Validation of BEHI Model through Field Generated Data for Assessing Bank Erosion along the River Haora, West Tripura, India

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Open access e-journal Earth Science India, eissn: 0974 8350 Vol. 6 (III), July, 2013, pp. 126-135 http://www.earthscienceindia.info/ Validation of BEHI Model through Field Generated Data for Assessing Bank Erosion along the River Haora, West Tripura, India Shreya Bandyopadhyay, Sushmita Saha, Kapil Ghosh and Sunil Kumar De* Department of Geography and Disaster Management, Tripura University, Suryamaninagar-799022, Tripura, India Email: desunil@yahoo.com *Corresponding author Abstract The objective of the present paper is to validate the Bank Erosion and Hazard Index (BEHI) model for the assessment of bank erosion with the values obtained from the cross sections along the Haora River of Tripura. The BEHI is an empirical bank erosion model, useful for estimating bank erosion of any small river, since it is intensively field based and helps to assess the erosion risk based on several parameters related to the river course. Data of different parameters for 60 spots along both banks of the River Haora within the Indian Territory have been generated for estimating bank erosion through BEHI model. 30 cross sections through such 60 spots have been obtained through field survey for 3 consecutive years and superimposed to estimate the amount of bank erosion empirically. From the comparative study between the values obtained through BEHI model and cross sections of the same places, it is found that the amount of bank erosion is identical for more than 75% cases that proves the applicability of this model in case of the River Haora. Keywords: BEHI Model, bank erosion, erosion risk, cross section Introduction Bank erosion is considered as a severe problem along most of the river banks in India. It claims huge amount of resource and lives throughout the country. A number of methods have so far been introduced throughout the world for estimating the amount of bank erosion and their prediction, but most of the methods are so complex and expensive that it is very much difficult to apply them in the field for estimating such erosion in a country like India. The BEHI (Bank Erosion and Hazard Index) is a popular model proposed by Rosgen (1996) and very much useful for estimating bank erosion risk through bank geometry and material stability (Rosgen,1999) as well as near-bank stresses resulting from flow conditions (Rosgen, 2001a, b). BEHI is helpful for estimating annual bank erosion from a single bank using regression analysis. The model has widely been used for estimating the amount of bank erosion in different regions of the world, such as, North Carolina (Jessup and Harman, 2004) and Arkansas (Van Eps et al., 2004). The Haora River, one of the major rivers of Tripura, originates from the western flank of the Baramura range. It flows through the middle of the Sadar Subdivision of Tripura, and after crossing the Indo Bangladesh border at Akhaura the river meets with the River Titas in Bangladesh. Sadar is the most populated subdivision in Tripura. Agartala, the capital city of

Validation of BEHI Model through field generated data for assessing bank erosion along the River Haora, West Tripura, India: Bandyopadhyay et al. Tripura is situated along the river within this subdivision. Both banks along the entire stretch of the river are densely populated since its debouching point near Chandrasadhubari. Bank erosion along the River Haora is, therefore, considered as a severe problem to the people of this area. In this paper Bank Erosion Hazard Index (BEHI) model has chosen for measuring the bank erosion rate of the River Haora as this model is particularly suitable for small rivers (length of River Haora is about 63 km). Field study has also been carried out in order to compare the applicability of this model for bank erosion estimation of the Haora River. Regional Setting Haora River is one of the major rivers of West Tripura District. It originated from the western flank of Baramura Range and flows through the Sadar Subdivision of Tripura to meet with the Titas River in Bangladesh. From the 1932 Survey of India (SOI) Topographical Map, it is found that the river is west flowing having an area of 457.97 km 2. The total length of the river is 63 km. The latitudinal extension of the river is 37 23 N and 23 53 N and longitudes of 91 15 E and 91 37 E. The river is basically a rain-fed river and a major part of the river is flowing through the alluvial structure which is easily prone to erosion. Fig.1: Location map of the Haora River basin and location of the cross sections. 127

Open access e-journal Earth Science India, eissn: 0974 8350 Vol. 6 (III), July, 2013, pp. 126-135 http://www.earthscienceindia.info/ Materials and Method The SOI topographical maps (1932) have been used to demarcate the basin area of the Haora River. Estimation of Bank Erosion by BEHI model: According to the BEHI model stream bank can be estimated by multiplying erodibility and erosivity. The equation (En. No.1) is: BEHI = E d E r 1 Where, E d = bank erodibility and E r = bank erosivity Bank Erodibility Bank erodibility has been estimated with the help of the following five variables: Bank height ratio Bank height ratio has been measured from the ratio of study height and bank-full height, where, the study height is the height of water level from the bank bottom during lean season and bank-full height is the height of the water level during peak flood period. Root cover It is the percentage area coverage of vegetation. It can be measured form digital images by analysing the vegetation index of it. But for this study the field data has been getting more importance because bushes and grass coverage have more control on bank erosion rather than a big canopy cover. Bank angle Bank angle has been measured from the toe to the top of the bank. The angle of bank angle can vary from very gentle to obtuse angle. Obtuse angle can be found in case of undercut and hanging banks. Surface protection The term surface protection means whether there are any natural or manmade elements which will reduce bank erosion. For the present study proportion of vegetation cover, bank embankment etc. have been considered. Bank material In the original model of BEHI bank material is considered as an important parameter, because it is very much helpful for determining the erosion risk of bank. But in the present study, bank material has been considered as a constant parameter, because the entire path of the river is flowing through alluvial structure.

Validation of BEHI Model through field generated data for assessing bank erosion along the River Haora, West Tripura, India: Bandyopadhyay et al. Table-1: Assigned index value for all the individual parameters to calculate BEHI. Adjective Hazard or risk rating categories Bank height ratio Vegetation Cover (%) Bank Angle(Deg) Surface Protection (% ) Totals VERY LOW Value 1.0-1.1 100-80 0-20 100-80 Index 1.0-1.9 1.0-1.9 1.0-1.9 1.0-1.9 4-7.6 LOW Value 1.11-1.19 79-55 21-60 79-55 Index 2.0-3.9 2.0-3.9 2.0-3.9 2.0-3.9 8-15.6 MODERATE Value 1.2-1.5 54-30 61-80 54-30 Index 4.0-5.9 4.0-5.9 4.0-5.9 4.0-5.9 16-23.6 MODERATE Value 1.6-2.0 29-15 81-90 29-15 Index 6.0-7.9 6.0-7.9 6.0-7.9 6.0-7.9 24-31.6 VERY HIGH Value 2.1-3.0 14-5 91-119 14-10 Index 8.0-9.0 8.0-9.0 8.0-9.0 8.0-9.0 32-36 EXTREME Value >3 <5 >119 <10 Index 10 10 10 10 40 Bank Erosivity of Near Bank Stress Bank erosivity or near bank stress can be estimated on the basis of the following parameters: i) Channel patterns, transverse bar or split channel/central bar, ii) Ratio of radius of curvature to bank-full width, iii) Ratio of near-bank maximum depth to bank-full mean depth, iv) Ratio of bank-full shear stress to average shear stress, v) Velocity profiles / Isovels Velocity gradient. Bank-full shear stress is (Andrews, 1980) the ratio of near bank slope and maximum depth of the river. Average shear stress can be measured from the ratio of average slope and average depth of the river. NBS= Bank-full shear stress (BFSS) / average shear stress (AVS).2 Where, BFSS= maximum slope / maximum depth 3 AVS= average slope / average depth.4 Therefore, NBS= (maximum slope / maximum depth) / (average slope / average depth) For estimating the BEHI scores in the present study area, 60 points have been selected along the both banks of the River Haora within the Indian Territory. All parameters stated above, have been measured systematically in the field for all such 60 points. 129

Open access e-journal Earth Science India, eissn: 0974 8350 Vol. 6 (III), July, 2013, pp. 126-135 http://www.earthscienceindia.info/ Table-2: Total parametric values for estimating NBS Bank Erosion Risk Rating Velocity gradient Near-bank stress/shear stress VERY LOW <0.5 <0.8 LOW 0.5-1.0 0.8-1.05 MODERATE 1.1-1.6 1.06-1.14 HIGH 1.61-2.0 1.15-1.19 VERY HIGH 2.1-2.4 1.20-1.60 EXTREME >2.4 >1.6 Mean BEHI scores are rated as having a high degree of bank instability (Andrews et. al., 1995). However, mean NBS (near-bank stress) scores are rated as low. Finally, BEHI and NBS regression relationships are used in order to determine the rate of erosion of the banks. For estimating the accuracy level of this model, rate of bank erosion has also been estimated from 30 cross sections for three consecutive years (2010-2012). All of these cross sections for the said three years have been taken during the pre-monsoon period (February- April) when the water level of the river remains low and the erosional/depositional signatures of the previous monsoon season remains prominent. The cross sections have been drawn by joining the aforesaid 60 points (selected for BEHI Model) out of which 30 points were taken along the right bank of the river and the remaining 30 points along the left bank, just opposite to the previous points. All of those annual cross sections for three consecutive years of each section have then been superimposed to measure the amount of bank erosion digitally. Finally both of the values from BEHI model and cross sectional study have been compared to determine the validity of the BEHI model in real field. Result and Discussion To calculate the BEHI variable, the 1 st step is the measurement of all these 60 points (both banks in 30 sections). From the values of bank height ratio (Fig-2A), it is clearly found that the ratio is very high in most of those 60 points because the water level in the river suddenly rises during peak monsoon season. The highest value (7.40) along the left bank is found in section 1 and for right bank it is the highest (6.19) in section 27. In case of root cover (Fig-2B), maximum coverage is found (72%) along the left bank of the river. In case of right bank it has come down to 65%.30-54% root coverage is found in most of the points (26) and only 1point is noticed having the coverage of<5%. From the amount of bank angle at such 60 spots (Fig-2C), if is found that most of the spots are having angle between 21-60. Among such spots, only 5 spots along the left bank and 3 spots along the right bank possess overhanging and obtuse angle.

Validation of BEHI Model through field generated data for assessing bank erosion along the River Haora, West Tripura, India: Bandyopadhyay et al. Fig. 2: Bar graphs of 4 different parameters of BEHI model. From the field survey it is found that 24 spots having the surface protection (Fig-2D) of less than 10%. In 15 spots, the surface protection is moderate and it is very high in terms of vegetation cover and some manmade embankments in 6 spots only. Fig. 3: Graphs showing numbers of spots are under difference BEHI and NBS classes. After calculating BEHI value from the above stated 4 parameters, it is found that among such 60 spots 23 spots are falling in moderate BEHI zone (20-25), followed by high BEHI zone (25-30) having the number 20. 10 spots are falling under very high BEHI values (30-40), but there is no spot in very low BEHI group (5-10). 131

Open access e-journal Earth Science India, eissn: 0974 8350 Vol. 6 (III), July, 2013, pp. 126-135 http://www.earthscienceindia.info/ From the Fig. 3 it is found the NBS values among these 60 spots that the highest number of spots (32) possesses low NBS value (5-10). The reason behind this low NBS value is that the velocity in the entire course of the Haora River is moderate to low. The BEHI and NBS values of those individual spots have been plotted in a graph (Fig. 4) from which it is found that 8 spots (5 in left bank, 3 in right bank) are falling in very high erosion category, 13 spots in high category (10 in Right bank), 22spots in moderate category (14 in left bank), 11spots in low category (6 in right bank) and 6 (3 in right bank) spots in very low category of erosion rate. Fig. 4: Scattered diagrams for calculating bank erosion for both banks (BEHI model). Table-3: Comparison between BEHI model and field generated data. Comparison Exactly match Slight difference No match No. of spots 33 13 14 Among those 30 cross sections three sections have been presented here on the basis of their relative significance. The 1 st section has been taken near the debouching point of the River (just few meters downstream from the confluence of the Rivers Haora and Bardwal). It is found that the left bank of the river is very steep and very much prone to erosion (Fig.1). Moreover, the value of bank erosion at this spot, as per the BEHI model has found high. From the cross sectional data if is also found that the spot is falling in very high erosion zone. In case of right bank, the results are a bit different. Amount of erosion estimated from cross sectional study is moderate while it is low as per the BEHI model. During field survey some artificial deposition was observed along the right bank. The river tends to remove those materials during flood, for which the amount of erosion received from the cross sectional data is high during the period of study. On the other hand, since the general slope at this spot is gentle (Fig. 6) and velocity of the river is also low, the risk of erosion as per the model should be low. In case of section no. 7 (Fig. 5), the erosional value as per the BEHI model and value received from the cross sectional study are not matching in the right bank. The slope along the bank is very steep (Fig-7) and the BEHI value is also very high, but no such erosion has been found during the period of study (2010-2012). The values of BEHI model and cross sectional data are exactly matching for both banks of the river along the cross section no. 25 (Fig. 5).

Validation of BEHI Model through field generated data for assessing bank erosion along the River Haora, West Tripura, India: Bandyopadhyay et al. Fig. 5: Superimposed profiles for 3 consecutive years of three sections. Fig. 6: Evidence of erosion in section-1 along the right bank of the Haora River. 133

Open access e-journal Earth Science India, eissn: 0974 8350 Vol. 6 (III), July, 2013, pp. 126-135 http://www.earthscienceindia.info/ Fig. 7: High risk of erosion along the right bank in section-7 as it posses cliff slope. By comparing the BEHI model with field generated erosion data, it is found that the values of erosion rate are similar in case of 33 spots among the selected 60 spots (55%), 13 spots (Table-3) are having slightly different values from each other (21.7%) and in case of 14 spots (Fig. 6) the values are totally different from each other. Among these 14 unmatched spots, 6 spots are having low rate of erosion during the study period of 3 consecutive years (Fig. 7). But the risk of erosion in those 6 points is high, because these spots are characterized by steep bank slope with less coverage of vegetation. Conclusions From the above discussion it is proved that the BEHI model is highly useful for estimating bank erosion in the Haora River of West Tripura. This models accuracy level is exactly matching with the reality in 55% cases and very close to reality in 21.7% cases having a total acceptability level of 76.7 %. Thus, the model is more or less valid for estimating the amount of bank erosion as well as for determining bank erosion hazard zonation for future planning. The outcome of the model will be very much useful for determining the highly erosion-prone areas those should be taken care of on emergency basis and vice versa in order to reduce the loss of live and property as well as to take long term necessary measures for checking such bank erosion. Further, with some modification by improving the quality of data and incorporating the spatio-temporal events, the accuracy level of this model can be increased. Acknowledgement: The authors are thankful to the anonymous reviewers for their kind suggestions for upgrading paper. References Andrews, E.D. (1980) Effective and bank full discharges of streams in the Yampa River Basin, Colorado and Wyoming. Journal of Hydrology, v. 46, pp. 311-330.

Validation of BEHI Model through field generated data for assessing bank erosion along the River Haora, West Tripura, India: Bandyopadhyay et al. Andrews, E.D. and Nankervis, James M. (1995) Effective discharge and the design of channel maintenance flows for gravel-bed rivers. In: J. E. Costa et al. (eds.) Natural and Anthropogenic Influences in Fluvial Geomorphology: The Wolman Volume, Geophys. Monogr. Ser., vol. 89, pp. 151 164, AGU, Washington, D. C. Jessup, A., Harman W. (2004) Unpublished BEHI results cited in Van Eps et al. USDANRCS, Salisbury, NC. Rosgen, D. L. (1996) Applied River Morphology. Wildland Hydrology Books, Pagosa Springs, Colorado, pp. 6-42. Rosgen, D. L. (1999) Development of a River Stability Index for Clean Sediment TMDL's. In: D.S. Olsen and J.P. Potyondy (ed.) Proceedings of Wildland Hydrology, AWRA, Bozeman, Montana, pp. 25-36. Rosgen, D. L. (2001a) A Practical Method of Computing Stream bank Erosion Rate, 7 th Federal Interagency Sediment Conference, March 24-29, Reno, Nevada. Rosgen, D.L. (2001b) A Stream Channel Stability Assessment Methodology.7th Federal Interagency Sedimentation Conference. March 25-29. Reno, Nevada. Van Eps, M.A., Formica S.J., Morris T.L., Beck J.M. and Cotter A.S. (2004) Using a bank erosion hazard index (BEHI) to estimate annual sediment loads from stream bank erosion in the west fork white river watershed. Arkans as Department of Environmental Quality, Environmental Preservation Division, Little Rock, AR. (Submitted on: 24.3.2013; Accepted on: 10.6.2013) 135