A proposed method of bank erosion vulnerability zonation and its application on the River Haora, Tripura, India

Geomorphology 224 (2014) 111–121

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A proposed method of bank erosion vulnerability zonation and its application on the River Haora, Tripura, India Shreya Bandyopadhyay a, Kapil Ghosh a, Sunil Kumar De b,⁎ a b

Department of Geography and Disaster Management, Tripura University, Suryamaninagar 799022, Tripura, India Department of Geography, North Eastern Hill University (NEHU), Shillong, Meghalaya 793022, India

a r t i c l e

i n f o

Article history: Received 20 February 2014 Received in revised form 27 June 2014 Accepted 10 July 2014 Available online 18 July 2014 Keywords: Bank erosion Bank erosion hazard index (BEHI) Near bank stress (NBS) Erosivity River gradient Bank erosion vulnerability zonation

a b s t r a c t In this paper a new RS-GIS based simple method has been proposed for estimating bank erosion. This method does not need intense field investigation and can provide erosion vulnerability zonation for the entire river. The method uses eight parameters, i.e., rainfall erosivity, lithological factor, bank slope, meander index, river gradient, soil erosivity, vegetation cover, and anthropogenic impact. Meteorological data, GSI maps, SRTM DEM (30-m horizontal resolution), LISS III (23.5-m resolution), and Google Images have been used to determine rain erosivity, lithological impact, bank slope, meander index, river gradient, vegetation cover, and anthropogenic activities. Soil map of the NBSSLP (National Bureau of Soil Survey and Land-use Planning, India) has been used for assessing soil erosivity index. By integrating the individual values of those six parameters out of those eight parameters (the first two parameters remained constant for the particular study area), a bank erosion vulnerability zonation map of the River Haora, Tripura, India (23°37′–23°53′ N. and 91°15′–91°37′ E.) has been prepared. The values have been compared with the existing BEHI-NBS method of 60 spots and also with field data of 30 cross sections (covering the 60 spots) taken along a 51-km stretch of the river within Indian Territory, and we found that the estimated values are matching with the existing method as well as with field data. The whole stretch has been divided into five hazard zones, i.e. very high, high, moderate, low and very low hazard zones; and they are cover 5.66, 16.81, 40.82, 29.67, and 9.04 km, respectively. © 2014 Elsevier B.V. All rights reserved.

1. Introduction Bank degradation is the result of a process that combines the erosive power of water (Bentrup and Hoag, 1998) and the effect of gravity. In addition, channel enlargement, bank instability, degradation of physical habitat, and numerous other geomorphic responses accelerate the process of bank erosion (Hammer, 1972; Arnold et al., 1982; Booth, 1990; Booth and Henshaw, 2001; Jacobson et al., 2001). Bank erosion is a severe problem to any fluvial system as it can generate up to 90% of the total sediment yield from a catchment (Olley et al., 1993; Prosser and Winchester, 1996; Wallbrink et al., 1998; Wasson et al., 1998). It is also considered a hazard because it causes loss of lives and properties. The Haora River, which is the lifeline of the Agartala City of Tripura, India, experiences severe bank erosion in several parts of its course. Prediction of the location and the extent of river bank erosion continues to be difficult despite the testing of a range of approaches and methods (Sandra and David, 2000). Several worldwide methods exist

⁎ Corresponding author. Tel.: +91 364 2723205; fax: +91 364 2550076. E-mail address: [email protected] (S.K. De).

http://dx.doi.org/10.1016/j.geomorph.2014.07.018 0169-555X/© 2014 Elsevier B.V. All rights reserved.

for estimating bank erosion. Among them, some of the well known and widely used methods are mentioned in Table 1. Most of these methods (Table 1) are either extensively field based or require highly advanced technology (PEEP method, test of a method to calculate near-bank velocity and boundary shear stress etc.). Moreover, these methods are unable to produce a zonation map for the entire stretch of any river. Other GIS-based methods, where prediction can be done from open source satellite images (Klaassen and Vermeer, 1988; Bhakal et al., 2005; Das and Saraf, 2007; Kummu et al., 2008; Sarkar et al., 2012), are applicable for the large rivers only. Therefore high resolution satellite images (which are very expensive) are necessary for the prediction of bank erosion of a small river (like the River Haora, having a length of 61.2 km). As a result, bank erosion of small rivers is poorly understood and thus poorly integrated into management strategy (Wang et al., 1997). Thus, the main objective of this paper is to propose a new GIS-based method for preparing zonation maps of bank erosion. This zonation has been done by considering eight parameters: i.e., (i) rainfall erosivity, (ii) lithological factors, (iii) slope of the river bank, (iv) meander index of each curve of the river, (v) river gradient (longitudinal), (vi) soil erodibility factor of the bank, (vii) vegetation cover of the bank, and (viii) anthropogenic factors present along and across the river. The main

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Table 1 Summary and method of different existing models for estimating bank erosion. Model

Methods

References

Graft

Erosion probability could be determined for any given cell by taking into account its distance laterally in the upstream direction to the active river channel, and a value representing flood magnitudes for the given period Superimposing the river banks of different time periods together and measuring the gap between them. BE = 0.016Q0.60 1.58 where BE is the bank erosion rate in metres of recession per year, and Q1.58 is the discharge (m3/s) of the 1.58-year recurrence interval flood event, assumed to represent bank-full discharge Quasi-continuous data on the magnitude, frequency and timing of the individual erosion and deposition on the river banks Subsurface bank erosion has been investigated for vertical banks by considering a sandy erodible layer overlaid by a clayey one under uniformly distributed constant overhead pressure Using erosion pins to large-scale studies using aerial photos and maps Investigating bed-deformation and bank line shifting in 2D planform in a moving boundary fitted-coordinate system, and a new formulation of nonequilibrium sediment transport is introduced to reproduce the channel processes. BEHI evaluates properties of stream banks related to stability; NBS evaluates channel flow conditions and how they affect bank stability. Together, BEHI and NBS are utilized as independent variables in a series of regression equations that predict annual lateral bank retreat.

Graft (1984), Sandra and David (2000)

Bank shifting Bank erosion

Photo Electronic Erosion Pin (PEEP) Experiment

Bank material strength Numerical analysis

Bank Erosion Hazard Index (BEHI) and Near Bank Stress (NBS)

advantage of this method is that all parameters can be estimated from secondary data, maps and images, and require less field investigation. 2. Regional setting Haora River is one of the major rivers of the West Tripura District. It originates from the western flank of the Baramura Range and flows through the Sadar subdivision of Tripura to meet with the Titas River in Bangladesh (located between the latitudes of 23°37′ N. and 23°53′ N. and between longitudes of 91°15′ E. and 91°37′ E.) (Fig. 1). The river flows west and drains at basin areas of 457.97 km2 (SOI Topographical Maps, 1932). The total length of the river is 61.2 km, in which 52 km is flowing within the Indian Territory. The proposed method has been applied only on the Indian part of the Haora River (marked as AB in Fig. 1). The river is primarily rain fed, and a major part of the river is flowing through the alluvial soil belt, which is prone to erosion. 3. Materials and method The 1932 Survey of India (SOI) topographical maps and 2009 Google images have been used for the demarcation of the Haora River basin and the present flow path of the river. Rainfall data has been collected from the Meteorological Department, Tripura. Several secondary maps, including soil and lithological maps, have been collected from the National Bureau of Soil Survey and Land Use Planning (NBSSLP) and from the Geological Survey of India, respectively. River slope gradient has been measured from a 30-m horizontal resolution SRTM digital elevation model (DEM). Meander curve, vegetation cover, and other parameters of the bank have been measured from the 2005 LISS III satellite image and from 2009 Google images. 3.1. Zonation mapping of bank erosion vulnerability For the preparation of bank erosion vulnerability zonation of the Haora River, 15 m on either side of the water's edge are considered as active bank zones. This demarcation has been done on the basis of maximum extension of bank erosion that can be noticed within the entire stretch, and it will be different from river to river.

Gilvear and Winterbottom (1992), Gilvear et al. (1994, 1999), Gilvear and Winterbottom (1998) Rutherfurd (2000), Prosser et al. (2001)

Lawler (1991, 1992a,b), Lawler and Leeks (1992), Lawler (1993a,b), Lawler et al. (1997) Imanshoar et al. (2012)

Thorne (1981) Nagata et al. (2000)

Rosgen (1996, 1999, 2001a,b), Nieber et al. (2008)

3.1.1. Rain erosivity (R) factor Soil erosion is closely related to rainfall through the combined effect of detachment by raindrops striking the soil surface and by the runoff (Mkhonta, 2000). Therefore, the following formula (Eq. (1)) has been used for estimating annual and seasonal R factors that was developed by Singh et al. (1981) in Indian context. Annual R−factor Ra ¼ 79 þ 0:363  P

ð1Þ

where, P = annual rainfall in mm. Risk of bank instability is found to be higher in the rainy days having high rainfall intensity with a number of lean days before because during lean periods the moisture of soils is drying up (Thorne et al., 1998). As a result of that, the cohesive power of soil is getting reduced. Any sudden rainfall with relatively higher intensity is leading the banks prone to erosion. For the calculation of rainfall erosivity, the following equation has been introduced: Ra  Rainfall erosivity R ¼

n X ðLd  Ri Þ k¼0

Rd

ð2Þ

where Ra = annual R factor in mm; Ld = number of lean days (a maximum 20-day limit has been considered within which soil can be dried up) before a rainy day (days are considered as rainy days when there is at least 10 mm of rainfall) (Bhattacharyya, 1993), Ri = rainfall amount of that particular day (if rainfall occurs continuously for several days, the average amount of those days should be considered); Rd = total number of rainy days in a year. In the case of the Haora River basin, there is only one rain gauge station for which the rainfall erosivity factor for the whole basin remains constant. 3.1.2. Lithological factor Lithological factor is also considered as an important factor because the materials along the river banks determine the resistivity of it (Twidale, 2004). Thus, the bank material along the river up to the

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Fig. 1. Location map of the study area. Blue lines show the cross sections along the Haora River for the measurement of erosion in the BEHI-NBS method and in field data. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

maximum water level should be mapped and then categorised on the basis of their resistivity. In case of the selected study area, the entire river is flowing through an alluvial region. Thus, the lithological factor also remains constant for the Haora River. 3.1.3. Slope of the river bank A positive correlation exists between bank instability and the slope factor. The greater the slope means the greater the risk of bank erosion. Thus for the proposed method slope factor of the banks has been estimated from the following formula (Eq. (3), Table 2): Slope factor S ¼ Sa  Sh

ð3Þ

where, Sa = slope angle of the banks and Sh = height of bank. Slope angle and bank height have been estimated from Google and from the DEM. For the estimation of slope, both banks of the river have been split out into smaller stretches based on visual interpretation. The horizontal distance from the water's edge up to the top of the bank has been measured, and an elevation profile from the river to the bank has been generated for the individual stretch from the Google image (Fig. 2A). For better accuracy, the profiles are georeferenced in metres in a GIS platform. In some stretches where no variations have been found, the horizontal distance line from water's edge up to the top of the bank (drawn from the Google image) has been superimposed onto a DEM to detect the altitudinal variation. The horizontal distance and the altitudinal

variation have been used for detecting slope value of an individual stretch. Still some stretches remained where the altitudinal variation could not be found. Those stretches have been considered as gentle, as all the depositional bank stretches (visible in Google) have been categorised as very gentle slope (Fig. 2B). After estimating slope factor of both banks of the Haora River, the values have been categorised (Table 2) into six groups, and a bank slope zonation map of the river has been prepared accordingly (Fig. 2). 3.1.4. Meander index (MI) Meandering curvatures of the river course have a great impact on bank erosion. In a straight-path river, water flows straight; but in a meander course, water hits the concave bank that generates shear stress. More acuteness of the bank curvature promotes more shear stress and thereby causes more erosion. The meandering index of each curvature of the Haora River has been estimated from the Google images by using the following formula: MI ¼

ACB AB

ð4Þ

where ACB = mender length of each curve, and AB = axial length. The values obtained from this equation have been assigned to the concave side of each meander only. All the convex sides have been considered as the depositional side, and hence a constant (0.5) value has been assigned (Fig. 3A, B).

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Table 2 Index value of six parameters for estimating BEVZ method. Category Type River bank slope

Slope (deg) Height (m) No. of Patches Length (km)

Meander ratio

No. of Patches Length (km)

River gradient (tanQ)

No. of patches Length (km)

Type

Type

Type Soil erosivity

Erosivity No. of patches Length (km) Type

Vegetation (%) Anthropogenic impacts

No. of patches Length (km) No. of patches Length (km)

1

2

3

4

5

6

Very gentle

Gentle

Moderate

Steep

Very steep

Cliff

11–20 0.21–0.5 46 20.82

21–40 0.51–1.5 76 36.62

41–55 1.51–2.5 44 21.76

56–70 2.51–4 16 7.8

N70 N4 6 3

Straight 1.51–1.10

Moderate 1.51–1.70

Meander 1.71–2.30

Acute meander N2.30

44 18.66

82 36.66

b10 0.2 29 12 Convex 0.5 122 36.56 Very gentle 0.01–0.7 15 5.3 Fine loamy Typic Epiquepts 0.16 4 11.2 Barren b10 9 0.6 48 44.75

Gentle 0.71–1.30

Moderate 1.31–2.1

46 17.88

48 20.44

Fine loamy Typic Dystrochrepts

Fine loamy Typic Udorthents

0.29 2 2

0.35 1 2.98

Highly sparse 10–20

Sparse 21–35

43 2.4 68 18.42

61 19.44 64 28.25

3.1.5. Longitudinal river gradient The term longitudinal gradient of a river means the steepness of the river bed. More river gradient implies more kinetic energy and more erosive power of the river. Change in minor gradient can have a large impact on bank erosion (Mertes and Dunne, 2007; Frings, 2008; Ashworth and Lewin, 2012). For estimating the longitudinal gradient of the river for the bank erosion vulnerability Zonation (BEVZ) method, the entire course of the Haora River has been divided into 500-m grid cells. Then the distance and the vertical height between the uppermost and lowermost points of the river within each particular grid have been

19 8.02

5 2.1 Very steep N3.81

Steep 2.11–3.8 8 3.1

11 4.28

Fine Typic Dystrochrepts

Coarse Loamy Typic Udorthents

0.36 1 8.98

0.54 5 76.84

Moderate 36–60

Dense 61–80

50 41.74 12 5.94

29 23.6 5 4.64

Highly dense N80 14.22

measured. The longitudinal gradient of the river has been estimated by using the following formula (Fig. 4A, B) −1

Longitudinal gradient ðϕiÞ ¼ tan

ABi CBi

ð5Þ

where ϕi = slope of the river in an individual cell, ABi = relative relief between the highest, and the lowest point of the cell, and CBi = the distance between these two points. River gradient has been estimated from an SRTM DEM with 30-m horizontal resolution. After estimating

Fig. 2. Classified bank slope map of the Haora River with the graph showing the total lengths of banks under different categories. (A) and (B) show the procedure of measuring the bank slope. [1], [2], and [3] show some parts of the river in large scale.

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Fig. 3. Classified meander index map of the Haora River with the graph showing the lengths of banks in different categories. (A) and (B) show the technique of measuring the meander value from the Google images. [1], [2], and [3] show some parts of the river in large scale.

the river gradient of individual cells, the values have been categorised into five types (Fig. 4) ranging from very gentle to very steep (Table 2).

Smith, 1978) for preparing the final soil erosivity map. Soil erodibility has been divided into five categories (Table 2).

3.1.6. Soil erosivity factor Depending on the varying resistance power of the soil, the stability of the bank varies accordingly. The type and the amount of sedimentation also depend on it (Maroulis and Nanson, 1996; Grabowski et al., 2011). The resistivity of soil depends on its texture, structure, rate of permeability, and organic matter content. For estimating soil erosivity, a soil taxonomy map (Fig. 5A) of the Haora River basin has been prepared based on the National Bureau of Soil Survey and Land-Use Planning (NSSLUP) map. After preparing the taxonomy map, the texture (sand, slit, clay), structure, organic matter, and permeability of all the soils (collected from the technical bulletins on soil series of Tripura and from the laboratory tests of soil samples) found along the Haora River course have been plotted into Nomo-graph (Wischmeier and

3.1.7. Vegetation cover Vegetation coverage along the banks has a great impact on protecting bank erosion by influencing channel adjustment and migration (Thorne, 1990; Dunaway et al., 1994; Friedman et al., 1998; Brooks, 1999). Root coverage within the soil reduces the rate of runoff and thus reduces erosion (Abernethy and Rutherfurd, 2000; Prosser et al., 2001). High density of leaves reduce rain splash erosion by restricting the direct contact of rain water with the ground. For the estimation of this parameter for the BEVZ method, low height vegetation with high canopy cover has been given more weightage because it is observed that dense scrub, and bushes (with high canopy cover, and high root density) can protect land better than single big trees with high canopy cover (Fig. 6). For estimating vegetation cover, a Normalized Difference

Fig. 4. Longitudinal river gradient map of the Haora River basin with the graph showing the lengths under different categories. (A) and (B) show the basic formula of measuring the gradient value from the DEM or Google images. [1], [2], and [3] show some parts of the river in large scale.

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Fig. 5. (A). Soil Taxonomy map of the Haora River basin. In this map 1 — Laterite, 2 — fine loamy Typic Dystrochrepts/Paleudults, 3 — fine loamy Umbric/Oxic Dystrochrepts, 4 — fine loamy Umbric/Typic Dystrochrepts, 5 — fine loamy Umbric Dystrochrepts, 6 — fine loamy Typic Kandiudults, 7 — fine loamy Typic Dystrochrepts, 8 — fine loamy Typic Epiaquepts, 9 — coarse loamy Typic Dystrochrepts, 10 — fine loamy Typic/over sandy Typic Epiaquepts, 11 — fine loamy Typic Haplumbrepts, 12 — fine Typic Dystrochrepts. (B). Soil erosivity map of the Haora River along with the graph indicating the total bank length in different categorises. [1], [2], and [3] show some parts of the river bank in large scale.

Vegetation Index (NDVI) map has been generated from a LISS III image. All the negative values obtained in NDVI have been considered as barren land. The positive values reflect different vegetation density (Shank, 2008). A canopy height map is also generated from visual interpretation of the Google image, where banks with sparse grass coverage have been assigned low weightage values (Fig. 6A) followed by single tree coverage (Fig. 6B), low density scrub, and bushes. The areas having big trees along with scrubs and bushes are given maximum weightage value (Fig. 6C). All these have been categorised based on canopy shape, size, and colour visualised in the Google image. After the preparation of NDVI, and the canopy height map, they have been merged to generate the final vegetation cover map. After preparing the final vegetation cover, the entire stretch has been divided (Fig. 6) into six categories (Table 2).

3.1.8. Anthropogenic factor An anthropogenic factor is considered as a major factor because during the present era man is a great modifier of landforms and also accelerates the risk of several hazards like stream channel erosion and sedimentation (Leopold, 1968, 1972). Several unscientific constructions such as dams, barrages, bridges, and roads across the river are leading to hydrologic change (Knox, 1977; Fitzpatrick and Knox, 2000) of the river. There is hardly any process of quantitative assessment of an anthropogenic impact found and practised. In the present method, an effort has been made to quantify the impact of anthropogenic activity on the river. The major anthropogenic impacts noticed along and across the river are marked from Google Earth. In the case of the Haora River five major types of anthropogenic activity: i.e. sand quarrying, roads or causeways, brick fields (dumping their waste products along the river

Fig. 6. Vegetation cover map of the Haora River basin with the graph, showing bank length under different categories. (A) and (B) are the pictorial evidence of different types of vegetation cover noticed along the river. [1], [2], and [3] show some parts of the river in large scale.

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bank), heavy and light bridges, and tilla cutting (Fig. 7a, b, c, d, e) are practised along and across the river. All these individual activities noticed along and across the entire stretch of the river have been marked with great care from the Google image. Three or four sample spots of individual activities have been surveyed based on which the remaining parts of the river affected by similar types of activities have been assumed for upstream and downstream segments (Table 3). For instance, there are 24 heavy- and light-weight carrying bridges across the river: four heavy-weight bridges and three light-weight bridges have been surveyed for getting an idea about the remaining affected areas. On the basis of these limits, five layers of multibuffering have been done for all of those individual activities. Then, an overlay map of all the activity buffering map has been prepared from which the final anthropogenic activity map is generated and categorised based on the number of overlapping buffers and the intensity of buffering (for example, if an area consists of two or three individual parametric buffer out of which at least two buffers are of high category, this area shall be considered as highly affected, and have been assigned as category 5; Fig. 7A). After getting all six parameters individually, general weightage values have been assigned to each of them. The main aim of this paper is to propose a generalised method that is applicable to any river. Thus, for weightage distribution, equal weightage have been assigned to all the parameters in round figures, since all of these parameters are largely related to one another. For instance, as there are six active parameters, 15% weightage has been given to each of them. The extra 10% weightage has been equally distributed among bank slope and meander index because these two parameters are assumed to be of higher importance (based on the field survey) in the case of the Haora River (these high weightage parameters may be changed in case of other rivers). Finally all the parameters are superimposed to prepare the final bank erosion vulnerability zonation (BEVZ) mapping (Fig. 8). 3.2. Comparison between proposed (BEVZ) and BEHI-NBS methods For validating the proposed BEVZ method, the result of bank erosion has been compared with another method, namely the Bank Erosion Hazard Index, and Near Bank Stress method (BEHI and NBS). This BEHI-NBS method has been applied before proposing the BEVZ method

117

Table 3 Major types of anthropogenic activity and their limit of effectiveness in river. Type of anthropogenic activity Brick fields Heavy weight bridges Light weight bridges Roads/causeways Sand collection spots Tilla cutoffs along the river

Nos.

9 9 14 8 20 7

Limit of affected area along the river Upstream (km)

Downstream (km)

Actual length of the brick fields 0.2 0.1 0.6 Along the spots Along the spots

1 0.5 0.3 1.5 0.5 Along the spots

on 60 spots (30 spots along the left bank, and 30 spots along the right bank) along the Haora River within its Indian territory. The applicability of this method on the Haora River has been estimated by comparing it with the field from the 30 cross-sectional (covering all 60 spots) data of three consecutive years (Bandyopadhyay et al., 2013). The accuracy level of this method for the Haora River is being estimated as 76.7%. 4. Result and discussion 4.1. Analysis of individual parameters The bank slope map of the study area indicates that the entire bank of the Haora River belongs to the moderate category of slope. Within the 102-km bank length (51 km length of each bank of the Haora River), a total of 36.62 km of bank falls under the moderate category of slope (Fig. 2) possessing 76 spots along the river. The second highest length, i.e., 21.76 km falls under the steep slope followed by the gentle slope, which covers 20.80 km of bank length. Only 10.8 km of bank is considered as very steep or cliff slope, which is restricted to the upper part of the river, particularly in the Champabari and Bhrigudaspara blocks (Fig. 2.1). From this single parameter we found that the risk of bank erosion of the river is considered as of moderate type. In the case of the meander index, more than one-third of the length of the river (36.58 km) is under convex bend (Fig. 3), where erosion is nominal. Excepting this, a total of 36.65 km of bank is considered as

Fig. 7. (A). Multibuffer zonation map of six individual anthropogenic activities, on going along the Haora River. (B). Anthropogenic impact map of the Haora River bank along with the graph showing total lengths in individual parameters. (a–e) are the major human activities: i.e., sand quarrying, road or causeway, brick fields, bridges, and tilla cutting, seen along the river.

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Fig. 8. (A). Final bank erosion vulnerability zonation (BEVZ) mapping along with the graph showing bank lengths in individual categories. (B). Zone wise distribution of BEVZ map.

moderate meander (meander index 1.51–1.7), and 82 meander spots falls under this category. Thus, each meander of this category, having an average of 450 m width, is experiencing a medium risk of erosion. Acute meander covers 2.1 km of the bank of the river, and only five of such meanders are: located in Agartala (Fig. 3.1), Khayerpur (Fig. 3.2), Champabari (Fig. 3.3), and in some other places.

When we consider that all other parameters (except longitudinal river gradient) are constant, river gradient is considered as the triggering factor of river velocity that controls river erosion. Longitudinal slope of the entire Haora River ranges from gentle to moderate. It indicates that rapid change in slope is not abundant along this river and that it also does not possess fluctuating velocity as well as a high risk

S. Bandyopadhyay et al. / Geomorphology 224 (2014) 111–121 Table 4 Comparison of erosional values between the BEHI-NBS and proposed methods. Right bank Profile Left bank no. BEHI Proposed BEHI Proposed 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

H M M M VL L M M M L VH M H M VH

H M L H M M H M M L VH H H M VH

H L H VH H H VH L H VL L H M M M

M L H H H H M L M M M H H M M

Right bank Profile Left bank no. BEHI Proposed BEHI Proposed 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30

H L M M M VH VH L M VL VH M VL L M

M M H M M VH VH L L M L L VL L L

VL M VH H H H M L M H M H VL L M

L H VH M M H M M M H M M L L L

VH = very high, H = high, M = moderate, L = low, and VL = very low. Green colour indicates the spot values where the bank erosion classes in both the methods are exactly matching with each other and the red colour indicates the spots where the bank erosion classes of the aforesaid methods are different.

of erosion. The highest length is found under a moderate gradient having a length of 20.44 km in 48 patches (Fig. 4.1), followed by a gentle gradient, having a length of 17.88 km along the river (46 patches). There are 11 patches covering 4.28 km length of the river that have a steep gradient. Although a steep gradient is mainly noticed at or near the upper catchment (Fig. 4.3), it is also found in a scattered manner throughout the river course (Fig. 4.2). In the case of soil, a maximum area along the Haora River is covered with alluvial soil, taxonomically known as fine loamy Umbric Dystrochrepts (Fig. 5.2). This type of soil covers an extensive length of 76.84 km of the Haora River bank (Fig. 5B) and causes the highest rate of erosion. Other types of soils are noticed in the upper (Fig. 5.3) and lower parts (Fig. 5.1) along the river. On an average, the risk of bank erosion in respect to the soil parameter is quite high along the Haora River as a whole. A moderate type of vegetation covers the greatest length (41.74 km) of the river banks (Fig. 6): 61 patches of this type have been found along the river bank. An average length of 680 m of the banks is continuously covered by this single type of vegetation (Fig. 6.2). Dense vegetation cover is the second highest category that occupies a 23.6-km length of the banks. This is also having an average of a 470-m length under a single patch. Barren vegetation is only noticed in 3 km of the bank along the lower stretch of the river (Fig. 6.1). It means, excepting the upper catchment of the river, that the entire stretch consists of a distinct type of vegetation and can be considered as a great measure for erosion. From the anthropogenic map, a total length of 44.75 km of bank is considered under very less-affected areas, but only 48 patches under this category have been found along the river. It is because an extensive area, particularly in the upper catchment (up to Purba Debendranagar along the river), remains almost unaffected from anthropogenic activities (Fig. 7). In the Champaknagar area, the river banks are considered as moderately to highly affected. 64 patches, covering a length of 28.25 km along the river, that are considered as moderately affected. In the Champaknagar and Jirania blocks (Fig. 7.2), the maximum area falls in the highly to very highly affected zones. The major anthropogenic activities noticed in these two blocks are sand collection, brick fields, bridges, and tilla cutting (Fig. 7A, C–E).

4.2. Analysis of BEVZ map In the final BEVZ map, the maximum area (40.82 km) falls under the moderate vulnerability zone, followed by the highly vulnerable zone that occupies 19.67 km of length along the river banks. Very low erosion zones are found only in the upper catchment and in some parts of the Pratapgarh block (Fig. 8A). For a better understanding, the entire stretch

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of the river has been divided into four zones based on population pressure: (i) Agartala zone, which is mainly marked for heavy growth of market and residential sectors (including the Agartala, Pratapgarh, and Jogendranagar blocks), more than 64% of the river banks fall into the very low to low vulnerable zones. Only one km of bank is under very high vulnerability: this may be because of the conservation measures taken in those areas (Fig. 8B). (ii) Khayerpur area, known for small industries, major bridges, and other constructional purposes (from Khyerpur up to Radhamohonpur), 49% of the banks fall into the moderately vulnerable zone, followed by the highly vulnerable zone covering 33% of the bank length (Fig. 8B). (iii) The highest vulnerable zones fall in the Jirania zone, which is mainly occupied by different industrial sectors (from Jirania-Bamkimnagar to Joynagar); 57% of the total bank length within this area fall into the very high to highly vulnerable category (19% is very high, 38% is highly vulnerable), followed by moderately vulnerable zones occupying 35% of the bank length of the area (Fig. 8B). (iv) Finally, in the Champabari–Brighudaspara zone, which is located in the rugged terrain, 54% of the banks have been considered as very high to highly vulnerable followed by 41% of the length that falls into the moderate zone. Only 5% of the banks in this area are considered as less vulnerable (Fig. 8B). 4.3. Validation of the BEVZ map with BEHI-NBS data After validating the proposed method with BEHI-NBS data for these 60 spots along the Haora River (Bandyopadhyay et al., 2013), we found that the values of both methods match in case of the 31 spots. In the case of 24 spots, values obtained in these two methods are showing a slight difference. But in the case of only five spots the values of both methods are completely different (Table 4). After validating the proposed method with the BEHI-NBS method, three years of cross-sectional data from the field have been taken into consideration for those five spots (marked in red in Table 3) where values are different. From the field data, we found that among those five spots, three spots of the BEHI-NBS values match with field data, and in the remaining two spots the proposed method is correct. Examples of two cross sections are given below. In the case of profile 10, taken at the confluence of the Haora and Donaigang rivers, the BEHI-NBS value along the right bank has been estimated as very low. But in the case of the proposed method, it falls into the moderate erosion zone. Again from the three consecutive years' (2010–2012) cross-profiles, we found that the right bank or the confluence zone is retrogressing (average rate of retrogression is 0.61 m) at a moderate rate (Fig. 9). Thus, we can say that the result in the proposed method is correct for this particular spot. Again in profile 26, which has taken in Pratapgarh (Fig. 10), the value of BEHI-NBS for the left bank has come as very high, but in the proposed method it is estimated as low. So from the cross-profile we found that between the years 2010 and 2011, 0.96 m retrogression has been estimated and in the years 2011–2012 the rate has come down to 0.24 m. The later year rate of erosion is showing less because of dumping of artificial material along the bank, which will be carried down the river very soon. Thus, from the field data it is clear that the BEHI-NBS estimation for this particular spot is better than the proposed one. 5. Conclusion After comparing the proposed method with the BEHI-NBS method and field-generated data, the accuracy level of this method for the Haora River has been estimated as 75% (in 31 spots the values are matching, in half of 22 spots the values are slightly different, and in 2 spots field data match the proposed method). Therefore, the proposed method can be well accepted for preparing the vulnerability zonation of the Haora River in order to take immediate necessary measures for controlling erosion. The method can also be applied to any other small rivers having similar characteristics because of its simplicity and

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Fig. 9. Cross section number 10 where proposed method (BEVZ) matches with field data for the right bank of the river.

Fig. 10. Cross section number 26 where for the left bank the BEHI-NBS method matches with the field data and the proposed method is revealed as in correct.

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