values of offset measurements within every kilometer generally provided more reliable results for features less than 2 m, whereas bin along the fault, yielding a cluster of 2–3 m offset at distances of 3–7 km, the high-resolution LiDAR-based DEM offered an overview of the study zone 11–12 km, and 17–20 km (Fig. 9C). Another prominent cluster of 1–4 m offset that has significant advantages for efficient measurements of features with occurs at a distance of 30–50 km, which also corresponds to the 2–3 m peak larger offsets. On the other hand, the LiDAR data enabled efficient pre- and in the COPD plot. The 6–7 m offset cluster is distributed along the whole fault remeasuring, an approach that helps to improve the accuracy and reliability length, although 13–14 m offsets are comparatively rare. This kind of clus- of field investigations. Therefore, if feasible, the pairing of these field and re- tered pattern of slip distribution is similar to that observed within other fault mote-sensing methods is the best approach (Zielke et al., 2012, 2015; Salisbury systems globally (e.g., McGill and Sieh, 1991; Zielke et al., 2010, 2012; Klinger et al., 2012; Scharer et al., 2014). et al., 2011; Ren et al., 2016).

GEOSPHERE | Volume 14 | Number 3 Chen et al. | Geomorphic offsets along the Laohu Shan creeping fault 1174 Research Paper

6 40 AB 4 y=1.0266x+0.1052 30 2

20 0 Offset (m) erence (field-LiDAR) 5 10 15 20 25 30 ff −2 10 −4

Confidence di −6 0 0510 15 20 25 30 35 40

LiDAR-derived measurements of offset (m) Field measurements of offset (m)

Figure 8. Diagrams comparing light detection and ranging (LiDAR)–derived and field measurements in terms of (A) offset magnitude and (B) confidence level.

Offset (m) C 20 A LiDAR scan gap 60 LiDAR-based Mes. Field Mes. 50 15

fset (m) 30 Of

20 5

10 B 0 0 0 10 20 30 40 50 0510 15 20 25 30 35 40 45 50 Distance along fault (km) COPD Distance along fault (km)

Figure 9. Diagrams showing the distributions of (A) individual offset measurements (including both light detection and ranging [LiDAR]–derived and field measurements [Mes.]) as a function of distance along strike, (B) cumulative offset probability density (COPD) values for the entire fault section, and (C) along-strike variations in the summed probability density function for multiple measurements within a 1 km nonoverlapping window. The COPD values were derived by stacking individual offset observations.

GEOSPHERE | Volume 14 | Number 3 Chen et al. | Geomorphic offsets along the Laohu Shan creeping fault 1175 Research Paper

TABLE 1. SUMMARY OF OFFSET MEASUREMENTS USING LIGHT DETECTION TABLE 1. SUMMARY OF OFFSET MEASUREMENTS USING LIGHT DETECTION AND RANGING (LiDAR) DIGITAL ELEVATION MODEL AND IMAGERY AND RANGING (LiDAR) DIGITAL ELEVATION MODEL AND IMAGERY (continued)

Offset measurement (m) Confidence Distance along Offset measurement (m) Confidence Distance along Site ID Site ID Optimal MinMax level rank strike* (km) OptimalMin Max level rank strike* (km) C362 2.5 23 32.624 C581 657 123.716 C361 2.6 2.2 392.771 C584 768 727. 433 C442 12.3 12 13 32.909 C451 21.2 20 22 528.699 C593 2.1 1. 6 2.6 72.932 C452-17.4 78 728.984 C363 13.4 12 15 13.039 C452-2413943528.984 C570 2.1 1. 5 2.7 93.118 C2243.24245129.120 C443 3 2.2 3.8 33.187 S686.8 6.47.2 329.363 C364 10.7 912.4 73.330 C23-1 768 529.806 C365 2.5 1. 5 2.7 73.444 C23-2464349329.806 C595 1. 91.4 2.4 13.557 C2414.21316329.806 S104 2.7 1. 53 14.145 C453 5.24.4 6731.175 C367 7. 77 8.4 74.483 C2520.61922531.698 C0 14.6 13 16 54.752 S57211923331.928 C1 2.8 2 3.2 94.905 C454 21 18 24 332.059 C3 2.7 2.1 3.3 34.992 C2613.31214.67 32.229 C5 35 31 39 55.266 C374 13.8 12 15 732.309 C4 8.4 7. 89 75.482 s597.1 68.2 332.724 C444 54 52 56 15.883 C2719.31820532.893 C6-1 9.3 8.6 10 96.322 s6265.57 333.871 C6-2 27 25 29 76.322 C456 38 35 41 534.373 S108 2.8 2.4 3.2 56.638 s656.3 58 334.427 C8 6.4 5.1 7. 71 9.900 C282.9 2.53.9 734.481 C617 55 50 60 510.728 s6465.57 134.578 C446 4.6 4.1 5.5 310.843 C457 30.6 28 32 334.859 C369 7. 3 6.6 8510.887 C30-22.5 23 535.689 s99 768 112.795 C30-123.52124535.689 s100-1 6.6 6.2 7. 63 14.209 C377-2 12.5 11.5 13.5 735.689 s100-2 27 26 28 314.209 C377-1 26.5 25 28 535.689 C583 7. 46 8.8 114.306 s502.1 1. 72.5 735.975 C597 21 20 22 114.720 C333.6 34 536.006 C568 45 41 49 114.788 C31292731336.031 C569 8610 114.818 s473.6 34.5 336.326 s82 8.4 710115.627 C3416.41517536.406 C11202122115.842 C36-13.7 34.7 336.849 C127.3 6.3 7. 55 16.079 C36-27.6 69 336.849 C370 6.1 5.8 7316.109 s447.4 68.8 337. 509 C1665 6.3 716.453 C376.3 5.97.2 737. 518 C17 6.2 5.5 7916.571 C3822.22024737.529 C449 6.8 67.6 916.867 C3932.63035537.545 C371 6.5 5.5 7517.432 C40504852337.563 C372 49 46 52 117. 683 C42-114.41316339.446 s85 1. 61 2.4 917. 862 C42-215.41317339.446 C573 2.8 2 3.3 518.864 C45211922540.289 C574 2.9 2 3.1 319.077 C463.5 2.43.8 540.326 C575 20.5 19 22 719.399 C47 435 340.428 C20161517720.303 C460 2.52 3340.483 C450 14.4 13 15 721. 191 C378 2.31.6 3340.551 C578 768 122.380 C379 7. 87 8.65 41.259 (continued) (continued)

GEOSPHERE | Volume 14 | Number 3 Chen et al. | Geomorphic offsets along the Laohu Shan creeping fault 1176 Research Paper

TABLE 1. SUMMARY OF OFFSET MEASUREMENTS USING LIGHT DETECTION INTERPRETATION AND RANGING (LiDAR) DIGITAL ELEVATION MODEL AND IMAGERY (continued)

Offset measurement (m) Confidence Distance along Determining the distribution of coseismic slip is critical for estimating the Site ID Optimal MinMax level rank strike* (km) magnitude of past earthquakes and the future earthquake potential of active faults (e.g., Sieh, 1978; Zielke et al., 2010, 2012; Salisbury et al., 2012; Hecker et C461 3 2.2 3.6 341. 329 C57 8.4 89 941. 606 al., 2013). However, the number of peaks present in the COPD diagram (Fig. 10) C58-1 3.9 3 4.8 941. 624 cannot be simply correlated to the sequence of paleoearthquakes, because the C58-2 7. 87.1 8.2 741. 624 reliability and accuracy of slip reconstructions for single events based only on C61-1 8.1 7. 49 742.118 offset measurements remain unclear. Adding on top of the complexity, for the C61-2 3.8 3.3 5742.118 C62201822742.365 Laohu Shan creeping section, the COPD peaks may include some amount of C63 2.8 2 3.6 142.458 displacement from fault creep, but it is unknown how long and how much the C380 6.8 67.6 742.548 fault creeps between events. Therefore, more reliable understanding of fault C381 31 29 33 543.125 slip history requires pairing of offset measurements and their distribution with C6511. 81013.6 343.614 paleoseismic and geochronological data in the same region. C6613.4 12 14 343.727 C468 5.5 5 6.5 744.287 The most likely scenario of paleoearthquake correlations and rupture events C469 5.4 5 6.4 945.149 along the Laohu Shan fault during the past 4000 yr is shown in Figure 10B (Yuan C382 323.4 345.207 et al., 1994; Liu-Zeng et al., 2007). From the Songshan paleoseismic trench, Liu- S317.7 7. 2 8.2 345.344 Zeng et al. (2007) found that the most recent earthquake event (SS1) was asso- C591 2.1 1 2.3 345.379 S28141216545.547 ciated with multiple en echelon cracks, with shearing fabric that extends almost C616 2.8 23 545.603 to the ground surface but does not offset the underlying sediment layers. They C470 6 5.5 6.5 945.714 attributed these features to the 1990 Mw 5.8 Tianzhu earthquake (SS1 event). C475 2.6 23 545.903 However, given the poor stratigraphy in the very top, the possibility that these S25 6.8 5.8 7. 53 45.962 represent the historical 1888 earthquake cannot be ruled out. Older events are C472 3.1 2.5 4946.008 C471 3.7 2.8 4946.028 interpreted at A.D. 1440–1640 (SS2), shortly after A.D. 890–1000 (SS3), and A.D. C473 3.8 3 4.5 946.038 0–410 (SS4; Liu-Zeng et al., 2007). The trenching at individual sites to the east of C67 8.1 6.8 8.6 546.161 the Songshan site yielded only one or two events that are less well documented, s20 18.8 17 20 746.338 although some of these events seem to correlate to events SS3 and SS4 at the C384 17 15 20 546.247 C383 8.1 7. 59 946.295 Songshan site (Yuan et al., 1994; Fig. 10B; Table 3). In addition, the 1888 Jingtai C697.2 6.5 7. 97 46.357 earthquake may have occurred at the eastern section of the Laohu Shan fault C707.5 6.7 8746.375 (Zhou et al., 1992). It was estimated to be a magnitude 61/4 event, based on reports C480-1 34.4 30 36 346.459 of damage near Jingtai recorded in a local chronicle (Gu, 1983). However, Zhou C480-2 20.6 18 23 346.459 C479-1 20.2 18 22 546.508 et al. (1992) updated the magnitude of the 1888 earthquake to be M ~7, on the C479-2 7. 46 8546.508 basis of field evidence such as fresh mole tracks, several left-lateral offsets of 2–3 C7113.9 12 14.5 746.547 m, and a re-evaluation of the historical records about this earthquake damage. C7213.3 12.6 14 946.561 Combining paleoseismic records in previous studies and offset measure- C7313.5 12 15 546.610 ments in this study, we reconstructed the slip curves for individual events that C605 2.6 23 546.624 C607 12.7 12 13.7 746.700 are hypothetically compatible with the paleoseismic data obtained along the S1615.5 14 17 548.329 Laohu Shan section of the Haiyuan fault (Yuan et al., 1994; Liu-Zeng et al., 2007). C7411. 11012548.471 Based on the distribution of observed peaks in the COPD plot (Fig. 10B), our C75 6.7 6 8.2 349.196 reconstruction considers peaks in offset probability with 2 m separation to be C777.5 68 949.905 C79 6.9 67.6 350.076 associated with different events. We manually connected these measurements S4 3 2.5 4952.157 along the fault to include as many representative offsets as possible (Zielke et S3 2.7 2 3.2 952.180 al., 2012). Haeussler et al. (2004) reviewed different approaches to graphically S2 2.9 2 3.6 752.204 fitted slip distributions, concluding that whatever approach was used, the result- C484 6.9 67.4 952.712 ing difference (compared with other approaches) was usually less than 0.5 m. C482 6.5 67.6 752.732 Considering the 1 m resolution of the LiDAR-derived imagery, a manual method *Distance is relative to the western end point of the fault with LiDAR coverage. is probably sufficient to reconstruct the slip distributions of historic earthquakes.

GEOSPHERE | Volume 14 | Number 3 Chen et al. | Geomorphic offsets along the Laohu Shan creeping fault 1177 Research Paper

TABLE 2. SUMMARY OF OFFSET MEASUREMENTS IN THE FIELD

Offset measurements (m) Distance along Site ID Longitude (°E) Latitude (°N) Confidence level rating* † Meas. 1Meas. 2Meas. 3 strike (km) S103 103.447337. 14655278 1. 31.5 1. 61LF+LR2.603 C362 103.447994 37.1463312.6 2.52.8 2LF+MR 2.624 C361 103.44911237. 146104 3.12.7 2.98HF+MR 2.771 C442 103.450607 37.14547512.913.514.25MF+MR2.909 C593 103.45081 37.14562 3.43.0 2.88HF+MR 2.932 C363 103.451936 37.145174 12.7 11.5 13.1 2LF+MR 3.039 C570 103.452792 37.145011 2.01.8 2.27MF+HR3.118 C443 103.453541 37.1448072.9 2.14.0 5MF+MR 3.187 C364 103.455068 37.14438510.79.8 11.5 9 HF+HR 3.330 C365 103.456396 37.1438612.1 1. 31.5 9 HF+HR 3.444 C595 103.45758 37.1439 2.83.3 2.21LF+LR3.557 S104 103.4640278 37.14277222 2.22.3 2.41LF+LR4.145 C367 103.467733 37.142135 7. 68.1 6.78HF+MR 4.483 C0 103.47084 37.14170514.812.116.35MF+MR4.752 C1 103.472533 37.1414132.1 2.32.6 7MF+HR 4.905 C3 103.47341537. 141382 2.82.6 2.93MF+LR4.992 C4 103.478952 37.1408427.3 6.68.2 9 HF+HR 5.482 S105 103.479675 37.14080833 2.21.9 2.33MF+LR5.550 S106 103.4812222 37.14055278 2.31.8 3.07MF+HR5.690 C6-1 103.48818137. 1393859.7 8.610.89HF+HR 6.322 C6-2 103.488383 37.139132 27.3 28.1 27.5 9 HF+HR 6.322 S108 103.4916889 37.13885833 2.02.9 2.35MF+MR6.638 C8 103.528725 37.1350635.5 5.96.2 2LF+MR 9.900 C446 103.53916737. 13483 4.95.2 4.13MF+LR10.843 C369 103.53966 37.1347275.3 6.56.2 5MF+MR 10.887 s95 103.5418194 37.13454444 1. 21.3 1. 45MF+MR11. 081 C447 103.542054 37.1344331.9 1. 61.2 4LF+HR11. 103 s96 103.5437361 37.13428889 1. 61.3 1. 41LF+LR11. 253 C448 103.550497 37.1334261.9 1. 82.1 1LF+LR11. 799 s97 103.5504861 37.133516671.1 0.91 1LF+LR11. 854 s98 103.5509778 37.13349444 11.1 0.71LF+LR11. 900 C10103.55113337. 1333461.8 1. 42 1LF+LR11. 913 s99 103.5609806 37.13223056 6.67.2 5.82LF+MR 12.795 s100-1 103.5768083 37.13044722 5.96.3 5.72LF+MR 14.209 s100-2 103.5768083 37.13044722 15.2 14.4 13 1LF+MR 14.209 C583 103.577829 37.1300747.1 8.37.6 1LF+LR14.306 C569 103.583478 37.129127 7. 38.1 9.01LF+LR14.818 s82 103.5925722 37.12825556 9.78.2 10.1 1LF+LR15.627 C12103.597528 37.1273667.2 7. 06.6 4 LF+HR 16.079 C370 103.597882 37.1273186.4 5.87.2 1LF+LR16.109 C16103.601629 37.1266165.8 5.56.3 7MF+HR 16.453 C17103.60294 37.1264325.7 6.86.0 7MF+HR 16.571 C449 103.60619837. 1263175.8 5.56.2 9 HF+HR 16.867 C371 103.612769 37.1252456.1 6.85.6 7MF+HR 17.432 s85 103.6174722 37.125086112.0 1. 81.7 9 HF+HR 17.862 s86 103.6246778 37.1244751.8 1. 61.4 3MF+LR 18.498 s87 103.623225 37.124613891.7 1. 51.3 1LF+LR18.371 s88 103.6221389 37.12468056 2.01.5 1. 82LF+MR 18.275 C573 103.62876137. 1240572.8 2.62.0 1LF+LR18.864 C574 103.63113637. 1236523.0 2.62.2 3 MF+LR19.077 (continued)

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TABLE 2. SUMMARY OF OFFSET MEASUREMENTS IN THE FIELD (continued)

Offset measurements (m) Distance along Site ID Longitude (°E) Latitude (°N) Confidence level rating* † Meas. 1Meas. 2Meas. 3 strike (km) C20103.644754 37.12173315.013.716.89HF+HR 20.303 C450 103.654723 37.12081413.013.713.49HF+HR 21.191 S79103.6644278 37.119255561.5 1. 41.3 5MF+MR 22.067 C577 103.664349 37.1193032.0 1. 81.6 7 HF+HR 22.081 C578 103.667844 37.1186145.5 6.06.5 6HF+LR22.380 C581 103.682429 37.1156898.1 7. 47.8 6HF+LR23.716 S76103.69776137. 1134556.6 5.77.2 4#N/A25.157 s75 103.700441 37.1130857.2 6.86.0 4#N/A 25.431 S73103.707078 37.11166 5.15.9 6.01#N/A 25.970 S72103.7101833 37.111244446.1 6.07.2 7MF+HR 26.229 S71103.7137194 37.11043611 7. 97.4 7. 63MF+LR26.555 C584 103.72337 37.1087197.1 6.56.0 1LF+LR27. 433 C451 103.737093 37.10568220.723.025.26HF+LR28.699 C452-1 103.74021237. 1050877.0 7. 47.2 8 HF+MR 28.984 S68103.7443972 37.10434722 8.06.8 8.26HF+LR29.363 C23-1 103.749139 37.1030837.6 6.56.0 6HF+LR29.806 C24103.758688 37.10098413.812.714.66HF+LR29.806 S53103.760721737. 10089722 1. 51.7 1. 81LF+LR30.865 C453 103.764016 37.0999416.7 5.87.0 9 HF+HR 31.175 s54 103.7677867 37.098883331.7 2.01.9 3MF+LR 31.527 C25103.770375 37.09798 23.7 22.1 20.2 8HF+MR31. 698 S57103.7720056 37.0974388921. 719.520.26HF+LR31. 928 C454 103.773438 37.09721923.025.820.96HF+LR32.059 C26103.77519637.09654311. 914.213.68HF+MR 32.229 C374 103.776127 37.09647512.411. 812.98HF+MR 32.309 s59 103.7805694 37.09526111 6.56.9 7. 35MF+MR32.724 s60 103.7811111 37.095072221.1 1. 30.9 2LF+MR 32.778 C27103.782309 37.09463619.817. 618.26HF+LR32.893 s62 103.7929806 37.092436116.5 7. 25.4 3 MF+LR33.871 s65 103.7990528 37.091244447.8 8.17.3 3MF+LR 34.427 C28103.79959 37.0910133.3 2.82.5 7MF+HR 34.481 s64 103.8006472 37.09076944 7. 75.2 6.16HF+LR34.578 C457 103.803681 37.09002512.812.513.91LF+LR34.859 C598 103.81031737.0885011.8 2.02.1 5MF+MR 35.472 C30-2 103.81269837.0880632.8 2.42.5 8HF+MR 35.689 C30-1 103.81269837.08806320.822.623.56HF+MR 35.689 C377-2 103.81323937.0879499.9 12.4 11.2 8HF+MR 35.689 C377-1 103.81323937.08794928.726.526.86HF+MR 35.689 s50 103.8157661 37.087302782.2 2.32.0 7MF+HR 35.975 C33103.816155 37.0873283.9 3.64.4 3 MF+LR36.006 C32103.81673137.087155 2.01.6 1. 83MF+LR36.060 s47 103.81957537.086372223.0 2.73.2 3 MF+LR36.326 C34103.82037 37.08599 15.8 15.0 14.5 5MF+MR 36.406 C36-1 103.82531837.0854 3.33.1 2.73MF+LR36.849 C36-2 103.82531837.0854 6.66.8 7. 63MF+LR36.849 C599 103.825608 37.0853231.3 1. 11.5 4LF+HR 36.876 s46 103.8288889 37.084569441.2 1. 11.0 3MF+LR 37.178 s45 103.8308083 37.084419440.9 1. 00.8 4 LF+HR 37.348 s44 103.8325667 37.08411417 7. 17.6 6.78HF+MR37. 509 C37103.83267 37.084106 6.36.8 7. 08HF+MR 37.518 (continued)

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TABLE 2. SUMMARY OF OFFSET MEASUREMENTS IN THE FIELD (continued)

Offset measurements (m) Distance along Site ID Longitude (°E) Latitude (°N) Confidence level rating* † Meas. 1Meas. 2Meas. 3 strike (km) C38103.832804 37.08406520.921. 819.08HF+MR37. 529 C590 103.835372 37.08353 1. 21.5 1. 67MF+HR37. 766 C42-1 103.853332 37.07861314.812.016.03MF+LR39.446 C42-2 103.853332 37.07861310.911. 211. 53MF+LR39.446 C44103.86110637.0767191.3 1. 11.0 2LF+MR 40.168 C45103.862379 37.076286 17.7 17.9 20.4 3 MF+LR40.289 C46103.86276437.076126 3.83.1 4.26HF+LR40.326 C47103.863888 37.0759663.0 2.93.1 7MF+HR 40.428 C460 103.864497 37.0758812.4 2.32.1 5MF+MR 40.483 C378 103.865225 37.07567 2.42.1 2.08HF+MR 40.551 C602 103.865445 37.0756490.9 0.80.7 3 MF+LR40.569 s42 103.8657853 37.075611670.9 1. 10.9 3 MF+LR40.601 C50103.86616637.0755671.3 1. 21.4 1LF+LR40.634 C49103.866543 37.0755281.4 1. 31.1 1LF+LR40.668 C53103.866941 37.0754940.8 0.60.9 8HF+MR 40.703 C52103.86714937.0754761.3 1. 41.3 1LF+LR40.721 C54103.867322 37.0754621.3 1. 41.3 1LF+LR40.739 C55103.867527 37.0754441.5 1. 41.2 9 HF+HR 40.756 S40103.868441737.075208331.7 1. 81.9 1LF+LR40.842 S39103.8685028 37.07518889 1. 41.3 1. 21LF+LR40.847 S38103.8685628 37.07517472 1. 31.4 1. 51LF+LR40.853 C379 103.872909 37.0739477.1 7. 76.9 7MF+HR 41.259 C461 103.873633 37.0737142.8 2.72.9 9 HF+HR 41.329 C57103.87651737.0726557.8 8.07.4 9 HF+HR 41.606 C58-1 103.87672737.0725982.7 3.02.8 9 HF+HR 41.624 C58-2 103.87672737.0725986.2 5.86.5 9 HF+HR 41.624 C60103.880583 37.0718331.9 1. 82.1 5MF+MR 41.978 C61-1103.882007 37.0711687.4 8.06.8 6HF+LR42.118 C61-2103.882007 37.0711683.6 4.13.3 6HF+LR42.118 C62103.884644 37.0704916.7 7. 06.8 9 HF+HR 42.365 C63103.88559 37.0700242.0 1. 92.1 1LF+LR42.458 C380 103.886542 37.0697596.4 6.56.3 9 HF+HR 42.548 C64103.887448 37.0693991.6 1. 51.2 3MF+LR 42.635 C381 103.892557 37.0675096.8 6.97.3 5MF+MR 43.125 S35103.8932067 37.067315281.6 1. 21.3 3MF+LR 43.188 S33103.893435 37.067319441.6 1. 01.1 2LF+MR 43.207 C65103.897636 37.06562911. 211. 010.88HF+MR 43.614 C66103.898779 37.065124 11.4 13.0 12.4 8HF+MR 43.727 C462 103.89911337.0650011.1 1. 01.1 1LF+LR43.758 C463 103.899327 37.0649181.7 1. 81.9 3 MF+LR43.779 C464 103.899484 37.0648571.2 1. 11.0 3MF+LR 43.795 C465 103.89961237.0648061.1 0.80.9 3 MF+LR43.805 C466 103.899708 37.064769 0.90.8 1. 03MF+LR43.816 C468 103.90460137.0628756.4 5.86.0 8HF+MR 44.287 C589 103.905903 37.062118 1. 81.7 1. 53MF+LR44.421 C469 103.913143 37.0582045.1 5.74.9 8HF+MR 45.149 C382 103.913742 37.0579633.9 3.23.4 6HF+LR45.207 S31103.9151389 37.057335836.9 7. 27.0 5MF+MR 45.344 C591 103.91553337.0574521.9 2.41.7 7MF+HR 45.379 C613 103.91581937.057141 2.01.5 1. 86HF+LR45.407 (continued)

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TABLE 2. SUMMARY OF OFFSET MEASUREMENTS IN THE FIELD (continued)

Offset measurements (m) Distance along Site ID Longitude (°E) Latitude (°N) Confidence level rating* † Meas. 1Meas. 2Meas. 3 strike (km) S30103.9161667 37.05687389 1. 11.0 1. 23MF+LR45.445 S29103.9161444 37.05687389 1. 61.8 1. 73MF+LR45.443 C615 103.916227 37.056813 2.01.6 2.18HF+MR 45.452 S28103.9171889 37.05631667 15.8 14.8 16.7 1LF+LR45.547 C616 103.917767 37.056029 2.72.2 2.13MF+LR45.603 C592 103.917897 37.055992 1. 51.2 1. 05MF+MR45.618 C470 103.91890137.055625 5.86.3 7. 17MF+HR45.714 S26103.9198806 37.05505278 1. 51.3 1. 48HF+MR 45.812 C604 103.919944 37.055061.7 1. 81.6 8 HF+MR 45.818 C475 103.920803 37.054655 2.62.7 2.41LF+LR45.903 C476 103.92097637.054575 1. 52.1 1. 71LF+LR45.921 S25103.921430637.054475 5.86.3 6.15MF+MR45.962 C472 103.921888 37.054234 3.73.6 3.87MF+HR46.008 C471 103.92209 37.054152 3.94.0 3.77MF+HR46.028 C473 103.92219637.054113.9 4.04.1 3MF+LR46.038 S22103.9229944 37.05372778 0.91.0 0.81LF+LR46.115 S23103.9228889 37.05377778 1. 21.3 1. 51LF+LR46.107 C67103.92341337.053372 7. 97.1 6.63MF+LR46.161 C68103.923593 37.053271 1. 81.9 1. 69HF+HR 46.182 s20 103.9252256 37.05261778 16.5 18.4 17.9 9 HF+HR 46.338 C384 103.924237 37.052861 14.9 14.2 13.9 8HF+MR 46.247 C383 103.92474537.052729 7. 17.8 7. 79HF+HR 46.295 C69103.92541337.052511 6.26.1 6.77MF+HR46.357 C70103.92560137.052458 7. 67.2 8.05MF+MR46.375 C479-2 103.926979 37.0519367.6 7. 77.5 5MF+MR 46.508 C71103.92741937.05185512.613.412.75MF+MR46.547 C72103.927562 37.05180812.813.111. 97MF+HR46.561 C73103.928095 37.05166113.114.013.75MF+MR46.610 C605 103.928239 37.0516152.0 2.12.2 5MF+MR 46.624 C607 103.929025 37.05138 12.4 12.5 12.4 7MF+HR 46.700 S16103.9463167 37.04620833 13.2 14.5 15.3 4LF+HR 48.329 C74103.947442 37.045912 11.1 10.4 12.6 2LF+MR 48.471 S15103.9530056 37.04484444 1. 71.3 1. 63MF+LR48.943 C75103.955725 37.044144 6.97.3 7. 42LF+MR 49.196 C76103.95620137.044053 1. 91.8 2.01LF+LR49.240 S10103.9603056 37.04290556 1. 71.5 1. 71LF+LR49.624 C77103.963393 37.042415 7. 26.4 6.79HF+HR 49.905 C79103.965333 37.042297.4 7. 66.5 5MF+MR 50.076 C610 103.96751637.042296 1. 11.3 1. 33MF+LR50.264 S7 103.97045 37.04278333 1. 61.5 1. 23MF+LR50.506 C80103.97070137.042777 1. 21.0 1. 01LF+LR50.524 C83103.971362 37.042749 1. 41.0 1. 13MF+LR50.580 S4 103.9894139 37.04226389 3.02.3 2.53MF+LR52.157 S3 103.9896528 37.04216944 3.02.1 2.32LF+MR 52.180 S2 103.9899861 37.04236111 2.72.3 2.22LF+MR 52.204 S1 103.9942861 37.041508331.9 2.01.8 1LF+LR52.598 C484 103.995589 37.0414516.7 7. 26.9 7MF+HR 52.712 C482 103.995798 37.0413784.7 5.65.6 5MF+MR 52.732 *LF, MF, and HF refer to low, median, and high quality of the fault zone element; LR, MR, and HR refer to low, median, and high quality of the landform element. †Distance is relative to the western end point of the fault with light detection and ranging (LiDAR) coverage.

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20 A 15 Event 4 fset (m)

10 Event 3

5 Event 2 Event 1 0

Cumulative of 0510 15 20 25 30 35 40 45 50 55 Distance along fault (km) creeping section by InSAR Figure 10. Speculative reconstruction of the slip functions Yujiatai of prior earthquakes (EQ) using offset measurements. (A) Shangen A 2.5-km-bin cumulative offset probability density (COPD) Songshan Amenxian Chenjiazhuang Songshanshui plot yielding an overall smooth offset distribution; a solid B line is used where neighboring bins both contain obser- SS1: 1990 or 1888 EQ Event 1 1888 Jingtai EQ (1st) vations, and a dotted line is used where data are inferred based on previous field studies. (B) Ages of paleoseismic Event 2 (SS2) events and event correlation scenario along the Laohu 1000 A.D. Event 3 (SS3) 1200±100 A.D. (2nd) Shan fault (Yuan et al., 1994, 1997; Liu-Zeng et al., 2007). Read lines denote paleoearthquakes possibly correlative with the slip curves in the COPD plot above; the black lines are for unrelated older events. InSAR—interferometric syn- .) Event 4 (SS4) thetic aperture radar. 0AD/BC 0±300 A.D. (3rd) Age (yr 1000 B.C. 1050±150 B.C. (4th)

2000 B.C.

2250±150 B.C. (5th)

Yuan et al. (1994) Events interpreted to correlate with COPD Liu-Zeng et al. (2007)

TABLE 3. LIST OF PALEOSEISMIC EVENTS ALONG THE LAOHU SHAN SECTION OF THE HAIYUAN FAULT Liu-Zeng et al. (2007)* Yuan et al. (1994) Event no.Age ranges Possible corresponding historical earthquakeEvent no.Age ranges† SS1 ModernOctober A.D. 1990, Mw 5.81 A.D. 1888 SS2 A.D. 1440–1640 December A.D. 1514 2A.D. 1200 ± 100 SS3 Shortly after A.D. 890–1000 November A.D. 1092 3A.D. 0 ± 300 SS4 A.D. 0–410 October A.D. 14341050 ± 150 B.C. 52250 ± 150 B.C. *Liu-Zeng et al. (2007) also identified events SS5 and SS6 in trench exposures, but without age constraints. †Yuan et al. (1994) reported ages in B.P. They identified eight events, with ~1000 yr recurrence interval of large earthquakes;only the latest five events are listed here.

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The curve connecting points with 2–3 m offsets at the distance of 30–50 km along the Laohu Shan fault cluster at 2–3 m, ~7 m, and ~14 m, a pattern similar along the fault (relative to the start point) is interpreted to define the coseismic to a locked fault (e.g., Wallace, 1968; Sieh, 1978; Rockwell and Pinnault, 1986; slip function associated with the most recent earthquake, plus some amount Rockwell, 1989; McGill and Sieh, 1991; Zielke et al., 2010; Klinger et al., 2011). In of creep during the period between seismic events (Fig. 10B). This inference the upper crust, most faults move through episodic brittle failure, in which the is based on the assumption that the smallest observable offsets are generated fault is locked for the majority of the time between slip events. Fewer active by the most recent slip event (e.g., Sieh, 1978; Zielke et al., 2010; Klinger et al., faults are known to steadily release strain via creep and clusters of microearth- 2011). The likely candidate for this event is the 1888 Jingtai earthquake, the quakes, at full or partial fault slip rates. Evidence of creep on active faults in largest historical event known to have occurred near Jingtai (Fig. 1), barring and around the Tibetan Plateau is uncommon. The other known case is the the 1920 Haiyuan M ~8 earthquake (Zhou et al., 1992; Liu-Zeng et al., 2007). Xianshuihe fault in the section near 31°N, which creeps mostly in response The later 1990 Mw 5.8 Tianzhu and 2000 Mw 5.6 Jingtai earthquakes are too to the 1973 M 7.6 Luhuo earthquake (Lv et al., 1997; Du et al., 2010; Zhang et small to be associated with the generation of 2–3 m surface offsets. We did not al., 2018). extend this most recent event along the entire Laohu Shan section of the fault Creep on the Laohu Shan fault is poorly understood compared to other because the most recent event at the Songshan trench site (SS1) is a cracking known creeping faults or fault sections, for instance, the Hayward-Calaveras event with nominal slip. Instead, we interpret that the 2–3 m offset group in fault (e.g., Lienkaemper et al., 1991, 2014; Simpson et al., 2001; Galehouse, the western part of the fault (from 0 to 25 km) may be mainly associated with 2002; Schmidt et al., 2005; Evans et al., 2012), the central San Andreas fault in the penultimate SS2 event, which Liu-Zeng et al. (2007) inferred to be possibly California (Smith and Wyss, 1968; Thatcher, 1979; Langbein et al., 1999; Roe- the A.D. 1514 historical earthquake (Fig. 10). Zhou et al. (1992) measured 5 m loffs, 2001; Ryder and Bürgmann, 2008; Lienkaemper et al., 2014), the Ismet- offsets two locations near Chenjia Zhuang (at the distance of ~32 km) and con- pasa section of the North Anatolian fault (Ambraseys, 1970; Cakir et al., 2005; sidered these offsets to represent the coseismic slip of the 1888 Jingtai earthquake. In our opinion, it is more likely that the 5 m measurements represent cumulative offsets from more than one event. As mentioned already, reconstruction of the slip distributions associated Cumulative offset (m) with earlier events is more challenging and has larger inherent uncertainties, primarily because the number of paleoseismic events exposed within trench stratigraphy does not necessarily equal the number of offset (i.e., COPD plot) 1888 A.D. EQ 0 peaks (Zielke et al., 2012; Salisbury et al., 2015). However, events SS3 and SS4 revealed by the Songshan trench are associated with larger displacement SS3 magnitudes and wider deformation zones, characteristics that led Liu-Zeng 2 et al. (2007) to speculate that these were large-magnitude and long-rupture events similar to the 1920 M ~8 Haiyuan earthquake. Thus, it is reasonable 4 to consider that these events were associated with longer rupture and larger 2.7 mm/yr slip amounts, i.e., 4–6 m offset interval between the 2–3 and ~7 m COPD slip SS4 6 peaks, and 5–7 m offset interval between the ~7 and ~13 m COPD peaks (Fig. 10). Combining this reconstruction of slip-per-event values and the timing of 5.0 mm/yr 8 paleoseismic events, the fault slip rate on the Laohu Shan section would be 3–5 mm/yr over the past 2000 yr (Fig. 11), a value that is roughly consistent 3.75 mm/yr 10 with the GPS loading rate on the fault (Gan et al., 2007). 12 DISCUSSION 14 2500 2000 1500 1000 500 Cavalié et al. (2008) and Jolivet et al. (2012) showed that the Laohu Shan Years B.P. section of the Haiyuan fault is undergoing aseismic creep at an average rate of ~5 mm/yr, similar to the fault loading rate, within the corresponding uncer- Figure 11. Slip-time function of the Laohu Shan section of the Haiyuan fault if the correlation tainties (Gan et al., 2007). Their modeling further indicated that creep occurs between paleoseismic events and offset measurements is valid. Gray boxes represent the age range and cumulative offset of the 1888 earthquake, and those correlative to events SS3 and over the entire seismogenic depth, with the highest rate at 5–15 km depth, SS4 at the Songshan site. The data indicate a best-estimated average slip rate of 3–5 mm/yr rather than shallow creep. In this study, we show that the geomorphic offsets during the past 2000 yr.

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Karabacak et al., 2011; Kaneko et al., 2013), and the Longitudinal Valley fault For the partial creeping scenario, the COPD peaks represent a combination (e.g, Lee et al., 2003; Thomas et al., 2014). Jolivet et al. (2013) calculated the dis- of stick-slip events and creep. The offset increment shown in Figure 9 is the tribution of friction coefficient along strike using the fault strike variations and sum of both the coseismic slip associated with infrequent surface-breaking a Mohr circle construction and found that the creep rate scaled logarithmically events and the cumulative creep that occurred between earthquake events. with the friction coefficient, in agreement with the rate-and-state friction law The partial creeping scenario allows the possibility that fault creep is a long- in a rate-strengthening regime. However, it is unclear whether the Laohu Shan term behavior, but it also requires the long-term creep rate to be smaller than fault has been continuously creeping over multiple-event time scales. If the the geological slip rate. The rapid creep rate observed during 2003–2009 on Laohu Shan fault section has been fully creeping during the last few thousand the Laohu Shan section of the Haiyuan fault may be unrepresentatively high. years, the COPD peaks observed would be an artifact of punctuated channel It could represent the afterslip of the 2000 Jingtai Mw 5.8 earthquake (Figs. formation. Along locked faults, well-separated offset groups with approxi- 2 and 3), or a long-lived acceleration driven by enhanced stress at the tip of mately equal increments of offset have been interpreted to represent slips-per- the adjacent 1920 M ~8 rupture that terminated at the Jingtai pull-apart ba- event associated with infrequently occurring surface-rupturing earthquakes sin. It is common on partially creeping faults for the surface creep rate to be (Wallace, 1968; Sieh, 1978; Rockwell and Pinnault, 1986; Rockwell, 1989; McGill higher following a brittle faulting event and then decrease to the background and Sieh, 1991; Liu-Zeng et al., 2006; Kondo et al., 2010). The underlying as- creep rate in the decades afterward (e.g., Kaneko et al., 2013; Lienkaemper sumption is that the landform-forming climatic events occur more frequently et al., 2014; Thomas et al., 2014; Zhang et al., 2018). The same earthquake than the recurrence of earthquakes. Ludwig-Grant et al. (2010) questioned this rupture may also cause the depth of creep to increase temporarily from shal- assumption by showing that one set of offset channels on a fan surface along low down to the seismogenic depth (Jolivet et al., 2012). However, since it the Carrizo Plain section of the San Andreas fault incised less frequently than has been more than 80 yr since the 1920 quake, its longevity at such a high they were offset by earthquakes. However, whether climate-driven channel rate is somewhat difficult to explain in the context of rate and state theory. formation alone can explain the similar offset increments needs to be tested. A A better characterization of the aseismic sliding along the Laohu Shan fault fully creeping fault or fault section would be an ideal setting to test whether the requires more geodetic observations as well as further seismological and geomorphic record of cumulative offsets on a creeping fault is different from a geological studies. locked fault. No data of this sort have been obtained for creeping faults to date. Our data show that the creeping portion of the Haiyuan fault contains multiple well-preserved and well-separated COPD peaks, with a pattern identical to that CONCLUSIONS on locked, noncreeping faults. Taken at the face value, our results may be interpreted as indicating that climate-driven channel formation occurred regularly LiDAR is a highly effective technique that allows the accurate mapping of in time, so as to record similar offset increments on a creeping fault. However, fault-offset landforms and fault slip. This paper presents new LiDAR-based slip this interpretation is valid only if the Laohu Shan fault has been creeping at its measurements for the Haiyuan fault, a major continental left-lateral fault on full geological slip rate over the long term, which may not be the case. the northern Tibetan Plateau. This fault represents the 30-km-long section of If the creep rate is similar to the long-term slip rate, and this balance is fault beyond the western termination of the great 1920 M ~8 Haiyuan earth- maintained over time scales of thousands of years or longer, then there will not quake rupture, an area where InSAR data suggest the fault has been creeping be enough moment accumulation for large-magnitude brittle ruptures. This is at a rate of 5 ± 1 mm/yr since 1993 (Cavalié et al., 2008; Jolivet et al., 2012). in conflict with both the historical earthquake and paleoseismic records, which LiDAR data enabled the identification of numerous offset gullies that yielded a show that this section of the fault underwent surface-rupturing events that re- wide range of offsets, from <2 m to 60 m. These data show a clear clustering curred approximately once every 1000 yr. There are at least two possibilities. of small offsets (2–3 m, ~7 m, and ~14 m), with the group of smallest offsets One possibility is that the creep on the Laohu Shan fault is a recent, transient probably representing the coseismic slip of the historical 1888 Jingtai earth- phenomenon, which does not occur on a geological time scale. In this scenario, quake plus creep during the interseismic period. Paleoseismic and historical the fault is capable of switching between creeping and surface-rupturing brittle earthquake records suggest that the Laohu Shan fault section is capable of faulting. Offset groupings represent coseismic slips associated with infrequent creeping and surface-rupturing brittle faulting. It also requires that the long- surface-breaking events. The second possibility is that the fault is partially term creep rate is smaller than the geological slip rate. Association of offset creeping, capable of both creeping and surface-rupturing brittle faulting. In this increments with known paleoseismic events suggests a slip rate of 3–5 mm/yr case, the creep on the Laohu Shan section is a shallow phenomenon, with the over the past 2000 years. Our new data indicate that the present high rate of fault remaining locked at depth, similar to the Ismetpasa segment of the North creep observed along the Laohu Shan section of the Haiyuan fault may repre- Anatolian fault in Turkey (Ambraseys, 1970; Ozener et al., 2010; Karabacak et al., sent transient acceleration of surface creep at the termination of the 1920 M ~8 2011; Kaneko et al., 2013) and the Hayward fault in northern California (Lienkae- Haiyuan earthquake rupture. These data also suggest that fault behavior of the mper et al., 1991; Simpson et al., 2001; Galehouse, 2002; Schmidt et al., 2005). Laohu Shan fault is capable of both stable creep and stick-slip.

GEOSPHERE | Volume 14 | Number 3 Chen et al. | Geomorphic offsets along the Laohu Shan creeping fault 1184 Research Paper

ACKNOWLEDGMENTS Haugerud, R.A., Harding, D.J., Johnson, S.Y., Harless, J.L., Weaver, C.S., and Sherrod, B.L., 2003, High-resolution LiDAR topography of the Puget Lowland, Washington: GSA Today, v. 13, no. 6, This study was supported by the National Natural Science Foundation of China (41761144065, p. 4–10, https://doi .org /10 .1130 /1052 -5173 (2003)13 <0004: HLTOTP>2 .0 .CO;2 . 41502188), State Key Laboratory of Earthquake Dynamics (LED2014A02, LED2017A01). The manu- He, W.G., and Lu, T.Y., 1994, Study on the segmentation of Laohushan fault zone: Northwestern script benefited from discussion and comments on earlier versions by Zhikun Ren, Kenneth Hud- Seismology Journal, v. 16, no. 3, p. 66–72 [in Chinese with English abstract]. nut, Ramon Arrowsmith, Daoyang Yuan, Sinan Akciz, and Ray Weldon. We thank two anonymous He, W.G., Liu, B.H., Lu, T.Y., Yuan, D.Y., and Liu, X.F., 1996, Holocene activity of faults around the reviewers and Associate Editor Colin Amos for careful and constructive reviews that help to im- Tianzhu basin and evolutionary process of the basin: Northwestern Seismology Journal, v. 18, prove the manuscript. no. 1, p. 61–66 [in Chinese with English abstract]. Hecker, S., Abrahamson, N.A., and Wooddell, K.E., 2013, Variability of displacement at a point: Implications for earthquake–size distribution and rupture hazard on faults: Bulletin of the Seis- REFERENCES CITED mological Society of America, v. 103, no. 2A, p. 651–674, https://doi .org /10 .1785 /0120120159 . 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