Morphometric diversity of supply-limited and transport-limited river systems in the Himalayan foreland

Journal Pre-proof Morphometric diversity of supply-limited and transport-limited river systems in the Himalayan foreland Somil Swarnkar, Rajiv Sinha, Shivam Tripathi

PII:

S0169-555X(19)30373-3

DOI:

https://doi.org/10.1016/j.geomorph.2019.106882

Reference:

GEOMOR 106882

To appear in: Received Date:

4 March 2019

Revised Date:

19 September 2019

Accepted Date:

20 September 2019

Please cite this article as: { doi: https://doi.org/ This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2019 Published by Elsevier.

Morphometric diversity of supply-limited and transport-limited river systems in the Himalayan foreland Somil Swarnkar1, Rajiv Sinha1 and Shivam Tripathi2

1Department

of Earth Sciences, Indian Institute of Technology Kanpur, Kanpur 208016, India

2Department

of Civil Engineering, Indian Institute of Technology Kanpur, Kanpur 208016,

India

ro of

Corresponding author: Rajiv Sinha ([email protected])

Jo

ur na

lP

re

-p

Graphical abstract

Highlights: Morphometric analysis integrated with sediment connectivity and stream power index Variable sediment flux in upper Ganga and upper Kosi basins linked to morphometric characteristics Variable hillslope-channel and catchment connectivity contributes to sediment flux variations Slope variations manifested in stream power index also influence sediment transport

Morphometric characterization has significant implications for sediment management

ro of

Abstract The Indo-Gangetic basin exhibits highly diverse hydro-geomorphic settings that

influence the hydrology, sediment production, and transport rates, and this, in turn, is

-p

manifested in morphometric diversity of river systems. The rivers draining the

western Gangetic plains (WGP) show incised channels attributable to high stream

re

power and low sediment yield. In contrast, the rivers draining the Eastern Gangetic Plains (EGP) have formed aggradational landforms such as megafans due to low

lP

stream power and high sediment yield. For a better process understanding of the causal factors of such spatial inhomogeneities in basins, a morphometric

ur na

characterization of their hinterlands is necessary. In this work, a set of morphometric parameters such as stream network, longitudinal profile, and hypsometric curve have been integrated with data on sediment connectivity and stream power index to

Jo

establish the form-process relationships in two contrasting basins, the upper Ganga basin (UGB) and the upper Kosi basin (UKB). The results of this study suggest that high sediment flux in the UKB is attributed to high rainfall, steep topography, unstable channel longitudinal profiles, and high sediment connectivity. A large part of these sediments gets deposited within the channel belt in the alluvial reaches and is remobilized during high flow events. However, the UGB produces fewer sediments

due to low rainfall, mild topography, stable channel longitudinal profile, and low sediment connectivity. Also, the presence of a major dam at Tehri further reduces the functional sediment connectivity in the Upper Ganga Basin. Keywords: Morphometry; sediment dynamics; sediment connectivity; GIS; Himalaya 1. Introduction The morphometry of any river basin fundamentally defines the mathematical

ro of

quantification of basin physiography (Clarke, 1966). The drainage basin parameters related to linear, areal, shape and relief aspects are primarily used in the

computation of different indices. The morphometric characteristics provide insights

-p

into the underlying relationship between controls and response (Horton, 1932, 1945), and therefore, can be used as proxies for understanding the hydro-geomorphic

re

evolution of the river basin. Quantitative assessment of the drainage networks and

(Thomas et al., 2012).

lP

basin shape are some of the most popular approaches to understand basin evolution

ur na

The morphometric characterization of the river basin is one of the essential steps towards developing an integrated geomorphic and hydrologic understanding of the basin (Yang and Shi, 2017). In several studies, morphometry was used to assess the geomorphic response of the basin and their controlling factors. For example,

Jo

Gregory and Walling (1968) suggested that geology and relief of the river basin are the key controls on sediment production and transport. Likewise, the role of basin morphometric properties has been explored by many researchers in terms of sediment production (Cotton, 1964; Bandara, 1974; Oguchi, 1997; Lin and Oguchi, 2004) and sediment delivery (Vanoni, 1975; Walling, 1983; Lane et al., 1997; Hassan et al., 2008). Further, Milliman and Syvitski (1992) identified basin elevation

as the most important control on sediment generation. Morphometric parameters have also been used to evaluate the sediment transport typology (e.g. debris flow, transitional or water flood; see Melton, 1965; De Scally et al., 2010; Santangelo et al., 2012; Bertrand et al., 2013). In the Himalayan context, Islam et al. (1999) have examined several morphometric properties of the river basin and concluded that channel gradient, relief ratio, tectonics, and lithology are the primary drivers for geomorphological changes.

ro of

Quantitative models of sediment yield have also been proposed based on the

relationship between morphometric characteristics of the river basins and observed

sediment yield records (Ludwig and Probst, 1998; Lu and Higgitt, 1999; Verstraeten

-p

and Poesen, 2001) and applied across the globe to assess the geomorphic diversity

re

of river basins. Global sediment load assessments suggest that the Himalayan rivers are among the highest sediment carriers in the world (Holeman, 1968; Milliman and

lP

Syvitstki, 1992; Summerfield and Hulton, 1994; Ludwig and Probst, 1998; Syvitski et al., 2005). The Ganga river delivers 14-16 Million tonnes of sediments annually at its

ur na

mountain exit (Haridwar) (Abbas and Subramanian, 1984; Sinha et al., 2005; Chakrapani and Saini, 2009) and more than 400 million tonnes (~1235 t/y/km2) annually at Farakka, upstream of its confluence with the Brahmaputra (Syvitski et al., 2005; Jain and Tandon, 2010). The Kosi basin has an annual sediment load of 101

Jo

million tonnes(~1915 t/y/km2) at the mountain exit (Chatara) and 43 million tonnes at Baltara before its confluence with the Ganga (Sinha et al., 2019). Earlier studies have suggested the role of hinterland characteristics on sedimentation in the downstream reaches that have sculpted and varied the landscape across the Gangetic plains (Sinha et al., 2005; Roy and Sinha, 2017). However, there is no quantitative analysis yet to link this geomorphic diversity to

morphometric characteristics of the hinterland for understanding the process-form linkages. In this work, morphometric analysis has been carried out in conjunction with sediment connectivity and stream power indices aimed at (a) assessing the hinterland characteristics, and (b) explaining the controls of spatial inhomogeneity in the eastern and western parts of the Ganga river basin. The results obtained from this study are useful for developing a sustainable river basin management plan and for understanding the sediment dynamics of the river basin.

ro of

2. Study area and input data

The Himalayan rivers are characterized by high discharge, high elevation, large

drainage areas, and active tectonics. These factors govern the hydrology of these

-p

rivers, particularly the sediment transport characteristics. Besides, the abundance of

re

unconsolidated rocks of younger formations in this river basin increases the upstream sediment availability (Subramanian, 1996). Wasson (2003) suggested that

lP

the Higher Himalaya (~80%) and the Lesser Himalaya (~20%) are the major sources of sediment supply for the Ganga and its tributaries. The monsoon in the northern

ur na

Indian region lasts for four months from June to September. However, in the northwestern region, monsoon rainfall occurs mostly in July and August months. The north-eastern region experiences high rainfall in all four monsoonal months. During the monsoon period, the Himalayan rivers transport > 80% of the total annual

Jo

sediment load. This sudden burst of sediment load creates havoc in the downstream regions in terms of channel aggradation, avulsion, loss of reservoir storage, loss of agricultural lands and many more. Therefore, the understandings of hinterland processes particularly those related to sediment production are equally important while planning the hydrological structures and erosion measures.

The Ganga river basin is known for its geomorphic diversity as a function of stream power and sediment supply (Sinha et al., 2005, 2017; Roy and Sinha, 2018). For instance, the Western Ganga Plains (WGP) exhibits incised river valleys due to high stream power and low sediment supply. In contrast, the Eastern Ganga Plains (EGP) is characterized by aggraded river valleys and megafans because of low stream power and high sediment supply of the rivers draining this region. For instance, the southern banks of the Ganga at Bithur near Kanpur and Yamuna at Kalpi in the

ro of

WGP expose ~15 m and ~33 m high cliff sections respectively (Gibling et al., 2005; Sinha et al., 2007). Even smaller tributaries in the WGP i.e. Sengar, Rind and Pandu show 8 – 10 m deep incised river valleys. In contrast, the EGP is characterized by

-p

rivers with aggraded valleys and two megafans built by the Kosi and Gandak (Sinha

re

et al., 2005).

Primarily, the geomorphic diversity in the eastern and western Gangetic plains has

lP

been attributed to spatial inhomogeneity in rainfall and hinterland tectonics (Sinha et al., 2005). A higher uplift rate has been documented in the hinterland of EGP (11.9 ±

ur na

3.1 mm/y in Nepal) compared to that in the WGP (6.9 ± 1.8 mm/y in Dehradun) (Peltzer and Saucier, 1996; Bilham et al., 1997; Wesnousky et al., 1999). A higher uplift rate would produce a higher sediment flux in the hinterland of the EGP that will then be pushed into the plains quickly because of higher average annual rainfall (900

Jo

to > 1600 mm) in this region compared to the WGP (600 to 1400 mm). Relatively higher rainfall or erosivity in the hinterland of the EGP would also enhance sediment production and mobilization (Sinha et al., 2005; Roy and Sinha, 2017). This study is focused on two river basins, i.e. Upper Ganga Basin (UGB) in the western and Upper Kosi Basin (UKB) in the eastern part of the Ganga basin (Fig. 1a). The mountainous part of both the basins are selected to assess the controls and

to interpret the process -form linkage. Dataset used for this study is listed in Table 1. A summary of geomorphic and hydrologic characteristics shown in Table 2 highlights the contrasting hydro-geomorphic settings of the two basins. 3. Methodology and data analysis The available global dataset has been used to analyze the hydrogeomorphic processes in the hinterland of the upper Ganga and upper Kosi basins. For this

ro of

study, the UGB is divided into three parts, namely, the Bhagirathi sub-basin (Bg) to the west, the Alaknanda sub-basin (Al) to the east and the remaining part termed as Lower sub-basin (Lb) of Devprayag (Fig. 1b). The UKB basin is divided into four

major sub-basins, namely the Tibetan part (Tb) to the north, the Sapt Kosi sub-basin

-p

(Su) to the west, the Arun sub-basin (Ar) in the middle, and the Tamor sub-basin

re

(Tm) to the east (Fig. 1c). To begin with, the hydrometeorological analysis was aimed at assessing the rainfall characteristics and runoff potential at inter- and intra-

lP

basin scale. Monthly average rainfall dataset for the period 1970 – 2000 was used to compute the average annual rainfall for both the basins. Spatial averages of monthly

ur na

and yearly rainfall values were used to assess the inter- and intra-basin inhomogeneities separately. Further, cumulative area percentage curves were used to plot the rainfall values and contributing area for individual sub-basins. These curves were mainly used in this work to compare the spatial rainfall variation in terms

Jo

of total area contribution for both the basins. The morphometric analysis included longitudinal profile generation, hypsometric curve, and hypsometric integral analysis to understand channel morphometry sediment generation potential, and basin evolution stages. Finally, sediment connectivity and stream power analyses were carried out to demonstrate the

variability in sediment transport characteristics. In this work, MATLAB toolbox and TopoToolbox 2 (Schwanghart and Scherler, 2014) were used for estimating and plotting different parameters. ArcGIS 10.1 was also used for spatial plotting in this work. We have adopted the slope-area method for stream network analysis (Hastings and Kampf, 2014; Avcioglu et al., 2017). The discontinuities in the slope-area curve were used to demarcate the stream heads and to assess the channel initiation threshold

ro of

for UGB and UKB. Subsequently, the extracted stream network was assigned stream order (So) following Strahler (1964) and then used to compute the

morphometric indices such as drainage density (Dd), bifurcation ratio (Rb) and

-p

stream frequency (Sf).

re

To assess the longitudinal profile of the UGB and the UKB, the longest stream channel was mapped using D8 flow direction and flow accumulation analysis.

lP

Subsequently, the length from the basin outlet and individual pixels elevation was used to plot the channel profile for all sub-basins of the UGB and the UKB. To

ur na

compare longitudinal profiles and assess the channel percentage length for different topographic slope, normalized length and elevation were assessed and displayed in respective plots for both the basin. Further, stream concavity index (SCI) was used to estimate the difference in area between the actual long profile and assumed

Jo

triangular profile (Radoane et al., 2003). Hypsometric curve (HC) and hypsometric integral (HI) have been considered as a measure of elevation distributions of landforms and to understand process-form relationships (Strahler, 1952; Schumm, 1956; Willgoose and Hancock, 1998). The HC is typically plotted between normalized elevation and percentage contributing

area. The percentage of basin area above a certain elevation threshold can be identified using this curve (Strahler, 1952). To compare basin characteristics and geomorphic response, HI was estimated by taking integral (trapezoidal are calculation) for each sub-basin (Keller and Pinter, 1996). The shapes of HC and corresponding HI values were used to classify diverse erosional stages and sediment dynamics in the basin. Sediment connectivity analysis was carried out using the index initially defined by

follows:

Dup W Sk √Ak ) = log10 ( ) di Ddn ∑i=k,nk Wi Si

-p

ICk = log10 (

ro of

Borselli et al. (2008) and modified by Cavalli et al. (2013). This index is defined as

(1)

re

ICk is sediment connectivity index (dimensionless) at the particular cell; k is cell

lP

number; Dup is upslope component; Ddn is downslope component; W is an average weight factor (usually considered as C-factor of RUSLE equation, dimensionless) of

ur na

the upslope contributing area; Sk is average slope (in m/m) of the upslope contributing area at particular cell (k); Ak is upslope contributing area (in m2) at cell (k); nk is the total number of the cell in the basin; di is length of ith cell along the flow path (in m); Wi is weight (C factor) at ith cell (dimensionless); Si is the slope (in m/m)

Jo

at ith cell.

Two components of the modified index of connectivity (Cavalli et al., 2013), are (a) ICchannel, where the target gets defined initially (such as main river channel) for the upslope contributing area, and (b) ICoutlet where the target is set at the catchment outlet. ICchannel represents hill-slope to channel sediment connectivity whereas ICoutlet

represents the channel to outlet sediment connectivity. Mishra et al. (2019) analyzed the sediment connectivity of the UKB using a C-factor map generated from land use land cover for the year 1990 based on re-classification of Landsat TM and ETM+ dataset. For this work, we have used, 90m SRTM DEM for topography and the classified map of C factor (RUSLE; Wischmeier and Smith, 1978; Swarnkar et al., 2018) generated from land-use & land-cover (LULC) maps of the year 2000 for the UGB and UKB. The C factors for an individual cell are obtained from the published

ro of

reference tables (Morgan, 2009; FAO, 1978) for a range of land use and agricultural practices.

Further, the stream power index (SPI), Eq. 2 has been used to evaluate the

-p

impedance of sediment conveyance from the hill slope to channel and total energy

re

stored in the system. SPI = ln(Ak tan(Sk ))

(2)

lP

This index is directly related to the upslope contributing area (as a proxy of

ur na

discharge) and topography steepness (Fontana and Marchi, 2003). 4. Results and analysis

4.1. Hydro-meteorological analysis

Jo

Analysis of the globally available rainfall dataset suggests that the spatial average annual rainfall ranges from 488 to 2310 mm for the UGB and from 189 to 2675 mm for the UKB (Fig. 2a & 2b). This results in the basin average rainfall of 1400 mm and 845 mm for UGB and UKB respectively (Table 2). However, the UGB is dominated by 1500-2000 mm of rainfall (42.6 % of the area) (Fig. 2c & 2d) in contrast to the UKB where 57% of the area receives less than 500 mm of rainfall and only 15.7% falls in the 1500-2000 mm zone. High cumulative rainfall during the monsoon period

are observed for Su, Ar and Tm sub-basins in the UKB (~1500 mm) compared to the Al and Bg sub-basins in the UGB (~ 900 mm) (Fig. 3a & 3b). Further, intra-basin comparison for the UGB suggests that the average annual rainfall in the Lb is higher (~1750 mm) followed by the Al (~1400 mm) and the Bg (~1250 mm) (Fig. 3c). In the UKB, except Tibet (350 mm), all three sub-basins (Su, Ar and Tm) have higher average annual rainfall values (1700-1800 mm) than the Al and the Bg (1250-1400 mm) of the UGB (Fig. 3c). Also, except Tibet (Tb), all other sub-basins (Su, Ar and

ro of

Tm) in the UKB show similar monthly variations throughout the year. The windward side average annual rainfall in the UKB is also higher (1750 mm) compared to that of the UGB (1500 mm; Fig. 3c). We argue therefore that rainfall-induced erosivity of the

-p

UKB is higher compared to the UGB.

re

4.2. Stream network analysis

Our results of stream network analysis suggest that the channel initiation threshold

lP

of the UGB (10 km2) is half of that of the UKB (20 km2) indicating a denser river network for the UGB compared to UKB. Strahler’s stream ordering suggests that a

ur na

6th order stream network is present in both the river basins (Fig. 4a & 4b). Drainage density (Dd) results also suggest comparatively higher values (0.21 km/km2) for the UGB compared to the UKB (0.16 km/km2) (Fig. 4c; Table 3). In the UGB, the lower sub-basin (Lb) has the highest Dd (0.23 km/km2) followed by Bg (0.21 km/km2) and

Jo

Al sub-basin (0.21 km/km2) (Fig. 4c; Table 3). In the UKB, the Tibetan sub-basin has the highest Dd (0.18 km/km2) followed by Ar (0.16 km/km2), Su (0.15 km/km2) and Tm sub-basin (0.15 km/km2). Similarly, the stream frequency data depict higher values in the UGB (Sf > 0.03 km-2) compared to the UKB (Sf > 0.015 km-2) (Fig. 4d; Table 3). This suggests that channel

processes are dominating over the hillslope processes in the UGB in contrast to the UKB which is largely dominated by hillslope processes. Further, the Bg and Al subbasins in the UGB and Su and Tm in the UKB have relatively higher values of bifurcation ratio (Rb) (4 – 4.5; Fig. 4e; Table 3). The lower sub-basin (Lb) of the UGB, and Ar and Tb sub-basins of the UKB show relatively low Rb (< 4). It has been suggested that the basins with bifurcation ratio ranging from 3 to 5 do not show any influence of tectonics (Strahler, 1964), and therefore, we interpret that the

ro of

variabilities in the bifurcation ratios are primarily controlled by modern geomorphic processes. 4.3. Longitudinal profile analysis

-p

Generally, the upper reaches of a river are dominated by incision processes and

re

sediment deposition occurs in the lower reaches. Under equilibrium conditions, the longitudinal profile is most gentle near the outlet and steepest near the channel

lP

heads, known as concave upward profile (Yatsu, 1955). In the UGB, the Bg and Al sub-basins show concave upward profile, and nearly equal longitudinal slope (Fig.

ur na

5a). Both river profiles satisfy the equilibrium condition which can be explained by the power-law between the local channel slope and the upslope contributing area (Flint, 1974). Flint’s equation considers the systematic declination of channel slope towards the outlet which can also be defined as a stable graded profile of the river

Jo

channel (Snow and Slingerland, 1987; Radoane et al., 2003; Roy and Sinha, 2018). In contrast, the Su, Tm, and Tb sub-basins of the UKB do not manifest the equilibrium condition (power-law) and exhibit over-steepened channel in the upstream and nearly flat channel in the downstream reaches (Fig. 5b). Nevertheless, the Ar sub-basin of the UKB follows the equilibrium condition. In the equilibrium condition, incision and uplift rates are in balance, and the longitudinal river profile

can be written as a power function between the drainage area and the local channel slope (Hack, 1973; Flint, 1974). However, in the river basins with higher differential uplift rate e.g. Su and Tm in the UKB (Snyder et al., 2000), over steepening of the river profiles in the upper reaches are more common. Such basins exhibit unstable or ungraded longitudinal profiles where incision and uplift rates are not in balance (Snyder et al., 2000; Tyagi et al., 2009). A longitudinal profile measure such as the stream concavity index (SCI) index shows

ro of

the eroded portion of the channel between the real profile and assumed original line profile joining source to mouth (Roy and Sinha, 2018). This analysis compares all

stream profiles in the normalized distance and normalized elevation domains. The

-p

SCI results for the UGB suggest that Bg has a relatively higher graded longitudinal

re

profile than Ar as manifested in lower SCI values (Bg: 0.19; Ar: 0.25) (Fig. 5c & 5e; Table 3). Relatively low SCI suggests that sediment production and transport

lP

processes balance each other, and these streams behave like a supply-limited system. On the other hand, the western (Su) and eastern (Tm) sub-basins in the

ur na

UKB show relatively higher SCI (> 0.27), and 40% of the upstream stream profile shows a very steep slope. However, the remaining 60% of the stream in the downstream of Su and Tm shows an almost flat gradient (Fig. 5d & 5e; Table 3). This suggests that the overall profiles of both the basins can be classified as weakly

Jo

graded, and particularly the downstream reaches can be characterized as a transport-limited system. Due to comparatively low SCI (0.25), the Ar sub-basin in the UKB shows relatively graded profile than other streams; 70% of the upstream reaches are steep and remaining 30% of the downstream reaches are flat (Fig. 5d & 5e; Table 3). Hence, the Ar sub-basin behaves more like a supply-limited system. The Tibetan sub-basin (Tb) shows the highest SCI value (0.3), and longitudinal

profiles of the streams in this region are mostly flat (Fig. 5b, 5d, and 5e). Hence, sediment transport potential from the Tibetan sub-basin is significantly low. 4.4. Hypsometric curve analysis Assuming the basin outlet as the local base level, the hypsometric curve between area and elevation suggests a total of 70,000 km3 and 200,000 km3 of geomorphic volume in the UGB and the UKB, respectively (Fig. 6a). Thus, the UKB has roughly

ro of

three times more volume than the UGB. Further, the hypsometry curve (HC) and hypsometric integral (HI) were used to evaluate the geomorphic evolution and sediment dynamics of the basins.

-p

We observe a slightly higher value of HI for the UKB (0.42) compared to the UGB (0.39) (Fig. 6b). Our HC results further show that 60% of the upstream part of the

re

UKB is covered with very uniform topography (except the areas covered with mountain peaks). The remaining 40% of the downstream region in the UKB is

lP

characterized by steep topography and therefore has a higher potential to generate sediments (Fig. 6b). However, the UGB is covered throughout with mild steep

ur na

topography. In terms of sediment dynamics, Bg sub-basin in the UGB has a higher potential to generate sediments and this suggests a significantly higher erosion potential than Al sub-basin in the east (Fig. 6c & 6e; Table 3). Due to the lowest HI

Jo

and concave-up profile of HC, the Lb sub-basin of the UGB would produce the lowest sediment flux if the upstream sediment contribution is not counted (Fig. 6b & 6e; Table 3). Likewise, in the UKB, the western (Su) and eastern (Tm) sub-basins show similar HI values (0.33) and throughout steep elevation profiles suggest a higher potential to generate sediment compared to the other two sub-basins (Fig. 6d & 6e; Table 3). However, in the Ar sub-basin, 60% of the area in the upstream shows

a gentle slope and the remaining 40% of the downstream reaches are characterized as the steep gradient. This suggests that the downstream region can transport sediment to the outlet more efficiently and most of the sediments originating from upstream are trapped midway. Except for a few high-elevation reaches, the Tibetan region (Tb sub-basin) shows a very gentle slope suggesting that the sediment source region is far away from the outlet, and hence sediment production and transport are relatively very low. Overall, the Al and Bg in the UGB (covering ~

ro of

18,000 km2 of area) and Su and Tm in the UKB (covering ~ 24,000 km2 of area) can be interpreted as the most efficient sub-basins to produce and transport sediments. 4.5. Sediment connectivity and stream power index analysis

-p

Sediment connectivity was estimated using outlet connectivity index (ICoutlet) and

re

hillslope-channel connectivity (ICchannel) for both the basins. Our ICoutlet results for the UGB suggest high values (> -5) in the most upstream part whereas the middle and

lP

lower parts show low values (> -9) (Fig. 7a). The downstream part of the UGB shows fairly low values of ICoutlet, which means that the sediment source region and the

ur na

outlet are not well connected for efficient sediment transport. In contrast, moderate (8 to -5) and high values (> -5) of ICoutlet in the most downstream region in the UKB (Fig. 7b) suggest that the channel is well connected to the outlet. The upstream reaches in the UKB do not show a good connection with the outlet and

Jo

predominately show very low ICoutlet values. Further, the intra-basin comparison suggests that the Al and Bg sub-basins of the UGB have relatively higher median ICoutlet value (-9.5) compared to the lower sub-basin (Lb, -9.87). This suggests that the upstream sub-basins in the UGB are slightly better connected with the outlet than the lower sub-basin, and hence sediment transfer will be more efficient in these subbasins.

In the UKB, the Su (-9.43), Tm (-9.51) and Ar (-9.59) sub-basins show similar median values of ICoutlet (Fig. 7c; Table 4). Thus, the relative connection with the basin outlet for effective sediment transfer is comparable for these three sub-basins in the UKB. Mishra et al. (2019) also showed similar values of ICoutlet with Arun showing the low values due to poorly developed channel sections and low slopes. We also note pockets of high ICoutlet values in Arun and Tamor which is in slight contrast to the work by Mishra et al. (2019) that used LULC data for 1990. It seems

ro of

therefore that there are perceptible changes in sediment connectivity close to the outlet between 1990 and 2000. In this work, the Tibetan sub-basin (Tb) has been

analyzed separately which shows low median ICoutlet values (-9.96) (Fig. 7c; Table 4)

-p

suggesting comparatively lower connectivity with the sub-basin outlet. This has been

low sediment transport efficiency.

re

attributed to U-shaped valleys and low slope (Mishra et al., 2019) and hence a very

lP

In the UGB, high ICchannel values (> -3.5) appear in the most upstream region of eastern (Al) and western (Bg) sub-basins, similar to ICoutlet. High ICchannel (>-3.5)

ur na

values near the tributaries suggest efficient and well-connected hillslopes to channel (Fig. 8a). However, the trunk channel in the UGB exhibits moderate to low ICchannel (> -3.6) and hence poor connectivity with hillslopes. Low ICchannel close to the trunk channel suggests less efficiency to transport sediments, and therefore, most of the

Jo

sediments gets deposited within the channel or close to the confluences with the tributaries.

In the upstream and downstream reaches of the UKB, higher ICchannel values (> -4.6) are observed near the tributaries and main river channel (Fig. 8b) compared to the middle region that shows low (< -8) to moderate (-8 to -4.7) values. High slopes in the upstream part and patches of agricultural lands on the lower slope in the

downstream part contribute to high ICchannel values (Mishra et al., 2019). Overall, the UKB has significantly high connectivity between hillslopes and channels, and the main river channel is also well connected to the outlet to provide efficient sediment pathways (Fig. 8b). A few isolated patches of high ICchannel are observed in the Tibetan part of the UKB because of grassland and patches of barren areas as also documented by Mishra et al., (2019) but they do not connect to the outlet as manifested in the low ICoutlet values, and therefore, there is no substantial sediment

ro of

transfer from these regions. Further, the intra-basin comparison suggests high median values of ICchannel in the Al (-5.45) and Bg (-5.24) in the UGB due to patches of high values in the far upstream

-p

region (Fig. 8c). However, the lower sub-basin (Lb, -6.76) shows a relatively lower

re

median value of ICchannel because of highly disconnected terrain with the channels. In the UKB, the median values of the ICchannel for different sub-basins vary in a small

lP

range (-6.6 to - 6.19).

Further, the stream power index (SPI) has been used to assess sediment transport

ur na

potential. In the UGB, high (> 7) to moderate (5 - 7) SPIs are observed in the upstream region (Fig. 9a), which facilitates higher sediment transport rate from hillslopes to channel and from channel to basin outlet. However, the SPI reduces substantially (< 5) in the downstream stretches of the UGB which decreases the

Jo

sediment transport capacity and encourages deposition. In the UKB, most of the middle and lower regions show high (> 7) to moderate (5 – 7) SPI values, which suggest relatively higher transport capacity to move sediments downstream (Fig. 9b). In the Tibetan region of the UKB, SPI is rather low (< 5) near the channel due to wide and flat valleys. High SPI values (> 7) are observed near the hills due to high elevation in the Tibetan region. Further, the intra-basin comparison of SPI shows that

Al (5.66) and Bg (5.54) have higher median values than Lb (5.09) in the UGB (Fig. 9c; Table 4), and therefore, these sub-basins (Al and Bg) have a higher potential to transport sediments. However, lower values of SPI in the lower basin influence the overall sediment transport process and encourages the deposition of most of the sediments in this stretch. In the UKB, Su (5.49) and Ar (5.49) sub-basins have relatively similar median values of SPI but and Tm (5.61) has a slightly higher value suggesting a relatively higher sediment transport potential. However, the Tb sub-

ro of

basin shows a relatively lower SPI median (4.67), and this suggests that the sediment transport potential of Tb is lower than the other sub-basins of the UKB. 5. Discussion

-p

5.1. Hydro-climatic controls on hinterland erosion and sediment flux

re

The Indian summer monsoon is strongly influenced by the tectonically-derived topography of the Himalaya (Olen et al., 2016). Notably, rainfall in the south-facing

lP

slopes of the Himalayan basins such as the UGB and the UKB are particularly influenced (Bhatt and Nakamura, 2005) and the strong rainfall is induced by the

ur na

orographic barriers (Bookhagen and Burbank, 2010). Our hydroclimatic analysis suggests that monsoonal rainfall occurs mostly in two months (Jul and Aug) in the hinterland of the UGB. In contrast, the UKB experiences high rainfall amount

Jo

throughout the monsoonal period (Jun-Sep; Fig. 3a & 3b). This is attributed to the fact that the hinterlands of the UGB (west) and the UKB (east) fall in different monsoonal depressions namely, the Arabian Sea and the Bay of Bengal respectively (Nandargi and Dhar, 2011). Our rainfall analysis supports this observation and suggests that all upstream sediment producing sub-basins (Al and Bg) of the UGB receive most of the annual rainfall during monsoonal months (~ 70%; 900-950 mm).

However, the longer duration of the monsoon period in the UKB (May-September) produces relatively higher annual rainfall (1750 mm) that produces higher rainfall erosivity and soil erosion compared to the UGB. It is also evident that the effective catchment areas for sediment production and mobilization for both the basins are almost equal. The effective or windward side catchment area is estimated by subtracting rain shadow or leeward side areas from the total basin. We note that less than 0.01% of total basin area can be categorised

ro of

as leeward side areas in the UGB, and therefore, the total basin area (21660 km2)

for the UGB is classified as effective or windward side catchment area. In contrast,

only 22,674 km2 out of the total basin area of 52,730 km2 is the effective catchment

-p

area for the UGB. A larger area covered by very high magnitude rainfall ranges

re

(2000-2500 mm; Fig. 2d) and higher cumulative rainfall during the monsoon in the UKB compared to the UGB differentiates the overall sediment production and

lP

transport characteristics. In the UGB, extratropical disturbance, also called western disturbance, produces the high magnitude events in the winter rainfall months (Nov-

ur na

Mar; Mani, 1981; Sikka, 1999). This meteorological condition originates from the Mediterranean and Caspian Sea and diminishes by the time it reaches central and eastern Himalaya. In the east, monsoonal depression or low-pressure areas from the Bay of Bengal causes heavy to very heavy rainfall events. Additionally, the

Jo

accentuation of the eastern end of the seasonal monsoon trough enhances the monsoonal duration in the eastern region (Nandargi and Dhar, 2011). Therefore, the eastern basin (UKB) receives higher rainfall during the monsoon periods compared to the western basin (UGB).

5.2. Hydro-geomorphic response of the basin Noticeable differences in the morphometry of stream network of the UGB and the UKB are manifested as variations in Dd, Sf, and Br that eventually determine the hydro-geomorphic response of the individual basins. The Dd is directly related to several hydrological processes i.e. infiltration, soil saturation, sheet erosion, overland

ro of

flow, and the interactions among these, and therefore to the production of runoff and sediment load in the basin (Moglen et al., 1998). Usually, a higher Dd value of a

basin suggests higher potential to generate runoff that in turn increases the sediment transport potential. Gardiner (1995) showed that Dd is largely associated with the

-p

underlying impermeable rocks and is inversely proportional to hydraulic conductivity.

re

Further, a higher Dd is also suggestive of low infiltration due to impermeable rocks and sparse vegetation (Gardiner, 1995; Verstappen, 1983; Ozdemir and Bird, 2009).

lP

Thus, most of the sub-basins in the UGB show a high probability to generate runoff due to comparatively higher Dd compared to the UKB. However, the windward side

ur na

average annual rainfall, as well as sediment production, in the UGB is lower than that in the UKB, and therefore, this morphometric factor does not translate into a higher discharge or higher sediment delivery.

Jo

Sediment connectivity analysis further suggests relatively lower ICoutlet and longitudinal profile and the hypsometric analysis indicates relatively stable hinterland in the UGB in terms of sediment production and dynamics. Hence, the UGB can be characterized as a supply-limited basin. On the other hand, higher erosion potential, high ICoutlet and ICchannel, unstable hinterland topography and over-steepened longitudinal channel profile suggest a much higher degree of sediment dynamics in

the UKB dominated by hillslope processes. Therefore, the UKB can be characterized as a transport-limited basin. 5.3. Influence of longitudinal profile and basin hypsometry on erosional and sediment transport processes The higher uplift rate in the hinterland of the UKB compared to that of the UGB has been documented in earlier studies (Peltzer and Saucier, 1996; Bilham et al., 1997;

ro of

Wesnousky et al., 1999). As a result, the over-steepened channel longitudinal profile is very common in the upstream reaches of the UKB and this increases the efficiency of sediment transport from the upstream sediment source region. It has also been documented that higher annual rainfall and uplift rate in the eastern Himalayas

-p

produce higher sediment load compared to the western Himalayas as a result of

re

elevated physical and chemical weathering (Galy and France-Lanord, 2001). A major part of the sediment load originated from the upstream areas gets deposited at the

lP

toe of the over-steepened channel due to major topographic or slope break. In the monsoon period and particularly during high magnitude rainfall events,

ur na

hydrological and sediment connectivity increases, and these temporary sediment storages get remobilized and move downstream towards the basin outlet. Our HC analysis further suggests that ~60% of the upstream topography (i.e. Tibetan region)

Jo

in the UKB has mild slopes and the remaining 40% of topography (i.e. Higher Himalaya and Siwaliks) is characterized by steep slopes. Also, the Tibetan region receives very low rainfall (< 500 mm) and has several rain shadow zones resulting in relatively low sediment production. However, the Higher Himalaya and Siwalik regions fall in the high rainfall zone that substantially increases the sediment generation potential and efficiency of sediment transport. On the other hand, the

UGB is characterized by the relatively lower order of erosion rate, stable longitudinal profile and low rainfall. The topography of the UGB is mostly covered by mild slope; a few knick points are present but no major break in slope is observed. Further, the downstream stretches of Al and Bg, around 50 km from the outlet, channels become relatively flat and hence the sediment transport capacity is substantially reduced. A basin with higher HI depicts an early phase of erosion cycle where diffusive mass wasting is more predominant and channels are surrounded by steep valleys. For

ro of

basins with high values of HI, the toe of the hypsometric curve (HC) is more

pronounced, which reflects higher elevation differences and high erosion potential in the downstream reaches. Hence, eroded sediments travel a shorter distance to the

-p

outlet and produce high sediment yield (Verstraeten et al., 2001). However, the

re

basins with lower HI values exhibit an enhanced phase of erosion cycle and are dominated by channel processes. Additionally, the head in the HC is a more

lP

distinguishable feature for the lower HI, which means that the elevated sediment source regions are located far away from the outlet. High sediment deposition and

ur na

low sediment yield are common in such basins (Verstraeten et al., 2001). Therefore, higher values of HI in a river basin suggest a higher potential to produce specific sediment yield (SSY) and vice versa. Our HC analysis further suggests that the western sub-basin (Bg) in the UGB has a comparatively higher sediment generation

Jo

and transport potential compared to the rest of the basin. However, a large intervention situated in the middle of the basin, the Tehri dam (see Fig. 1b), plays a significant role and traps most of the sediments originated from the upstream region. On the contrary, there is no storage structure present in the western sub-basin (Al) of the UGB, and therefore, this sub-basin transfers most of the sediments to the lower sub-basin (Lb). However, the topography of the Lb is relatively flat with wide valleys

near the channel. Hence, the majority of sediment flux from Al gets deposited and this reduces the sediment delivery at the outlet of the UGB. Therefore, a cascading sub-basin assemblage and presence of the man-made structure in the UGB increases the probability of intermediate deposition and reduces the sediment yield at the outlet. 5.4. Effect of sediment connectivity and stream power on sediment dynamics

ro of

Hitherto, it has been shown that the sediment dynamics of the UGB and the UKB basins are influenced by variability in hydro-climate and differences in hydro-

geomorphic response. Sediment connectivity and stream power analysis further

-p

validate our observations for both the basins.

Integrating the results of sediment connectivity, hydro-climatic and morphometric

re

analyses, it is evident that the ICoutlet in most parts of the UKB, except for the Tibetan region, is moderate to high where annual rainfall is also high and the terrain is steep.

lP

However, low ICoutlet decreases the contribution from the Tibetan region and parts of Higher Himalaya of the UKB. To demonstrate the combined effect of inhomogeneity

ur na

in sediment connectivity and stream power on sediment transport potential, spatial results obtained from ICoutlet, ICchannel and SPI analysis are added and classified into five categories of sediment transport potential for both the basins (Fig. 10a & 10b).

Jo

This analysis is based on the fact that sediment connectivity and stream power are equally important for the efficient conveyance of sediment flux to the lower elevation regions. Our analysis suggests that the downstream reaches of the UKB have high to very high potential to move sediments (Fig. 10b). These results reaffirm that a major part of the sediment flux of the UKB is derived from the Higher and Lesser Himalayan region whereas the Tibetan and parts of the Higher Himalayan region in

the basin usually store sediments near slope breaks and transport it only during high magnitude flood events. Further, the distance between the source region and basin outlet is less, which means high specific sediment yield (SSY) is very common in this basin. Convincingly, Mishra et al. (2019) and Sinha et al. (2019) have also observed similar trends of sediment connectivity and sediment yield in the UKB. On the other hand, high ICoutlet and ICchannel are observed in most of the upstream reaches in the UGB, but annual rainfall is moderately low, the topography is steep

ro of

and the uplift rate is low. Hence, the sediment generation potential of this basin is relatively low. The downstream region of the UGB shows low ICoutlet and ICchannel, which means that most of the sediments derived from upstream reaches get

-p

deposited in the channel or near the toe of hillslopes; this significantly reduces the

re

sediment delivery or SSY from this basin. Sediment connectivity, as well as sediment transport potential, further decrease due to the presence of hydraulic interventions

lP

such as the Tehri dam. Our combined map of sediment connectivity and stream power index further suggests that sediment transport potential is moderate in both

ur na

the upstream sub-basins (Al and Bg; Fig. 10a) in the UGB. However, the lower subbasin (Lb) has very low sediment transport potential and most of the material does not reach the basin outlet and gets deposited in between. Therefore, the production and conveyance of sediment flux from the UGB are lower compared to the UKB due

Jo

to weak channel-to-outlet (ICoutlet) and hillslopes-to-channel connectivity (ICchannel). 5.5. Implications for sediment management

The Ganga river and its tributaries are well known for producing and transporting a large amount of sediment load annually. To manage excess sediments from the Ganga basin, knowledge of different hydro-geomorphic processes and their

relationship with the produced sediment load is an essential step. An efficient sediment management framework requires (a) identification of hotspots sediment generation and deposition, (b) quantification of sediment fluxes, (c) mitigation strategies for reducing sediment flux, and (d) utilization plan for excess sediments (Sinha, 2018). In this study, we identify the major source of sediment production and transport (Fig. 10) governed by different hydro-geomorphic processes in the hinterlands of the basins located in the eastern and western parts of the Himalayan

ro of

foreland. For instance, the UGB behaves as a supply-limited basin due to sedimentation in the reservoirs which results in storage loss and thereby loss of

serviceable life of the reservoirs. Therefore, a systematic and recurrent bathymetric

-p

survey of reservoirs is an essential step for dredging excess sediment load from the reservoirs. Though dams and reservoirs are built to lower the risk of flood in the

re

downstream region, the local population may be exposed to the larger risks of

lP

siltation and bank erosion due to downstream encroachment of the floodplains. Hence, monitoring the downstream ‘river space’ encroachment is also an important

ur na

measure for the river basin sediment management. Further, this study demonstrates that the UKB behaves as a transport-limited river system, where depositional processes dominate. Therefore, the strategic dredging of sediments from the river channel may be necessary to increase water holding

Jo

capacity and lower the flood risks. The dredging or de-siltation in the river channel should be done carefully to avoid any disturbance in the hydro-geomorphic regime and loss of riverine biodiversity. Further, flow control structures such as embankments, weirs, and barrages should be planned and constructed in such a way that lateral sediment connectivity between channel and floodplain is not broken. Lateral sediment connectivity maintains the fertility of floodplains and lowers the risk

of floods. Moreover, estimation of soil erosion and sediment load by using the modeling framework presented here helps us to identify the major sediment generation regions and to understand the spatial inhomogeneities in soil erosion and sediment load and their causal factors. Modeled soil erosion rates and sediment load vales would be essential inputs for quantifying sediment balance and understanding the overall sediment dynamics of the river basin. Likewise, it would be a significant step towards sustainable sediment management if we not only educate the local

ro of

community about the consequences of soil erosion and excess sediment load, but also encourage them to use excess silt for agricultural and other purposes. 6. Conclusions

-p

The geomorphic diversity of the eastern and western parts of the Himalayan foreland

re

has been addressed using different hydro-geomorphic indicators i.e. rainfall variability, channel morphometry, basin hypsometry, sediment connectivity, and

lP

stream power index. Significant differences are noted between the two representative basins, the UGB and UKB, and these are manifested in variable

ur na

sediment dynamics. Our analysis suggests that the windward side of the UKB receives higher annual rainfall (1750 mm) compared to that of the UGB (1500 mm), which produces higher rainfall erosivity in the UKB. Since the rain shadow regions cover a very large area in the UKB (57%) compared to the UGB (0.01%), the

Jo

effective sediment contributing area from the remaining 43% region in the UKB (~ 22,674 km2) that receives > 500 mm of rainfall annually is similar to that of the UGB (~ 21,660 km2).

Further, the hinterland of the UGB shows higher values for Dd and Sf than that of the UKB, and this suggests that channel processes dominate over hillslope processes in

the UGB. However, it has been also observed that the stream network in the UGB does not show much influence of tectonics due to relatively low Rb (< 5). Channels in the UGB and the UKB show graded and weakly-graded longitudinal profiles, respectively. Disequilibrium between uplift and incision rates are more evident in channel profiles of the UKB than the UGB. Therefore, the UGB and the UKB represent supply-limited and transport-limited systems, respectively. Also, high values of sediment connectivity, both ICoutlet and ICchannel, increase the

ro of

SSY in the UKB and most of this is derived from the Higher and Lesser Himalaya whereas the Tibetan region is relatively passive in terms of sediment dynamics.

Sediment connectivity in the upstream region of the UGB is also high but sediments

-p

are not mobilized efficiently due to lower rainfall compared to the UKB. In the lower

re

reaches of the UGB, sediment connectivity reduces substantially leading to limited sediment mobilization and extensive deposition. Besides, the presence of a major

deposition.

ur na

7. Acknowledgments

lP

hydraulic structure in the UGB further increases sediment dis-connectivity and

The first author acknowledges the Ph.D. studentship from IIT Kanpur. We are thankful for the critical comments from two anonymous reviewers and the guest

Jo

editor, Edgardo Latrubesse, which helped to make this paper much sharper and insightful. This paper was finalized while one of the authors (RS) was visiting the IPG, Paris during his sabbatical and this support is thankfully acknowledged.

References Abbas, N., & Subramanian, V., 1984. Erosion and sediment transport in the Ganges river basin (India). Journal of Hydrology, 69(1-4), 173-182. Avcioglu, B., Anderson, C. J., & Kalin, L., 2017. Evaluating the Slope‐Area Method to Accurately Identify Stream Channel Heads in Three Physiographic Regions. JAWRA Journal of the American Water Resources Association, 53(3), 562-575.

ro of

Bandara, C. M., 1974. Drainage density and effective precipitation. Journal of Hydrology, 21(2), 187-190.

Bertrand, M., Liébault, F., & Piégay, H., 2013. Debris-flow susceptibility of upland catchments. Natural Hazards, 67(2), 497-511.

-p

Bilham, R., Larson, K., & Freymueller, J., 1997. GPS measurements of present-day

re

convergence across the Nepal Himalaya. Nature, 386(6620), 61. Borselli, L., Cassi, P., & Torri, D., 2008. Prolegomena to sediment and flow connectivity in the landscape: a GIS and field numerical assessment. Catena, 75(3),

lP

268-277.

Bookhagen, B., & Burbank, D. W., 2010. Toward a complete Himalayan hydrological

ur na

budget: Spatiotemporal distribution of snowmelt and rainfall and their impact on river discharge. Journal of Geophysical Research: Earth Surface, 115(F3). Bhatt, B. C., & Nakamura, K., 2005. Characteristics of monsoon rainfall around the Himalayas revealed by TRMM precipitation radar. Monthly Weather Review, 133(1),

Jo

149-165.

Cavalli, M., Trevisani, S., Comiti, F., & Marchi, L., 2013. Geomorphometric assessment of spatial sediment connectivity in small Alpine catchments. Geomorphology, 188, 31-41. Chakrapani, G. J., & Saini, R. K., 2009. Temporal and spatial variations in water discharge and sediment load in the Alaknanda and Bhagirathi Rivers in Himalaya, India. Journal of Asian Earth Sciences, 35(6), 545-553.

Clarke, J. I., 1966. Morphometry from maps. Essays in geomorphology, 252, 235274. Cotton, C. A., 1964. The control of drainage density. New Zealand Journal of Geology and Geophysics, 7(2), 348-352. De Scally, F. A., Owens, I. F., & Louis, J., 2010. Controls on fan depositional processes in the schist ranges of the Southern Alps, New Zealand, and implications for debris-flow hazard assessment. Geomorphology, 122(1-2), 99-116. Defourny, P., Bontemps, S., Martin, B., Brockman, C., Fomferra, N., Grit, K., Kruger,

ro of

O., 2011. CCI land cover project – product specification document, version 1.2. www.esa-landcover-cci.org.

FAO, 1978. Methodology for assessing soil degradation, Report on the FAO/UNEP expert consultation, Rome, 25–27.

Water Resources Research, 10(5), 969-973.

-p

Flint, J. J., 1974. Stream gradient as a function of order, magnitude, and discharge.

re

Fontana, G. D., & Marchi, L., 2003. Slope–area relationships and sediment dynamics

lP

in two alpine streams. Hydrological Processes, 17(1), 73-87. Galy, A., & France-Lanord, C., 2001. Higher erosion rates in the Himalaya: Geochemical constraints on riverine fluxes. Geology, 29(1), 23-26.

ur na

Gansser, A., 1964. Geology of the Himalaya. Wiley-Interscience, New York. Gardiner, V., 1995. Channel networks: progress in the study of spatial and temporal variations of drainage density. Changing river channels, 65-85. Gibling, M. R., Tandon, S. K., Sinha, R., & Jain, M., 2005. Discontinuity-bounded

Jo

alluvial sequences of the southern Gangetic Plains, India: aggradation and degradation in response to monsoonal strength. Journal of Sedimentary Research, 75(3), 369-385.

Gregory, K. J., & Walling, D. E., 1968. The variation of drainage density within a catchment. Hydrological Sciences Journal, 13(2), 61-68. Hack, J. T., 1973. Stream-profile analysis and stream-gradient index. Journal of Research of the US Geological Survey, 1(4), 421-429.

Hassan, M. A., Church, M., Xu, J., & Yan, Y., 2008. Spatial and temporal variation of sediment yield in the landscape: Example of Huanghe (Yellow River). Geophysical Research Letters, 35(6). Hastings, B. E., & Kampf, S. K., 2014. Evaluation of digital channel network derivation methods in a glaciated subalpine catchment. Earth Surface Processes and Landforms, 39(13), 1790-1802. Holeman, J. N., 1968. The sediment yield of major rivers of the world. Water resources research, 4(4), 737-747.

ro of

Horton, R. E., 1932. Drainage‐basin characteristics. Eos, transactions american geophysical union, 13(1), 350-361.

Horton, R. E., 1945. Erosional development of streams and their drainage basins;

hydrophysical approach to quantitative morphology. Geological society of America

-p

bulletin, 56(3), 275-370.

Islam, M. R., Begum, S. F., Yamaguchi, Y., & Ogawa, K., 1999. The Ganges and

re

Brahmaputra rivers in Bangladesh: basin denudation and sedimentation. Hydrological Processes, 13(17), 2907-2923.

lP

Jain, V., & Tandon, S. K., 2010. Conceptual assessment of (dis) connectivity and its application to the Ganga River dispersal system. Geomorphology, 118(3-4), 349-

ur na

358.

Keller, E. A., & Pinter, N., 1996. Active tectonics (Vol. 19). Upper Saddle River, NJ: Prentice Hall.

Lane, L. J., Hernandez, M., & Nichols, M., 1997. Processes controlling sediment yield from watersheds as functions of spatial scale. Environmental Modelling &

Jo

Software, 12(4), 355-369.

Lin, Z., & Oguchi, T., 2004. Drainage density, slope angle, and relative basin position in Japanese bare lands from high-resolution DEMs. Geomorphology, 63(3-4), 159173. Lu, X., & Higgitt, D. L., 1999. Sediment yield variability in the Upper Yangtze, China. Earth Surface Processes and Landforms: The Journal of the British Geomorphological Research Group, 24(12), 1077-1093.

Ludwig, W., & Probst, J. L., 1998. River sediment discharge to the oceans; presentday controls and global budgets. American Journal of Science, 298(4), 265-295. Mani, A., 1981. The climate of the Himalaya. The Himalaya: aspects of changes, 315. Melton, M. A., 1965. The geomorphic and paleoclimatic significance of alluvial deposits in southern Arizona. The Journal of Geology, 73(1), 1-38. Milliman, J. D., & Syvitski, J. P., 1992. Geomorphic/tectonic control of sediment discharge to the ocean: the importance of small mountainous rivers. The Journal of

ro of

Geology, 100(5), 525-544. Mishra, K., Sinha, R., Jain, V., Nepal, S., & Uddin, K., 2019. Towards the

assessment of sediment connectivity in a large Himalayan river basin. Science of The Total Environment, 661, 251-265.

-p

Moglen, G. E., Eltahir, E. A., & Bras, R. L., 1998. On the sensitivity of drainage density to climate change. Water Resources Research, 34(4), 855-862.

re

Morgan, R. P. C., 2009. Soil erosion and conservation, John Wiley and Sons.

lP

Nandargi, S., & Dhar, O. N., 2011. Extreme rainfall events over the Himalayas between 1871 and 2007. Hydrological sciences journal, 56(6), 930-945. Oguchi, T., 1997. Drainage density and relative relief in humid steep mountains with

ur na

frequent slope failure. Earth Surface Processes and Landforms: The Journal of the British Geomorphological Group, 22(2), 107-120. Olen, S. M., Bookhagen, B., & Strecker, M. R., 2016. Role of climate and vegetation density in modulating denudation rates in the Himalaya. Earth and Planetary Science

Jo

Letters, 445, 57-67.

Ozdemir, H., & Bird, D., 2009. Evaluation of morphometric parameters of drainage networks derived from topographic maps and DEM in point of floods. Environmental geology, 56(7), 1405-1415. Peltzer, G., & Saucier, F., 1996. Present‐day kinematics of Asia derived from geologic fault rates. Journal of Geophysical Research: Solid Earth, 101(B12), 2794327956.

Radoane, M., Rãdoane, N., & Dumitriu, D., 2003. Geomorphological evolution of longitudinal river profiles in the Carpathians. Geomorphology, 50(4), 293-306. Roy, N. G., & Sinha, R., 2017. Linking hydrology and sediment dynamics of large alluvial rivers to landscape diversity in the Ganga dispersal system, India. Earth Surface Processes and Landforms, 42(7), 1078-1091. Roy, N. G., & Sinha, R., 2018. Integrating channel form and processes in the Gangetic plains rivers: Implications for geomorphic diversity. Geomorphology, 302, 46-61.

ro of

Santangelo, N., Daunis‐i‐Estadella, J., Di Crescenzo, G., Di Donato, V., Faillace, P. I., Martín‐Fernández, J. A., Romano, P., Santo, A., and Scorpio, V., 2012.

Topographic predictors of susceptibility to alluvial fan flooding, Southern Apennines. Earth surface processes and landforms, 37(8), 803-817.

-p

Schumm, S. A., 1956. Evolution of drainage systems and slopes in badlands at

Perth Amboy, New Jersey. Geological society of America bulletin, 67(5), 597-646.

re

Schwanghart, W., & Scherler, D., 2014. TopoToolbox 2–MATLAB-based software for topographic analysis and modeling in Earth surface sciences. Earth Surface

lP

Dynamics, 2(1), 1-7.

Sikka, D. R., 1999. Influence of Himalayas and snow cover on the weather and

ur na

climate of India-A review. The Himalayan Environment, 37-52. Sinha, R., 2018. Sediment management of the Himalayan rivers: a challenge for river managers (Editorial). Current Science, 115 (3), 367-368. Sinha, R., Jain, V., Babu, G. P., & Ghosh, S., 2005. Geomorphic characterization and diversity of the fluvial systems of the Gangetic Plains. Geomorphology, 70(3-4),

Jo

207-225.

Sinha, R., Bhattacharjee, P., Sangode, S.J., Gibling, M.R. and Tandon, S.K., Jain, M. Godfrey, D. (2007). Valley and interfluve sediments in the southern Ganga plains, India: exploring facies and magnetic signatures. Sedimentary Geology, 201, 386411.

Sinha, R., Mohanta, H., Jain, V., & Tandon, S. K., 2017. Geomorphic diversity as a river management tool and its application to the Ganga River, India. River Research and Applications, 33(7), 1156-1176. Sinha, R., Gupta, A., Mishra, K., Tripathi, S., Nepal, S., Wahid, S. M., & Swarnkar, S., 2019. Basin-scale hydrology and sediment dynamics of the Kosi River in the Himalayan foreland. Journal of Hydrology. Snow, R. S., & Slingerland, R. L., 1987. Mathematical modeling of graded river profiles. The journal of geology, 95(1), 15-33.

ro of

Snyder, N. P., Whipple, K. X., Tucker, G. E., & Merritts, D. J., 2000. Landscape response to tectonic forcing: Digital elevation model analysis of stream profiles in the Mendocino triple junction region, northern California. Geological Society of America Bulletin, 112(8), 1250-1263.

-p

Strahler, A. N., 1952. Hypsometric (area-altitude) analysis of erosional topography. Geological Society of America Bulletin, 63(11), 1117-1142.

re

Strahler, A. N., 1964. Quantitative geomorphology of drainage basins and channel network. Handbook of Applied Hydrology, 4-76.

lP

Subramanian, V., 1996. The sediment load of Indian rivers-an update. IAHS Publications-Series of Proceedings and Reports-Intern Assoc Hydrological Sciences,

ur na

236, 183-190.

Summerfield, M. A., & Hulton, N. J., 1994. Natural controls of fluvial denudation rates in major world drainage basins. Journal of Geophysical Research: Solid Earth, 99(B7), 13871-13883.

Swarnkar, S., Malini, A., Tripathi, S., & Sinha, R., 2018. Assessment of uncertainties

Jo

in soil erosion and sediment yield estimates at ungauged basins: an application to the Garra River basin, India. Hydrology and Earth System Sciences, 22(4), 24712485.

Syvitski, J. P., Vörösmarty, C. J., Kettner, A. J., & Green, P., 2005. Impact of humans on the flux of terrestrial sediment to the global coastal ocean. science, 308(5720), 376-380.

Thomas, J., Joseph, S., Thrivikramji, K. P., Abe, G., & Kannan, N., 2012. Morphometrical analysis of two tropical mountain river basins of contrasting environmental settings, the southern Western Ghats, India. Environmental Earth Sciences, 66(8), 2353-2366. Tyagi, A. K., Chaudhary, S., Rana, N., Sati, S. P., & Juyal, N., 2009. Identifying areas of differential uplift using steepness index in the Alaknanda basin, Garhwal Himalaya, Uttarakhand. Current Science, 1473-1477. Vanoni, V. A., 1975. Sedimentation engineering, ASCE manuals and reports on

ro of

engineering practice—No. 54. American Society of Civil Engineers, New York, NY. Verstappen H. Th., 1983. Applied geomorphology. ITC, Enschede.

Verstraeten, G., & Poesen, J., 2001. Factors controlling sediment yield from small intensively cultivated catchments in a temperate humid climate. Geomorphology,

-p

40(1-2), 123-144.

209-237.

re

Walling, D. E., 1983. The sediment delivery problem. Journal of hydrology, 65(1-3),

Wasson, R. J., 2003. A sediment budget for the Ganga–Brahmaputra catchment.

lP

Current science, 1041-1047.

Wesnousky, S. G., Kumar, S., Mohindra, R., & Thakur, V. C., 1999. Uplift and

ur na

convergence along the Himalayan Frontal Thrust of India. Tectonics, 18(6), 967-976. Willgoose, G., & Hancock, G., 1998. Revisiting the hypsometric curve as an indicator of form and process in transport‐limited catchment. Earth Surface Processes and Landforms: The Journal of the British Geomorphological Group, 23(7), 611-623.

Jo

Wischmeier, W. H., & Smith, D. D., 1978. Predicting rainfall erosion losses. Agricultural Handbook no. 537, US Department of Agriculture. Science and Education Administration, 1978. Yang, H., & Shi, C., 2017. Basin form characteristics, causes and implications of the ten kongduis in the upper reaches of the Yellow River. Quaternary International, 453, 15-23.

Yatsu, E., 1955. On the longitudinal profile of a graded river. EoS Trsns, AGU 35,

Jo

ur na

lP

re

-p

ro of

655-663.

FIGURE CAPTIONS Figure 1. Map of India showing the location of the hinterland of the upper Ganga basin (UGB) and the Kosi basin (Kb). Elevation and stream network maps are shown for the hinterland of (b) the UGB and (c) the KB. Important cities, gauge and dam

Jo

ur na

lP

re

-p

ro of

locations are also shown in both the maps.

Figure 2. Spatial distribution of average annual rainfall for (a) the UGB and (b) the UKB. The areal distribution of average annual rainfall is shown by (c) cumulative area curve and by (d) bar plot.

ro of -p re

lP

Figure 3. Intra-basin average monthly rainfall variations for (a) the UGB and (b) the UKB. Each sub-basins and whole basin average annual rainfall values are plotted in

Jo

ur na

(c) bar graph. The average values for the whole basins are represented with ‘W’.

ro of -p re lP

Figure 4. Stream order (Strahler, 1964) maps for (a) the UGB and (b) the UKB. Bar plots of (c) drainage density, (d) stream frequency and (e) bifurcation ratio are shown

Jo

ur na

for all the sub-basins and the whole (W) basin.

ro of -p re lP

Figure 5. Channel longitudinal profiles for (a) the UGB and (b) the UKB. Stream concavity profiles are shown for different sub-basins for (c) the UGB, and (d) the

Jo

ur na

UKB. The sub-basins stream concavity index comparison is shown in (e).

ro of -p re

Figure 6. (a) Elevation and cumulative area plots for the UGB and the UKB. Hypsometric comparisons between (b) the UGB & the UKB, (c) sub-basins of the

lP

UGB and (d) sub-basins of the UKB are shown. Inter-basins and intra-basins comparison of hypsometric integrals are shown (e). The ‘W’ represents the

Jo

ur na

hypsometric integral for the whole basin.

ro of -p re

Figure 7. The ICoutlet maps for (a) the UGB and (b) the UKB. The white patches are glaciers. The distributions of ICoutlet for each sub-basin and whole basin are shown

lP

by the box and whisker plot (c). Upper and lower whisker represent 95% and 5% confidence interval, respectively. The body of the box and whisker plots represents

Jo

ur na

50% distribution of the data. The red line inside the box represents the median value.

ro of -p re

Figure 8. The ICchannel maps for (a) the UGB and (b) the UKB are shown. The white patches are glaciers. The distributions of ICchannel for each sub-basin and whole basin

Jo

ur na

lP

are shown by the box and whisker plots (c).

ro of -p re

Figure 9. Stream power index (SPI) maps for (a) the UGB and (b) the UKB. The

Jo

ur na

whisker plots (c).

lP

distribution of SPI for each sub-basin and whole basin is shown by the box and

ro of -p re

Jo

ur na

white patches are glaciers.

lP

Figure 10. Sediment transport potential maps for (a) the UGB and (b) the UKB. The

ro of

-p

re

lP

ur na

Jo

Table 1 Input dataset used in present study

Sr. No.

Input Data

Name & Agency

Reference

1

Digital Elevation Model (DEM)

SRTM (Shuttle Radar Topography Mission)

2

Land use and land cover

European Satellite Agency (ESA)

300 m spatial resolution; year 2000

Defourny et al. (2011)

3

Annual average rainfall

WorldClim

30’ spatial resolution; spatial average data for period 1970 - 2000; version 2

Fick and Hijmans (2017)

Jarvis et al. (2008)

ro of

Specifications 90 m spatial resolution; year 2001; database version 4.1

Table 2 Basin characteristics of the upper Ganga basin (UGB) and the upper Kosi basin (UKB) UGB 21,660 km2 (up to Haridwar)

Basin geology

Tethyan sediments, Higher Himalayan crystalline, Lesser Himalayan (Siwaliks) sedimentary lithologies

Major tributaries Av. Annual discharge at outlet

Bhagirathi, Alaknanda

Average sediment yield Landcover

845 mm

Indrawati, Bhote Kosi, Tama Kosi, Dudh Kosi, Sun Kosi, Arun, and Tamor

850 cumecs

1545 cumecs

14 x 106 tons

101 x 106 tons

ur na

Average annual suspended sediment load

1400 mm

3796 m

re

Basin average rainfall

3148 m

lP

Mean elevation

UKB 52,730 km2 (upto Chatara)

-p

Characteristics Basin area

646 t/y/km2

1915 t/y/km2

Forest (20.5%), agricultural land (66.4%), urban (2.1%), water (5.2%), grasslands (5.3%)

Forest (41.0 %), agricultural land (41%), urban (0.6%), water (7.7%), grasslands (25.2%)

Based on Gansser (1964); Subramaniam (1993); Sinha et al. (2005); Defourny et al. (2011); Sinha et

Jo

al. (2019).

Bg

Al

Lb

W

Upper Kosi Basin (UKB) Su

Ar

Tm

2963

21660 18160 11525 6054

16991 52730 area in the UKB

4.13

4.16

3.77

3.77

4.16

3.58

3.61

3.87

0.210

0.209

0.230 0.212

0.151

re

Drainage Density

0.160 0.149

0.179

0.164

Dd (km/km2)

0.034

0.034

0.036 0.034

0.017

0.018 0.019

0.020

0.019

Integral (HI)

0.46

0.40

0.36

0.39

0.32

0.42

0.31

0.19

0.42

Stream Concavity Index (SCI)

0.183

0.243

___

___

0.265

0.152 0.260

0.300

___

ur n

Stream Frequency

4.49

-p

11050

al P

(Rb)

Hypsometric

W

7647

Bifurcation Ratio

Sf (km )

Inferences

Alaknanda is the largest basin in UGB and Tibetan part occupies the largest

Area (km2)

-2

Tb

ro

Upper Ganga Basin (UGB)

Parameter

of

Table 3 Morphometric parameters comparision for the hinterland sub-basins of the upper Ganga basin (UGB) and the upper Kosi basin (UKB)

No strong geological control in any of the basins High and quick runoff in UGB compared to UKB; will result in higher steam power and therefore incision Dominance of channel processes in UGB in contrast to hillslope processes in UKB Higher potential of sediment production in UKB compared to UGB

Jo

Note: Bg – Bhagirathi, Al – Alaknanda, Lb- Lower basin of UGB; Su- Sapta Kosi, Ar – Arun, Tm - Tamor, Tb - Tibetan part of UKB; W- Whole basi

Table 4 Mean and standard deviation of outlet conectivity (ICoutlet), channel connectivity (ICchannel) and stream power index (SPI) for individual hinterland sub-basins of the upper Ganga basin (UGB) and the upper Kosi basin (UKB).

Channel Connectivity

Stream Power Index

(ICoutlet)

(ICchannel)

(SPI)

µ

σ

media

n

Alaknanda

Ganga

(Al)

basin

Lower basin

(UGB)

(Lb) Whole basin (W) Sun Kosi (Su) Arun Kosi (Ar)

Upper Kosi basin

-9.28

-9.48

-9.34

-9.87

-9.54

-9.56

-9.37

-9.43

-9.32

-9.59

-9.19

Tamor (Tm)

-9.51

-9.28

Tibet (Tb)

-9.96

-9.73

ur na

(UKB)

Whole basin

-3.70

-5.06

2.12

-3.63

-5.14

2.18

-5.69

-6.41

1.98

-3.87

-5.29

9 1.1 4 1.0 3 1.1 1 1.1

1.0

1.1

-9.75

-9.38

2

0.9 3

1.0

48

5.59

1.26

1.26

5.09

5.17

1.19

2.18

5.53

5.58

1.26

1.91

5.49

5.53

1.29

-5.94

1.79

5.49

5.51

1.28

-5.35

-6.26

1.95

5.61

5.66

1.25

-5.39

-6.08

1.56

4.67

4.46

1.67

-6.10

1.76

5.23

5.15

1.53

-5.31

5

5.54

5.69

-5.13

3

σ

5.66

-5.29

0

Jo

(W)

1.0

µ

-p

Upper

-9.51

medi an

-6.17

re

(Bg)

n

lP

Bhagirathi

σ

µ

of

media

ro

Sub-basin Name

Outlet Connectivity