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248 K. NARENDRA AND OTHERS
Integrating Remote Sensing and GIS for Identification of
Groundwater Prospective Zones in the Narava Basin,
Visakhapatnam Region, Andhra Pradesh
K. NARENDRA^1 , K. N AGESWARA R AO 2 and P. S WARNA LATHA 3
(^1) Department of Civil Engineering, GITAM University, Visakhapatnam - 530 045 (^2) Discipline of Geography, Indira Gandhi National Open University, Maidan Garhi, New Delhi - 110 068 (^3) Department of Geography, Andhra University, Visakhapatnam - 530 003 Email: narendra@gitam.edu
Abstract: This paper mainly deals with the integrated approach of remote sensing and Geographical Information System (GIS) to delineate groundwater prospective zones in Narava basin, Visakhapatnam region. The various thematic maps generated for delineating groundwater potential zones are geomorphology, geology, lineament density, drainage density, slope and land use/land cover (LULC). Weighted index overlay (WIO) technique is used to investigate a number of choice possibilities and evaluate suitability according to the associated weight of each unit. The integrated map of the area shows different zones of groundwater prospects, viz. very good (18.9% of the area), good (26.4% of the area), moderate (17.1% of the area) and poor (37.6% of the area). The categorization of groundwater potential was in good agreement with the available water column in the basin area.
Keywords: Groundwater prospective zones, Remote sensing, GIS, Narava basin, Visakhapatnam, Andhra Pradesh.
al. 2006; Vijith, 2007; Suja Rose and Krishnan, 2009). The remote sensing systems provide synoptic coverage and accurate spatial information, which enable economical utilisation over conventional methods of hydrogeological surveys. Rapid advances in the development of the GIS, which, provides spatial data integration and tools for natural resource management has been proved to be an efficient and successful tool for groundwater studies (Shahid et al. 2000; Jaiswal et al. 2003; Sreedevi et al. 2005; Nageswara Rao and Narendra, 2006; Mondal et al. 2008; Adham et al. 2010). With the capabilities of remotely sensed data and GIS techniques, numerous thematic maps can be integrated to produce a conceptual model for delineation of ground- water potential zones (Chowdhury et al. 2009; Murthy and Mamob, 2009; Gupta and Srivastava, 2010). One of the most accepted method is weighted index overlay (WIO) for assigning weights and relative ranks based on the multi- criteria evaluations for decision making (Pratap et al. 2000; Javed and Wani, 2009; Nagarajan and Singh, 2009; Subba Rao, 2009; Jha et al. 2010). In this study, an attempt was made to utilize a similar method to identify groundwater prospective zones in the Narava basin area.
INTRODUCTION Groundwater is gaining more and more importance in India owing to the ever increasing demand for water supplies, especially in areas with inadequate surface water supplies. More than 85% of rural and nearly 50% of urban population depend on the groundwater for drinking purposes, while, it accounts for nearly 60% of the total irrigation in the country. According to Central Ground Water Board (CGWB, 2007) out of total number of 5723 blocks/ watershed assessed in the country, 839 are categorized as over exploited, 226 as critical and 30 are infested with saline groundwater. The rate of withdrawal of groundwater is increasing continuously due to rapid growth of population accompanied by agricultural and industrial development. The occurrence and movement of groundwater in an area is governed by several factors such as topography, lithology, geological structure, depth of weathering, slope, land use/ land cover (LULC), and interrelationship between these factors. To understand groundwater prospects of an area, integration of different thematic layers is required. In the hard rock terrain, availability of groundwater is limited and its occurrence is essentially confined to fractures and/or weathered horizons (Krishnamurthy et al. 2000; Chandra et
JOURNAL GEOLOGICAL SOCIETY OF INDIA Vol.81, February 2013, pp.248-
0016-7622/2013-81-2-248/$ 1.00 © GEOL. SOC. INDIA
INTEGRATING REMOTE SENSING AND GIS FOR IDENTIFICATION OF GROUNDWATER PROSPECTIVE ZONES 249
STUDY AREA
The area under study, Narava basin, is bounded with arcuate hill ranges of Eastern Ghats province in Visakhapatnam region. The area lies between 17°40' N to 17°57' N latitudes and 83°02' E to 83°19' E longitudes and covers an area of about 516 km 2 (Fig. 1). Visakhapatnam is well connected to other parts of the country by all modes of transport. Visakhapatnam region experiences a semi-arid climate. The average annual rainfall is 110 cm. The monsoon
brings over 80% of the annual rainfall between the months of June to November, with the highest precipitation occurring in August and October. The area has maximum and minimum temperatures of 38.5ºC and 19.4ºC respectively. April and May are generally hottest months and December and January are coldest months. Relative humidity varies between 70- 85% throughout the year, especially, very high in day time because of marine influence. The study area is underlain by crystalline rocks of Archaean age consisting of khondalite, charnockite,
Fig.1. Location map of the study area.
INTEGRATING REMOTE SENSING AND GIS FOR IDENTIFICATION OF GROUNDWATER PROSPECTIVE ZONES 251
validated by using groundwater level data. The methodology adopted in this study is given in the flow chart (Fig. 2).
RESULTS AND DISCUSSION
Geomorphology
The relief, slope, extent of weathering, type of weathered material and overall assemblage of different landforms play an important role in defining the groundwater regime, especially in the hard rocks. Geomorphology was assigned highest weight because it has a dominant role in the
movement and storage of groundwater in the study area (Thomas et al. 2009). Visual interpretation of digitally enhanced images enables identification of the various geomorphic units in the present study (Table 2). Various landforms identified in the area, as shown in Fig. 3, are structural hills, denudational hills, residual hills, burried pediments, weathered pediplains, gullied/ravines, bajada, alluvial plains, abandoned channel, swampy/mudflats and beach sand. Structural hills: These are formed predominantly by khondalite meta-sediments covering an area of 86.2 km 2.
Satellite data
False colour composite (FCC)
SOI topomaps
Base map
Digital image analysis
Aster GDEM
Hillshade Shaded relief
Slope Geomorphology Geology Lineaments Drainage Land use/land cover
Sobel filterEdge detection Linear enhancementBand combinations
Lineament density
Drainage density
Supervised classification
Accuracy assessment Density function (using Spatial Analyst)
Rasterization
Thematic layers
Classified images
WIO analysis (through ArcGIS model)
Ground truth Output analysis/assessment Water level data
Groundwater prospective zones
Open source data
Geometric rectification
Ground truth (GPS survey)
Rank 1 Very good 2 Good 3 Moderate 4 Poor
Fig.2. The methodology adopted for the present study.
252 K. NARENDRA AND OTHERS
These occupy the NNE, SSE, west and eastern part of the study area. Because of high slope and relief, groundwater prospect in this zone is considered as poor. Denudational hills: A group of massive hills formed due to differential erosion and weathering. These occupy WSW part of the study area. The groundwater prospect in this zone is also considered as poor. Residual hills: The isolated gneissic rock exposures in central part of the basin are identified as residual hills. Because of steep slopes and high runoff these zones are not suitable for groundwater prospecting. Burried pediments: A Pediment is a gently inclined erosional surface carved in bedrock. These are formed with moderate slopes and occupy an area of 142.2 km^2 in the basin. They are considered as moderate zones for groundwater potential. Weathered pediplains: A pediplain is a gently undulating landscape broken by isolated residual uplands and covered by a varying thickness of overburden material
with red soil cover. These plains consist of semi-stratified deposits of sediments that are regularly brought from upland catchment area. Pediplain is considered as good prospect zone for groundwater development. Gullied/ravines: It is highly rugged and ravenous topography. These features comprise fine grained semi- consolidated alluvium found at SW, west and eastern parts of study area. Pebble layers are present at various heights of gully lands indicating the deposition at various stages. Gullies are identified on FCC imagery with their light green tone reflectance in association with hills and streams. The areal extent of this unit is 30.1 km 2. Groundwater occurrence is limited due to high run off and its impermeable nature hence, considered as poor prospective zone for ground- water exploration. Bajada: It consists of a series of coalescing alluvial fans built by streams which debouch onto a pediment. The surface of a bajada is slightly undulating in character. This is observed around Errakonda and Kailasa hilly regions
Table 2. Image and physical characteristics of different landforms in the study area Geomorphic unit Image elements Landform characteristics (ground observation) Area km 2 Structural hills Dark red tone, coarse texture, Linear to arcuate hills, dissected, khondalite group rocks, mostly dendritic 86. irregular shape drainage, jointed, ridges, average height 300 m, strong to very steep slopes Denudational hills Dull red tone, coarse texture, Weathered khondalite, dendritic drainage, moderate to steep slopes, sparse 12. irregular shape vegetation Residual hills Dark grey tone, coarse texture, Erosional surfaces, isolated mounds, which have undergone the process of 2. shape and size-irregular and denudation. Steep slopes, radial drainage, act as runoff zones. rounded Burried pediments Light red to red tone, moderate Gentle to moderate slopes, devoid of vegetation with various depths of 142. to fine texture weathering material, shallow sediment cover, rocky and gravely surfaces, dendritic to sub-dendritic drainage, mostly vegetated or cultivated lying at foot hills. Weathered Green-bluish mixed tone, Covered with thin layer of soil at places, has natural vegetation. Dendritic pediplains moderate to fine texture to sub-dendritic drainage, nearly level to gentle slopes, rocky erosional 102. surfaces. Gullied/ravines Light green-yellow mixed tone, Sand and gravel outwash plains due to stream erosion, enclosed with hills, moderate to fine texture, undulating terrain, deep cuts, fine sandy material and irregular shapes. irregular pattern 30. Bajada Light greyish for moisture to Accumulation zone of colluvial material derived from surrounding hills, dark red for vegetation, fine shallow to deep fine sand, silt clay soils. texture and irregular shape 9. Alluvial plains Greyish green tone with light Moderately deep to well drained, nearly level (flat) slopes, ravine deposits pink-red patches, checker underlain by gravel and kankar pan. Prominent growth of plantations board pattern (cultivated lands), (cashew, casuarina, mango, etc.) and crop lands 125. fine texture Abandoned channel Dull greyish and red tone Disappeared stream, fluvial material, nearly level slopes 0. Swampy/mudflats Light pink-bluish tone, fine Low lying tidal flat with mud/salt flats, mangrove, swamps, generally, texture barren or with salt loving weeds 1. Beach sand White, fine textured, definite Narrow stretch of unconsolidated sand deposited by tidal waves along the shape shoreline 0.
254 K. NARENDRA AND OTHERS
appears as black in colour enriched with rare minerals. Over exploitation of groundwater along the coast line disturbs the sensitive balance between fresh and brackish water resulting in sea water intrusion (NRSA, 1999). This geomorphic unit is considered as poor prospective zone for groundwater development.
Geology
The basin area is underlain by Archaean age group of rocks. The major rock exposures are khondalite, charnockite, migmatite, pyroxene granulates and quartzite bands (Fig. 4). The rock types include under the khondalite group are garnet-sillimanite gneiss, quartzite bands and migmatite gneiss. A thin sheet of alluvium also occurs, which, is not
forming an aquifer to yield water. The litho-units in the study area were evaluated and assigned suitable weightages as per their hydrogeological properties (Table 1).
Lineament Density Lineament map was prepared by using satellite imagery and geological maps. Lineaments are the manifestation of linear features that can play a major role in identifying suitable sites for groundwater recharge (Chowdary et al. 2009). Orientation of the lineaments is usually analyzed by rose diagrams. The lineament trends are predominantly along ENE-SSW direction (Fig. 5). The purpose of the lineament density analysis is to calculate frequency of the lineaments per unit area. Lineament density is calculated
Fig.4. Geology of the study area.
INTEGRATING REMOTE SENSING AND GIS FOR IDENTIFICATION OF GROUNDWATER PROSPECTIVE ZONES 255
using Kernel density (Silverman, 1986). The delineated lineaments were converted into zones of different lineament densities, viz. low (49.4%), moderate (34.7%) and high (15.9%) using Density function in Spatial Analyst tool of ArcGIS (Fig. 6). Areas with high lineament density are good for groundwater development (Sander, 2007). High values of lineament density are recorded in the ENE and western parts of the study area indicating good groundwater potential.
Drainage Density
A drainage map of the area gives an idea about the permeability of rocks and also gives an indication of the yield of the basin (Wisler and Brater, 1959). A drainage map of the study area was generated from the vectorization of base map as well as satellite imagery, representing the network of streams in the catchments, followed by the tributaries upto the 6 th^ order. The drainage pattern in the Narava basin area was dendritic, parallel and radial type. The preferred orientation of 1 st^ order streams show dominant NNW-SSE orientation, while 2 nd^ order streams show ENE/ NW-SSW/SE direction (Fig. 7). Drainage density is the ratio of the total length of the stream to the area of the drainage basin. The drainage density map was generated from drainage network of the basin using GIS software. High drainage density is an unfavourable site for groundwater existence, moderate drainage density has moderate groundwater potential and less/no drainage density is high groundwater potential zone (Todd and Mays, 2005). The
effect of drainage density on runoff volume is associated with the time during which, the runoff remains in the watershed. The drainage density map is classified into three categories, viz. low (<0.75 km/km 2 ), medium (0.75 to 1. km/km^2 ) and high (>1.5 km/km^2 ) is shown in Fig. 8. Seventy percent of the study area falls under low to moderate drainage density category. Thus, low drainage density was assigned for good ranking as high drainage density implies low groundwater potential.
Slope Topography relates to the local and regional relief and gives an idea about the general direction of groundwater flow and its influence on groundwater recharge (Gupta and Srivastava, 2010). The slope percentage map (Fig. 9) of the area was generated from the digital elevation model. Based on the percentage of slope the entire Narava basin is classified into seven categories as per IMSD (1995) guidelines (Table 3). About 2/3 of the area is under nearly level to gentle slope (0-5%) category, which accounts 74.7%
Fig.5. Lineament map of the study area (Inset rose diagram showing lineaments trend).
Fig.6. Lineament density map of the study area.
Table 3. Slope categories and distribution of area of the basin Slope category Slope Area percentage km 2 % Nearly level 0-1 70.1 13. Very gentle 1-3 238.7 46. Gentle 3-5 76.6 14. Moderate 5-10 35.4 6. Strong 10-15 14.6 2. Moderately steep to steep 15-35 44.8 8. Very steep >35 35.8 6.
INTEGRATING REMOTE SENSING AND GIS FOR IDENTIFICATION OF GROUNDWATER PROSPECTIVE ZONES 257
land (32.2%), fallow land (4.1%), forest land (20.9%), wastelands (7.9%) and water bodies (6.1%) were identified in the study area. From the point of view of land use, crop land with vegetation is an excellent site for groundwater exploration (Todd and Mays, 2005). The area with water bodies is good for groundwater recharge and fallow land is poor for it (Chowdary et al. 2009). About sixty percent of the basin area, covered by forest, crop land and water bodies is favorable for groundwater potential. The detailed weights
and ranks are given in Table 1 based on their groundwater prospect zones.
Depth to Water Level The water levels for pre-monsoon (May) and post- monsoon (November) seasons were collected from 152 dug wells with depth range of 9-18 meters below ground level (m bgl) during 2008 and 2009. The depth of water levels in 2008 varied from 1.6 m to 14.3 m and 0.5 to 7.3 m bgl during pre-monsoon and post-monsoon seasons respectively, while in 2009, they ranged from 2 to 14.4 m bgl and 0.6 to 7.9 m bgl respectively. The groundwater level data (attributes) were imported into spatial theme for GIS analysis. The graphical representation of available water column from different well locations during pre- and post-monsoon seasons in the study area is shown in Fig. 11. During pre-monsoon season, about 50% of the wells have water column of less than 1 m depth, 10% of the wells are completely dry and the remaining 40% wells have water column ranging from 1 to 4 m. During post-monsoon season, about in 70% of the wells, the available water column ranges from 2 to 6 m, while in the remaining wells the amount of water column exceeds 6 m.
GIS Overlay Analysis To demarcate the different groundwater prospective zones, all the thematic layers such as geomorphology, geology, lineament density, drainage density, slope, land use/ land cover are integrated through Spatial Analyst in ArcGIS. The groundwater potential map (Fig. 12) was generated on the basis of weights and ranks assigned to different features of the thematic layers in GIS, which was classified into groundwater prospect zones based on the decision as very good (18.9% of the area), good (26.4% of the area), moderate (17.1% of the area) and poor (37.6% of the area). The maximum area is characterized by moderate to very good potential zone that occupies 62.4% of total area. The map indicates that the stream courses, alluvial plains, pediplains and burried pediments with associated lineaments
Table 4. Spatial distribution of various land use/land cover classes with their areal extent of the study area Class Area km 2 % Builtup land 148.8 28. Crop land 166.1 32. Fallow land 21.1 4. Forest land 107.6 20. Wastelands 40.6 7. Water bodies 31.8 6.
Fig.8. Drainage density map of the study area.
Fig.9. Slope percentage map of the study area.
258 K. NARENDRA AND OTHERS
are identified as good prospective zones, while, the steep sloping hills underlain by compact lithology and high drainage density are classified as poor prospective areas. To validate the groundwater potential zones, groundwater level data collected from existing wells is utilized. In large diameter wells (dug wells), the contribution of well storage to the well discharge is large in relation to inflow for considerable part of pumping period (Edward, 1974) and accordingly, the available water column in wells inventoried is considered for analysis. It was found that the categorization of groundwater potential was in good
agreement with the available water column in the basin area.
CONCLUSIONS
The mapping of groundwater resources has assumed importance in recent years because of increased demand for water. Utilization of remote sensing and GIS is a powerful tool for water resources management. It plays an important role in integrating all the data to generate various thematic maps in the study area such as geomorphology, geology, lineament density, drainage density, slope and land use/land
Fig.10. Land use/land cover map of the study area.
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