Out-of-sequence reactivation of the Munsiari thrust in the Relli River basin, Darjiling Himalaya, India: Insights from Shuttle Radar Topography Mission digital elevation model-based geomorphic indices

Out-of-sequence reactivation of the Munsiari thrust in the Relli River basin, Darjiling Himalaya, India: Insights from Shuttle Radar Topography Mission digital elevation model-based geomorphic indices

    Out-of-sequence reactivation of the Munsiari thrust in the Relli River basin, Darjiling Himalaya, India: Insights from Shuttle Radar ...

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    Out-of-sequence reactivation of the Munsiari thrust in the Relli River basin, Darjiling Himalaya, India: Insights from Shuttle Radar Topography Mission digital elevation model-based geomorphic indices Manas Mukul, Vinee Srivastava, Malay Mukul PII: DOI: Reference:

S0169-555X(16)31000-5 doi: 10.1016/j.geomorph.2016.10.029 GEOMOR 5816

To appear in:

Geomorphology

Received date: Revised date: Accepted date:

19 April 2016 17 October 2016 19 October 2016

Please cite this article as: Mukul, Manas, Srivastava, Vinee, Mukul, Malay, Out-ofsequence reactivation of the Munsiari thrust in the Relli River basin, Darjiling Himalaya, India: Insights from Shuttle Radar Topography Mission digital elevation model-based geomorphic indices, Geomorphology (2016), doi: 10.1016/j.geomorph.2016.10.029

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ACCEPTED MANUSCRIPT Out-of-sequence reactivation of the Munsiari Thrust in the Relli River basin, Darjiling Himalaya, India: Insights from Shuttle Radar Topography Mission digital elevation model-based geomorphic indices

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Manas Mukul1, Vinee Srivastava2, Malay Mukul2* 1

KIIT University, Bhubaneswar, India 751024; [email protected] Dept of Earth Sciences, Indian Institute of Technology Bombay, Mumbai, India 400076; [email protected] *Corresponding author: [email protected]

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Abstract

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Quantitative tectonic geomorphology has emerged as a powerful discipline for studying evolution of topography, landscapes, and neotectonics using geomorphic indices computed from digital elevation data such as the Shuttle Radar Topography Mission (SRTM) data. We computed SRTM-based geomorphic indices to study neotectonics in the Relli River basin in the Darjiling Himalaya. We also used Real Time Kinematic Global Positioning System (RTK-GPS) independent checkpoints to assess the quality of the SRTM data used to compute the geomorphic indices along with their uncertainties. Our analysis revealed that though the SRTM C-Band 90-m resolution (C90) digital elevation data has been used extensively for geomorphic studies, the 30-m resolution (C30) data were significantly more accurate. Moreover, geomorphic indices computed using SRTM C30 and C90 elevations in the Relli basin indicate that normalized, nondimensional indices such as the relief ratio (Rh), hypsometric integral (HI), basin elongation (Re), and valley floor width-to-height ratio (Vf) are statistically indistinguishable with uncertainty (1σ) at least an order of magnitude below the index value. The geomorphic indices in the Relli basin reveal neotectonic activity related to the Munsiari thrust (MT) and intraformational faults in its footwall in the Lesser Himalayan rocks and also indicate that the basin is at an early mature stage close to equilibrium between tectonic and erosional process. However, analysis of the uncertainties associated with the indices suggest that the normalized or nondimensional geomorphic indices have the lowest uncertainties and that neotectonics in the Relli basin may only be confined to reactivation of the MT. The reactivation of the MT by out-of-sequence neotectonics implies the possibility of large earthquake events in the Darjiling Himalaya and significant seismic and landslide hazard for populations in large towns specifically located on the MT. Our new approach of looking at geomorphic indices and their uncertainties delivers a novel perspective for improved understanding of out-of-sequence neotectonics in river basins that may be applied more broadly across the Himalaya and elsewhere. Keywords: SRTM-based geomorphic indices; Darjiling Himalaya; Munsiari thrust; out-ofsequence deformation

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ACCEPTED MANUSCRIPT 1. Introduction The Earth’s landscape is shaped by the interaction between topography-building

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tectonic and topography-reducing erosion-related climatic processes (e.g., Andermann and

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Gloaguen, 2009; Pérez-Peña et al., 2009; Whittaker, 2012) and the resultant evolution of the

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landscape can be studied quantitatively using digital elevation data. The surface of the earth that defines the landscape can be bare or with objects like trees and buildings on it. Digital

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elevation data without defining the surface type are used for digital elevation models (DEM) (Peckham and Gyozo, 2007). If the surface definition is important, digital terrain models

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(DTM) or digital surface models (DSM) are constructed for bare surfaces and with objects respectively (Florinsky, 1998; Maune, 2001; Li et al., 2004). However, DEM and DTM have

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also been used interchangeably (e.g., Podobnikar, 2009). Availability of high-quality DEM

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has helped quantitative tectonic geomorphology emerge as a powerful discipline for studying

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evolution of topography and landscapes. This was made possible by computation of geomorphic indices from the digital elevation data from which the role of active tectonics in shaping the evolving landscape at and within mountain fronts over different time scales can

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be quantified and assessed (Keller and Pinter, 1996, 2002; Azor et al., 2002; Bull, 2008; Burbank and Anderson, 2011). Geomorphologic studies — such as understanding the alongstrike variations of morphotectonic features in the western foothills of Taiwan (Chen et al., 2003), investigation of active tectonics (Keller and Pinter, 1996), identification of geomorphic signatures of active tectonics in the west Lidder watershed (Bhat et al., 2013), appraisal of active tectonics in Hindu Kush (Mahmood and Gloaguen, 2012), analysis of longitudinal profile of Choushui River (Lee and Tsai, 2010), and studying China's Longmen Shan fault zone — and their implications for regional tectonic activity (Burchfiel et al., 1995) have used geomorphic indices.

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ACCEPTED MANUSCRIPT The Global Shuttle Radar Topography Mission (SRTM) 90-m resolution DEM, with a single pixel representing a surface area of 90 m x 90 m (Jarvis et al., 2008), has been used

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widely to compute geomorphic indices for geomorphologic studies worldwide (e.g., Malik

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and Mohanty, 2007; Dehbozorgi et al., 2010; Ahmad et al., 2014; Antón et al., 2014).

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However, these studies have not taken into account the vertical or height accuracy of the SRTM data, and consequently, the uncertainties associated with the computed geomorphic indices were unknown. Moreover, the vertical accuracy of the SRTM data is also known to

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get adversely affected in densely vegetated regions (Shortridge, 2006), higher elevation areas

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(Karwel and Ewaik, 2008; Mukul et al., 2015, 2016), and in regions of data voids in which interpolation algorithms (Jarvis et al., 2008) are used to fill in data. All these are likely to lead

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to large uncertainties in SRTM heights and, consequently, in quantitative indices computed

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using these heights. However, the geomorphologic studies that have used SRTM data to compute geomorphic indices (e.g., Biswas and Grasemann, 2005; Sreedevi et al., 2009;

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Dehbozorgi et al., 2010; Antón et al., 2014; Mosavi and Arian, 2015) assumed the data to be free of errors and uncertainty. These assumptions need to be tested and evaluated to decide if

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the interpretations based on such geomorphic indices are statistically robust and retain their validity even when the vertical uncertainty of the SRTM data that were used to compute them is accounted for.

We explore neotectonic activity in the Relli River basin in the Darjiling Himalaya, India, using geomorphic indices computed with the SRTM data set. We first use standard methodology prevalent in the literature wherein we compute geomorphic indices from as is SRTM 90-m data without taking uncertainties into account. Next, we compute the uncertainties associated with the SRTM-based geomorphic indices in the Relli basin that involve elevation using the widely used 90-m, as well as recently released 30-m, resolution SRTM DEM in this study and compare the results. The Relli is an ~32-km-long tributary of 3

ACCEPTED MANUSCRIPT the River Tista draining a horseshoe-shaped catchment in the Darjiling-Sikkim Himalaya. The Relli basin has reasonable access and visibility to carry out high-precision, Real Time

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Kinematic Global Positioning System (RTK-GPS) surveys to establish independent

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checkpoints (ICPs) to assess the vertical accuracy of the SRTM data in the region. The Relli

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River basin is also located in a unique geological setting in the Darjiling Himalaya east of the active Lesser Himalayan Duplex (LHD) and north of the active mountain front in the Darjiling Himalaya (Mukul et al., 2007; Mukul, 2000, 2010; Mitra et al., 2010; Goswami et

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al., 2012; Chakrabarti-Goswami et al., 2013; Kar et al., 2014). The Relli catchment is also

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cross-cut by the Main Central thrust 2 (MCT 2), which is equivalent to the regionally defined Munsiari thrust (MT) that carries Lesser Himalayan amphibolite facies, Paro-Lingtse schist

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and gneiss in its hanging wall over green schist facies Daling phyllite and quartzite in its

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footwall (Mitra et al., 2010). The geomorphology of the Relli basin is, therefore, controlled by the MT fault zone as well as fault-related lithological contrast. As the Relli basin has not

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been studied earlier, the results of this study will provide well-constrained insights on the outof-sequence neotectonics north of the neotectonically active Himalayan mountain front in the

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Darjiling Himalaya and outside the influence of the LHD. Active tectonics studies based on GPS measurements in the Darjiling Himalaya reveal that the Relli basin is presently locked along with the rest of the frontal Darjiling Himalaya (Mukul et al., 2009, 2014). In this study, we first explore the effect of height or vertical uncertainties in the source data used for computing geomorphic indices. This is an issue that has not been addressed earlier even though it is vital for obtaining statistically meaningful indices and results. We then use the results to study neotectonics in the Relli basin. We address the following questions in the analysis from the Relli basin: (i) How much is the uncertainty associated with as is 90-m and 30-m resolution C-Band SRTM DEM heights and the geomorphic indices computed from them in the Relli catchment? (ii) What do the geomorphic indices 4

ACCEPTED MANUSCRIPT reveal about the status and significance of neotectonic activity in the Relli basin? (iii) Are additional insights obtained from geomorphic indices using SRTM data with height

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uncertainties or is the current practice of using as is SRTM data without height uncertainty

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good enough?

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2. Geological setting of the Relli basin

We examine the status and significance of neotectonic activity using SRTM-based

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geomorphic indices in a small (Relli) river basin in the Darjiling Himalaya. The Relli River is a tributary of the river Tista and joins it south of the Tista low dam stage III power house

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(26º59'56"N; 88º26'31"E; Fig. 1). The maximum length of the Relli profile is ~32 km. Its ~180-km2 catchment is located near Kalimpong town between latitudes 26º57'00"N and

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27º7'30"N and longitudes 88º24'00"E and 88º39'00"E in the Darjiling Himalaya (Fig. 1). The

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western end of the catchment, where it joins the Tista, is open while the eastern end is closed

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resulting in a horseshoe-shaped catchment. The Relli basin is located north of the mountain front in the region and east of the LHD in the areas (Fig. 1) that have been recognized as neotectonically active regions (Mukul, 2010; Goswami et al., 2012; Chakrabarti-Goswami et

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al., 2013; Kar et al., 2014). Neotectonic activity east of the LHD and north of the Himalayan mountain front in the region has implications for models of out-of-sequence deformation in the Lesser Himalaya (e.g. Mukul et al., 2007). In the absence of any other study in this region, geomorphic indices in the Relli basin provide insights on neotectonic activity in the Lesser Himalaya in the study area. The northeastern part of the catchment drains Lesser Himalayan amphibolite facies, Paro-Lingtse schist, and gneiss; whereas the southwestern part is located on green schist facies, Lesser Himalayan, Daling phyllite and quartzite in the hanging wall and the footwall of the MT (Mitra et al., 2010) respectively (Fig. 1). The Gish transverse zone, which is a sinistral strike-slip transverse fault, intersects the NE tip of the basin near the source of the Relli (Mukul et al., 2009; Mukul, 2010) whereby the river flows 5

ACCEPTED MANUSCRIPT on a fault gouge near its source (Fig. 1). The Geil Khola thrust, mapped as an intraformational thrust in the Lesser Himalayan Daling section in the Ramgarh thrust sheet

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(Banerjee, 2016), extends into the Relli basin (Fig. 1).

Fig. 1. Location of the study area in the Darjiling Himalayas (India) highlighting the Relli basin and the 193 RTK GPS independent checkpoints (ICPs). Knickpoints are located at A, B, and C on the Relli River longitudinal profile. The green square in the inset is the study area.

3. Methodology The first step in the evaluation of the uncertainties in the SRTM DEM-based geomorphic indices is to quantify the vertical or height uncertainty associated with the DEM. We first do this for SRTM 90-m data that have been routinely used in the literature to compute geomorphic indices and then for the recently released as is and outlier removed SRTM 30-m data.

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ACCEPTED MANUSCRIPT 3.1. Preparation of SRTM digital elevation models (DEMs) We downloaded the 30-m and 90-m resolution C-Band SRTM DEMs for the Relli

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basin (Fig. 1) from the CGAIR and USGS websites. The 4.1 version C-Band SRTM data in

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90-m resolution (C90) were obtained from the SRTM data search and download page of the

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CGAIR website: http://srtm.csi.cgiar.org/SELECTION/inputCoord.asp. The C-Band SRTM data in 30-m resolution (C30) were downloaded from the U.S. Geological Survey website

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using the Earth explorer interface: http://earthexplorer.usgs.gov/. We obtained both DEMs as GeoTiff raster files and clipped them to our study area (Fig. 1).

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3.2. Obtaining RTK-GPS ellipsoidal heights from independent checkpoints (ICPs) Field surveys were done using dual-frequency Real Time Kinematic Global

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Navigation Satellite System (RTK-GNSS) using the global positioning system (GPS), and

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ellipsoidal heights were obtained at 193 locations or ICPs in the northwestern part of the Relli

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basin (Fig. 1). These locations were measured on accessible roads along valley-to-watershed transects following standard methodology (Rodriguez et al., 2005, 2006). Because of constraints in accessibility and thick forest cover that restricted satellite visibility, no ICPs

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could be measured along the southeastern part of the Relli basin. The RTK-GNSS consists of a base receiver positioned at a known location along with mobile rover receivers. The base receivers send corrections to the rover receivers in real time to obtain the elevation with an uncertainty of ~1-1.5 dm at various locations or at the ICPs (El-Rabbany, 2002). The average elevation of the 193 locations was ~990 m with a minimum and maximum of ~576 and ~1321 m respectively. The errors at each of these ICPs were obtained by subtracting the elevation of C30 and C90 SRTM data from the ICP elevation and subjected to statistical analysis to find the accuracy and uncertainty of the C30 and C90 DEMs in the study area. The elevations of multiple ICPs within a single 90- or 30-m SRTM 7

ACCEPTED MANUSCRIPT pixel were averaged out to avoid redundancy in error computations. Hence, out of 193 locations, 146 points for C90 and 187 points for C30 were used for statistical analysis.

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3.3. Statistical analysis for computation of accuracy and uncertainty of C90 and C30 data

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The errors obtained for C90 and C30 DEMs were subjected to statistical analysis to

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compute the accuracy and uncertainty of as is C90 and C30 data. Most users of SRTM data sets use the data as is, and so analysis of uncorrected SRTM data products is most relevant

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for understanding the validity of the methodology currently being followed. All 146 C90 and 187 C30 points were used to compute the mean error (ME), mean absolute error (MAE), root

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mean square error (RMSE), standard deviation (SD), and the standard error (SE; Table 1). The errors were then further analysed to identify outliers with large errors using the

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box plots (Fig. 2) for the C90 and C30 data. Values greater than the upper quartile or less

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than the lower quartile by more than 3/2 times the interquartile range were identified as

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outliers from the box-plot analysis. We identified 6 C90 and 13 C30 outliers from the boxplot (Fig. 2) analysis. The C90 outliers consisted of data having errors < -20 m and > 20 m. The outliers for the C30 data had errors < -12 m and > 13 m. The outliers were filtered, and

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outlier-free data sets were statistically analysed for recomputing the uncertainty. The outlierfiltered data used for statistical analysis consisted of 140 C90 and 174 C30 points (Table1).

Fig. 2. Box plot for C90 and C30 errors indicating the presence of outliers.

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ACCEPTED MANUSCRIPT 3.4. Computation of geomorphic indices The delineated Relli watershed (Appendix A) for C90 and C30 were used to compute

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and compare the following geomorphic indices that are typically used to identify neotectonics

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in river basins (Table 2): relief ratio, drainage basin asymmetry, basin elongation ratio,

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hypsometric integral, stream length gradient index and valley height-width ratio (Strahler, 1952; Schumm, 1956; Pike and Wilson, 1971; Hack, 1973; Bull and McFadden, 1977;

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Gardner et al., 1987). The relief ratio, hypsometric integral, valley height-width ratio, and stream length gradient index are indices requiring elevation in their computation. These

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indices were computed and the differences in the index values along with their uncertainties compared for the C90 and C30 SRTM DEMs. The vertical ellipsoidal uncertainties were

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obtained from the results of our elevation error analysis. The horizontal positioning

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uncertainty or absolute geolocation error of 8.8 m for Eurasia was used from the literature

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(Rodriguez et al., 2005, 2006). Two-dimensional areal uncertainty estimates were not available and, therefore, were not considered. The basin elongation ratio and the drainage basin asymmetry are two indices that involve area. The uncertainties of the remaining indices

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were computed by propagating the vertical (height) and location (position) uncertainties to the function based on the indices (Appendix B). For relief ratio, valley floor width-to-height ratio, and stream length gradient index, both height and position were involved. 4. Results The uncertainties associated with the geomorphic indices are largely dependent on the uncertainties of the SRTM heights used to compute the indices. We first computed some of the commonly used geomorphic indices for testing the active tectonics in the Relli basin and then subsequently explored the uncertainty associated with the indices that required elevation as an input parameter. 9

ACCEPTED MANUSCRIPT 4.1. Statistical analysis of the C90 and C30 SRTM DEMs in the Relli basin The computed RMSE of as is C90 and C30 data was 10.31 and 5.44 m respectively.

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The ME for C90 was 0.33 m with SD and SE of 10.34 and 0.86 m respectively (Table 1). The

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ME for C30 was -0.01 m with lower SD and SE values of 5.46 m and 0.40 m respectively

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(Table 1). Table 1

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C30 As is 187 -0.01 3.97 5.46 0.40 5.44

Outlier filtered 174 0.37 3.20 4.03 0.31 4.03

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Number of points Mean error [m] Mean absolute error [m] Standard deviation [m] Standard error Root mean square error [m]

As is 146 0.33 6.97 10.34 0.86 10.31

Outlier filtered 140 0.60 5.93 7.53 0.64 7.53

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C90

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Data sets

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Results of the statistical analysis of the as is C90 and C30 SRTM data

The results were also computed for outlier-filtered C90 and C30 data (Table 1). The accuracy of the data improved after the outliers were filtered. The outlier-filtered RMSE were 7.53 and

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4.03 m for C90 and C30 data respectively (Table 1). The MAE also improved marginally by 1.04 m for C90 and 0.77 m for C30 data (Table 1). The outlier-filtered C90 and C30 also had the lowest SD of 7.53 and 4.03 m respectively. 4.2 Geomorphic indices of the Relli basin from the C90 and C30 DEMs 4.2.1 Relief ratio (Rh) The relief ratio (Rh) is computed from the elevation of the river source (ZS), river mouth (ZM), and the maximum watershed length (L). The relief ratio (Schumm, 1956) describes the grade of the river and is derived as follows:

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The ZS values from the C90 and C30 DEMs were 1992 and 2005 m respectively. Similarly,

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the ZM values derived from the C90 and C30 were 215 and 211 m respectively (Table 2). The maximum watershed length (L) for C90 and C30 was 23.60 km. From the above data the

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relief ratio (Rh) was computed to ~0.075 for C90 and C30 DEMs. The uncertainty (1σ) associated with the relief ratio (Rh) decreased from 0.80 to 0.39% in C90 and C30 data sets

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respectively (Table 2). The Rh values and their uncertainties were similar for C90 and C30 data sets because of the L being large (23.6 ±0.012 km) compared to ZS and ZM, which are in

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metres (Table 2). Also, Rh is a nondimensional, normalized index, whereby the uncertainty is minimized.

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4.2.2 Drainage basin asymmetry (AF)

The drainage basin asymmetry factor (Gardner et al., 1987) is used to detect the

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tectonic tilting of small scale as well as large area drainage basin irrespective of local or regional tilt (Hare and Gardner, 1985). It is defined as the ratio between the downstream right

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drainage area (AR) of the main drainage line and the total area (AT) as defined below: (2)

The drainage basin asymmetry factor for the Relli watershed was found to be 56.95 for C90 and for C30 data (Table 2) with AR = 103.02 km2 and AT = 180.88 km2. As area computation did not involve elevation or point locations, no uncertainty was computed for AF. Also, AF is a nondimensional, normalized index whereby uncertainty is minimized. 4.2.3 Basin elongation ratio (Re)

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ACCEPTED MANUSCRIPT The basin elongation ratio (Re) is defined as the ratio of the diameter of the circle having the same area as the basin (AT) and the maximum basin length (L; Schumm, 1956)

(3)

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and is computed using the following equation (Schumm, 1956):

Based on the Re, the basins are classified as circular (Re > 0.9), oval (0.8 < Re < 0.9), less elongated (0.7< Re <0.8), and elongated (Re < 0.7; Strahler, 1964). The basin elongation ratio

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using C90 and C30 data for the Relli basin was computed to 0.64 ±0.0003 (Table 2). The

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ratio and its uncertainty is influenced by large L (23.6 ±0.012 km) in the denominator. Also, Re is a nondimensional, normalized index whereby uncertainty is minimized.

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4.2.4 Hypsometric curve and hypsometric integral (HI) The measure of the relationship between area in the watershed and elevation is known

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as hypsometry (Langbein, 1947; Strahler, 1952). The hypsometric curve allows for comparison of areas of different sizes and elevations and consists of a normalized cumulative

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area along the x-axis and normalized elevation along the y-axis. The shape of the curve obtained indicates the geomorphic processes in a watershed (Strahler, 1952). A convex curve indicates a youthful basin categorized by rough relief indicating active tectonics, whereas a concave curve is related with an old basin where alluvial or fluvial processes dominate. A concave-convex curve is an indication of a mature basin where tectonics and erosion work in near equilibrium (Strahler, 1952). The hypsometric curves for the Relli watershed for C90 and for C30 data have a concave-convex shape (Fig. 3).

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Fig. 3. Hypsometric curves for the Relli basin using C90 and C30 data.

A basin’s relief can be quantified easily by the hypsometric integral (HI). The HI can be used

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to identify tectonically active regions and is computed from the formula (Pike and Wilson,

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1971):

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where Hmean, Hmin, and Hmax are the mean elevation, minimum elevation, and maximum elevation of the watershed respectively. The HI values range between 0 and 1 with values close to 0 indicating the basin to be at an old-age stage and values close to 1 indicating a

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youthful stage (Strahler, 1964). The basin at the youthful stage is characterized by rugged relief and deep incision, whereas old-age basins have subdued relief (Strahler, 1964; Keller and Pinter, 2002). Mature basins are at the intermediate stage where the geomorphic progression occurs at near stability. The Relli watershed HI for C90 and C30 was computed to 0.40 using the Hmean, Hmin, and Hmax values (Table 2). The difference in the HI for the two DEMs were visible only when computed to four places after the decimal. The uncertainty of the height elevations decreased from 10.34 m for C90 data to 5.46 m for C30 data, inducing an uncertainty of 0.007 (1.75%) to 0.004 (1%) respectively in the computed HI of ~0.4 (Table 2). The height uncertainty is normalized in this index as the numerator and the

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ACCEPTED MANUSCRIPT denominator involve height differences resulting in a low uncertainty for the index as well as near identical values of the index for C30 and C90 data.

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4.2.5 Stream length gradient index (SL)

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The stream length gradient index (SL) is used to show the relationship between stream power, tectonics, and rock resistance (Hack, 1973; Keller and Pinter, 2002) and is computed

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using the following equation:

(5)

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where ΔH is the difference in elevation, and Δl the length of the stream reach where the index is to be computed. Thus (ΔH/Δl) is the gradient of the stream reach. The L is the channel

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length from the drainage divide to the centre of the reach. Stream power is a function of water

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slope and discharge. The discharge correlates with the channel length, and the water slope is

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computed by the slope of the channel or the gradient of the stream reach (Ata, 2008). The change in stream power is affected by the change in slope induced by tectonic deformation or differential rock resistance from lithological variation and is reflected in anomalous SL values

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in these regions. The SL for the Relli River was computed by taking the reach length of 2.5 km from as is C90 and C30 DEMs (Table 3) and plotted over the longitudinal river profile (Fig. 4). The uncertainty for each of the SL values were obtained by error propagation (Appendix B) arising from ΔH/Δl (uncertainty in meters; Table 3) that gets multiplied by L (uncertainty in kms) and is, therefore, directly proportional to the length of the stream. The SL index is not a normalized or nondimensional index and has the dimensions of L. 4.2.6 Valley floor width-to-height ratio (Vf) The U- and V-shaped valleys can be identified by the valley floor width-to-height ratio (Vf; Bull and McFadden, 1977) geomorphic index, which is defined as: 14

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where Erd and Eld are elevations of the right and left valley divides respectively, Esc the

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valley floor elevation, and Vfw the valley floor width. Also, Vf is a nondimensional,

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normalized index whereby uncertainty is minimized. Values closer to 0 are V shaped and those close to 1 or above 1 are U shaped. The V-shaped valleys indicate the presence of areas affected by tectonic uplift. The U-shaped valleys indicate the attainment of erosion at the

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base level (Keller and Pinter, 2002; Keller, 1986). The Vf for the Relli basin were computed at every 2.5 km of the channel length at points where SL were computed (Table 3). For all

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the reaches (Table 3) the Vf values were found to be between 0.07 and 0.41 (Table 3) for C90 and for C30 data. The uncertainty of Vf for C90 ranged between 2.5 and 30%, whereas the

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same for C30 was between 2.5 and 20% (Table 3).

Fig. 4. The NE-SW longitudinal profile of the Relli River with SL and Vf values. The SL values of C90 and C30 are shown over the profile, and the Vf values are shown below the profile. The values in red indicate the presence of two knickpoints (A and B); C is another point with a high SL value. The uncertainties associated with the values are listed in Table 3.

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ACCEPTED MANUSCRIPT Table 2 Results of the geomorphic indices from the Relli watershed

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As is C90

As is C30 180.88

Watershed area (AT) (km )

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Length (km) L [error in %] ZS ± 1σ (m) [error in %] ZM ± 1σ (m) [error in %] Relief ratio (Rh) [error in %] Drainage basin asymmetry (AF)

23.6 ±0.012 [0.05%] 1992 ±10.34 [0.52%] 215 ±10.34 [4.81%] 0.075 ±0.0006 [0.80%] 56.95

Basin elongation ratio (Re) [error in %] Mean elevation (m) of the watershed (Hmean) ±1σ (m) [error in %] Minimum elevation (m) of the watershed (Hmin) ±1σ (m) [error in %] Maximum elevation(m) of the watershed (Hmax) ±1σ (m) [error in %] Hypsometric integral (HI) [error in %]

0.64 ±0.0003 [0.05%] 1075.76 ±10.34 [0.96%] 215 ±10.34 [4.80%] 2370 ±10.34 [0.44%] 0.4 ±0.007 [1.75%]

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23.6 ±0.012 [0.05%] 2005 ±5.46 [0.27%] 211 ±5.46 [2.59 %] 0.076 ±0.0003 [0.39%] 56.95 0.64 ±0.0003 [0.05%] 1077.38 ±5.46 [0.51%] 211 ±5.46 [2.59 %] 2373 ±5.46 [0.23%] 0.4 ±0.004 [0.96%]

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Table 3

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Geomorphic indices

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S. No

Results of the stream length gradient index (SL) and valley floor width-to-height ratio (Vf) with uncertainty computed for the Relli stream using as is C90 and C30 DEM C90 SL (m)

C30 SL (m)

C90 Vf

C30 Vf

02.5

226.14 ±007.74

230.07 ±4.70

0.10 ±0.04

0.10 ±0.03

05

392.18 ±022.12

391.59 ±11.83

0.30 ±0.03

0.28 ±0.03

3

07.5

521.27 ±036.63

521.69 ±19.50

0.11 ±0.02

0.11 ±0.02

4

10 (point A)

865.57 ±051.40

898.32 ±28.45

0.13 ±0.02

0.13 ±0.01

5

12.5

547.40 ±065.35

537.40 ±33.96

0.15 ±0.01

0.14 ±0.01

6

15

523.74 ±080.60

524.99 ±42.72

0.20 ±0.01

0.20 ±0.01

7

17.5

508.41 ±094.85

490.47 ±48.36

0.41 ±0.01

0.41 ±0.01

8

20

499.34 ±109.94

523.06 ±60.85

0.15 ±0.01

0.15 ±0.01

9

22.5

518.30 ±123.49

586.84 ±73.88

0.23 ±0.01

0.23 ±0.01

10

25 (point B)

928.82 ±140.08

874.26 ±69.73

0.15 ±0.01

0.15 ±0.01

11

27.5 (point C)

822.95 ±153.83

721.57 ±71.29

0.16 ±0.01

0.16 ±0.01

12

30

676.43 ±170.70

621.67 ±82.89

0.07 ±0.01

0.07 ±0.01

13

32.5

682.29 ±182.69

625.32 ±88.45

0.38 ±0.02

0.39 ±0.02

1 2

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Channel length (km)

No.

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ACCEPTED MANUSCRIPT 5. Discussion The analysis of SRTM data reveals that the RMSE of the errors for as is C90 and C30

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SRTM data (Table 1) are close to the SRTM goal of 9.7 m (Farr et al., 2007; Mukul et al.,

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2015) in the Relli basin of the Darjiling Himalaya. Removal of outliers from the data further

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improved the RMSE errors. The results also reveal that the C30 data are significantly more accurate than the C90 data. Therefore, C30 SRTM data must now be used in place of the

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older C90 data. Calculation of area and length using C30 and C90 data gave identical results (Table 2). This indicates negligible horizontal offset between the two data sets (Nuth and

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Kääb, 2011) during resampling of the measured C30 SRTM data to C90. The SRTM C-Band 90-m data have been used extensively in tectonic geomorphology to compute geomorphic

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indices (e.g., Malik and Mohanty, 2007; Dehbozorgi et al., 2010; Ahmad et al., 2014; Antón

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et al., 2014) to study active tectonics in river basins, though the uncertainty in the SRTM elevations has been ignored in computing these indices. We have used SRTM C-Band 90-m

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and the recently released 30-m data to compute geomorphic indices with uncertainties based on 193 RTK GNSS independent checkpoints to study active tectonics in the Relli basin and

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out-of-sequence deformation in the frontal Darjiling Himalaya. Relief ratio (Rh) computed for the Relli basin indicate that it is steep (Rh ~0.075). The Rh is a robust index as it is nondimensional and C90 and C30 data gave almost identical values of the index with uncertainty of <1% (1σ); the uncertainty associated with Rh using C30 data was almost half that with C90 data (Table 2). Drainage basin asymmetry factor (AF) of ~57 (>50) indicated a tilt of the Relli basin to the left or east. This tilt is also evident from the longer lengths of the eastern tributaries compared to the western tributaries from the watershed (Fig. 1). Basin elongation ratio (Re) of 0.64 for the Relli basin indicates that it is elongated (Strahler, 1964) and slightly tectonically active (Re range 0.5 to 0.75; e.g., Cuong and Zuchiewicz, 2001). The Re, like Rh and AF, appears to be a robust index as it was 17

ACCEPTED MANUSCRIPT identical for C90 and for C30 data and is a nondimensional index. The Re uncertainties (1σ) were <0.1% and only dependent on horizontal uncertainty associated with length of the basin.

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Hypsometric integral (HI) of 0.4 computed for the Relli basin for C90 and C30 data indicated

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that the basin is tectonically active but in a mature state where geomorphic erosional and

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tectonic processes are in near equilibrium without a clear dominance of one over the other. The HI was sensitive to height uncertainties but a nondimensional index so that the C90 and C30 (1σ) uncertainties were within 1 and 2% respectively (Table 2), making it a robust index.

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Hypsometric curves for the Relli basin using C90 and C30 data (Fig. 3) have a sigmoidal or a

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concave-convex shape indicating a mature stage of development as also indicated by the HI index of 0.4.

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The longitudinal profile of the Relli River approximates an equilibrium, concave-up

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profile (orange line in Fig. 4) with local convex and concave departures from the profile. The valley floor width-to-height ratio (Vf) along the longitudinal profile of the Relli River for C90

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and C30 SRTM data was <0.5, indicating V-shaped tectonically active valleys in the Relli basin. Also, no significant difference between the valley floor width-to-height ratios and their

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uncertainties computed using the C90, and C30 SRTM data (Table 3; Fig. 4), suggests that it is a robust index. A concave departure from the equilibrium profile occurs near the source of the river that may be explained by the river flowing over fault gouge produced by crushing and fracturing in the Gish transverse zone (Fig. 1) that is much weaker and less resistant to weathering than the intact Paro gneisses and schists occurring in the hanging wall of the MT resulting in a lesser slope. The SL index computed from C30 and C90 data in this region, therefore, was anomalously low (226-392 m) compared to the rest of the profile (>500 m). In addition, three zones (A, B, and C) with pronounced convexities off the equilibrium profile were identified (Fig. 4). The stream length gradient (SL) Index at A was >860 m, almost 310 m more than the adjacent regions with SL indices between 520 and 550 m for C30 and for 18

ACCEPTED MANUSCRIPT C90 data. Zone A corresponds to the MT fault zone in the field (Fig. 1). The SL index was expected to be different on either side of the fault because of different lithologies. However,

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they were found to be ~520-540 m and statistically identical. Therefore, the anomalously

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high SL index in the MT fault zone could be attributed either to tectonic uplift or extreme

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strain-hardening where the fault zone rocks have been hardened during fault zone deformation to become more resistant than the hanging wall and footwall rocks. However, studies on the MT/MCT 2 fault zone have revealed strain softening (Bhattacharyya and

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Mitra, 2011) rather than strain hardening. Therefore, we interpret the high SL index values

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and the convexity in the longitudinal profile in zone A to indicate active uplift and reactivation in the MT fault zone. The lithology south of the MT fault zone consists

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dominantly of Daling phyllites and slates and that is reflected in the SL indices of ~500 m

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until zone B. In zones B and C, the longitudinal profile exhibited a pronounced convexity and high SL index (~720-929 m) compared to the NE (~518-586 m) and SW (~621-625 m). The

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B and C zones occur along the strike continuation of the trace of the Geil Khola thrust that has been mapped as an intraformational fault in the Ramgarh thrust sheet within the Daling

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rocks in the Tista River section (Banerjee, 2016), suggesting that the Geil Khola thrust extends into the Relli basin. Quartzite bands have been observed within the Daling section in the footwall of the Geil Khola thrust and that explains the marginally higher (~620-680 m) SL indices SW of zones B and C compared to that (~520-580 m) NE of them (Fig. 4). The SL indices computed using C30 and C90 data were within 4 and 25 m of each other NE and SW of zone A respectively (Fig. 4). The difference increased to 32 m in zone A and then to ~54101 m from near zone B to the join of the Relli with Tista. However, uncertainties associated with C30 SL indices are ~40-50% lower than C90 indices (Table 3), which makes the C30more reliable than the C90 data set. The SL index, however, is not a nondimensional index and has large uncertainties that are directly proportional to the channel length (L; Appendix

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ACCEPTED MANUSCRIPT B; Table 3). For as is C90 and C30 data, the SL index uncertainty increases from ~3 and ~2% (L = 2.5 km) to ~27 and ~14% (L = 32.5 km) respectively. These results suggest that the SL

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index for rivers with large channel length may not be statistically significant (e.g., at L = 32.5

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km, the uncertainty in C90 SL index is ~27%). Moreover, knickpoints identified along the

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longitudinal profile of a river also need to be statistically significant. The C30-based SL index at A (898.32 ±28.45 m) is statistically higher than the indices NE (521.69 ±19.50 m) and SW (537.40 ±33.96 m) of A. Therefore, our interpretation that the knickpoint at A is related to

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neotectonic uplift in the MT fault zone is statistically robust. Also, for the C30-based SL

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indices in the regions of B and C, the difference between B and C is statistically significant (152 ±99.72 m). However, the differences between C and SL indices SE of C are not

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statistically significant (99.9 ±109.33 m and 96.25 ±113.6 m at 30 and 32.5 km respectively;

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Table 3). Consequently, the knickpoint at C is not valid, and only those at A and B are real. If the same analysis is done with C90 data, the difference between B and C (105.87 ±208 m) is

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also not statistically significant, and the SL index at B may only be significantly different from the SL index NE of it (410.5 ±263.36 m). Therefore, the knickpoint associated with the

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Geil Khola thrust may simply be a reflection of contrasting lithologies across the fault and not uplift in the fault zone. Hence, this clearly indicates that geomorphologic and tectonic interpretations of the SL indices along the longitudinal profile of a river may change when their uncertainties are also considered. In summary, the study of the geomorphologic indices in the Relli River basin indicates that it is a mature basin close to equilibrium between tectonic and erosional processes but punctuated by tectonic activity in the MT fault zone. An intraformational knickpoint with the Daling rocks is possibly related to lithological contrast between hanging wall phyllite and footwall quartzite across the Geil Khola thrust. However, active out-ofsequence deformation in the Relli basin occurs by reactivation in the MT fault zone. Out-of20

ACCEPTED MANUSCRIPT sequence deformation in the Darjiling Himalaya has been reported south of the Relli basin in the Tista valley (Mukul, 2000; Mukul et al., 2007). The present study establishes that the out-

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of-sequence deformation observed in the Tista valley extends farther to the north and east and

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involves reactivation in the MT fault zone. This indicates that slip along the basal

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decollement of the Himalayan wedge, or the Main Himalayan thrust (MHT), had not only reached the Himalayan front in great earthquake events (e.g., in A.D. 1100; Kumar et al., 2010) but also reactivated faults north of the Himalayan front (e.g., MT) in out-of-sequence

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large earthquake events in the Darjiling Himalaya. This, in turn, implies that towns like

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Kalimpong (population ~50,000) and Gangtok (population ~100,000) that are located on MT in the region face significant seismic hazard from possible future reactivation of the MT in

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addition to great decollement earthquakes. Moreover, the occurrence of widespread

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landslides in the Relli basin along the trace of the MT may also have originated from

6. Conclusions 

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reactivation of the MT in out-of-sequence events.

The as is C30 SRTM data is, in general, significantly more accurate than the as is C90

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data. However, negligible horizontal offset between the two data sets exists as area and length computations using both data sets give near identical results. Nevertheless, the C30 data should be used for all future geomorphic studies for better vertical accuracy. 

The RMSEs for as is SRTM heights in the Relli basin appear to be close to the SRTM-RMSE goal of 9.72 m, which suggests that the SRTM data in the region is of excellent quality. Removal of outliers further improved the RMSE and data quality.



Geomorphic indices computed using SRTM C30 and C90 elevations in the Relli basin indicate that normalized, nondimensional indices such as the relief ratio (Rh), hyposmetric integral (HI), basin elongation (Re), and valley floor width-to-height 21

ACCEPTED MANUSCRIPT ratio (Vf) are statistically indistinguishable with uncertainty (1σ) at least an order of magnitude below the index value. Any SRTM data product can, therefore, be used to

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compute these indices as they are not sensitive to uncertainty in SRTM data products.

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The stream length gradient index (SL), however, is not nondimensional and is

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sensitive to SRTM height uncertainty that is directly proportional to the longitudinal channel length. Therefore, use of the SL index in geomorphic analysis must be accompanied by analysis of their uncertainty.

An analysis of the geomorphic indices in the Relli basin of the Darjiling Himalaya

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reveals that the basin has been affected by tectonic activity related to the reactivation in the MT fault zone and/or intraformational faults in its footwall in the Daling rocks

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but is at an early mature stage. Relief ratio (Rh) of 0.075 indicates high gradient,

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hypsometric integral (HI) of 0.4 an active but mature basin, basin elongation (Re) of 0.64 a slightly active basin, and valley floor width-to-height ratio (Vf) <0.5 indicates

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V-shaped valleys in an active basin. Drainage basin asymmetry (AF) points to an easttilted basin, whereas a sigmoidal or a concave-convex hypsometric curve indicates an

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active but mature basin. The longitudinal profile of the Relli River approximates an equilibrium, concave profile with knickpoints pointing to an active but mature basin. 

The distribution of SL indices along the longitudinal river profile can be best explained by knickpoints resulting out of tectonic activity along the MT and Geil Khola thrust traces in the basin, suggesting neotectonic out-of-sequence deformation in the Relli basin. However, on considering the uncertainties associated with the SL indices that increase downstream, the Geil Khola thrust knickpoint is more likely to be a reflection of lithological contrast across the fault than tectonic uplift.

22

ACCEPTED MANUSCRIPT 

Reactivation of the Munsiari thrust (MT) by out-of-sequence neotectonics implies the possibility of future large earthquake events in the Darjiling Himalaya and significant

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seismic and landslide hazards for populations in large towns located on the MT.

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Acknowledgements

The work was funded partially by the Ministry of Earth Sciences India, Grant No. MoES/16/01/09-RDEAS and Department of Science and Technology India, Grant No.

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SR/S4/ES-415/2009 to Malay. VS acknowledges IITB for the Teaching Assistantship in the Department of Earth Sciences. Critical reviews by two anonymous reviewers and comments

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by handling editors Pradeep Srivastava and Vimal Singh as well as Editor-in-Chief Dick Marston helped to significantly improve the quality of this paper. We benefited from

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discussions with Jason Barnes and D. Ramakrishnan.

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