Journal of Indian Geomorphology Volume 6, 2018 z ISSN 2320-0731 Indian Institute of Geomorphologists (IGI) $SSOLFDWLRQRI7RSRJUDSKLF3RVLWLRQ,QGH[IRU&ODVVL¿FDWLRQRI Landforms in Dudhatoli Region of Garhwal Himalaya, Uttarakhand

Devi Dutt Chauniyal and Surajit Dutta Department of Geography, HNB Garhwal University, Srinagar, Garhwal, Uttarakhand-246174 Email: [email protected] (Corresponding author)

Abstract: *,6DQG'(0KDYHEHHQZLGHO\XVHGIRUFODVVL¿FDWLRQDQGUHSUHVHQWDWLRQ of terrain ingeomorphic studies. A number of computer-based algorithms have been developed for analysingmorphometric properties. The main objective of the present study is to classify landforms in the Dudhatoli region of Garhwal Lesser Himalaya using Topographical Position Index (TPI). Advanced spatial statistical and image processing DOJRULWKPVKDYHEHHQXVHGIRUWKHLGHQWL¿FDWLRQRIODQGIRUPV'LJLWDO(OHYDWLRQ0RGHOV with 20m resolution and ASTER DEM have been used for landform analysis. The authors applied 11 different TPI values from 2 to 22 with 2 × 2 intervals. By using TPI, tenlandform categories were generated. Among these, some of the landform classes were occupying less than 1% areal coverage, so theten generated classes were merged into six classes. The other important parameters obtained from the DEM are slope position index,stream power index (SPI), topographic wet index (TWI), Planform Curvature and slope aspects. DEM not only shows the elevation and slope values but has VLJQL¿FDQWSRWHQWLDOLQODQGIRUPDQDO\VLV+LJKULGJHVORZKLOOVZDWHUGLYLGHVYDOOH\V planner surfaces are well represented in TPI which are frequently found in the mountain ODQGVFDSH7KLVODQGIRUPFODVVL¿FDWLRQFDQEHXVHGLQDSSOLFDWLRQRIQDWXUDOYHJHWDWLRQ analysis and recreational planning in the Dudhatoli region of the Garhwal Himalaya.

Introduction (Horton, 1945; Miller, 1953; Coates, 1958). Advancement in GIS technology, Geomorphologists are now using various generation of new software and spatial computer-based approaches in the GIS analytical methods are facilitating HQYLURQPHQW LQFOXGLQJ FODVVL¿FDWLRQ RI contemporary geomorphological studies PRUSKRPHWULF SDUDPHWHUV ¿OWHU WHFKQLTXHV (Pike, 1999). Digital Elevation Models cluster analysis, and multivariate statistics '(0 KDVEHHQZLGHO\XVHGIRUFODVVL¿FDWLRQ for the derivation of landform characteristics. and representation of terrain in geospatial Guisan, et al. (1999) and Weiss (2001) analysis (Franklin, 1987; Ventura and Irvin, introduce customised GIS application for 2000). Many computer based algorithms are VHPLDXWRPDWLF ODQGIRUP FODVVL¿FDWLRQ developed for calculating geomorphological Janness (2004, 2006) applied a method of properties of earth surface. Previously, calculating surface area grid directly from calculating morphometric parameters DEM. Topographic Position Index (TPI) was manually was tedious and time consuming ¿UVW GH¿QHG E\ *DOODQW DQG :LOVRQ  

28 JOURNAL OF INDIAN GEOMORPHOLOGY: VOLUME 6, 2018 and since then TPI has been widely applied applications of TPI methodology in varied by large numbers of researchers all over the UHVHDUFK ¿HOGV KDYH EHHQ PHQWLRQHG LQ ZRUOGIRUWKHFODVVL¿FDWLRQRIODQGIRUPV Table 1. D. Reu et al.   FODVVL¿HG WKH TPI techniques is being used extensively heterogeneous landscape in northwest LQ WKH ¿HOG RI WKH (DUWK 6FLHQFH KRZHYHU Belgium using TPI and DEV (deviation limited references are available for the from mean elevation) methods. Seif (2014) Himalayan region. One potential area of DSSOLHG 73, IRU ODQGIRUP FODVVL¿FDWLRQ E\ application of TPI in the Himalayas can be slope position classes in Oshtoran Kooh IRUODQGIRUPFODVVL¿FDWLRQEDVHGRQFKDQJHV Mountains in Iran. Similarly, Alijani and of slope and pattern of land use. Keeping this Sarmadian (2015) have applied TPI method in view, the TPI technique has been used in IRU FODVVL¿FDWLRQ RI SDUHQW PDWHULDO DQG the present study on an experimental basis. estimation of slope changes in Kouhin region, Qazvin Province, Iran. Landform Objective of the study DURXQG =DJURV PRXQWDLQ KDV EHHQ FODVVL¿HG The main objectives of the present study by Seif (2014) by using TPI technique. Other are: i) classifying the mountain landforms

Author Year Method used Used for Place Correlated agricultural land Chendes, V. et al. 2009 TPI Romania hilly region use types with landforms units Digital Terrain Subtropical forest Okinawa Island and Zawawi, A.B.A. 2015 Model (DTM) and management planning and Yambaru island in Japan TPI ODQGIRUPFODVVL¿FDWLRQ Topographic factors for White Mountains of Bunn, A.G. et al. 2011 TPI PRGL¿HGWUHHULQJFKURQRORJ\ California American chestnut at Fei, S. et al. 2007 TPI Spatial habitat modelling Mammoth Cave National Park in USA Estimating the effects of Kwangneung Han, H. et al 2015 topographic position on the Experimental Forest in herb species diversity South Korea Landuse and landcover Kapidag Peninsula, Tagil, S. 2015 TPI FODVVL¿FDWLRQ Turkey Dispersing mountain pine Marie C. de la beetle populations in different 2011 TPI western Canada Giroday. et al. landscape features during a range expansion Establishing relationship Tagil, S. and 2008 TPI between landform and land YazorenPolji Turkey Janness, J. use Identifying malaria vector Clennon, J.A. et al 2010 TPI Zambia breeding habitats Coastal geomorphology and Wright, D.J. and TPI and GIS 2008 analysed marine reserves with - Heyman, W.D. application habitat mapping

APPLICATION OF TOPOGRAPHIC POSITION INDEX IN DUDHATOLI REGION 29 of Dudhatoli region of lesser Himalaya into passes through central part of the region from different terrain units based on TPI method, NW to SE direction. Granite and gneisses are ii) determination of relationship between the main rock types in the core zone, while topographic attributes and landform classes phyllite and quartzite are in the southern in the Dudhatoli region. and northern margins of the syncline. The northern and southern boundaries of the Study Area Dudhatoli syncline are marked by North The Dudhatoli region of lesser Almora Thrust (NAT) and South Almora +LPDOD\D LV VLWXDWHG ZLWKLQ ƒƍƎ( Thrust (SAT) respectively.

Figure 1. Location of the study area

WR ƒƍƎ( DQG ƒƍƎ1 WR ƒƍƎ1 LQ WKH 8WWDUDNKDQG VWDWH RI Methodology India. It lies within the boundaries of Chamoli, The base map has been prepared on the Pauri and partially withinAlmora district basis of 1:50,000 SoI topographical sheets (Fig.1). The Dudhatoli region of Garhwal (53N/4, 53N/8, 53O/1, 53O/5 and 53J/16). Himalaya is characterised by a unique Landsat 8 ETM+ data of 28 May 2015 has assemblage of landforms. It is the ‘water been used (http://earthexplorer.usgs.gov; tower’ of lesser Himalaya in Uttarakhand of path 145 row 39) for extraction of land region which is the source of perennial use and vegetation related data. The ground riverslike Ramganga in the east, Bino in YHUL¿FDWLRQZDVFDUULHGRXWE\*36*DUPLQ the south, Nayar in the west and Ata Gad (a 72. The entire analysis fromremotely sensed tributary of Pinderriver) in the northeast. The data was done in Arc GIS (v.9.3) and ERDAS whole terrain is mountainous with elevation (v.9.1). The methodological framework is ranging between 1098 m to 3120 m from msl. JLYHQLQWKHÀRZFKDUW )LJ  The total geographical area of the region is approximately 493 Km2. Generation of DEM and extraction of Geologically the area falls in the topographic attributes Dudhatoli synclinal zone. The synclinal axis The DEM was generated by digitising

30 JOURNAL OF INDIAN GEOMORPHOLOGY: VOLUME 6, 2018 Figure 2. The data base and methodology adopted the contours at 40 m interval from SoI RYHUODQGÀRZVDQGLVDIXQFWLRQRIWKLFNQHVV Topographical sheets. Subsequently the DEM of soil horizons, soil organic matter, pH, was interpolated with the topographic analysis silt and sand content and distribution of surface tool of ERDAS (v. 9.1) software and vegetation cover (Florinsky, 2012). As it was converted into a grid format. The VSHFL¿FFDWFKPHQWDUHDDQGVWHHSQHVVRIVORSH topographic parameters — elevation, slope, increases, the amount of water contributed DVSHFW FXUYDWXUH ÀRZ DFFXPXODWLRQ DQG by up-slope areas and the velocity of water ÀRZGLUHFWLRQZHUHGLUHFWO\H[WUDFWHGIURPWKH also increases — leading to increase in DEM usingthe ‘surface’ and ‘hydrology’ stream power and erosion potential (Moore tools in Arc GIS (v. 9.3).The stream power and Burch, 1986). SPI is calculated by the index (SPI) and topographic wet index (TWI) following formula (Danielson, 2013) and ZHUHFDOFXODWHGRQWKHEDVLVRIVORSHDQGÀRZ FODVVL¿HGLQ7DEOH accumulation data set with the help of spatial 63, /Q ÀRZDFFBGHP   VORSHB analysis by raster calculator. GHP  The SPI values vary from –13.9 to 7.7 STREAM POWER INDEX (SPI) ZKLFK DUH FODVVL¿HG LQWR  &ODVVHV EDVHG Stream power index indicates theerosive on natural break. The mean and SD values SRZHU DVVRFLDWHG ZLWK ÀRZLQJ ZDWHU ZKLFK of SPI are calculated as –0.17 and ± 1.79 is based on the assumption that discharge is respectively which indicates the uneven SURSRUWLRQDOWRWKHVSHFL¿HGDUHD :LOVRQDQG distribution of SPI in the study area because Lorang, 1999). It is the relationship between of variation of slope steepness.It is observed energy expenditure of a stream and quantity that 32.59% of the area is under moderate of sediment transportation (Bagnold, 1966). SPI class followed by low SPI (25.19% area). SPI controls the potential erosive power of Only 5.40 % of the area is under very high

APPLICATION OF TOPOGRAPHIC POSITION INDEX IN DUDHATOLI REGION 31 SPI, whereasthe very low SPI class covers Topographic Position Index (TPI) 18.87% area of the total (Table 2). 73, LV D VLPSOL¿FDWLRQ RI WKH ODQGVFDSH Topographic Wet Index (TWI) Position Index (LPI) developed by Weiss This TWI parameter is used for the (2001). TPI values provide very simple

Table 2. Categorisation of Stream Power Index (SPI) Stream Power Index (SPI) Value Area in Km2 Area in % Comment Very Low –13.95 to –1.80 93.06 18.87 Low Low –1.80 to +0.15 124.22 25.19 Moderate 0.15 to 0.88 160.72 32.59 Moderate High 0.88 to 1.82 88.46 17.94 High Very High 1.82 to 7.73 26.65 5.40 Total 493.11 100 Mean –0.17, Standard Deviation (SD) ± 1.79

FODVVL¿FDWLRQ RI ODQGIRUPV 63, LV FORVHO\ and powerful technique ofclassifying the related with TWI which is used to estimate entire landscape into small morphological the erodibility potential of the terrain categories (Tagil and Jenness, 2008). (Sharma, 2010). The TWI has been also used According to Jenness (2006) the basis of to describe the spatial soil moisture patterns WKH 73, FODVVL¿FDWLRQ V\VWHP LV VLPSO\ WKH (Kirkby, 1975; Wilson and Gallant, 2000) and difference between a cell elevation value and landslide susceptibility (Gorumet al., 2008). the average elevation of the neighbourhood The TWI is calculated by following formula around that cell. Positive values mean the cell 7:,  /Q ÀRZDFFBGHP     is higher than its surroundings while negative VORSHBGHP  values mean it is lower. High TPI values are found on ridge tops whereas low TPI values

Figure 3. Topographic attributes of the Dudhatoli region 32 JOURNAL OF INDIAN GEOMORPHOLOGY: VOLUME 6, 2018 are found in valleys. Zero TPI value is found YHU\GLI¿FXOWWRLGHQWLI\WKHGLIIHUHQWW\SHVRI in the plains. topographic features. TPI is by nature a scale- The following formula has been used for dependent Index.Windows of different scales calculatingthe TPI: covering the neighbourhoodof the nodal point 73, =±ȈQ±=QQ have been used indelineation of TPI. In the :KHUH =  HOHYDWLRQ RI WKH QRGDO SRLQW present study the authors applied 11 different under evaluation. TPI grids ranging from 2×2 to 22×22. TPI, =Q  HOHYDWLRQ RI JULG ZLWKLQ WKH ORFDO 6ORSH 3RVLWLRQ DQG ODQGIRUP FODVVL¿FDWLRQ window. were carried out using Arc GIS Topography Q  WRWDO QXPEHU RI VXUURXQGLQJ SRLQWV Tools, which have been developed based on employed in the evaluation. Arc View Tools (v. 3.3) by Jenness (2006). The Slope Position Classes generally vary )RU WKH LGHQWL¿FDWLRQ DQG FODVVL¿FDWLRQ RI from +1 to – 1 of the TPI threshold value. ODQGIRUP6ORSH3RVLWLRQ&ODVVL¿FDWLRQLVWKH ,QDWWHPSWLQJDODQGIRUPFODVVL¿FDWLRQLWLV next essential prerequisite.

Figure 4. TPI values of Dudhatoli region using windows of varying dimensions

APPLICATION OF TOPOGRAPHIC POSITION INDEX IN DUDHATOLI REGION 33 6ORSH3RVLWLRQ&ODVVL¿FDWLRQ LH ULGJHV DQG YDOOH\V FRXOG EH LGHQWL¿HG :HLVV   ZDV WKH ¿UVW WR FDOFXODWH (Fig. 3.). It shows that as the scale increases 6ORSH 3RVLWLRQ IRU WKH LGHQWL¿FDWLRQ DQG (from 2 to 20 TPI) slope position classes are FODVVL¿FDWLRQ RI ODQGIRUP /RJLFDOO\ KLJK decreasing and small landforms are no longer TPI values would be found near the top of LGHQWL¿DEOH )LJ  ,Q WKH SUHVHQW VWXG\ hills, while low TPI values would be found the slope value is disappearing after the in valley bottoms (Tagil and Jenness, 2008). threshold of 20×20 TPI (Table 3, Fig. 4). It is Using a window size of TPI grid 2×2, most clear that low TPI scale is very useful for the individual ridge lines, valleys, mid-slopes LGHQWL¿FDWLRQRIVPDOOODQGIRUPVZKLOHKLJK and other small size features are delineated at TPI (>20×20) scale is useful for generalised WKH¿QHVWVFDOH )LJ 2QWKHRWKHUKDQGLQ ODQGIRUP FODVVL¿FDWLRQ 7KH FKRLFH RI 73, ODUJH VFDOH FODVVL¿FDWLRQ ZLWK 73, JULG VL]H scale depends open the requirement of the 20×20, only generalised landform units user.

Table 3. Slope Position classes and the percentage of area under each clas Grid 2 4 6 8 10 12 14 16 18 20 22 Class TPI TPI TPI TPI TPI TPI TPI TPI TPI TPI TPI Valley 40.3 45.6 47.1 47.7 48.2 48.5 48.7 48.9 49.1 49.3 49.4 Gentle Slope 2.0 0.4 0.1 0.1 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Steep Slope 16.3 7.2 4.3 3.1 2.3 1.9 1.6 1.4 1.2 1.1 1.0 Ridge 41.4 46.8 48.5 49.1 49.4 49.6 49.7 49.7 49.7 49.7 49.6 Total Area in % 100 100 100 100 100 100 100 100 100 100.0 100

Figure 5. Slope classes of Dudhatoli region and their area (%) using different TPI grid size (Weiss 2001)

34 JOURNAL OF INDIAN GEOMORPHOLOGY: VOLUME 6, 2018 Figure 6. Slope classes of Dudhatoli region using windows of varying dimensions Topographic Position Index and Landform only the generalised landforms. Therefore, &ODVVL¿FDWLRQ according to Weiss (2001) and Jenness )ROORZLQJ WKH ODQGIRUP FODVVL¿FDWLRQ (2006), the TPI with small scale 2 m radius methodology of Weiss (2001) and Jenness circular window and large scale 20 m radius (2006), the Dudhatoli region has been circular windows were combined and in the FODVVL¿HGLQWRPLFURODQGIRUPXQLWV7KH73, ¿QDO UHVXOW RI ODQGIRUP FODVVHV D YHULW\ RI algorithm was used using windowsof 2 m to nested landforms could be distinguished. 22 m, covering 11spatially varying classes Thus the whole Dudhatoli region is (Fig. 5). After the test of 11 windows, it was FODVVL¿HGLQWRODQGIRUPFODVVHVEDVHGRQ found that 2×2 window gave the best result small and large scale Slope Position Classes showing the very small topographic forms. (Weiss, 2001). Table 4 reveals that some of The 20×20 window on the contrary, depicted the landform classes are occupying less than

APPLICATION OF TOPOGRAPHIC POSITION INDEX IN DUDHATOLI REGION 35 1% areal coverage and their existence is DFFRUGLQJ WR ¿HOG FKDUDFWHULVWLFV DQG ORFDO negligible in the study area. Hence, these10 knowledge (Table 4). classes are merged into six classes and new Table 4 shows that the maximum areal names have been assigned to these classes coverage of 27% is found on the ‘high mountain

Table 4/DQGIRUP&ODVVL¿FDWLRQEDVHGRQ:HLVV  RQFRPELQHG73,YDOXHVRIPDQGPFLUFXODUZLQGRZV Class Landform Area km2 Area (%) New Class Area km2 Area (%) 1 Mountain tops, high ridges 133.13 27 High Mountain Ridges 133.13 27 2 Open slopes 1.08 0.22 Upper Hills and Divides 45.95 9.32 3 Upper slopes, mesas 44.86 9.1 Mid-slope drainages, 4 2 0.4 Mid Slope Zone 68.85 13.96 shallow valleys Upland drainages, 5 66.86 13.56 headwaters 6 Local ridges/ hills, in valleys 72.17 14.64 Lower Hills & Divides 74.42 15.09 Mid-slope ridges, small hills 7 2.25 0.46 in plains 8 U-shaped valleys 40.99 8.31 Valley Bottoms 41.03 8.32 9 Small plains 0.04 0.01 Canyons, deeply, incised 10 129.74 26.31 Wide Valley Floor Zone 129.74 26.31 streams Total 493.11 100 Total 493.11 100

Figure 7. Landform classes of Dudhatoli region

36 JOURNAL OF INDIAN GEOMORPHOLOGY: VOLUME 6, 2018 Figure 8. Land form classes of Hindwal Gad ridges’ followed by ‘valley bottom’(26.3%). 6),having maximum areal coverage (27%). The minimum areal coverage (8.3%) is found Altitudinally the zonefalls within 2500 LQWKHµYDOOH\ÀRRU¶]RQHIROORZHGE\µXSSHU m to 3100 m, descendingin all directions hills and divides’(9.3%). ‘Mid slope’ zone IURP 'XGKDWROL WRS 7KH KLJK ÀDW WRSV DUH and ‘lower hill and divides’zone occupies locally known as Danda. Alpine pastures 14% and 15% of the total area respectively. are found above 2800m in which nomads 7KHUHVXOWVZHUHYHUL¿HGLQWKH¿HOGDQGWKH set up their temporary settlements locally landform classes matched almost completely known as Kharak. Around these pastures with the topographic formations. The there are coniferous forests. During winters Dudhatoli region being a mountainous terrain this part is under snow. This zone is mostly the altitude varies between 1098 m to 3120 used for tourism, trekking and site seeing. m from msl and hence, overall 53.3% of the Kodiyabaggad (3031m) is the vantage point, DUHDLVFODVVL¿HGXQGHUKLJKULGJHVDQGYDOOH\ having the best view of the Himalayas. bottoms. Figure7 shows an enlarged portion (ii) Upper slope zone: The major of Figure 6. Here the landform units of water divides are associated with the high Hindwal Gad in Ramganga catchment have mountain zone, but with decreasing altitude, been depicted, which is located at the south- these ranges separate from the main range eastern part of Dudhatoli region. Each unit and descend towards the valleys. This zone is clearly indicating the pattern of mountain covers 15% of the total area.These low hill ODQGIRUP 7KHVH ODQGIRUP FODVVL¿FDWLRQV ranges and water divides are locally known can be used for watershed management as Dhar. Covered by temperate forest mainly planning in the mountainous area. The basic oak and associated species, this zone supplies characteristics of each region is given below- the headwater to the streams. Occasional (i) High ridges: The high mountain snowfall occurs during winter season on the ranges of Dudhatoli region are shown hill tops. The zone is dominated by numbers by dark red colour on the map (Fig. of saddles locally known as Khals. Uphain

APPLICATION OF TOPOGRAPHIC POSITION INDEX IN DUDHATOLI REGION 37 khal, Nagchulakhal, and Pirsain are the Bino, Massangadi and Eastern Nayar are prominent Khals. Motorable roads, serving prominent. This zone covers about 8.23% of rural service centres are passing through the total area. The slope of the area is about these Khals. 20°. Valley spurs are prominent features (iii) Mid slope: This zone covers about which are intensively cultivated. Colluvial 23.28% of the study area, with gently fans and cones are sometime found at the slopingspurs covered by pine forests. The piedmont slopes. The fertility of the soil is upper part of the spurshas concave slope comparatively higher than other zones. The ZLWK GHQVH PL[HG IRUHVWV 0RVW RI WKH ¿UVW area is well connected by roads and trekking and second order streams join each other routes with other parts of the basin. Small and gives a dissected look to the terrain. It ÀRRGSODLQWHUUDFHVDUHDOVRIRXQGDORQJWKH is in this part where maximum mass wasting banks of the higher order streams like Bino, activities are found. Ramganga and Nayar River which are locally (iv) Lower hills: Between the middle known as Baggad. slope zone and the valley bottoms there are While using the TPI method to generate the rounded hills and water divides (13.96 morphological types, the effects of scale km2). The spur dominated area where the and generalisation need special attention. settlements and cultivated land are located The results are dependent upon the nature of along the spurs, is locally known as Sar. The the area and scale of the map.In the present spurs are convex in nature extending towards study generalised results are satisfactory to the valleys. Most of the water divides are some extent because it is a homogeneous either under wastelands or degraded pine mountainous terrain. There is not much forest cover. variation in the topography. Generalised (v) Valley bottoms: These consist of features i.e. hill ranges, valleys, mid-slopes, channel beds covering 26.31% of the area, river channels and slope features are clearly which is second highest among the landform visible on the map. For clearly identifying FODVVL¿FDWLRQ XQLWV %HLQJ D PRXQWDLQRXV micro landform features a different map terrain with high drainage density, the areal scale will be necessary. Thus TPI provides coverage of this zone is high. It is dissected by a powerful tool to describe topographic numerous rivulets locally known as Gad and attributes of any study area. Gadhera. These features are clearly visible in the lowest TPI index. Third and fourth Topographic Attributes and Landform order channel beds are clearly visible in this Classes zone. Narrow ‘V’ shaped valleys, gorges and 7KH ¿YH WRSRJUDSKLF DWWULEXWHV LH hollows are the prominent features along the elevation, slope, stream power index, valley bottoms, mostly under dense mixed planform index and topographic wet index forests. In some areas this zone is prone DUH FRUUHODWHG ZLWK  ODQGIRUP FODVVL¿HG to stream bank erosion, landsliding and units by using the standard Arc View Zonal slumping. Most of the springs are sinking Statistical function to calculate statistics for underground in this zone which is partially topographic attributes within each landscape responsible for slumping and sliding in this class. part. Elevation: (vi) Wide valley zone: Some of the valley The mean elevation of the study area ÀRRUVDUHFRPSDUDWLYHO\ZLGHUWKDQRWKHUVLQ is 2062 m from msl. Being a part of the lower portion. Among theseRamganga, high mountain range, limited variations

38 JOURNAL OF INDIAN GEOMORPHOLOGY: VOLUME 6, 2018 Table 5. Relationship of Landform Classes and Topographic Attributes Landform Stream Plan form Landform Elevation Slope Topographic wet SL Area in Power Index Curvature Classes Mean± SD Mean ± SD Index Mean ± SD Km2 Mean ± SD Mean± SD 2183.04 ± 0.39 ± 1 High Ridges 133.13 23.0 ± 9.5 –1.26 ±1.83 –32.57 ± 356.86 371.61 0.44 Upper slope 2148.97 ± –0.01 ± 2 45.95 20.4 ± 9.6 0.05 ± 1.09 –183.72 ± 1205.50 zones 365.12 0.21 2198.95 ± –0.39 ± 3 Mid Slope 68.85 25.2 ± 9.2 0.63 ± 0.86 2.19 ± 97.63 364.62 0.41 1983.64 ± –1.17 ± 0.41 ± 4 Lower Hills 74.42 26.5 ± 9.1 –6.66 ± 136.55 351.03 2.16 0.40 Valley 1911.64 ± 0.03 ± 5 41.03 20.1 ± 11.1 0.13 ± 1.29 302.14 ± 1552.09 Bottoms 349.28 0.22 Wide Valley 1948.20 ± –0.41 ± 6 129.74 23.0 ± 10.1 0.93 ± 1.12 34.93 ± 398.80 Zone 361.00 0.49 areobserved in the parameter of altitude. The slope indicate concave curvature with –0.41 classes of mid slope, upper slope, and ridges and –0.39 mean value respectively,while are above the mean height, while wide valley landform classes lower hill and ridges are and lower hillshave elevation below the mean having positive convex curvature with elevation value. The mean SD is 360.44. +0.39 and +0.41 mean value srespectively. Slope: The wide valley zone and upper slope zone The mean slope of the six landform classes indicate linear planform curvature with 0.03 is 23°. Table 5 shows that the classes of lower and –0.01 mean values respectively. hills and mid slope are having slopegreater Stream Power Index (SPI): than the mean slope. The topographical Stream power index is directly related classes of valley, wide valley zone, upper to both slope and catchment area which slope zone and ridges are found below mean indicates theerosive power of the basin or slope of the study area (Table 5). The overall area. The overall SPImean value is calculated mean deviation among the landform classes to be 0.69. Landform classes of high ridges, is 9.77. lower hills indicate negative SPI of –1.26 and Planform Curvature: –1.17 respectively while rest of the landform Planform curvature is calculated by 3×3 classes are having positive SPI values. Mid cell neighbourhood based on the algorithm -slope zone is much nearer to mean value i.e. suggested by Zevenbergen and Thorne 0.63. Negative SPI values indicate that a cell (1987) in Arc GIS 9.3 surface tool. A positive is lower than its neighbours (Table 5). value of planform curvature indicates the Topographic Wet Index (TWI): surface is convex at the cell, while negative This parameter is closely related with SPI values indicate the surface is concave at the which is used to estimate the erosive power of cell and zero value indicates that the surface the terrain (Chen and Lee, 2010). The overall is linear. In the Dudhatoli area planform TWI mean value is calculated to be 19.38. curvature values varies between –8.2 to Landform classes of high ridges, upper slope +4.97. The mean curvature value of is 0.02. zone and lower hills indicate negative TWI Landform classes of valley bottoms and mid (Table 5) while rest of the landform classes

APPLICATION OF TOPOGRAPHIC POSITION INDEX IN DUDHATOLI REGION 39 are having positive TWI values. Investigation $6&VHLWHBYRQ$6& UHWULHYHG RQ YHUL¿HG WKDW PLG VORSH YDOOH\ ERWWRPV DQG 2016-1-29). wide valley zone shave high soil moisture Chendes,V., Dumitru, S. and Simota, C. (2009) DQG DUH IDYRXUDEOH IRU HURVLRQ GHEULV ÀRZ Analyzing the landforms-agricultural land and landslide. use types relationship using a DTM based indicator, USAMV Bucharest , Series A, Vol. Conclusion LII: 135–140. 7HUUDLQ FODVVL¿FDWLRQ RQ WKH EDVLV RI Clennon, J.A, Kamanga, A., Musapa, M., Shiff, TPI values provides a simple yet powerful C. and Glass, G.E. (2010) Identifying malaria vector breeding habitats with remote sensing technique to classify the entire landscape data and terrain-based landscape indices in into small morphological classes (Tagil and Zambia. International Journal of Health Jenness, 2008). Application of this algorithm Geographics, 9(1): 45–58. in ArcGIS platform helped to identify 6 Coates, D.R. (1958) Quantitative geomorphology morphological classes in the Dudhatoli of small drainage basin in southern Indiana, region. The method gave generalised results Department of Geology, Colombia University, with 22 m window size, but it is found that 2 New York: Technical report 10, Proj. ONR- m window gave the best results in identifying NR-389-042. micro landforms on the highly sloping hilly Danielson, T. (2013) Utilizing a High Resolution terrain. The result more or less conforms to Digital Elevation Model (DEM) to Develop the terrain classes suggested by Weiss (2001) a Stream Power Index (SPI) for the Gilmore and Jeness (2006). 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